Technology is increasingly touted as an alternative to the Irish backstop, especially in light of the government’s difficulty to find a Brexit strategy that can command a majority in the House of Commons. As academics, we have been following the debate around the role of technology in monitoring the border with interest, but also scepticism and frustration. Technology can foster government innovation in countless ways and digital technologies, in particular, have the potential transform the way in which government makes policy and designs public services. Yet, in the context of the Irish border debate, the focus on ‘technological solutions’ is becoming a red herring and distracts from the political choices ahead. Technology cannot solve the Irish border problem and it is time to face the facts.

1: Technology cannot ensure a ‘frictionless border’

Any legal or regulatory restrictions on the movement of goods or people between the UK and the Republic of Ireland post-Brexit will make border-related friction inevitable. Setting the restrictions is a matter of political agreements. Technology can help enforce the legal or regulatory restrictions, but it cannot prevent the introduction of friction compared to the status quo. For example, technology may speed up documentation, processing, and inspections, but it cannot eliminate the need for these procedures, whose existence will mean new burdens on those undergoing them.

2:  There will be a need for new infrastructure at or near the border

Technology may make it possible for some checks to be carried out away from the border. For example, machine learning algorithms can assist in identifying suspicious vehicles and police forces can stop and inspect them away from the border. Regardless of where the relevant inspections are carried out, however, there will be a need for new infrastructure at or near the border, such as camera systems that record the identity of the vehicles crossing the frontier. The amount of new infrastructure needed will depend on how strict the UK and the EU decide to be in enforcing restrictions on the movement of goods and people. At a minimum, cameras will have to be installed at the border. Stricter enforcement regimes will require additional infrastructure such as sensors, scanners, boom barriers or gates.

3: ‘Frictionless’ solutions are in direct conflict with the Brexit goal to ‘take back control’ over borders

There is a fundamental conflict between the goals of minimising friction and enforcing compliance. For example, friction for Irish and UK citizens traveling across the Irish border could be reduced by a system that allows passenger vehicles registered within the Common Travel Area to cross the border freely. This approach, however, would make it difficult to monitor whether registered vehicles are used to facilitate unauthorised movements of people or goods across the border. More generally, the more effective the border management system is in detecting and preventing non-compliant movements of goods or people across the border, the more friction there will be.

4: Technology has known imperfections

Many of the ‘technological solutions’ that have been proposed as ways to minimise friction have blind spots when it comes to monitoring and enforcing compliance – a fact quietly acknowledged through comments about the solutions’ ‘dependence on trust’. Automated licence plate recognition systems, for example, can easily be tricked by using stolen or falsified number plates. Probabilistic algorithmic tools to identify the ‘high risk’ vehicles selected for inspections will fail to identify some cases of non-compliance. Technological tools may lead to improvements over risk-based approaches that rely on human judgment alone, but they cannot, on their own, monitor the border safely.

5: Government will struggle to develop the relevant technological tools

Suggestions that the border controversy may find a last-minute solution by relying on technology seem dangerously detached from the realities of large-scale technology projects, especially in the public sector. In addition to considerable expertise and financial investments, such projects need time, a resource that is quickly running out as March 29 draws closer. The history of government technology projects is littered with examples of failures to meet expectations, enormous cost overruns, and troubled relationships with computer services providers.

A recent example is the mobile phone app meant to facilitate the registration of the 3.7 million EU nationals living in the UK that cannot work on iPhones. Private companies will be keen to sell technological solutions to the backstop problem, with firms like Fujitsu and GSM already signalling their interest in addressing this technological challenge. Under time pressure, government will struggle to evaluate the feasibility of the technological solutions proposed by these private providers, negotiate a favourable contract, and ensure that the resulting technology is fit for purpose.

Technological tools can help implement customs rules, but they cannot fill the current political vacuum. The design, development, and implementation of border management tools require regulatory clarity—prior knowledge of the rules whose monitoring and enforcement the technical tools are meant to support. What these rules will be for the UK-Ireland border following Brexit is a political question. The recent focus on ‘technological solutions’, rather than informing the debate around this question, seems to have served as a strategy for avoiding substantive engagement with it. It is time for government to accept that technology cannot solve the Irish border problem and move on to find real, feasible alternatives.

Authors:

Professor Helen Margetts, Professor of Society and the Internet, Oxford Internet institute, University of Oxford;  Director of the Public Policy Programme, The Alan Turing Institute

Dr Cosmina Dorobantu, Research Associate, Oxford Internet Institute, University of Oxford; Deputy Director of the Public Policy Programme, The Alan Turing Institute

Dr Florian Ostmann, Policy Fellow, Public Policy Programme, The Alan Turing Institute

Christina Hitrova, Digital Ethics Research Assistant, Public Policy Programme, The Alan Turing Institute

Disclaimer: The views expressed in this article are those of the listed members of The Alan Turing Institute’s Public Policy Programme in their individual academic capacities, and do not represent a formal view of the Institute.

Following the banking crisis, and a groundswell of popular opposition to the existing political system in 2009, the people of Iceland embarked on a unique process of constitutional reform. Having opened the entire drafting process to public input and scrutiny, these efforts culminated in Iceland’s 2011 draft crowdsourced constitution: reputedly the world’s first. In his Policy & Internet article “When Does Public Participation Make a Difference? Evidence From Iceland’s Crowdsourced Constitution”, Alexander Hudson examines the impact that the Icelandic public had on the development of the draft constitution. He finds that almost 10 percent of the written proposals submitted generated a change in the draft text, particularly in the area of rights.

This remarkably high number is likely explained by the isolation of the drafters from both political parties and special interests, making them more reliant on and open to input from the public. However, although this would appear to be an example of successful public crowdsourcing, the new constitution was ultimately rejected by parliament. Iceland’s experiment with participatory drafting therefore demonstrates the possibility of successful online public engagement — but also the need to connect the masses with the political elites. It was the disconnect between these groups that triggered the initial protests and constitutional reform, but also that led to its ultimate failure.

We caught up with Alexander to discuss his findings.

Ed: We know from Wikipedia (and other studies) that group decisions are better, and crowds can be trusted. However, I guess (re US, UK) I also feel increasingly nervous about the idea of “the public” having a say over anything important and binding. How do we distribute power and consultation, while avoiding populist chaos?  

Alexander: That’s a large and important question, which I can probably answer only in part. One thing we need to be careful of is what kind of public we are talking about. In many cases, we view self-selection as a bad thing — it can’t be representative. However, in cases like Wikipedia, we see self-selected individuals with specialized knowledge and an uncommon level of interest collaborating. I would suggest that there is an important difference between the kind of decisions that are made by careful and informed participants in citizens’ juries, deliberative polls, or Wikipedia editing, and the oversimplified binary choices that we make in elections or referendums.

So, while there is research to suggest that large numbers of ordinary people can make better decisions, there are some conditions in terms of prior knowledge and careful consideration attached to that. I have high hopes for these more deliberative forms of public participation, but we are right to be cautious about referendums. The Icelandic constitutional reform process actually involved several forms of public participation, including two randomly selected deliberative fora, self-selected online participation, and a popular referendum with several questions.

Ed: A constitution is a very technical piece of text: how much could non-experts realistically contribute to its development — or was there also contribution from specialised interest groups? Presumably there was a team of lawyers and drafters managing the process? 

Alexander: All of these things were going on in Iceland’s drafting process. In my research here and on a few other constitution-making processes in other countries, I’ve been impressed by the ability of citizens to engage at a high level with fundamental questions about the nature of the state, constitutional rights, and legal theory. Assuming a reasonable level of literacy, people are fully capable of reading some literature on constitutional law and political philosophy, and writing very well-informed submissions that express what they would like to see in the constitutional text. A small, self-selected set of the public in many countries seeks to engage in spirited and for the most part respectful debate on these issues. In the Icelandic case, these debates have continued from 2009 to the present.

I would also add that public interest is not distributed uniformly across all the topics that constitutions cover. Members of the public show much more interest in discussing issues of human rights, and have more success in seeing proposals on that theme included in the draft constitution. Some NGOs were involved in submitting proposals to the Icelandic Constitutional Council, but interest groups do not appear to have been a major factor in the process. Unlike some constitution-making processes, the Icelandic Constitutional Council had a limited staff, and the drafters themselves were very engaged with the public on social media.

Ed: I guess Iceland is fairly small, but also unusually homogeneous. That helps, presumably, in creating a general consensus across a society? Or will party / political leaning always tend to trump any sense of common purpose and destiny, when defining the form and identity of the nation?

Alexander: You are certainly right that Iceland is unusual in these respects, and this raises important questions of what this is a case of, and how the findings here can inform us about what might happen in other contexts. I would not say that the Icelandic people reached any sort of broad, national-level consensus about how the constitution should change. During the early part of the drafting process, it seems that those who had strong disagreements with what was taking place absented themselves from the proceedings. They did turn up later to some extent (especially after the 2012 referendum), and sought to prevent this draft from becoming law.

Where the small size and homogeneous population really came into play in Iceland is through the level of knowledge that those who participated had of one another before entering into the constitution-making process. While this has been over emphasized in some discussions of Iceland, there are communities of shared interests where people all seem to know each other, or at least know of each other. This makes forming new societies, NGOs, or interest groups easier, and probably helped to launch the constitution-making project in the first place. 

Ed: How many people were involved in the process — and how were bad suggestions rejected, discussed, or improved? I imagine there must have been divisive issues, that someone would have had to arbitrate? 

Alexander: The number of people who interacted with the process in some way, either by attending one of the public forums that took place early in the process, voting in the election for the Constitutional Council, or engaging with the process on social media, is certainly in the tens of thousands. In fact, one of the striking things about this case is that 522 people stood for election to the 25 member Constitutional Council which drafted the new constitution. So there was certainly a high level of interest in participating in this process.

My research here focused on the written proposals that were posted to the Constitutional Council’s website. 204 individuals participated in that more intensive way. As the members of the Constitutional Council tell it, they would read some of the comments on social media, and the formal submissions on their website during their committee meetings, and discuss amongst themselves which ideas should be carried forward into the draft. The vast majority of the submissions were well-informed, on topic, and conveyed a collegial tone. In this case at least, there was very little of the kind of abusive participation that we observe in some online networks. 

Ed: You say that despite the success in creating a crowd-sourced constitution (that passed a public referendum), it was never ratified by parliament — why is that? And what lessons can we learn from this?

Alexander: Yes, this is one of the most interesting aspects of the whole thing for scholars, and certainly a source of some outrage for those Icelanders who are still active in trying to see this draft constitution become law. Some of this relates to the specifics of Iceland’s constitutional amendment process (which disincentives parliament from approving changes in between elections), but I think that there are also a couple of broadly applicable things going on here. First, the constitution-making process arose as a response to the way that the Icelandic government was perceived to have failed in governing the financial system in the late 2000s. By the time a last-ditch attempt to bring the draft constitution up for a vote in parliament occurred right before the 2013 election, almost five years had passed since the crisis that began this whole saga, and the economic situation had begun to improve. So legislators were not feeling pressure to address those issues any more.

Second, since political parties were not active in the drafting process, too few members of parliament had a stake in the issue. If one of the larger parties had taken ownership of this draft constitution, we might have seen a different outcome. I think this is one of the most important lessons from this case: if the success of the project depends on action by elite political actors, they should be involved in the earlier stages of the process. For various reasons, the Icelanders chose to exclude professional politicians from the process, but that meant that the Constitutional Council had too few friends in parliament to ratify the draft.

Read the full article: Hudson, A. (2018) When Does Public Participation Make a Difference? Evidence From Iceland’s Crowdsourced Constitution. Policy & Internet 10 (2) 185-217. DOI: https://doi.org/10.1002/poi3.167

Alexander Hudson was talking to blog editor David Sutcliffe.

Despite much work on offline social movements and coalition building, few studies have used social network analysis to examine the influence of brokers of online activists (i.e. those who act as a bridge between different ideological groups), or their role in information diffusion across a network. In her Policy & Internet article “Brokerage Roles and Strategic Positions in Twitter Networks of the 2011 Egyptian Revolution”, Deena Abul-Fottouh tests whether social movements theory of networks and coalition building — developed to explain brokerage roles in offline networks, between established parties and organisations — can also be used to explain what happens online.

Social movements theory suggests that actors who occupy an intermediary structural position between different ideological groups are more influential than those embedded only in their own faction. That is, the “bridging ties” that link across political ideologies have a greater impact on mobilization than the bonding ties within a faction. Indeed, examining the Egyptian revolution and ensuing crisis, Deena finds that these online brokers were more evident during the first phase of movement solidarity between liberals, islamists, and socialists than in the period of schism and crisis (2011-2014) that followed the initial protests. However, she also found that the online brokers didn’t match the brokers on the ground: they played different roles, complementing rather than mirroring each other in advancing the revolutionary movement.

We caught up with Deena to discuss her findings:

Ed: Firstly: is the “Arab Spring” a useful term? Does it help to think of the events that took place across parts of the Middle East and North Africa under this umbrella term — which I suppose implies some common cause or mechanism?

Deena: Well, I believe it’s useful to an extent. It helps describe some positive common features that existed in the region such as dissatisfaction with the existing regimes, a dissatisfaction that was transformed from the domain of advocacy to the domain of high-risk activism, a common feeling among the people that they can make a difference, even though it did not last long, and the evidence that there are young people in the region who are willing to sacrifice for their freedom. On the other hand, structural forces in the region such as the power of deep states and the forces of counter-revolution were capable of halting this Arab Spring before it burgeoned or bore fruit, so may be the term “Spring” is no longer relevant.

Ed: Revolutions have been happening for centuries, i.e. they obviously don’t need Twitter or Facebook to happen. How significant do you think social media were in this case, either in sparking or sustaining the protests? And how useful are these new social media data as a means to examine the mechanisms of protest?

Deena: Social media platforms have proven to be useful in facilitating protests such as by sharing information in a speedy manner and on a broad range across borders. People in Egypt and other places in the region were influenced by Tunisia, and protest tactics were shared online. In other words, social media platforms definitely facilitate diffusion of protests. They are also hubs to create a common identity and culture among activists, which is crucial for the success of social movements. I also believe that social media present activists with various ways to circumvent policing of activism (e.g. using pseudonyms to hide the identity of the activists, sharing information about places to avoid in times of protests, many platforms offer the possibility for activists to form closed groups where they have high privacy to discuss non-public matters, etc.).

However, social media ties are weak ties. These platforms are not necessarily efficient in building the trust needed to bond social movements, especially in times of schism and at the level of high-risk activism. That is why, as I discuss in my article, we can see that the type of brokerage that is formed online is brokerage that is built on weak ties, not necessarily the same as offline brokerage that usually requires high trust.

Ed: It’s interesting that you could detect bridging between groups. Given schism seems to be fairly standard in society (Cf filter bubbles etc.) .. has enough attention been paid to this process of temporary shifting alignments, to advance a common cause? And are these incidental, or intentional acts of brokerage?

Deena: I believe further studies need to be made on the concepts of solidarity, schism and brokerage within social movements both online and offline. Little attention has been given to how movements come together or break apart online. The Egyptian revolution is a rich case to study these concepts as the many changes that happened in the path of the revolution in its first five years and the intervention of different forces have led to multiple shifts of alliances that deserve study. Acts of brokerage do not necessarily have to be intentional. In social movements studies, researchers have studied incidental acts that could eventually lead to formation of alliances, such as considering co-members of various social movements organizations as brokers between these organizations.

I believe that the same happens online. Brokerage could start with incidental acts such as activists following each other on Twitter for example, which could develop into stronger ties through mentioning each other. This could also build up to coordinating activities online and offline. In the case of the Egyptian revolution, many activists who met in protests on the ground were also friends online. The same happened in Moldova where activists coordinated tactics online and met on the ground. Thus, incidental acts that start with following each other online could develop into intentional coordinated activism offline. I believe further qualitative interviews need to be conducted with activists to study how they coordinate between online and offline activism, as there are certain mechanisms that cannot be observed through just studying the public profiles of activists or their structural networks.

Ed: The “Arab Spring” has had a mixed outcome across the region — and is also now perhaps a bit forgotten in the West. There have been various network studies of the 2011 protests: but what about the time between visible protests .. isn’t that in a way more important? What would a social network study of the current situation in Egypt look like, do you think?

Deena: Yes, the in-between times of waves of protests are as important to study as the waves themselves as they reveal a lot about what could happen, and we usually study them retroactively after the big shocks happen. A social network of the current situation in Egypt would probably include many “isolates” and tiny “components”, if I would use social network analysis terms. This started showing in 2014 as the effects of schism in the movement. I believe this became aggravated over time as the military coup d’état got a stronger grip over the country, suppressing all opposition. Many activists are either detained or have left the country. A quick look at their online profiles does not reveal strong communication between them. Yet, this is what apparently shows from public profiles. One of the levers that social media platforms offer is the ability to create private or “closed” groups online.

I believe these groups might include rich data about activists’ communication. However, it is very difficult, almost impossible to study these groups, unless you are a member or they give you permission. In other words, there might be some sort of communication occurring between activists but at a level that researchers unfortunately cannot access. I think we might call it the “underground of online activism”, which I believe is potentially a very rich area of study.

Ed: A standard criticism of “Twitter network studies” is that they aren’t very rich — they may show who’s following whom, but not necessarily why, or with what effect. Have there been any larger, more detailed studies of the Arab Spring that take in all sides: networks, politics, ethnography, history — both online and offline?

Deena: To my knowledge, there haven’t been studies that have included all these aspects together. Yet there are many studies that covered each of them separately, especially the politics, ethnography, and history of the Arab Spring (see for example: Egypt’s Tahrir Revolution 2013, edited by D. Tschirgi, W. Kazziha and S. F. McMahon). Similarly, very few studies have tried to compare the online and offline repertoires (see for example: Weber, Garimella and Batayneh 2013, Abul-Fottouh and Fetner 2018). In my doctoral dissertation (2018 from McMaster University), I tried to include many of these elements.

Read the full article: Abul-Fottouh, D. (2018) Brokerage Roles and Strategic Positions in Twitter Networks of the 2011 Egyptian Revolution. Policy & Internet 10: 218-240. doi:10.1002/poi3.169

Deena Abul-Fottouh was talking to blog editor David Sutcliffe.

Issue Outline

Governments, the private sector, and civil society are beginning to work together to challenge extremist exploitation of digital communications. Both Islamic and right-wing extremists use websites, blogs, social media, encrypted messaging, and filesharing websites to spread narratives and propaganda, influence mainstream public spheres, recruit members, and advise audiences on undertaking attacks.

Across the world, public-private partnerships have emerged to counter this problem. For example, the Global Internet Forum to Counter Terrorism (GIFCT) organized by the UN Counter-Terrorism Executive Directorate has organized a “shared hash database” that provides “digital fingerprints” of ISIS visual content to help platforms quickly take down content. In another case, the UK government funded ASI Data Science to build a tool to accurately detect jihadist content. Elsewhere, Jigsaw (a Google-owned company) has developed techniques to use content recommendations on YouTube to “redirect” viewers of extremist content to content that might challenge their views.

While these are important and admirable efforts, their impacts and effectiveness is unclear. The purpose of this special issue is to map and evaluate emerging public-private partnerships, technologies, and responses to online extremism. There are three main areas of concern that the issue will address:

(1) the changing role of content moderation, including taking down content and user accounts, as well as the use of AI techniques to assist;

(2) the increasing focus on “counter-narrative” campaigns and strategic communication; and

(3) the inclusion of global civil society in this agenda.

This mapping will contribute to understanding how power is distributed across these actors, the ways in which technology is expected to address the problem, and the design of the measures currently being undertaken.

Topics of Interest

Papers exploring one or more of the following areas are invited for consideration:

Content moderation

• Efficacy of user and content takedown (and effects it has on extremist audiences);
• Navigating the politics of freedom of speech in light of the proliferation of hateful and extreme speech online;
• Development of content and community guidelines on social media platforms;
• Effect of government policy, recent inquiries, and civil society on content moderation practices by the private sector (e.g. recent laws in Germany, Parliamentary inquiries in the UK);
• Role and efficacy of Artificial Intelligence (AI) and machine learning in countering extremism.

Counter-narrative Campaigns and Strategic Communication

• Effectiveness of counter-narrative campaigns in dissuading potential extremists;
• Formal and informal approaches to counter narratives;
• Emerging governmental or parastatal bodies to produce and disseminate counter-narratives;
• Involvement of media and third sector in counter-narrative programming;
• Research on counter-narrative practitioners;
• Use of technology in supporting counter-narrative production and dissemination.

Inclusion of Global Civil Society

• Concentration of decision making power between government, private sector, and civil society actors;
• Diversity of global civil society actors involved in informing content moderation and counter-narrative campaigns;
• Extent to which inclusion of diverse civil society/third sector actors improves content moderation and counter-narrative campaigns;
• Challenges and opportunities faced by global civil society in informing agendas to respond to online extremism.

Submitting your Paper

We encourage interested scholars to submit 6,000 to 8,000 word papers that address one or more of the issues raised in the call. Submissions should be made through Policy & Internet’s manuscript submission system. Interested authors are encouraged to contact Jonathan Bright (jonathan.bright@oii.ox.ac.uk) and Bharath Ganesh (bharath.ganesh@oii.ox.ac.uk) to check the suitability of their paper.

Special Issue Schedule

The special issue will proceed according to the following timeline:

Paper submission: 30 October 2018

First round of reviews: January 2019

Revisions received: March 2019

Final review and decision: May 2019

Publication (estimated): December 2019

The special issue as a whole will be published at some time in late 2019, though individual papers will be published online in EarlyView as soon as they are accepted.

In their Policy & Internet article “Understanding Popularity, Reputation, and Social Influence in the Twitter Society“, David Garcia, Pavlin Mavrodiev, Daniele Casati, and Frank Schweitzer examine popularity, reputation, and social influence on Twitter using network information on more than 40 million users. They integrate measurements of popularity, reputation, and social influence to evaluate what keeps users active, what makes them more popular, and what determines their influence in the network.

Popularity in the Twitter social network is often quantified as the number of followers of a user. That implies that it doesn’t matter why some user follows you, or how important she is, your popularity only measures the size of your audience. Reputation, on the other hand, is a more complicated concept associated with centrality. Being followed by a highly reputed user has a stronger effect on one’s reputation than being followed by someone with low reputation. Thus, the simple number of followers does not capture the recursive nature of reputation.

In their article, the authors examine the difference between popularity and reputation on the process of social influence. They find that there is a range of values in which the risk of a user becoming inactive grows with popularity and reputation. Popularity in Twitter resembles a proportional growth process that is faster in its strongly connected component, and that can be accelerated by reputation when users are already popular. They find that social influence on Twitter is mainly related to popularity rather than reputation, but that this growth of influence with popularity is sublinear. In sum, global network metrics are better predictors of inactivity and social influence, calling for analyses that go beyond local metrics like the number of followers.

We caught up with the authors to discuss their findings:

Ed.: Twitter is a convenient data source for political scientists, but they tend to get criticised for relying on something that represents only a tiny facet of political activity. But Twitter is presumably very useful as a way of uncovering more fundamental / generic patterns of networked human interaction?

David: Twitter as a data source to study human behaviour is both powerful and limited. Powerful because it allows us to quantify and analyze human behaviour at scales and resolutions that are simply impossible to reach with traditional methods, such as experiments or surveys. But also limited because not every aspect of human behaviour is captured by Twitter and using its data comes with significant methodological challenges, for example regarding sampling biases or platform changes. Our article is an example of an analysis of general patterns of popularity and influence that are captured by spreading information in Twitter, which only make sense beyond the limitations of Twitter when we frame the results with respect to theories that link our work to previous and future scientific knowledge in the social sciences.

Ed.: How often do theoretical models (i.e. describing the behaviour of a network in theory) get linked up with empirical studies (i.e. of a network like Twitter in practice) but also with qualitative studies of actual Twitter users? And is Twitter interesting enough in itself for anyone to attempt to develop an overall theoretico-empirico-qualitative theory about it?

David: The link between theoretical models and large-scale data analyses of social media is less frequent than we all wish. But the gap between disciplines seems to be narrowing in the last years, with more social scientists using online data sources and computer scientists referring better to theories and previous results in the social sciences. What seems to be quite undeveloped is an interface with qualitative methods, specially with large-scale analyses like ours.

Qualitative methods can provide what data science cannot: questions about important and relevant phenomena that then can be explained within a wider theory if validated against data. While this seems to me as a fertile ground for interdisciplinary research, I doubt that Twitter in particular should be the paragon of such combination of approaches. I advocate for starting research from the aspect of human behaviour that is the subject of study, and not from a particularly popular social media platform that happens to be used a lot today, but might not be the standard tomorrow.

Ed.: I guess I’ve see a lot of Twitter networks in my time, but not much in the way of directed networks, i.e. showing direction of flow of content (i.e. influence, basically) — or much in the way of a time element (i.e. turning static snapshots into dynamic networks). Is that fair, or am I missing something? I imagine it would be fun to see how (e.g.) fake news or political memes propagate through a network?

David: While Twitter provides amazing volumes of data, its programming interface is notorious for the absence of two key sources: the date when follower links are created and the precise path of retweets. The reason for the general picture of snapshots over time is that researchers cannot fully trace back the history of a follower network, they can only monitor it with certain frequency to overcome the fact that links do not have a date attached.

The generally missing picture of flows of information is because when looking up a retweet, we can see the original tweet that is being retweeted, but not if the retweet is of a retweet of a friend. This way, without special access to Twitter data or alternative sources, all information flows look like stars around the original tweet, rather than propagation trees through a social network that allow the precise analysis of fake news or memes.

Ed.: Given all the work on Twitter, how well-placed do you think social scientists would be to advise a political campaign on “how to create an influential network” beyond just the obvious (Tweet well and often, and maybe hire a load of bots). i.e. are there any “general rules” about communication structure that would be practically useful to campaigning organisations?

David: When we talk about influence on Twitter, we usually talk about rather superficial behaviour, such as retweeting content or clicking on a link. This should not be mistaken as a more substantial kind of influence, the kind that makes people change their opinion or go to vote. Evaluating the real impact of Twitter influence is a bottleneck for how much social scientists can advise a political campaign. I would say than rather than providing general rules that can be applied everywhere, social scientists and computer scientists can be much more useful when advising, tracking, and optimizing individual campaigns that take into account the details and idiosyncrasies of the people that might be influenced by the campaign.

Ed.: Random question: but where did “computational social science” emerge from – is it actually quite dependent on Twitter (and Wikipedia?), or are there other commonly-used datasets? And are computational social science, “big data analytics”, and (social) data science basically describing the same thing?

David: Tracing back the meaning and influence of “computational social science” could take a whole book! My impression is that the concept started few decades ago as a spin on “sociophysics”, where the term “computational” was used as in “computational model”, emphasizing a focus on social science away from toy model applications from physics. Then the influential Science article by David Lazer and colleagues in 2009 defined the term as the application of digital trace datasets to test theories from the social sciences, leaving the whole computational modelling outside the frame. In that case, “computational” was used more as it is used in “computational biology”, to refer to social science with increased power and speed thanks to computer-based technologies. Later it seems to have converged back into a combination of both the modelling and the data analysis trends, as in the “Manifesto of computational social science” by Rosaria Conte and colleagues in 2012, inspired by the fact that we need computational modelling techniques from complexity science to understand what we observe in the data.

The Twitter and Wikipedia dependence of the field is just a path dependency due to the ease and open access to those datasets, and a key turning point in the field is to be able to generalize beyond those “model organisms”, as Zeynep Tufekci calls them. One can observe these fads in the latest computer science conferences, with the rising ones being Reddit and Github, or when looking at earlier research that heavily used product reviews and blog datasets. Computational social science seems to be maturing as a field, make sense out of those datasets and not just telling cool data-driven stories about one website or another. Perhaps we are beyond the peak of inflated expectations of the hype curve and the best part is yet to come.

With respect to big data and social data science, it is easy to get lost in the field of buzzwords. Big data analytics only deals with the technologies necessary to process large volumes of data, which could come from any source including social networks but also telescopes, seismographs, and any kind of sensor. These kind of techniques are only sometimes necessary in computational social science, but are far from the core of topics of the field.

Social data science is closer, but puts a stronger emphasis on problem-solving rather than testing theories from the social sciences. When using “data science” we usually try to emphasize a predictive or explorative aspect, rather than the confirmatory or generative approach of computational social science. The emphasis on theory and modelling of computational social science is the key difference here, linking back to my earlier comment about the role of computational modelling and complexity science in the field.

Ed.: Finally, how successful do you think computational social scientists will be in identifying any underlying “social patterns” — i.e. would you agree that the Internet is a “Hadron Collider” for social science? Or is society fundamentally too chaotic and unpredictable?

David: As web scientists like to highlight, the Web (not the Internet, which is the technical infrastructure connecting computers) is the largest socio-technical artifact ever produced by humanity. Rather than as a Hadron Collider, which is a tool to make experiments, I would say that the Web can be the Hubble telescope of social science: it lets us observe human behaviour at an amazing scale and resolution, not only capturing big data but also, fast, long, deep, mixed, and weird data that we never imagined before.

While I doubt that we will be able to predict society in some sort of “psychohistory” manner, I think that the Web can help us to understand much more about ourselves, including our incentives, our feelings, and our health. That can be useful knowledge to make decisions in the future and to build a better world without the need to predict everything.

Read the full article: Garcia, D., Mavrodiev, P., Casati, D., and Schweitzer, F. (2017) Understanding Popularity, Reputation, and Social Influence in the Twitter Society. Policy & Internet 9 (3) doi:10.1002/poi3.151

David Garcia was talking to blog editor David Sutcliffe.

In their Policy & Internet article “Does the Internet Encourage Political Participation? Use of an Online Platform by Members of a German Political Party,” Katharina Gerl, Stefan Marschall, and Nadja Wilker examine the German Greens’ online collaboration platform to ask why only some party members and supporters use it. The platform aims improve the inclusion of party supporters and members in the party’s opinion-formation and decision-making process, but it has failed to reach inactive members. Instead, those who have already been active in the party also use the online platform. It also seems that classical resources such as education and employment status do not (directly) explain differences in participation; instead, participation is motivated by process-related and ideological incentives.

We caught up with the authors to discuss their findings:

Ed.: You say “When it comes to explaining political online participation within parties, we face a conceptual and empirical void” .. can you explain briefly what the offline models are, and why they don’t work for the Internet age?

Katharina / Stefan / Nadja: According to Verba et al. (1995) the reasons for political non-participation can be boiled down to three factors: (1) citizens do not want to participate, (2) they cannot, (3) nobody asked them to. Speaking model-wise we can distinguish three perspectives: Citizens need certain resources like education, information, time and civic skills to participate (resource model and civic voluntarism model). The social psychological model looks at the role of attitudes and political interest that are supposed to increase participation. In addition to resources and attitudes, the general incentives model analyses how motives, costs and benefits influence participation.

These models can be applied to online participation as well, but findings for the online context indicate that the mechanisms do not always work like in the offline context. For example, age plays out differently for online participation. Generally, the models have to be specified for each participation context. This especially applies for the online context as forms of online participation sometimes demand different resources, skills or motivational factors. Therefore, we have to adapt and supplemented the models with additional online factors like internet skills and internet sophistication.

Ed.: What’s the value to a political party of involving its members in policy discussion? (i.e. why go through the bother?)

Katharina / Stefan / Nadja: Broadly speaking, there are normative and rational reasons for that. At least for the German parties, intra-party democracy plays a crucial role. The involvement of members in policy discussion can serve as a means to strengthen the integration and legitimation power of a party. Additionally, the involvement of members can have a mobilizing effect for the party on the ground. This can positively influence the linkage between the party in central office, the party on the ground, and the societal base. Furthermore, member participation can be a way to react on dissatisfaction within a party.

Ed.: Are there any examples of successful “public deliberation” — i.e. is this maybe just a problem of getting disparate voices to usefully engage online, rather than a failure of political parties per se?

Katharina / Stefan / Nadja: This is definitely not unique to political parties. The problems we observe regarding online public deliberation in political parties also apply to other online participation platforms: political participation and especially public deliberation require time and effort for participants, so they will only be willing to engage if they feel they benefit from it. But the benefits of participation may remain unclear as public deliberation – by parties or other initiators – often takes place without a clear goal or a real say in decision-making for the participants. Initiators of public deliberation often fail to integrate processes of public deliberation into formal and meaningful decision-making procedures. This leads to disappointment for potential participants who might have different expectations concerning their role and scope of influence. There is a risk of a vicious circle and disappointed expectations on both sides.

Ed.: Based on your findings, what would you suggest that the Greens do in order to increase participation by their members on their platform?

Katharina / Stefan / Nadja: Our study shows that the members of the Greens are generally willing to participate online and appreciate this opportunity. However, the survey also revealed that the most important incentive for them is to have an influence on the party’s decision-making. We would suggest that the Greens create an actual cause for participation, meaning to set clear goals and to integrate it into specific and relevant decisions. Participation should not be an end in itself!

Ed.: How far do political parties try to harness deliberation where it happens in the wild e.g. on social media, rather than trying to get people to use bespoke party channels? Or might social media users see this as takeover by the very “establishment politics” they might have abandoned, or be reacting against?

Katharina / Stefan / Nadja: Parties do not constrain their online activities to their own official platforms and channels but also try to develop strategies for influencing discourses in the wild. However, this works much better and has much more authenticity as well as credibility if it isn’t parties as abstract organizations but rather individual politicians such as members of parliament who engage in person on social media, for example by using Twitter.

Ed.: How far have political scientists understood the reasons behind the so-called “crisis of democracy”, and how to address it? And even if academics came up with “the answer” — what is the process for getting academic work and knowledge put into practice by political parties?

Katharina / Stefan / Nadja: The alleged “crisis of democracy” is in first line seen as a crisis of representation in which the gap between political elites and the citizens has widened drastically within the last years, giving room to populist movements and parties in many democracies. Our impression is that facing the rise of populism in many countries, politicians have become more and more attentive towards discussions and findings in political science which have been addressing the linkage problems for years. But perhaps this is like shutting the stable door after the horse has bolted.

Read the full article: Gerl, K., Marschall, S., and Wilker, N. (2016) Does the Internet Encourage Political Participation? Use of an Online Platform by Members of a German Political Party. Policy & Internet doi:10.1002/poi3.149

Katharina Gerl, Stefan Marschall, and Nadja Wilker were talking to blog editor David Sutcliffe.

In their Policy & Internet article “Crowdsourced Deliberation: The Case of the Law on Off-Road Traffic in Finland”, Tanja Aitamurto and Hélène Landemore examine a partially crowdsourced reform of the Finnish off-road traffic law. The aim of the process was to search for knowledge and ideas from the crowd, enhance people’s understanding of the law, and to increase the perception of the policy’s legitimacy. The participants could propose ideas on the platform, vote others’ ideas up or down, and comment.

The authors find that despite the lack of explicit incentives for deliberation in the crowdsourced process, crowdsourcing indeed functioned as a space for democratic deliberation; that is, an exchange of arguments among participants characterized by a degree of freedom, equality, and inclusiveness. An important finding, in particular, is that despite the lack of statistical representativeness among the participants, the deliberative exchanges reflected a diversity of viewpoints and opinions, tempering to a degree the worry about the bias likely introduced by the self-selected nature of citizen participation.

They introduce the term “crowdsourced deliberation” to mean the deliberation that happens (intentionally or unintentionally) in crowdsourcing, even when the primary aim is to gather knowledge rather than to generate deliberation. In their assessment, crowdsourcing in the Finnish experiment was conducive to some degree of democratic deliberation, even though, strikingly, the process was not designed for it.

We caught up with the authors to discuss their findings:

Ed.: There’s a lot of discussion currently about “filter bubbles” (and indeed fake news) damaging public deliberation. Do you think collaborative crowdsourced efforts (that include things like Wikipedia) help at all more generally, or .. are we all damned to our individual echo chambers?

Tanja and Hélène: Deliberation, whether taking place within a crowdsourced policymaking process or in another context, has a positive impact on society, when the participants exchange knowledge and arguments. While all deliberative processes are, to a certain extent, their own microcosms, there is typically at least some cross-cutting exposure of opinions and perspectives among the crowd. The more diverse the participant crowd is and the larger the number of participants, the more likely there is diversity also in the opinions, preventing strictly siloed echo chambers.

Moreover, it all comes down to design and incentives in the end. In our crowdsourcing platform we did not particularly try to attract a cross-cutting section of the population so there was a risk of having only a relatively homogenous population self-selecting into the process, which is what happened to a degree, demographically at last (over 90% of our participants were educated male professionals). In terms of ideas though, the pool was much more diverse than the demography would have suggested, and techniques we used (like clustering) helped maintain the visibility (to the researchers) of the minority views.

That said, if what you are is after is maximal openness and cross-cutting exposure, nothing beats random selection, like the one used in mini-publics of all kinds, from citizens’ juries to deliberative polls to citizens’ assemblies… That’s what Facebook and Twitter should use in order to break the filter bubbles in which people lock themselves: algorithms that randomize the content of our newsfeed and expose us to a vast range of opinions, rather than algorithms that maximize similarity with what we already like.

But for us the goal was different and so our design was different. Our goal was to gather knowledge and ideas and for this self-selection (the sort also at play in Wikipedia) is better than random-selection: whereas with random selection you shut the door on most people, in crowdsourcing platform you just let the door open to anyone who can self-identify as having a relevant form of knowledge and has the motivation to participate. The remarkable thing in our case is that even though we didn’t design the process for democratic deliberation, it occurred anyway, between the cracks of the design so to speak.

Ed.: I suppose crowdsourcing won’t work unless there is useful cooperation: do you think these successful relationships self-select on a platform, or do things perhaps work precisely because people may NOT be discussing other, divisive things (like immigration) when working together on something apparently unrelated, like an off-road law?

Tanja and Hélène: There is a varying degree of collaboration in crowdsourcing. In crowdsourced policymaking, the crowd does not typically collaborate on drafting the law (unlike the crowd does in Wikipedia writing), but they rather respond to the crowdsourcer’s, in this case, the government’s prompts. In this type of crowdsourcing, which was the case in the crowdsourced off-road traffic law reform, the crowd members don’t need to collaborate with each other in order the process to achieve its goal of finding new knowledge. The crowd, can, of course decide not to collaborate with the government and not answer the prompts, or start sabotaging the process.

The degree and success of collaboration will depend on the design and the goals of your experiment. In our case, crowdsourcing might have worked even without collaboration because our goal was to gather knowledge and information, which can be done by harvesting the contributions of the individual members of the crowd without them interacting with each other. But if what you are after is co-creation or deliberation, then yes you need to create the background conditions and incentives for cooperation.

Cooperation may require bracketing some sensitive topics or else learning to disagree in respectful ways. Deliberation, and more broadly cooperation are social skills — human technologies you might say — that we still don’t know how to use very well. This comes in part from the fact that our school systems do not teach those skills, focused as they are on promoting individual rather than collaborative success and creating an eco-system of zero-sum competition between students, when in the real world there is almost nothing you can do all by yourself and we would be much better off nurturing collaborative skills and the art or technology of deliberation.

Ed.: Have there been any other examples in Finland — i.e. is crowdsourcing (and deliberation) something that is seen as useful and successful by the government?

Tanja and Hélène: Yes, there has been several crowdsourced policymaking processes in Finland. One is a crowdsourced Limited Liability Housing Company Law reform, organized by the Ministry of Justice in the Finland government. We examined the quality of deliberation in the case, and the findings show that the quality of deliberation, as measured by Discourse Quality Index, was pretty good.

Read the full article: Aitamurto, T. and Landemore, H. (2016) Crowdsourced Deliberation: The Case of the Law on Off-Road Traffic in Finland. Policy & Internet 8 (2) doi:10.1002/poi3.115.

Tanja Aitamurto and Hélène Landemore were talking to blog editor David Sutcliffe.

The empirical findings of their comparative analysis across three types of news platforms broadly support the assumption that platform design affects the level of deliberative quality of user comments. Deliberation was most likely to be found in news fora, which are of course specifically designed to initiate user discussions. News websites showed a lower level of deliberative quality, with Facebook coming last in terms of meeting deliberative design criteria and sustaining deliberation. However, while Facebook performed poorly in terms of overall level of deliberative quality, it did promote a high degree of general engagement among users.

The study’s findings suggest that deliberative discourse in the virtual public sphere of the Internet is indeed possible, which is good news for advocates of deliberative theory. However, this will only be possible by carefully considering how platforms function, and how they are designed. Some may argue that the “power of design” (shaped by organizers like media companies), contradicts the basic idea of open debate amongst equals where the only necessary force is Habermas’s “forceless force of the better argument”. These advocates of an utterly free virtual public sphere may be disappointed, given it’s clear that deliberation is only likely to emerge if the platform is designed in a particular way.

We caught up with the authors to discuss their findings:

Ed: Just briefly: what design features did you find helped support public deliberation, i.e. reasoned, reciprocal, respectful, constructive discussion?

Katharina / Dennis / Christiane: There are several design features which are known to influence online deliberation. However, in this study we particularly focus on moderation, asynchronous discussion, clear topic definition, and the availability of information, which we have found to have a positive influence on the quality of online deliberation.

Ed.: I associate “Internet as a deliberative space” with Habermas, but have never read him: what’s the short version of what he thinks about “the public sphere” — and how the Internet might support this?

Katharina / Dennis / Christiane: Well, Habermas describes the public sphere as a space where free and equal people discuss topics of public import in a specific way. The respectful exchange of rational reasons is crucial in this normative ideal. Due to its open architecture, the Internet has often been presented as providing the infrastructure for large scale deliberation processes. However, Habermas himself is very skeptical as to whether online spaces support his ideas on deliberation. Ironically, he is one of the most influential authors in online deliberation scholarship.

Ed.: What do advocates of the Internet as a “deliberation space” hope for — simply that people will feel part of a social space / community if they can like things or comment on them (and see similar viewpoints); or that it will result in actual rational debate, and people changing their minds to “better” viewpoints, whatever they may be? I can personally see a value for the former, but I can’t imagine the latter ever working, i.e. given people basically don’t change?

Katharina / Dennis / Christiane: We are thinking that both hopes are present in the current debate, and we partly agree with your perception that changing minds seems to be difficult. But we may also be facing some methodological or empirical issues here, because changing of minds is not an easy thing to measure. We know from other studies that deliberation can indeed cause changes of opinion. However, most of this probably takes place within the individual’s mind. Robert E. Goodin has called this process “deliberation within” and this is not accessible through content analysis. People do not articulate “Oh, thanks for this argument, I have changed my mind”, but they probably take something away from online discussions which makes them more open minded.

Ed.: Does Wikipedia provide an example where strangers have (oddly!) come together to create something of genuine value — but maybe only because they’re actually making a specific public good? Is the basic problem of the idea of the “Internet supporting public discourse” that this is just too aimless an activity, with no obvious individual or collective benefit?

Katharina / Dennis / Christiane: We think Wikipedia is a very particular case. However, we can learn from this case that the collective goal plays a very important role for the quality of contributions. We know from empirical research that if people have the intention of contributing to something meaningful, discussion quality is significantly higher than in online spaces without that desire to have an impact.

Ed.: I wonder: isn’t Twitter the place where “deliberation” now takes place? How does it fit into, or inform, the deliberation literature, which I am assuming has largely focused on things like discussion fora?

Katharina / Dennis / Christiane: This depends on the definition of the term “deliberation”. We would argue that the limitation to 280 characters is probably not the best design feature for meaningful deliberation. However, we may have to think about deliberation in less complex contexts in order to reach more people; but this is a polarizing debate.

Ed.: You say that “outsourcing discussions to social networking sites such as Facebook is not advisable due to the low level of deliberative quality compared to other news platforms”. Facebook has now decided that instead of “connecting the world” it’s going to “bring people closer together” — what would you recommend that they do to support this, in terms of the design of the interactive (or deliberative) features of the platform?

Katharina / Dennis / Christiane: This is a difficult one! We think that the quality of deliberation on Facebook would strongly benefit from moderators, which should be more present on the platform to structure the discussions. By this we do not only mean professional moderators but also participative forms of moderation, which could be encouraged more by mechanisms which support such behaviour.

Read the full article: Katharina Esau, Dennis Friess, and Christiane Eilders (2017) Design Matters! An Empirical Analysis of Online Deliberation on Different News Platforms. Policy & Internet 9 (3) 321-342.

Katharina (@kathaesa), Dennis, and Christiane were talking to blog editor David Sutcliffe.

However, only limited guidance is given by international human rights monitoring bodies and courts on how to apply human rights law to the design and use of Internet technology, especially when developed by non-state actors. And while the Internet can certainly facilitate the exercise and fulfilment of human rights, it is also conducive to human rights violations, with many Internet organizations and companies currently grappling with their responsibilities in this area.

To help understand how digital technology can support the exercise of human rights, we—Corinne Cath, Ben Zevenbergen, and Christiaan van Veen—organized a workshop at the 2017 Citizen Lab Summer Institute in Toronto, on ‘Coding Human Rights Law’. By gathering together academics, technologists, human rights experts, lawyers, government officials, and NGO employees, we hoped to gather experience and scope the field to:

1. Explore the relationship between connected technology and human rights;

2. Understand how this technology can support the exercise of human rights;

3. Identify current bottlenecks for integrating human rights considerations into Internet technology; and

4. List recommendations to provide guidance to the various stakeholders working on human-rights strengthening technology.

In the workshop report “Coding Human Rights Law: Citizen Lab Summer Institute 2017 Workshop Report“, we give an overview of the discussion. We address multiple legal and technical concerns. We consider the legal issues arising from human rights law being state-centric, while most connected technologies are being developed by the private sector. We also discuss the applicability of current international human rights frameworks to debates about new technologies. We cover the technical issues that arise when trying to code for human rights, in particular when human rights considerations are integrated into the design and operationalization of Internet technology. We conclude by identifying some areas for further debate and reflection, six of which we list below:

Integrating Human Rights into Internet Technology Design: Six Considerations

Legal:

1. Further study of the application of instruments of the existing human rights framework, (like the UN Guiding Principles for Business and Human Rights) to Internet actors is needed, including the need for new legal instruments at the national and international level that specify the human rights responsibilities of non-state actors.

2. More research is needed to analyse and rebuild the theories underpinning human rights, given the premises and assumptions grounding them may have been affected by the transition to a digitally mediated society. Much has been done on the rights to privacy and free speech, but more analysis of the relevance of other human rights in this area is needed.

3. Human rights frameworks can best be approached as a legal minimum baseline, while other frameworks, like data protection legislation or technology-specific regulation, provide content to what is aimed for above and beyond this minimum threshold.

Technical:

1. Taking into account a wider range of international human rights would benefit the development of human rights oriented Internet technology. This means thinking beyond the right to privacy and freedom of expression to include (for example), the right to equality and non-discrimination, and the right to work.

2. Internet technologies, in general, must be developed with an eye towards their potential negative impact and human rights impact assessments undertaken to understand that impact. This includes knowledge of the inherent tensions that exist between different human rights and ensuring that technology developers are precise and considerate about where in the Internet stack they want to have an impact.

3. Technology designers, funders, and implementers need to be aware of the context and culture within which a technology will be used, by involving the target end-users in the design process. For instance, it is important to ensure that human-rights-enabling technology does not price out certain populations from using it.

Internet technology can enable the exercise of human rights—if it is context-aware, recognises the inherent tensions between certain rights (privacy and knowledge; free speech and protection from abuse for example), flexible yet specific, legally sound and ethically just, modest in its claims, and actively understanding and mitigating of potential risks.

With these considerations, we are entering uncharted waters. Unless states have included human rights obligations directly into their national laws, there are few binding obligations on the private sector actors pushing forward the technology. Likewise, there are also few methodologies for developing human-right-enabling technology—meaning that we should be careful and considerate about how these technologies are developed.

Read the workshop report: Corinne Cath, Ben Zevenbergen, and Cristiaan van Veen (2018) Coding Human Rights Law: Citizen Lab Summer Institute 2017 Workshop Report. Posted: 14 February, 2018.

In their article “Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR” which is forthcoming in the Harvard Journal of Law & Technology, Sandra Wachter, Brent Mittelstadt, and Chris Russell present the concept of “unconditional counterfactual explanations” as a novel type of explanation of automated decisions that could address many of these challenges. Counterfactual explanations describe the minimum conditions that would have led to an alternative decision (e.g. a bank loan being approved), without the need to describe the full logic of the algorithm.

Relying on counterfactual explanations as a means to help us act rather than merely to understand could help us gauge the scope and impact of automated decisions in our lives. They might also help bridge the gap between the interests of data subjects and data controllers, which might otherwise be a barrier to a legally binding right to explanation.

We caught up with the authors to explore the role of algorithms in our everyday lives, and how a “right to explanation” for decisions might be achievable in practice:

Ed: There’s a lot of discussion about algorithmic “black boxes” — where decisions are made about us, using data and algorithms about which we (and perhaps the operator) have no direct understanding. How prevalent are these systems?

Sandra: Basically, every decision that can be made by a human can now be made by an algorithm. Which can be a good thing. Algorithms (when we talk about artificial intelligence) are very good at spotting patterns and correlations that even experienced humans might miss, for example in predicting disease. They are also very cost efficient—they don’t get tired, and they don’t need holidays. This could help to cut costs, for example in healthcare.

Algorithms are also certainly more consistent than humans in making decisions. We have the famous example of judges varying the severity of their judgements depending on whether or not they’ve had lunch. That wouldn’t happen with an algorithm. That’s not to say algorithms are always going to make better decisions: but they do make more consistent ones. If the decision is bad, it’ll be distributed equally, but still be bad. Of course, in a certain way humans are also black boxes—we don’t understand what humans do either. But you can at least try to understand an algorithm: it can’t lie, for example.

Brent: In principle, any sector involving human decision-making could be prone to decision-making by algorithms. In practice, we already see algorithmic systems either making automated decisions or producing recommendations for human decision-makers in online search, advertising, shopping, medicine, criminal justice, etc. The information you consume online, the products you are recommended when shopping, the friends and contacts you are encouraged to engage with, even assessments of your likelihood to commit a crime in the immediate and long-term future—all of these tasks can currently be affected by algorithmic decision-making.

Ed: I can see that algorithmic decision-making could be faster and better than human decisions in many situations. Are there downsides?

Sandra: Simple algorithms that follow a basic decision tree (with parameters decided by people) can be easily understood. But we’re now also using much more complex systems like neural nets that act in a very unpredictable way, and that’s the problem. The system is also starting to become autonomous, rather than being under the full control of the operator. You will see the output, but not necessarily why it got there. This also happens with humans, of course: I could be told by a recruiter that my failure to land a job had nothing to do with my gender (even if it did); an algorithm, however, would not intentionally lie. But of course the algorithm might be biased against me if it’s trained on biased data—thereby reproducing the biases of our world.

We have seen that the COMPAS algorithm used by US judges to calculate the probability of re-offending when making sentencing and parole decisions is a major source of discrimination. Data provenance is massively important, and probably one of the reasons why we have biased decisions. We don’t necessarily know where the data comes from, and whether it’s accurate, complete, biased, etc. We need to have lots of standards in place to ensure that the data set is unbiased. Only then can the algorithm produce nondiscriminatory results.

A more fundamental problem with predictions is that you might never know what would have happened—as you’re just dealing with probabilities; with correlations in a population, rather than with causalities. Another problem is that algorithms might produce correct decisions, but not necessarily fair ones. We’ve been wrestling with the concept of fairness for centuries, without consensus. But lack of fairness is certainly something the system won’t correct itself—that’s something that society must correct.

Brent: The biases and inequalities that exist in the real world and in real people can easily be transferred to algorithmic systems. Humans training learning systems can inadvertently or purposefully embed biases into the model, for example through labelling content as ‘offensive’ or ‘inoffensive’ based on personal taste. Once learned, these biases can spread at scale, exacerbating existing inequalities. Eliminating these biases can be very difficult, hence we currently see much research done on the measurement of fairness or detection of discrimination in algorithmic systems.

These systems can also be very difficult—if not impossible—to understand, for experts as well as the general public. We might traditionally expect to be able to question the reasoning of a human decision-maker, even if imperfectly, but the rationale of many complex algorithmic systems can be highly inaccessible to people affected by their decisions. These potential risks aren’t necessarily reasons to forego algorithmic decision-making altogether; rather, they can be seen as potential effects to be mitigated through other means (e.g. a loan programme weighted towards historically disadvantaged communities), or at least to be weighed against the potential benefits when choosing whether or not to adopt a system.

Ed: So it sounds like many algorithmic decisions could be too complex to “explain” to someone, even if a right to explanation became law. But you propose “counterfactual explanations” as an alternative— i.e. explaining to the subject what would have to change (e.g. about a job application) for a different decision to be arrived at. How does this simplify things?

Brent: So rather than trying to explain the entire rationale of a highly complex decision-making process, counterfactuals allow us to provide simple statements about what would have needed to be different about an individual’s situation to get a different, preferred outcome. You basically work from the outcome: you say “I am here; what is the minimum I need to do to get there?” By providing simple statements that are generally meaningful, and that reveal a small bit of the rationale of a decision, the individual has grounds to change their situation or contest the decision, regardless of their technical expertise. Understanding even a bit of how a decision is made is better than being told “sorry, you wouldn’t understand”—at least in terms of fostering trust in the system.

Sandra: And the nice thing about counterfactuals is that they work with highly complex systems, like neural nets. They don’t explain why something happened, but they explain what happened. And three things people might want to know are:

(1) What happened: why did I not get the loan (or get refused parole, etc.)?

(2) Information so I can contest the decision if I think it’s inaccurate or unfair.

(3) Even if the decision was accurate and fair, tell me what I can do to improve my chances in the future.

Machine learning and neural nets make use of so much information that individuals have really no oversight of what they’re processing, so it’s much easier to give someone an explanation of the key variables that affected the decision. With the counterfactual idea of a “close possible world” you give an indication of the minimal changes required to get what you actually want.

Ed: So would a series of counterfactuals (e.g. “over 18” “no prior convictions” “no debt”) essentially define a space within which a certain decision is likely to be reached? This decision space could presumably be graphed quite easily, to help people understand what factors will likely be important in reaching a decision?

Brent: This would only work for highly simplistic, linear models, which are not normally the type that confound human capacities for understanding. The complex systems that we refer to as ‘black boxes’ are highly dimensional and involve a multitude of (probabilistic) dependencies between variables that can’t be graphed simply. It may be the case that if I were aged between 35-40 with an income of £30,000, I would not get a loan. But, I could be told that if I had an income of £35,000, I would have gotten the loan. I may then assume that an income over £35,000 guarantees me a loan in the future. But, it may turn out that I would be refused a loan with an income above £40,000 because of a change in tax bracket. Non-linear relationships of this type can make it misleading to graph decision spaces. For simple linear models, such a graph may be a very good idea, but not for black box systems; they could, in fact, be highly misleading.

Chris: As Brent says, we’re concerned with understanding complicated algorithms that don’t just use hard cut-offs based on binary features. To use your example, maybe a little bit of debt is acceptable, but it would increase your risk of default slightly, so the amount of money you need to earn would go up. Or maybe certain convictions committed in the past also only increase your risk of defaulting slightly, and can be compensated for with higher salary. It’s not at all obvious how you could graph these complicated interdependencies over many variables together. This is why we picked on counterfactuals as a way to give people a direct and easy to understand path to move from the decision they got now, to a more favourable one at a later date.

Ed: But could a counterfactual approach just end up kicking the can down the road, if we know “how” a particular decision was reached, but not “why” the algorithm was weighted in such a way to produce that decision?

Brent: It depends what we mean by “why”. If this is “why” in the sense of, why was the system designed this way, to consider this type of data for this task, then we should be asking these questions while these systems are designed and deployed. Counterfactuals address decisions that have already been made, but still can reveal uncomfortable knowledge about a system’s design and functionality. So it can certainly inform “why” questions.

Sandra: Just to echo Brent, we don’t want to imply that asking the “why” is unimportant—I think it’s very important, and interpretability as a field has to be pursued, particularly if we’re using algorithms in highly sensitive areas. Even if we have the “what”, the “why” question is still necessary to ensure the safety of those systems.

Chris: And anyone who’s talked to a three-year old knows there is an endless stream of “Why” questions that can be asked. But already, counterfactuals provide a major step forward in answering why, compared to previous approaches that were concerned with providing approximate descriptions of how algorithms make decisions—but not the “why” or the external facts leading to that decision. I think when judging the strength of an explanation, you also have to look at questions like “How easy is this to understand?” and “How does this help the person I’m explaining things to?” For me, counterfactuals are a more immediately useful explanation, than something which explains where the weights came from. Even if you did know, what could you do with that information?

Ed: I guess the question of algorithmic decision making in society involves a hugely complex intersection of industry, research, and policy making? Are we control of things?

Sandra: Artificial intelligence (and the technology supporting it) is an area where many sectors are now trying to work together, including in the crucial areas of fairness, transparency and accountability of algorithmic decision-making. I feel at the moment we see a very multi-stakeholder approach, and I hope that continues in the future. We can see for example that industry is very concerned with it—the Partnership in AI is addressing these topics and trying to come up with a set of industry guidelines, recognising the responsibilities inherent in producing these systems. There are also lots of data scientists (eg at the OII and Turing Institute) working on these questions. Policy-makers around the world (e.g. UK, EU, US, China) preparing their countries for the AI future, so it’s on everybody’s mind at the moment. It’s an extremely important topic.

Law and ethics obviously has an important role to play. The opacity, unpredictability of AI and its potentially discriminatory nature, requires that we think about the legal and ethical implications very early on. That starts with educating the coding community, and ensuring diversity. At the same time, it’s important to have an interdisciplinary approach. At the moment we’re focusing a bit too much on the STEM subjects; there’s a lot of funding going to those areas (which makes sense, obviously), but the social sciences are currently a bit neglected despite the major role they play in recognising things like discrimination and bias, which you might not recognise from just looking at code.

Brent: Yes—and we’ll need much greater interaction and collaboration between these sectors to stay ‘in control’ of things, so to speak. Policy always has a tendency to lag behind technological developments; the challenge here is to stay close enough to the curve to prevent major issues from arising. The potential for algorithms to transform society is massive, so ensuring a quicker and more reflexive relationship between these sectors than normal is absolutely critical.

Read the full article: Sandra Wachter, Brent Mittelstadt, Chris Russell (2018) Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR. Harvard Journal of Law & Technology (Forthcoming).

This work was supported by The Alan Turing Institute under the EPSRC grant EP/N510129/1.

Sandra Wachter, Brent Mittelstadt and Chris Russell were talking to blog editor David Sutcliffe.

By coincidence, our small research team of Joss Wright, Mark Graham, and me had set out earlier in the year to investigate the economic geography of darknet markets. We had started our data collection a few weeks earlier, and the events took us by surprise: it doesn’t happen every day that a primary information source gets shut down by the police… While we had anticipated that some markets would close during our investigations, it all happened rather quickly. On the other hand, this also gave us a rare opportunity to observe what happens after such a takedown. The actions by law enforcement were deliberately structured to seed distrust in illicit trading platforms. Did this effort succeed? Let’s have a look at the data…

The chart above shows weekly trading volumes on darknet markets for the period from May to July 2017. The black line shows the overall trading volume across all markets we observed at the time. Initially, Alphabay (in blue) represented a significant share of this overall trade, while Hansa (in yellow) was comparably small. When Alphabay was closed in week 27, overall sales dropped: many traders lost their primary market. The following week, Hansa trading volumes more than doubled, until it was closed as well. More important however is the overall trend: while the takedowns lead to a short-term reduction in trade, in the longer term, people simply moved to other markets. (Note that we estimate trading volumes from buyer reviews, which are often posted days or weeks after a sale. The apparent Alphabay decline in weeks 25-27 is likely attributable to this delay in posting feedback: many reviews simply hadn’t been posted yet by the time of the market closure.)

In other words, within less than a month, overall trading volumes were back to previous levels. This matches prior research findings after similar takedown efforts — see below for links to some relevant papers. But does this suggest that the darknet market ecosystem as a whole has a kind of distributed resilience against interventions? This remains to be seen. While the demand for illicit goods appears unchanged, these markets are under increasing pressures. Since the two takedowns, there have been reports of further market closures, long-running distributed denial of service attacks, extortion attempts, and other challenges. As a result, there is renewed uncertainty about the long-term viability of these platforms. We’ll keep monitoring…

Further reading (academic):

• Décary-Hétu & Giommoni (2017), “Do police crackdowns disrupt drug cryptomarkets? A longitudinal analysis of the effects of Operation Onymous”
• Ladegaard (2017). “We Know Where You Are, What You Are Doing and We Will Catch You: Testing Deterrence Theory in Digital Drug Markets.“
• Duxbury & Haynie (2017), “Building them up, breaking them down: Topology, vendor selection patterns, and a digital drug market’s robustness to disruption”

Further reading (popular):

• Wired: “Global police spring a trap on thousands of dark web users”
• Krebs on Security: “Exclusive: Dutch Cops on AlphaBay ‘Refugees’”

The above map shows the global distribution of the Fentanyl trade on the darknet. The US accounts for almost 40% of global darknet trade, with Canada and Australia at 15% and 12%, respectively. The UK and Germany are the largest sellers in Europe with 9% and 5% of sales. While China is often mentioned as an important source of the drug, it accounts for only 4% of darknet sales. However, this does not necessarily mean that China is not the ultimate site of production. Many of the sellers in places like the US, Canada, and Western Europe are likely intermediaries rather than producers themselves.

In the next few months, we’ll be sharing more visualisations of the economic geographies of products on the darknet. In the meantime you can find out more about our work by Exploring the Darknet in Five Easy Questions.

Follow the project here: https://www.oii.ox.ac.uk/research/projects/economic-geog-darknet/

Twitter: @OiiDarknet

Research responding to this call for a better understanding of IGD is still at a formative stage, and there are active debates surrounding it. There is a growing literature that suggests there is a basis to expect that excessive or problematic gaming may be related to lower health, though findings in this area are mixed. Some argue for a theoretical framing akin to a substance abuse disorder (i.e. where gaming is considered to be inherently addictive), while others frame Internet-based gaming as a self-regulatory challenge for individuals.

In their article “A prospective study of the motivational and health dynamics of Internet Gaming Disorder“, Netta Weinstein, the OII’s Andrew Przybylski, and Kou Murayama address this gap in the literature by linking self-regulation and Internet Gaming Disorder research. Drawing on a representative sample of 5,777 American adults they examine how problematic gaming emerges from a state of individual “dysregulation” and how it predicts health — finding no evidence directly linking IGD to health over time.

This negative finding indicates that IGD may not, in itself, be robustly associated with important clinical outcomes. As such, it may be premature to invest in management of IGD using the same kinds of approaches taken in response to substance-based addiction disorders. Further, the findings suggests that more high-quality evidence regarding clinical and behavioural effects is needed before concluding that IGD is a legitimate candidate for inclusion in future revisions of the Diagnostic and Statistical Manual of Mental Disorders.

We caught up with Andy to explore the implications of the study:

Ed: To ask a blunt question upfront: do you feel that Internet Gaming Disorder is a valid psychiatric condition (and that “games can cause problems”)? Or is it still too early to say?

Andy: No, it is not. It’s difficult to overstate how sceptical the public should be of researchers who claim, and communicate their research, as if Internet addiction, gaming addiction, or Internet gaming disorder (IGD) are recognized psychiatric disorders. The fact of the matter is that American psychiatrists working on the most recent revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM5) highlighted that problematic online play was a topic they were interested in learning more about. These concerns are highlighted in Section III of the DSM5 (entitled “Emerging Measures and Models”). For those interested in this debate see this position paper.

Ed: Internet gaming seems like quite a specific activity to worry about: how does it differ from things like offline video games, online gambling and casino games; or indeed the various “problematic” uses of the Internet that lead to people admitting themselves to digital detox camps?

Andy: In some ways computer games, and Internet ones, are distinct from other activities. They are frequently updated to meet players expectations and some business models of games, such as pay-to-play are explicitly designed to target high engagement players to spend real money for in-game advantages. Detox camps are very worrying to me as a scientist because they have no scientific basis, many of those who run them have financial conflicts of interest when they comment in the press, and there have been a number of deaths at these facilities.

Ed: You say there are two schools of thought: that if IGD is indeed a valid condition, that it should be framed as an addiction, i.e. that there’s something inherently addictive about certain games. Alternatively, that it should be framed as a self-regulatory challenge, relating to an individual’s self-control. I guess intuitively it might involve a bit of both: online environments can be very persuasive, and some people are easily persuaded?

Andy: Indeed it could be. As researchers mainly interested in self-regulation we’re most interested in gaming as one of many activities that can be successfully (or unsuccessfully) integrated into everyday life. Unfortunately we don’t know much for sure about whether there is something inherently addictive about games because the research literature is based largely on inferences based on correlational data, drawn from convenience samples, with post-hoc analyses. Because the evidence base is of such low quality most of the published findings (i.e. correlations/factor analyses) regarding gaming addiction supporting it as valid condition likely suffer from the Texas Sharpshooter Fallacy.

Ed: Did you examine the question of whether online games may trigger things like anxiety, depression, violence, isolation etc. — or whether these conditions (if pre-existing) might influence the development of IGD?

Andy: Well, our modelling focused on the links between Internet Gaming Disorder, health (mental, physical, and social), and motivational factors (feeling competent, choiceful, and a sense of belonging) examined at two time points six months apart. We found that those who had their motivational needs met at the start of the study were more likely to have higher levels of health six months later and were less likely to say they experienced some of the symptoms of Internet Gaming Disorder.

Though there was no direct link between Internet Gaming Disorder and health six months later, we perform an exploratory analysis (one we did not pre-register) and found an indirect link between Internet Gaming Disorder and health by way of motivational factors. In other words, Internet Gaming Disorder was linked to lower levels of feeling competent, choiceful, and connected, which was in turn linked to lower levels of health.

Ed: All games are different. How would a clinician identify if someone was genuinely “addicted” to a particular game — there would presumably have to be game-by-game ratings of their addictive potential (like there are with drugs). How would anyone find the time to do that? Or would diagnosis focus more on the individual’s behaviour, rather than what games they play? I suppose this goes back to the question of whether “some games are addictive” or whether just “some people have poor self-control”?

Andy: No one knows. In fact, the APA doesn’t define what “Internet Games” are. In our research we define ask participants to define it for themselves by “Think[ing] about the Internet games you may play on Facebook (e.g. Farmville), Tablet/Smartphones (e.g. Candy Crush), or Computer/Consoles (e.g. Minecraft).” It’s very difficult to overstate how suboptimal this state of affairs is from a scientific perspective.

Ed: Is it odd that it was the APA’s Substance-Related Disorders Work Group that has called for research into IGD? Are “Internet Games” unique in being classed as a substance, or are there other information based-behaviours that fall under the group’s remit?

Andy: Yes it’s very odd. Our research group is not privy to these discussions but my understanding is that a range of behaviours and other technology-related activities, such as general Internet use have been discussed.

Ed: A huge amount of money must be spent on developing and refining these games, i.e. to get people to spend as much time (and money) as possible playing them. Are academics (and clinicians) always going to be playing catch-up to industry?

Andy: I’m not sure that there is one answer to this. One useful way to think of online games is using the example of a gym. Gyms are most profitable when many people are paying for (and don’t cancel) their memberships but owners can still maintain a small footprint. The world’s most successful gym might be a one square meter facility, with seven billion members but no one ever goes. Many online games are like this, some costs scale nicely, but others have high costs, like servers, community management, upkeep, and power. There are many studying the addictive potential of games but because they constantly reinvent the wheel by creating duplicate survey instruments (there are literally dozens that are only used once or a couple of times) very little of real-world relevance is ever learned or transmitted to the public.

Ed: It can’t be trivial to admit another condition into the Diagnostic and Statistical Manual of Mental Disorders (DSM-5)? Presumably there must be firm (reproducible) evidence that it is a (persistent) problem for certain people, with a specific (identifiable) cause — given it could presumably be admitted in courts as a mitigating condition, and possibly also have implications for health insurance and health policy? What are the wider implications if it does end up being admitted to the DSM-5?

Andy: It is very serious stuff. Opening the door to pathologizing one of the world’s most popular recreational activities risks stigmatizing hundreds of millions of people and shifting resources in an already overstretched mental health systems over the breaking point.

Ed: You note that your study followed a “pre-registered analysis plan” — what does that mean?

Andy: We’ve discussed the wider problems in social, psychological, and medical science before. But basically, preregistration, and Registered Reports provide scientists a way to record their hypotheses in advance of data collection. This improves the quality of the inferences researchers draw from experiments and large-scale social data science. In this study, and also in our other work, we recorded our sampling plan, our analysis plan, and our materials before we collected our data.

Ed: And finally: what follow up studies are you planning?

Andy: We are now conducting a series of studies investigating problematic play in younger participants with a focus on child-caregiver dynamics.

Read the full article: Weinstein N, Przybylski AK, Murayama K. (2017) A prospective study of the motivational and health dynamics of Internet Gaming Disorder. PeerJ 5:e3838 https://doi.org/10.7717/peerj.3838

Additional peer-reviewed articles in this area by Andy include:

Przybylski, A.K. & Weinstein N. (2017). A Large-Scale Test of the Goldilocks Hypothesis: Quantifying the Relations Between Digital Screens and the Mental Well-Being of Adolescents. Psychological Science. DOI: 10.1177/0956797616678438.

Przybylski, A. K., Weinstein, N., & Murayama, K. (2016). Internet Gaming Disorder: Investigating the Clinical Relevance of a New Phenomenon. American Journal of Psychiatry. DOI: 10.1176/appi.ajp.2016.16020224.

Przybylski, A. K. (2016). Mischievous responding in Internet Gaming Disorder research. PeerJ, 4, e2401. https://doi.org/10.7717/peerj.2401

For more on the ongoing “crisis in psychology” and how pre-registration of studies might offer a solution, see this discussion with Andy and Malte Elson: Psychology is in crisis, and here’s how to fix it.

Andy Przybylski was talking to blog editor David Sutcliffe.

There is a large and growing body of research examining rumour management on social media platforms. However, most of these studies treat it as a technical matter, and little attention has been paid to the social and political aspects of rumour. In their Policy & Internet article “How Social Media Construct ‘Truth’ Around Crisis Events: Weibo’s Rumor Management Strategies after the 2015 Tianjin Blasts“, Jing Zeng, Chung-hong Chan and King-wa Fu examine the content moderation strategies of Sina Weibo, China’s largest microblogging platform, in regulating discussion of rumours following the 2015 Tianjin blasts.

Studying rumour communication in relation to the manipulation of social media platforms is particularly important in the context of China. In China, Internet companies are licensed by the state, and their businesses must therefore be compliant with Chinese law and collaborate with the government in monitoring and censoring politically sensitive topics. Given most Chinese citizens rely heavily on Chinese social media services as alternative information sources or as grassroots “truth”, the anti-rumour policies have raised widespread concern over the implications for China’s online sphere. As there is virtually no transparency in rumour management on Chinese social media, it is an important task for researchers to investigate how Internet platforms engage with rumour content and any associated impact on public discussion.

We caught up with the authors to discuss their findings:

Ed.: “Fake news” is currently a very hot issue, with Twitter and Facebook both exploring mechanisms to try to combat it. On the flip-side we have state-sponsored propaganda now suddenly very visible (e.g. Russia), in an attempt to reduce trust, destabilise institutions, and inject rumour into the public sphere. What is the difference between rumour, propaganda and fake news; and how do they play out online in China?

Jing / Chung-hong / King-wa: The definition of rumour is very fuzzy, and it is very common to see ‘rumour’ being used interchangeably with other related concepts. Our study drew the definition of rumour from the fields of sociology and social psychology, wherein this concept has been most thoroughly articulated.

Rumour is a form of unverified information circulated in uncertain circumstances. The major difference between rumour and propaganda lies in their functions. Rumour sharing is a social practice of sense-making, therefore it functions to help people make meaning of an uncertain situation. In contrast, the concept of propaganda is more political. Propaganda is a form of information strategically used to mobilise political support for a political force.

Fake news is a new buzz word and works closely with another buzz term – post-truth. There is no established and widely accepted definition of fake news, and its true meaning(s) should be understood with respect to specific contexts. For example, Donald Trump’s use of “fake news” in his tweets aims to attack a few media outlets who have reported unfavourable stories about the him, whereas ungrounded and speculative “fake news” is created and widely circulated on the public’s social media. If we simply understand fake news as a form of fabricated news, I would argue that fake news can operate as either rumour, propaganda, or both of them.

It is worth pointing out that, in the Chinese contexts, rumour may not always be fake and propaganda is not necessarily bad. As pointed out by different scholars, rumour functions as a social protest against the authoritarian state’s information control. And in the Chinese language, the Mandarin term Xuanchuan (‘propaganda’) does not always have the same negative connotation as does its English counterpart.

Ed.: You mention previous research finding that the “Chinese government’s propaganda and censorship policies were mainly used by the authoritarian regime to prevent collective action and to maintain social stability” — is that what you found as well? i.e. that criticism of the Government is tolerated, but not organised protest?

Jing / Chung-hong / King-wa: This study examined rumour communication around the 2015 Tianjin blasts, therefore our analyses did not directly address Weibo users’ attempts to organise protest. However, regarding the Chinese government’s response to Weibo users’ criticism of its handling of the crisis, our study suggested that some criticisms of the government were tolerated. For example, the messages about local government officials mishandling of the crisis were not heavily censored. Instead, what we have found seems to confirm that social stability is of paramount importance for the ruling regime and thus online censorship was used as a mean to maintain social stability. It explains Weibo’s decision to silence the discussions on the assault of a CNN reporter, the chaotic aftermath of the blasts and the local media’s reluctance to broadcast the blasts.

Ed.: What are people’s responses to obvious government attempts to censor or head-off online rumour, e.g. by deleting posts or issuing statements? And are people generally supportive of efforts to have a “clean, rumour-free Internet”, or cynical about the ultimate intentions or effects of censorship?

Jing / Chung-hong / King-wa: From our time series analysis, we found different responses from netizens with respect to topics but we cannot find a consistent pattern of a chilling effect. Basically, the Weibo rumour management strategies, either deleting posts or refuting posts, will usually stimulate more public interest. At least as shown in our data, netizens are not supportive of those censorship efforts and somehow end up posting more messages of rumours as a counter-reaction.

Ed.: Is online rumour particularly a feature of contemporary Chinese society — or do you think that’s just a human thing (we’ve certainly seen lots of lying in the Brexit and Trump campaigns)? How might rumour relate more generally to levels of trust in institutions, and the presence of a strong, free press?

Jing / Chung-hong / King-wa: Online rumour is common in China, but it can be also pervasive in any country where use of digital technologies for communication is prevalent. Rumour sharing is a human thing, yes you can say that. But it is more accurate to say, it is a societally constructed thing. As mentioned earlier, rumour is a social practice of collective sense-making under uncertain circumstances.

Levels of public trust in governmental organisations and the media can directly impact rumour circulation, and rumour-debunking efforts. When there is a lack of public trust in official sources of information, it opens up room for rumour circulation. Likewise, when the authorities have low credibility, the official rumour debunking efforts can backfire, because the public may think the authorities are trying to hide something. This might explain what we observed in our study.

Ed.: I guess we live in interesting times; Theresa May now wants to control the Internet, Trump is attacking the very institution of the press, social media companies are under pressure to accept responsibility for the content they host. What can we learn from the Chinese case, of a very sophisticated system focused on social control and stability?

Jing / Chung-hong / King-wa: The most important implication of this study is that the most sophisticated rumour control mechanism can only be developed on a good understanding of the social roots of rumour. As our study shows, without solving the more fundamental social cause of rumour, rumour debunking efforts can backfire.

Read the full article: Jing Zeng, Chung-hong Chan and King-wa Fu (2017) How Social Media Construct ‘Truth’ Around Crisis Events: Weibo’s Rumor Management Strategies after the 2015 Tianjin Blasts. Policy & Internet 9 (3) 297-320. DOI: 10.1002/poi3.155

Jing Zeng, Chung-hong Chan and King-wa Fu were talking to blog editor David Sutcliffe.

Using cross-sectional survey data from five e-enabled elections in Estonia — a country with a decade’s experience of nationwide remote Internet voting — the authors show e-voting to be strongly persistent among voters, with clear evidence of habit formation. While a technological fix probably won’t address the underlying reasons for low turnout, it could help stop further decline by making voting easier for those who are more likely to turn out. Arresting turnout decline by keeping those who participate participating might be one realistic goal that e-voting is able to achieve.

We caught up with the authors to discuss their findings:

Ed.: There seems to be a general trend of declining electoral turnouts worldwide. Is there any form of consensus (based on actual data) on why voting rates are falling?

Mihkel / Kristjan: A consensus in terms of a single major source of turnout decline that the data points to worldwide is clearly lacking. There is however more of an agreement as to why certain regions are experiencing a comparatively steeper decline. Disenchantment with democracy and an overall disappointment in politics is the number one reason usually listed when discussing lower and declining turnout levels in new democracies.

While the same issues are nowadays also listed for older established democracies, there is no hard comparative evidence for it. We do know that the level of interest in and engagement with politics has declined across the board in Western Europe when compared to the 1960-70s, but this doesn’t count as disenchantment, and the clear decline in turnout levels in established democracies started a couple of decades later, in the early 1990s.

Given that turnout levels are still widely different depending on the country, the overall worldwide decline is probably a combination of the addition of new democracies with low and more-rapidly declining turnout levels, and a plethora of country-specific reasons in older democracies that are experiencing a somewhat less steep decline in turnout.

Ed.: Is the worry about voting decline really about “falling representation” per se, or that it might be symptomatic of deeper problems with the political ecosystem, i.e. fewer people choosing politics as a career, less involvement in local politics, less civic engagement (etc.). In other words — is falling voting (per se) even the main problem?

Mihkel / Kristjan: We can only agree; it clearly is a symptom of deeper problems. Although high turnout is a good thing, low turnout is not necessarily a problem as people have the freedom not to participate and not to be interested in politics. It becomes a problem when low turnout leads to a lack of legitimacy of the representative body and consequently also of the whole process of representation. And as you rightly point out, real problems start much earlier and at a lower level than voting in parliamentary elections. The paradox is that the technology we have examined in our article — remote internet voting — clearly can’t address these fundamental problems.

Ed.: I’m assuming the Estonian voters were voting remotely online (rather than electronically in a booth), i.e. in their own time, at their convenience? Are you basically testing the effect of offering a more convenient voting format? (And finding that format to be habit-forming?).

Mihkel / Kristjan: Yes. One of the reasons we examined Internet voting from this angle was the apparent paradox of every third vote being cast online but also only a minute increase in turnout. A few other countries also experimenting with electronic voting have seen no tangible differences in turnout levels. The explanation is of course that it is a convenience voting method that makes voting simpler for people who are already quite likely to vote — now they simply use a more convenient option to do so. But what we noted in our article was a clearly higher share of electronic voters who turned out more consistently over different elections in comparison to voters voting on paper, and even when they didn’t show traits that usually correlate with electronic voting, like living further away from polling stations. So convenience did not seem to tell the whole story, even though it might have been one of the original reasons why electronic voting was picked up.

Ed.: Presumably with remote online voting, it’s possible to send targeted advertising to voters (via email and social media), with links to vote, i.e. making it more likely people will vote in the moment, in response to whatever issues happen to be salient at the time. How does online campaigning (and targeting) change once you introduce online voting?

Mihkel / Kristjan: Theoretically, parties should be able to lock voters in more easily by advertising links to the voting solution in their online campaigns; as in banners saying “vote for me and you can do it directly here (linked)”. In the Estonian case there is an informal agreement to remain from doing that, however, in order to safeguard the neutrality of online voting. Trust in online voting is paramount, even more so than is the case with paper voting, so it probably is a good idea to try to ensure that people trust the online voting solution to be controlled by a neutral state agent tasked with conducting the elections, in order to avoid any possible associations between certain parties and the voting environment (which linking directly to the voting mechanism might cause to happen). That can never be 100% ensured though, so online campaigns coupled with online voting can make it harder for election authorities to convey the image of impartiality of their procedures.

As for voting in the moment I don’t see online voting to be substantially more susceptible to this than other voting modes — given last minute developments can influence voters voting on paper as well. I think the latest US and French presidential elections are a case in point. Some argue that the immediate developments and revelations in the Clinton email scandal investigation a couple of weeks before voting day turned the result. In the French case the hacking and release of Macron’s campaign communications immediately before voting day however didn’t play a role in the outcome. Voting in the moment will happen or not regardless of the voting mode being used.

Ed.: What do you think the barriers are to greater roll-out of online voting: presumably there are security worries, i.e. over election hacking and lack of a paper trail? (and maybe also worries about the possibility of coercive voting, if it doesn’t take place alone in a booth?)

Mihkel / Kristjan: The number one barrier to greater roll-out remains security worries about hacking. Given that people cannot observe electronic voting (i.e. how their vote arrives at the voting authorities) the role of trust becomes more central than for paper voting. And trust can be eroded easily by floating rumours even without technically compromising voting systems. The solution is to introduce verifiability into the system, akin to a physical ballot in the case of paper voting, but this makes online voting even more technologically complex.

A lot of research is being put into verifiable electronic voting systems to meet very strict security requirements. The funny thing is however that the fears holding back wider online voting are not really being raised for paper voting, even though they should. At a certain stage of the process all paper votes become bits of information in an information system as local polling stations enter or report them into computer systems that are used to aggregate the votes and determine the seat distribution. No election is fully paper based anymore.

Vote coercion problems of course cannot be ruled out and is by definition more likely when the voting authorities don’t exercise control over the immediate voting environment. I think countries that suffer from such problems shouldn’t introduce a system that might exacerbate that even more. But again, most countries allow for multiple modes that differ in the degree of neutrality and control exercised by the election authority. Absentee ballots and postal voting (which is very widespread in some countries, like Switzerland), are as vulnerable to voter coercion as is remote Internet voting. Online voting is simply one mode of voting — maintaining a healthy mix of voting modes is probably the best solution to ensure that elections are not compromised.

Ed.: I guess declining turnout is probably a problem that is too big and complex to be understood or “fixed” — but how would you go about addressing it, if asked to do so..?

Mihkel / Kristjan: We fully agree — the technology of online voting will not fix low turnout as it doesn’t address the underlying problem. It simply makes voting somewhat more convenient. But voting is not difficult in the first place — with weekend voting, postal voting and absentee ballots; just to name a few things that already ease participation.

There are technologies that have a revolutionary effect (i.e. that alter impact and that are truly innovatory) and then there are small technological fixes that provide for a simpler and more pleasurable existence. Online voting is not revolutionary; it does not give a new experience of participation, it is simply one slightly more convenient mode of voting and for that a very worthwhile thing. And I think this is the maximum that can be done and that is within our control when it comes to influencing turnout. Small incremental fixes to a large multifaceted problem.

Children have never been afforded the full sovereignty of adulthood (Cunningham, 2009) but both these concepts suggest children have become the points of application for new forms of power that have emerged from the digitisation of society. The most dominant form of this power is called “platform capitalism” (Srnicek, 2016). As a result of platform capitalism’s success, there has never been a stronger association between data, young people’s private lives, their relationships with friends and family, their life at school, and the broader political economy. In this post I will define platform capitalism, outline why it has come to dominate children’s relationship to the internet and suggest two reasons in particular why this is problematic.

Children predominantly experience the Internet through platforms

‘At the most general level, platforms are digital infrastructures that enable two or more groups to interact. They therefore position themselves as intermediaries that bring together different users: customers, advertisers, service providers, producers, suppliers, and even physical objects’ (Srnicek 2016, p43). Examples of platforms capitalism include the technology superpowers – Google, Apple, Facebook, and Amazon. There are, however, many relevant instances of platforms that children and young people use. This includes platforms for socialising, platforms for audio-visual content, platforms that communicate with smart devices and toys, and platforms for games and sports franchises and platforms that provide services (including within in the public sector) that children or their parents use.

Young people choose to use platforms for play, socialising and expressing their identity. Adults have also introduced platforms into children’s lives: for example Capita SIMS is a platform used by over 80% of schools in the UK for assessment and monitoring (over the coming months at the Oxford Internet Institute we will be studying such platforms, including SIMS, for The Oak Foundation). Platforms for personal use have been facilitated by the popularity of tablets and smartphones.

Amongst the young, there has been a sharp uptake in tablet and smart phone usage at the expense of PC or laptop use. Sixteen per cent of 3-4 year olds have their own tablet, with this incidence doubling for 5-7 year olds. By the age of 12, smartphone ownership begins to outstrip tablet ownership (Ofcom, 2016). For our research at the OII, even when we included low-income families in our sample, 93% of teenagers owned a smartphone. This has brought forth the ‘appification’ of the web that Zittrain predicted in 2008. This means that children and young people predominately experience the internet via platforms that we can think of as controlled gateways to the open web.

Platforms exist to make money for investors

In public discourse some of these platforms are called social media. This term distracts us from the reason many of these publicly floated companies exist: to make money for their investors. It is only logical for all these companies to pursue the WeChat model that is becoming so popular in China. WeChat is a closed circuit platform, in that it keeps all engagements with the internet, including shopping, betting, and video calls, within its corporate compound. This brings WeChat closer to monopoly on data extraction.

Platforms have consolidated their success by buying out their competitors. Alphabet, Amazon, Apple, Facebook and Microsoft have made 436 acquisitions worth $131 billion over the last decade (Bloomberg, 2017). Alternatively, they just mimic the features of their competitors. For example, when Facebook acquired Instagram it introduced Stories, a feature use by Snapchat, which lets its users upload photos and videos as a ‘story’ (that automatically expires after 24 hours).

The more data these companies capture that their competitors are unable to capture, the more value they can extract from it and the better their business model works. It is unsurprising therefore that during our research we asked groups of teenagers to draw a visual representation of what they thought the world wide web and internet looked like – almost all of them just drew corporate logos (they also told us they had no idea that platforms such as Facebook own WhatsApp and Instagram, or that Google owns YouTube). Platform capitalism dominates and controls their digital experiences — but what provisions do these platforms make for children?

The General Data Protection Regulation (GDPR) (set to be implemented in all EU states, including the UK, in 2018) says that platforms collecting data about children below the age of 13 years shall only be lawful if and to the extent that consent is given or authorised by the child’s parent or custodian. Because most platforms are American-owned, they tend to apply a piece of Federal legislation known as COPPA; the age of consent for using Snapchat, WhatsApp, Facebook, and Twitter, for example, is therefore set at 13. Yet, the BBC found last year that 78% of children aged 10 to 12 had signed up to a platform, including Facebook, Instagram, Snapchat and WhatsApp.

Platform capitalism offloads its responsibilities onto the user

Why is this a problem? Firstly, because platform capitalism offloads any responsibility onto problematically normative constructs of childhood, parenting, and paternal relations. The owners of platforms assume children will always consult their parents before using their services and that parents will read and understand their terms and conditions, which, research confirms, in reality few users, children or adults, even look at.

Moreover, we found in our research many parents don’t have the knowledge, expertise, or time to monitor what their children are doing online. Some parents, for instance, worked night shifts or had more than one job. We talked to children who regularly moved between homes and whose estranged parents didn’t communicate with each other to supervise their children online. We found that parents who are in financial difficulties, or affected by mental and physical illness, are often unable to keep on top of their children’s digital lives.

We also interviewed children who use strategies to manage their parent’s anxieties so they would leave them alone. They would, for example, allow their parents to be their friends on Facebook, but do all their personal communication on other platforms that their parents knew nothing about. Often then the most vulnerable children offline, children in care for example, are the most vulnerable children online. My colleagues at the OII found 9 out of 10 of the teenagers who are bullied online also face regular ‘traditional’ bullying. Helping these children requires extra investment from their families, as well as teachers, charities and social services. The burden is on schools too to address the problem of fake news and extremism such as Holocaust denialism that children can read on platforms.

This is typical of platform capitalism. It monetises what are called social graphs: i.e. the networks of users who use its platforms that it then makes available to advertisers. Social graphs are more than just nodes and edges representing our social lives: they are embodiments of often intimate or very sensitive data (that can often be de-anonymised by linking, matching and combining digital profiles). When graphs become dysfunctional and manifest social problems such as abuse, doxxing, stalking, and grooming), local social systems and institutions — that are usually publicly funded — have to deal with the fall-out. These institutions are often either under-resourced and ill-equipped to these solve such problems, or they are already overburdened.

Are platforms too powerful?

The second problem is the ecosystems of dependency that emerge, within which smaller companies or other corporations try to monetise their associations with successful platforms: they seek to get in on the monopolies of data extraction that the big platforms are creating. Many of these companies are not wealthy corporations and therefore don’t have the infrastructure or expertise to develop their own robust security measures. They can cut costs by neglecting security or they subcontract out services to yet more companies that are added to the network of data sharers.

Again, the platforms offload any responsibility onto the user. For example, WhatsApp tells its users; “Please note that when you use third-party services, their own terms and privacy policies will govern your use of those services”. These ecosystems are networks that are only as strong as their weakest link. There are many infamous examples that illustrate this, including the so-called ‘Snappening’ where sexually explicit pictures harvested from Snapchat — a platform that is popular with teenagers — were released on to the open web. There is also a growing industry in fake apps that enable illegal data capture and fraud by leveraging the implicit trust users have for corporate walled gardens.

What can we do about these problems? Platform capitalism is restructuring labour markets and social relations in such a way that opting out from it is becoming an option available only to a privileged few. Moreover, we found teenagers whose parents prohibited them from using social platforms often felt socially isolated and stigmatised. In the real world of messy social reality, platforms can’t continue to offload their responsibilities on parents and schools.

We need some solutions fast because, by tacitly accepting the terms and conditions of platform capitalism – particularly when that they tell us it is not responsible for the harms its business model can facilitate – we may now be passing an event horizon where these companies are becoming too powerful, unaccountable, and distant from our local reality.

References

Hugh Cunningham (2009) Children and Childhood in Western Society Since 1500. Routledge.

Sonia Livingstone, Amanda Third (2017) Children and young people’s rights in the digital age: An emerging agenda. New Media and Society 19 (5).

Deborah Lupton, Ben Williamson (2017) The datafied child: The dataveillance of children and implications for their rights. New Media and Society 19 (5).

Nick Srnicek (2016) Platform Capitalism. Wiley.

But we’re not buying anything, just looking. The stringent ethics process governing his research means he currently can’t even contact anyone on the marketplace.

[Read more: Exploring the Darknet in Five Easy Questions]

Martin Dittus is a Data Scientist at the Oxford Internet Institute, and I’ve come to his office to find out about the OII’s investigation (undertaken with Mark Graham and Joss Wright) of the economic geographies of illegal economic activities in anonymous Internet marketplaces, or more simply: “mapping the darknet”. Basically: what’s being sold, by whom, from where, to where, and what’s the overall value?

Between 2011 and 2013, the Silk Road marketplace attracted hundreds of millions of dollars worth of bitcoin-based transactions before being closed down by the FBI, but relatively little is known about the geography of this global trade. The darknet throws up lots of interesting research topics: around traffic in illegal wildlife products, the effect of healthcare policies on demand for illegal prescription drugs, whether law enforcement has (or can have) much of an impact, questions around the geographies of trade (e.g. sites of production and consumption), and the economics of these marketplaces — as well as the ethics of researching all this.

OII researchers tend to come from very different disciplinary backgrounds, and I’m always curious about what brings people here. A computer scientist by training, Martin first worked as a software developer for Last.fm, an online music community that built some of the first pieces of big data infrastructure, “because we had a lot of data and very little money.” In terms of the professional experience he says it showed him how far you can get by being passionate about your work — and the importance of resourcefulness; “that a good answer is not to say, ‘No, we can’t do that,’ but to say: ‘Well, we can’t do it this way, but here are three other ways we can do it instead.’”

Resourcefulness is certainly something you need when researching darknet marketplaces. Two very large marketplaces (AlphaBay and Hansa) were recently taken down by the FBI, DEA and Dutch National Police, part-way through Martin’s data collection. Having your source suddenly disappear is a worry for any long-term data scraping process. However in this case, it raises the opportunity of moving beyond a simple observational study to a quasi-experiment. The disruption allows researchers to observe what happens in the overall marketplace after the external intervention — does trade actually go down, or simply move elsewhere? How resilient are these marketplaces to interference by law enforcement?

Having originally worked in industry for a few years, Martin completed a Master’s programme at UCL’s Centre for Advanced Spatial Analysis, which included training in cartography. The first time I climbed the three long flights of stairs to his office to say hello we quickly got talking about crisis mapping platforms, something he’d subsequently worked on during his PhD at UCL. He’s particularly interested in the historic context for the recent emergence of these platforms, where large numbers of people come together over a shared purpose: “Platforms like Wikipedia, for example, can have significant social and economic impact, while at the same time not necessarily being designed platforms. Wikipedia is something that kind of emerged, it’s the online encyclopaedia that somehow worked. For me that meant that there is great power in these platform models, but very little understanding of what they actually represent, or how to design them; even how to conceptualise them.”

“You can think of Wikipedia as a place for discourse, as a community platform, as an encyclopaedia, as an example of collective action. There are many theoretical ways to interpret it, and I think this makes it very powerful, but also very hard to understand what Wikipedia is; or indeed any large and complex online platform, like the darknet markets we’re looking at now. I think we’re at a moment in history where we have this new superpower that we don’t fully understand yet, so it’s a time to build knowledge.” Martin claims to have become “a PhD student by accident” while looking for a way to participate in this knowledge building: and found that doing a PhD was a great way to do so.

Whether discussing Wikipedia, crisis-mapping, the darknet, or indeed data infrastructures, it’s great to hear people talking about having to study things from many different angles — because that’s what the OII, as a multidisciplinary department, does in spades. It’s what we do. And Martin certainly agrees: “I feel incredibly privileged to be here. I have a technical background, but these are all intersectional, interdisciplinary, highly complex questions, and you need a cross-disciplinary perspective to look at them. I think we’re at a point where we’ve built a lot of the technological building blocks for online spaces, and what’s important now are the social questions around them: what does it mean, what are those capacities, what can we use them for, and how do they affect our societies?”

Social questions around darknet markets include the development of trust relationships between buyers and sellers (despite the explicit goal of law enforcement agencies to fundamentally undermine trust between them); identifying societal practices like consumption of recreational drugs, particularly when transplanted into a new online context; and the nature of market resilience, like when markets are taken down by law enforcement. “These are not, at core, technical questions,” Martin says. “Technology will play a role in answering them, but fundamentally these are much broader questions. What I think is unique about the OII is that it has a strong technical competence in its staff and research, but also a social, political, and economic science foundation that allows a very broad perspective on these matters. I think that’s absolutely unique.”

There were only a few points in our conversation where Martin grew awkward, a few topics he said he “would kind of dance around“ rather than provide on-record chat for a blog post. He was keen not to inadvertently provide a how-to guide for obtaining, say, fentanyl on the darknet; there are tricky unanswered questions of class (do these marketplaces allow a gentrification of illegal activities?) and the whitewashing of the underlying violence and exploitation inherent to these activities (thinking again about blood cannabis); and other areas where there’s simply not yet enough research to make firm pronouncements.

But we’ll certainly touch on some of these areas as we document the progress of the project over the coming months, exploring some maps of the global market as they are released, and also diving into the ethics of researching the darknet; so stay tuned!

Until then, Martin Dittus can be found at:

Web: https://www.oii.ox.ac.uk/people/martin-dittus/
Email: martin.dittus@oii.ox.ac.uk
Twitter: @dekstop

Follow the darknet project at: https://www.oii.ox.ac.uk/research/projects/economic-geog-darknet/

Twitter: @OiiDarknet

We caught up with Martin Dittus, a data scientist working with Mark Graham and Joss Wright on the OII’s darknet mapping project, to find out some basics about darknet markets, and why they’re interesting to study.

Firstly: what actually is the darknet?

Martin: The darknet is simply a part of the Internet you access using anonymising technology, so you can visit websites without being easily observed. This allows you to provide (or access) services online that can’t be tracked easily by your ISP or law enforcement. There are actually many ways in which you can visit the darknet, and it’s not technically hard. The most popular anonymising technology is probably Tor. The Tor browser functions just like Chrome, Internet Explorer or Firefox: it’s a piece of software you install on your machine to then open websites. It might be a bit of a challenge to know which websites you can then visit (you won’t find them on Google), but there are darknet search engines, and community platforms that talk about it.

The term ‘darknet’ is perhaps a little bit misleading, in that a lot of these activities are not as hidden as you might think: it’s inconvenient to access, and it’s anonymising, but it’s not completely hidden from the public eye. Once you’re using Tor, you can see any information displayed on darknet websites, just like you would on the regular internet. It is also important to state that this anonymisation technology is entirely legal. I would personally even argue that such tools are important for democratic societies: in a time where technology allows pervasive surveillance by your government, ISP, or employer, it is important to have digital spaces where people can communicate freely.

And is this also true for the marketplaces you study on the darknet?

Martin: Definitely not! Darknet marketplaces are typically set up to engage in the trading of illicit products and services, and as a result are considered criminal in most jurisdictions. These market platforms use darknet technology to provide a layer of anonymity for the participating vendors and buyers, on websites ranging from smaller single-vendor sites to large trading platforms. In our research, we are interested in the larger marketplaces, these are comparable to Amazon or eBay — platforms which allow many individuals to offer and access a variety of products and services.

The first darknet market platform to acquire some prominence and public reporting was the Silk Road — between 2011 and 2013, it attracted hundreds of millions of dollars worth of bitcoin-based transactions, before being shut down by the FBI. Since then, many new markets have been launched, shut down, and replaced by others… Despite the size of such markets, relatively little is known about the economic geographies of the illegal economic activities they host. This is what we are investigating at the Oxford Internet Institute.

And what do you mean by “economic geography”?

Martin: Economic geography tries to understand why certain economic activity happens in some places, but not others. In our case, we might ask where heroin dealers on darknet markets are geographically located, or where in the world illicit weapon dealers tend to offer their goods. We think this is an interesting question to ask for two reasons. First, because it connects to a wide range of societal concerns, including drug policy and public health. Observing these markets allows us to establish an evidence base to better understand a range of societal concerns, for example by tracing the global distribution of certain emergent practices. Second, it falls within our larger research interest of internet geography, where we try to understand the ways in which the internet is a localised medium, and not just a global one as is commonly assumed.

So how do you go about studying something that’s hidden?

Martin: While the strong anonymity on darknet markets makes it difficult to collect data about the geography of actual consumption, there is a large amount of data available about the offered goods and services themselves. These marketplaces are highly structured — just like Amazon there’s a catalogue of products, every product has a title, a price, and a vendor who you can contact if you have questions. Additionally, public customer reviews allow us to infer trading volumes for each product. All these things are made visible, because these markets seek to attract customers. This allows us to observe large-scale trading activity involving hundreds of thousands of products and services.

Almost paradoxically, these “hidden” dark markets allow us to make visible something that happens at a societal level that otherwise could be very hard to research. By comparison, studying the distribution of illicit street drugs would involve the painstaking investigative work of speaking to individuals and slowly trying to acquire the knowledge of what is on offer and what kind of trading activity takes place; on the darknet it’s all right there. There are of course caveats: for example, many markets allow hidden listings, which means we don’t know if we’re looking at all the activity. Also, some markets are more secretive than others. Our research is limited to platforms that are relatively open to the public.

Finally: will you be sharing some of the data you’re collecting?

Martin: This is definitely our intention! We have been scraping the largest marketplaces, and are now building a reusable dataset with geographic information at the country level. Initially, this will be used to support some of our own studies. We are currently mapping, visualizing, and analysing the data, building a fairly comprehensive picture of darknet market trades. It is also important for us to state that we’re not collecting detailed consumption profiles of participating individuals (not that we could). We are independent academic researchers, and work neither with law enforcement, nor with platform providers.

Primarily, we are interested in the activity as a large-scale global phenomenon, and for this purpose, it is sufficient to look at trading data in the aggregate. We’re interested in scenarios that might allow us to observe and think about particular societal concerns, and then measure the practices around those concerns in ways that are quite unusual, that otherwise would be very challenging. Ultimately, we would like to find ways of opening up the data to other researchers, and to the wider public. There are a number of practical questions attached to this, and the specific details are yet to be decided — so stay tuned!

Martin Dittus is a researcher and data scientist at the Oxford Internet Institute, where he studies the economic geography of darknet marketplaces. More: @dekstop

Follow the project here: https://www.oii.ox.ac.uk/research/projects/economic-geog-darknet/

Twitter: @OiiDarknet

Further reading (academic):

• Dolliver et al. (2016), “A Geographic Analysis of Drug Trafficking patterns on the Tor Network”. Geographical Review DOI: 10.1111/gere.12241
• Buskirk et al. (2016), “Who Sells What? Country Specific Differences in Substance Availability on the Agora Cryptomarket”. International Journal of Drug Policy 35: 16-23.
• Broséus et al. (2017), “A Geographical Analysis of Trafficking on a Popular Darknet Market”. Forensic Science International 277:88-102.

Further reading (popular):

• Wired: Dark net drug markets kept alive by great customer service
• The Guardian: Dark web marketplaces AlphaBay and Hansa shut down

Martin Dittus was talking to OII Managing Editor David Sutcliffe.

In his Policy & Internet article “Platform Logic: An Interdisciplinary Approach to the Platform-based Economy“, Jonas Andersson Schwarz argues that digital platforms enact a twofold logic of micro-level technocentric control and macro-level geopolitical domination, while supporting a range of generative outcomes between the two levels. Technology isn’t ‘neutral’, and what designers want may clash with what users want: so it’s important that we take a multi-perspective view of the role of digital platforms in contemporary society. For example, if we only consider the technical, we’ll notice modularity, compatibility, compliance, flexibility, mutual subsistence, and cross-subsidization. By contrast, if we consider ownership and organizational control, we’ll observe issues of consolidation, privatization, enclosure, financialization and protectionism.

When focusing on local interactions (e.g. with users), the digital nature of platforms is seen to strongly determine structure; essentially representing an absolute or totalitarian form of control. When we focus on geopolitical power arrangements in the “platform society”, patterns can be observed that are worryingly suggestive of market dominance, colonization, and consolidation. Concerns have been expressed that these (overwhelmingly US-biased) platform giants are not only enacting hegemony, but are on a road to “usurpation through tech — a worry that these companies could grow so large and become so deeply entrenched in world economies that they could effectively make their own laws”.

We caught up with Jonas to discuss his findings:

Ed.: You say that there are lots of different ways of considering “platforms”: what (briefly) are some of these different approaches, and why should they be linked up a bit? Certainly the conference your paper was presented at (“IPP2016: The Platform Society”) seemed to have struck an incredibly rich seam in this topic, and I think showed the value of approaching an issue like digital platforms from multiple disciplinary angles.

Jonas: In my article I’ve chosen to exclusively theorize *digital* platforms, which of course narrows down the meaning of the concept, to begin with. There are different interpretations as for what actually constitutes a digital platform. There has to be an element of proprietary control over the surface on which interaction takes place, for example. While being ubiquitous digital tools, free software and open protocols need not necessarily be considered as platforms, while proprietary operating systems should.

Within contemporary media studies there is considerable divergence as to whether one should define so-called over-the-top streaming services as platforms or not. Netflix, for example: In a strict technical sense, it’s not a platform for self-publishing and sharing in the way that YouTube is—but, in an economic sense, Netflix definitely enacts a multi-sided market, which is one of the key components of a what a platform does, economically speaking. Since platforms crystallize economic relationships into material infrastructure, conceptual conflation of this kind is unavoidable—different scholars tend to put different emphasis on different things.

Hence, when it comes to normative concerns, there are numerous approaches, ranging from largely apolitical computer science and design management studies, brandishing a largely optimistic view where blithe conceptions of innovation and generativity are emphasized, to critical approaches in political economy, where things like market dominance and consolidation are emphasized.

In my article, I try to relate to both of these schools of thought, by noting that they each are normative — albeit in vastly different ways — and by noting that not only do they each have somewhat different focus, they actually bring different research objects to the table: Usually, “efficacy” in purely technical interaction design is something altogether different than “efficacy” in matters of societal power relations, for example. While both notions can be said to be true, their respective validity might differ, depending on which matter of concern we are dealing with in each respective inquiry.

Ed.: You note in your article that platforms have a “twofold logic of micro-level technocentric control and macro-level geopolitical domination” .. which sounds quite a lot like what government does. Do you think “platform as government” is a useful way to think about this, i.e. are there any analogies?

Jonas: Sure, especially if we understand how platforms enact governance in really quite rigid forms. Platforms literally transform market relations into infrastructure. Compared to informal or spontaneous social structures, where there’s a lot of elasticity and ambiguity — put simply, giving-and-taking — automated digital infrastructure operates by unambiguous implementations of computer code. As Lawrence Lessig and others have argued, the perhaps most dangerous aspect of this is when digital infrastructures implement highly centralized modes of governance, often literally only having one point of command-and-control. The platform owner flicks a switch, and then certain listings and settings are allowed or disallowed, and so on…

This should worry any liberal, since it is a mode of governance that is totalitarian by nature; it runs counter to any democratic, liberal notion of spontaneous, emergent civic action. Funnily, a lot of Silicon Valley ideology appears to be indebted to theorists like Friedrich von Hayek, who observed a calculative rationality emerging out of heterogeneous, spontaneous market activity — but at the same time, Hayek’s call to arms was in itself a reaction to central planning of the very kind that I think digital platforms, when designed in too rigid a way, risk erecting.

Ed.: Is there a sense (in hindsight) that these platforms are basically the logical outcome of the ruthless pursuit of market efficiency, i.e. enabled by digital technologies? But is there also a danger that they could lock out equitable development and innovation if they become too powerful (e.g. leading to worries about market concentration and anti-trust issues)? At one point you ask: “Why is society collectively acquiescing to this development?” .. why do you think that is?

Jonas: The governance aspect above rests on a kind of managerialist fantasy of perfect calculative rationality that is conferred upon the platform as an allegedly neutral agent or intermediary; scholars like Frank Pasquale have begun to unravel some of the rather dodgy ideology underpinning this informational idealism, or “dataism,” as José van Dijck calls it. However, it’s important to note how much of this risk for overly rigid structures comes down to sheer design implementation; I truly believe there is scope for more democratically adaptive, benign platforms, but that can only be achieved either through real incentives at the design stage (e.g. Wikipedia, and the ways in which its core business idea involves quality control by design), or through ex-post regulation, forcing platform owners to consider certain societally desirable consequences.

Ed.: A lot of this discussion seems to be based on control. Is there a general theory of “control” — i.e. are these companies creating systems of user management and control that follow similar conceptual / theoretical lines, or just doing “what seems right” to them in their own particular contexts?

Jonas: Down the stack, there is always a binary logic of control at play in any digital infrastructure. Still, on a higher level in the stack, as more complexity is added, we should expect to see more non-linear, adaptive functionality that can handle complexity and context. And where computational logic falls short, we should demand tolerable degrees of human moderation, more than there is now, to be sure. Regulators are going this way when it comes to things like Facebook and hate speech, and I think there is considerable consumer demand for it, as when disputes arise on Airbnb and similar markets.

Ed.: What do you think are the main worries with the way things are going with these mega-platforms, i.e. the things that policy-makers should hopefully be concentrating on, and looking out for?

Jonas: Policymakers are beginning to realize the unexpected synergies that big data gives rise to. As The Economist recently pointed out, once you control portable smartphones, you’ll have instant geopositioning data on a massive scale — you’ll want to own and control map services because you’ll then also have data on car traffic in real time, which means you’d be likely to have the transportation market cornered, self driving cars especially… If one takes an agnostic, heterodox view on companies like Alphabet, some of their far-flung projects actually begin to make sense, if synergy is taken into consideration. For automated systems, the more detailed the data becomes, the better the system will perform; vast pools of data get to act as protective moats.

One solution that The Economist suggests, and that has been championed for years by internet veteran Doc Searls, is to press for vastly increased transparency in terms of user data, so that individuals can improve their own sovereignty, control their relationships with platform companies, and thereby collectively demand that the companies in question disclose the value of this data — which would, by extent, improve signalling of the actual value of the company itself. If today’s platform companies are reluctant to do this, is that because it would perhaps reveal some of them to be less valuable than what they are held out to be?

Another potentially useful, proactive measure, that I describe in my article, is the establishment of vital competitors or supplements to the services that so many of us have gotten used to being provided for by platform giants. Instead of Facebook monopolizing identity management online, which sadly seems to have become the norm in some countries, look to the Scandinavian example of BankID, which is a platform service run by a regional bank consortium, offering a much safer and more nationally controllable identity management solution.

Alternative platform services like these could be built by private companies as well as state-funded ones; alongside privately owned consortia of this kind, it would be interesting to see innovation within the public service remit, exploring how that concept could be re-thought in an era of platform capitalism.

Read the full article: Jonas Andersson Schwarz (2017) Platform Logic: An Interdisciplinary Approach to the Platform-based Economy. Policy & Internet DOI: 10.1002/poi3.159.

Jonas Andersson Schwarz was talking to blog editor David Sutcliffe.

The workshop welcomed a wide range of advocates in areas of intimate partner violence and sex work; engineers, designers, developers, and academics working on IT ethics. The objectives of the day were threefold:

(1) to better understand the lack of gender considerations in technology design,

(2) to formulate critical questions for functional requirement discussions between advocates and developers of gender-based violence applications; and

(3) to establish a set of criteria by which new applications can be assessed from a gender perspective.

Following three conceptual takeaways from the workshop, we share instructive primers for developers interested in creating technologies for those affected by gender-based violence.

Survivors, sex workers, and young people are intentional technology users

Increasing public awareness of the prevalence gender-based violence, both on and offline, often frames survivors of gender-based violence, activists, and young people as vulnerable and helpless. Contrary to this representation, those affected by gender-based violence are intentional technology users, choosing to adopt or abandon tools as they see fit. For example, sexual assault victims strategically disclose their stories on specific social media platforms to mobilize collective action. Sex workers adopt locative technologies to make safety plans. Young people utilize secure search tools to find information about sexual health resources near them. To fully understand how and why some technologies appear to do more for these communities, developers need to pay greater attention to the depth of their lived experience with technology.

Context matters

Technologies designed with good intentions do not inherently achieve their stated objectives. Functions that we take for granted to be neutral, such as a ‘Find my iPhone’ feature, can have unintended consequences. In contexts of gender-based violence, abusers and survivors appropriate these technological tools. For example, survivors and sex workers can use such a feature to share their whereabouts with friends in times of need. Abusers, on the other hand, can use the locative functions to stalk their victims. It is crucial to consider the context within which a technology is used, the user’s relationship to their environment, their needs, and interests so that technologies can begin to support those affected by gender-based violence.

Vulnerable communities perceive unique affordances

Drawing from ecological psychology, technology scholars have described this tension between design and use as affordance, to explain how a user’s perception of what can and cannot be done on a device informs their use. Designers may create a technology with a specific use in mind, but users will appropriate, resist, and improvise their use of the features as they see fit. For example, the use of a hashtags like #SurvivorPrivilege is an example of how rape victims create in-groups on Twitter to engage in supportive discussions, without the intention of it going viral.

Action Item

1. Predict unintended outcomes

Relatedly, the idea of devices as having affordances allows us to detect how technologies lead to unintended outcomes. Facebook’s ‘authentic name’ policy may have been instituted to promote safety for victims of relationship violence. The social and political contexts in which this policy is used, however, disproportionately affects the safety of human rights activists, drag queens, sex workers, and others — including survivors of partner violence.

2. Question the default

Technology developers are in a position to design the default settings of their technology. Since such settings are typically left unchanged by users, developers must take into account the effect on their target end users. For example, the default notification setting for text messages display the full message content in home screen. A smartphone user may experience texting as a private activity, but the default setting enables other people who are physically co-present to be involved. Opting out of this default setting requires some technical knowledge from the user. In abusive relationships, the abuser can therefore easily access the victim’s text messages through this default setting. So, in designing smartphone applications for survivors, developers should question the default privacy setting.

3. Inclusivity is not generalizability

There appears to be an equation of generalizability with inclusivity. An alarm button that claims to be for generally safety purposes may take a one-size-fits-all approach by automatically connecting the user to law enforcement. In cases of sexual assault, especially involving those who are of color, in sex work, or of LGBTQ identities, survivors are likely to avoid such features precisely because of its connection to law enforcement. This means that those who are most vulnerable are inadvertently excluded from the feature. Alternatively, an alarm feature that centers on these communities may direct the user to local resources. Thus, a feature that is generalizable may overlook target groups it aims to support; a more targeted feature may have less reach, but meet its objective. Just as communities’ needs are context-based, inclusivity, too, is contextualized. Developers should realize that that the broader mission of inclusivity can in fact be completed by addressing a specific need, though this may reduce the scope of end-users.

4. Consider co-designing

How, then, can we develop targeted technologies? Workshop participants suggested co-design (similarly, user-participatory design) as a process through which marginalized communities can take a leading role in developing new technologies. Instead of thinking about communities as passive recipients of technological tools, co-design positions both target communities and technologists as active agents who share skills and knowledge to develop innovative, technological interventions.

5. Involve funders and donors

Breakout group discussions pointed out how developers’ organizational and funding structures play a key role in shaping the kind of technologies they create. Suggested strategies included (1) educating donors about the specific social issue being addressed, (2) carefully considering whether funding sources meet developers’ objectives, and (3) ensuring diversity in the development team.

6. Do no harm with your research

In conducting user research, academics and technologists aim to better understand marginalized groups’ technology uses because they are typically at the forefront of adopting and appropriating digital tools. While it is important to expand our understanding of vulnerable communities’ everyday experience with technology, research on this topic can be used by authorities to further marginalize and target these communities. Take, for example, how tech startups like this align with law enforcement in ways that negatively affect sex workers. To ensure that research done about communities can actually contribute to supporting those communities, academics and developers must be vigilant and cautious about conducting ethical research that protects its subjects.

7. Should this app exist?

The most important question to address at the beginning of a technology design process should be: Should there even be an app for this? The idea that technologies can solve social problems as long as the technologists just “nerd harder” continues to guide the development and funding of new technologies. Many social problems are not necessarily data problems that can be solved by an efficient design and padded with enhanced privacy features. One necessary early strategy of intervention is to simply raise the question of whether technologies truly have a place in the particular context and, if so, whether it addresses a specific need.

Our workshop began with big questions about the intersections of gender-based violence and technology, and concluded with a simple but piercing question: Who designs what for whom? Implicated here are the complex workings of gender, sexuality, and power embedded in the lifetime of newly emerging devices from design to use. Apps and platforms can certainly have their place when confronting social problems, but the flow of data and the revealed information must be carefully tailored to the target context.

If you want to be involved with these future projects, please contact Kate Sim or Ben Zevenbergen.

The workshop was funded by the Princeton’s Center for Information Technology Policy (CITP), Princeton’s University Center for Human Values, the Ford Foundation, the Mozilla Foundation, and Princeton’s Council on Science and Technology.

This post was originally posted on CITP’s Freedom to Tinker blog.

A third way in employment classification

In the U.S. policy debate around the gig economy, many have called for a ‘third category’ between protected employment and unprotected self-employment. The interesting thing is that in the UK such a category already exists. An employment tribunal decision last year determined that Uber drivers were not employees or contractors, but ‘workers’, enjoying some of the benefits of employment but not all. The review recommends making use this ‘worker’ category and renaming it ‘dependent contractor’.

The review calls for greater emphasis on control over one’s work as a factor in determining whether someone is a ‘dependent contractor’ or genuinely self-employed. The question of control has featured prominently in recent research on gig economy platforms (see, for example: Rosenblat & Stark 2016, Graham et al. 2017). Uber promises freedom, but in practice uses a variety of nudges and constraints to manage workers quite closely. Platforms for digitally delivered work like graphic design don’t necessarily try to control the workers in the same way at all. So focusing on control can help distinguish between the employment status implications of different platforms, which can be quite different.

Of course, the fact that someone is genuinely self-employed doesn’t necessarily mean that they are well off. Self-employed people are often relatively poor and suffer from unpredictability of income. So it’s good that the report also calls for extending more safety nets and other support to self-employed people (p. 74-81).

The report also calls for greater clarity in law, and for alignment of the definitions between different branches of law (employment law and tax law, p. 38). This seems like such an obvious thing to do. As someone coming from a civil law system, I have always marvelled at common law’s ability to evolve through court decisions, but that spontaneous and complex evolution has a price. As the Review states, many people in Britain don’t know their rights, and even if they do, it is often prohibitively expensive to pursue them.

Fair piece rates

The Review’s section on piece rates (p. 38) is very interesting and in many ways forward-looking, but likely to cause contention.

Piece rates mean that workers are paid on the basis of the number of tasks completed (e.g. meals delivered) rather than on the basis of hours worked. This is how many gig work platforms function today. The Review suggests that platforms be required to use their data to calculate how much a worker can earn per hour from such piece rates, given what they know about the demand for the tasks and how long it usually takes to complete them. Based on this calculation, platforms would be required to set their piece rate so that on average it produces an hourly rate that clears the National Minimum Wage with a 20% margin of error.

One argument likely to be put forward in opposition is that since platforms have all the data necessary to calculate the average hourly rate, why don’t they just pay the average hourly rate instead of the piece rate? As the Review notes, piece rates are used in work where the employer cannot monitor the hours worked, such as for people who fill envelopes with information for mailshots from home. Platforms usually monitor their pieceworkers intensively, so they could just as well pay hourly rates.

I think this is a fairly strong argument, but not without its limits. Piece rates are a substitute for more direct managerial control. Employers who pay hourly rates are pickier about whom they accept into their ranks in the first place, whereas one of the strengths of these platforms is that essentially anyone can sign up and start working right away with a minimal hurdle. And workers who are paid on an hourly basis usually cannot take breaks quite as easily as pieceworkers. This low entry barrier and potential for almost minute-by-minute flexibility are genuine features of platform-based piecework, and some workers value them.

I say potential for flexibility, because actual flexibility for the worker depends on how much work there is available on the platform, as I discuss in an upcoming paper. Pieceworkers also have to put more effort into managing their own time than regular workers, though platform design can ameliorate this.

Flexibility or erosion?

The Review moreover suggests that platforms should be allowed to offer piecework at times when demand is so low as to result in hourly earnings below minimum wage, as long as the worker is fully informed of this. To quote: “If an individual knowingly chooses to work through a platform at times of low demand, then he or she should take some responsibility for this decision.” (p. 38) This is likely to be a very contentious point.

On the one hand, the report is using an old trope of laissez-faire labour policy: if the worker chooses to work for such low pay, or in such terrible conditions, who are we to stop them? Yet such choices are not independent, but shaped by and constitutive of wider structural forces. If there is nothing else on offer, of course the worker will rather accept a pittance than starve; but if every labourer accepted a pittance, soon employers would find it necessary to offer little else. The minimum wage must thus remain inviolable as a bulwark against exploitation, goes the labour movement refrain.

On the other hand, it is probably also true that much of the work that is available on platforms during off-hours will simply not be done if the cost is higher (and indeed was not done before platforms arrived). Eaters will cook at home or pick up a meal themselves instead of paying double for delivery. Part of the value of platforms is that they make marginal, low-value transactions at least somewhat feasible by matching interested parties and bringing down transaction costs. In doing so they grow the total pie of work available. As an incremental source of income for someone with another job or studies, these edges of the pie may be very appealing.

The challenge for policymakers is to prevent what is intended to be a side gig for students from becoming the desperate sustenance of families. In 1999, Japan deregulated the use of temporary contract workers, partly with the aim of helping students and housewives gain work experience and earn additional income to supplement the salaries of the male breadwinners, who enjoyed life-long employment. Less than a decade later, almost a third of the labour force found themselves on such contracts, including millions of breadwinners (Imai 2011).

The same pros and cons also apply to the idea of the third ‘dependent contractor’ category: it could help employers accommodate more diverse life situations and business models, but it could also represent an erosion of rights if regular employees eventually find themselves in that category. Early results from our ongoing research suggest that some Fortune 500 companies that are experimenting with online gig work platforms are not doing so with the intention of replacing regular employees, but as a complement and substitute to temporary staffing agencies. But statistics will be necessary to evaluate the wider impacts of platforms on labour markets and society.

Statistics on the gig economy

When it comes to statistics, the Review points out that “official data is not likely to include the increasing number of people earning additional money in a more casual way, through the use of online platforms for example” (p. 25). This is a real problem: official labour market statistics don’t capture platform-based work, or when they do, they don’t make it possible to distinguish it from ordinary self-employment income. This makes it impossible to properly evaluate the role that platforms are taking in the modern labour market.

To help address this paucity of data, we have created the Online Labour Index, the first economic indicator that provides an online gig economy equivalent of conventional labour market statistics. It shows that the online gig economy grew by a whopping 26 percent over the past year, and that UK-based employers are among its leading users in the world. By online gig economy we refer to digitally delivered platform work like design, data entry, and virtual assistant services, rather than local services like delivery. The index is constructed by ‘scraping’ all the gigs from the six biggest platforms in real time and calculating statistics on them; a similar approach could possibly be used to create new statistics on the local gig economy, to complement inadequate official labour market statistics.

Open issues

There is much more in the 116-page Review. For instance, the issue of flexibility gets a lot of attention, and is something that colleagues and I are also doing research on. The question of “flexibility for whom – workers or employers” will no doubt continue to feature in the debates on the future of work and employment.

I hope you enjoyed my hot take, and I hope to return to these topics in a future blog post!

***

Prof. Vili Lehdonvirta is an economic sociologist who studies the design and socioeconomic implications of digital marketplaces and platforms, using conventional social research methods as well as novel data science approaches. He is the Principal Investigator of iLabour, a 5-year research project funded by the European Research Council. @ViliLe

As a policy agenda, open government can be thought of as involving four variables: transparency, participation, collaboration, and digital technologies in democratic processes. Although the variables are all interpreted in different ways, participation, collaboration, and digital technology provide the greatest challenge to government, given they imply a major restructuring of public administration, whereas transparency goals (i.e., the disclosure of open data and the provision of monitoring tools) do not. Indeed, transparency is mentioned in the earliest accounts of open government from the 1950s.

The authors show the emergence of competing models of open government in Europe, with transparency and digital technologies being the most prominent issues in open government, and participation and collaboration being less considered and implemented. The standard model of open government seems to stress innovation and openness, and occasionally of public–private collaboration, but fails to achieve open decision making, with the policy-making process typically rooted in existing mechanisms. However, the authors also see the emergence of a policy framework within which democratic innovations can develop, testament to the vibrancy of the relationship between citizens and the public administration in contemporary European democracies.

We caught up with the authors to discuss their findings:

Ed.: Would you say there are more similarities than differences between these countries’ approaches and expectations for open government? What were your main findings (briefly)?

Emiliana / Donatella: We can imagine the four European countries (France, Italy, Spain and the UK) as positioned in a continuum between a participatory frame and an economic/innovation frame: on the one side, we could observe that French policies focus on open government in order to strenghten and innovate the tradition of débat public; at the opposite side, the roots of the UK’s open government are in cost-efficiency, accountability and transparency arguments. Just between those two poles, Italian and Spanish policies situate open government in the context of a massive reform of the public sector, in order to reduce the administrative burden and to restore citizen trust in institutions. Two years after we wrote the article, we can observe that both in Italy and Spain something has changed, and participation has regained attention as a public policy issue.

Ed.: How much does policy around open data change according to who’s in power? (Obama and Trump clearly have very different ideas about the value of opening up government..). Or do civil services tend to smooth out any ideological differences around openness and transparency, even as parties enter and leave power?

Emiliana / Donatella: The case of open data is quite peculiar: it is one of the few policy issues directly addressed by the European Union Commission, and now by the transnational agreement on the G8 Open Data Charter, and for this reason we could say there is a homogenising trend. Moreover, opening up data is an ongoing process — started at least eight years ago — that will be too difficult for any new government to stop. As for openness and transparency in general, Cameron (and now May), Hollande, Monti (and then Renzi) and Rajoy’s governments, all wrote policies with a strong emphasis on innovation and openness as the key for a better future.

In fact, we observed that at the national level, the rhetoric of innovation and openness is bipartisan, and not dependent on political orientation — although the concrete policy instruments and implementation strategies might differ. It is also for this reason that governments tend to remain in the “comfort zone” of transparency and public-private partnerships: they still evocate a change in the relationship between public sector and civil society, but they don’t actually address this change.

Still, we should highlight that at the regional and local levels open data, transparency and participation policies are mostly promoted by liberal and/or left-leaning administrations.

Ed.: Your results for France (i.e. almost no mention of the digital economy, growth, or reform of public services) are basically the opposite of Macron’s (winning) platform of innovation and reform. Did Macron identify a problem in France; and might you expect a change as he takes control?

Emiliana / Donatella: Macron’s electoral programme is based on what he already did while in charge at the Ministry of Economy: he pursued a French digital agenda willing to attract foreign investments, to create digital productive hubs (the French Tech), and innovate the whole economy. Interestingly, however, he did not frame those policies under the umbrella of open government, preferring to speak about “modernisation”. The importance given by Macron to innovation in the economy and public sector finds some antecedents in the policies we analysed: the issue of “modernisation” was prominent and we expect it will be even more, now that he has gained the presidency.

Ed.: In your article you analyse policy documents, i.e. texts that set out hopes and intentions. But is there any sense of how much practical effect these have: particularly given how expensive it is to open up data? You note “the Spanish and Italian governments are especially focused on restoring trust in institutions, compensating for scandals, corruption, and a general distrust which is typical in Southern Europe” .. and yet the current Spanish government is still being rocked by corruption scandals.

Emiliana / Donatella: The efficacy of any kind of policies can vary depending on many factors — such as internal political context, international constraints, economic resources, and clarity of policy instruments. In addition, we should consider that at the national level, very few policies have an immediate consequence on citizens’ everyday lives. This is surely one of the worst problems of open government: from the one side, it is a policy agenda promoted in a top-down perspective — from international and/or national institutions; and from the other side, it fails to engage local communities in a purposeful dialogue. At such, open government policies appear to be self-reflective acts by governments, as paradoxical as this might be.

Ed.: Despite terrible, terrible things like the Trump administration’s apparent deletion of climate data, do you see a general trend towards increased datafication, accountability, and efficiency (perhaps even driven by industry, as well as NGOs)? Or are public administrations far too subject to political currents and individual whim?

Emiliana / Donatella: As we face turbulent times, it would be very risky to assert that tomorrow’s world will be more open than today’s. But even if we observe some interruptions, the principles of open democracy and open government have colonised public agendas: as we have tried to stress in our article, openness, participation, collaboration and innovation can have different meanings and degrees, but they succeeded in acquiring the status of policy issues.

And as you rightly point out, the way towards accountability and openness is not a public sector’s prerogative any more: many actors from civil society and industry have already mobilised in order to influence government agendas, public opinion, and to inform citizens. As the first open government policies start to produce practical effects on people’s everyday lives, we might expect that public awareness will rise, and that no individual will be able to ignore it.

Ed.: And does the EU have any supra-national influence, in terms of promoting general principles of openness, transparency etc.? Or is it strictly left to individual countries to open up (if they want), and in whatever direction they like? I would have thought the EU would be the ideal force to promote rational technocratic things like open government?

Emiliana / Donatella: The EU has the power of stressing some policy issues, and letting some others be “forgotten”. The complex legislative procedures of the EU, together with the trans-national conflictuality, produce policies with different degrees of enforcement. Generally speaking, some EU policies have a direct influence on national laws, whereas some others don’t, leaving with national governments the decision of whether or not to act. In the case of open government, we see that the EU has been particularly influential in setting the Digital Agenda for 2020 and now the Sustainable Future Agenda for 2030; in both documents, Europe encourages Member States to dialogue and collaborate with private actors and civil society, in order to achieve some objectives of economic development.

At the moment, initiatives like the Open Government Partnership — which runs outside the EU competence and involves many European countries — are tying up governments in trans-national networks converging on a set of principles and methods. Because of that Partnership, for example, countries like Italy and Spain have experimented with the first national co-drafting procedures.

Read the full article: De Blasio, E. and Selva, D. (2016) Why Choose Open Government? Motivations for the Adoption of Open Government Policies in Four European Countries. Policy & Internet 8 (3). DOI: doi:10.1002/poi3.118.

Emiliana De Blasio and Donatella Selva were talking to blog editor David Sutcliffe.

While nearly a third of the adolescent respondents reported experiencing significant bullying in the past few months, cyberbullying was much less common, with around five percent of respondents reporting recent significant experiences. Both traditional and cyberbullying were independently associated with lower mental well-being, but only the relation between traditional bullying and well-being was robust. This supports the view that cyberbullying is unlikely to provide a source for new victims, but rather presents an avenue for further victimisation of those already suffering from traditional forms of bullying.

This stands in stark contrast to media reports and the popular perception that young people are now more likely to be victims of cyberbullying than traditional forms. The results also suggest that interventions to address cyberbullying will only be effective if they also consider the dynamics of traditional forms of bullying, supporting the urgent need for evidence-based interventions that target *both* forms of bullying in adolescence. That said, as social media and Internet connectivity become an increasingly intrinsic part of modern childhood, initiatives fostering resilience in online and every day contexts will be required.

We caught up with Andy and Lucy to discuss their findings:

Ed.: You say that given “the rise in the use of mobile and online technologies among young people, an up to date estimation of the current prevalence of cyberbullying in the UK is needed.” Having undertaken that—what are your initial thoughts on the results?

Andy: I think a really compelling thing we learned in this project is that researchers and policymakers have to think very carefully about what constitutes a meaningful degree of bullying or cyberbullying. Many of the studies and reports we reviewed were really loose on details here while a smaller core of work was precise and informative. When we started our study it was difficult to sort through the noise but we settled on a solid standard—at least two or three experiences of bullying in the past month—to base our prevalence numbers and statistical models on.

Lucy: One of the issues here is that studies often use different measures, so it is hard to compare like for like, but in general our study supports other recent studies indicating that relatively few adolescents report being cyberbullied only—one study by Dieter Wolke and colleagues that collected between 2014-2015 found that whilst 29% of school students reported being bullied, only 1% of 11-16 year olds reported only cyberbullying. Whilst that study was only in a handful of schools in one part of England, the findings are strikingly similar to our own. In general then it seems that rates of cyberbullying are not increasing dramatically; though it is concerning that prevalence rates of both forms of bullying—particularly traditional bullying—have remained unacceptably high.

Ed.: Is there a policy distinction drawn between “bullying” (i.e. young people) and “harassment” (i.e. the rest of us, including in the workplace)—and also between “bullying” and “cyber-bullying”? These are all basically the same thing, aren’t they—why distinguish?

Lucy: I think this is a good point; people do refer to ‘bullying’ in the workplace as well. Bullying, at its core, is defined as intentional, repeated aggression targeted against a person who is less able to defend him or herself—for example, a younger or more vulnerable person. Cyberbullying has the additional definition of occurring only in an online format—but I agree that this is the same action or behaviour, just taking place in a different context. Whilst in practice bullying and harassment have very similar meanings and may be used interchangeably, harassment is unlawful under the Equality Act 2010, whilst bullying actually isn’t a legal term at all. However certain acts of bullying could be considered harassment and therefore be prosecuted. I think this really just reflects the fact that we often ‘carve up’ human behaviour and experience according to our different policies, practices and research fields—when in reality they are not so distinct.

Ed.: I suppose online bullying of young people might be more difficult to deal with, given it can occur under the radar, and in social spaces that might not easily admit adults (though conversely, leave actual evidence, if reported..). Why do you think there’s a moral panic about cyberbullying — is it just newspapers selling copy, or does it say something interesting about the Internet as a medium — a space that’s both very open and very closed? And does any of this hysteria affect actual policy?

Andy: I think our concern arises from the uncertainty and unfamiliarity people have about the possibilities the Internet provides. Because it is full of potential—for good and ill—and is always changing, wild claims about it capture our imagination and fears. That said, the panic absolutely does affect policy and parenting discussions in the UK. Statistics and figures coming from pressure groups and well-meaning charities do put the prevalence of cyberbullying at terrifying, and unrealistically high, levels. This certainly has affected the way parents see things. Policy makers tend to seize on the worse case scenario and interpret things through this lens. Unfortunately this can be a distraction when there are known health and behavioural challenges facing young people.

Lucy: For me, I think we do tend to panic and highlight the negative impacts of the online world—often at the expense of the many positive impacts. That said, there was—and remains—a worry that cyberbullying could have the potential to be more widespread, and to be more difficult to resolve. The perpetrator’s identity may be unknown, may follow the child home from school, and may be persistent—in that it may be difficult to remove hurtful comments or photos from the Internet. It is reassuring that our findings, as well as others’, suggest that cyberbullying may not be associated with as great an impact on well-being as people have suggested.

Ed.: Obviously something as deeply complex and social as bullying requires a complex, multivalent response: but (that said), do you think there are any low-hanging interventions that might help address online bullying, like age verification, reporting tools, more information in online spaces about available help, more discussion of it as a problem (etc.)?

Andy: No easy ones. Understanding that cyber- and traditional bullying aren’t dissimilar, parental engagement and keeping lines of communication open are key. This means parents should learn about the technology their young people are using, and that kids should know they’re safe disclosing when something scary or distressing eventually happens.

Lucy: Bullying is certainly complex; school-based interventions that have been successful in reducing more traditional forms of bullying have tended to involve those students who are not directly involved but who act as ‘bystanders’—encouraging them to take a more active stance against bullying rather than remaining silent and implicitly suggesting that it is acceptable. There are online equivalents being developed, and greater education that discourages people (both children and adults) from sharing negative images or words, or encourages them to actively ‘dislike’ such negative posts show promise. I also think it’s important that targeted advice and support for those directly affected is provided.

Ed.: Who’s seen as the primary body responsible for dealing with bullying online: is it schools? NGOs? Or the platform owners who actually (if not-intentionally) host this abuse? And does this topic bump up against wider current concerns about (e.g.) the moral responsibilities of social media companies?

Andy: There is no single body that takes responsibility for this for young people. Some charities and government agencies, like the Child Exploitation and Online Protection command (CEOP) are doing great work. They provide a forum for information for parents and professionals for kids that is stratified by age, and easy-to-complete forms that young people or carers can use to get help. Most industry-based solutions require users to report and flag offensive content and they’re pretty far behind the ball on this because we don’t know what works and what doesn’t. At present cyberbullying consultants occupy the space and the services they provide are of dubious empirical value. If industry and the government want to improve things on this front they need to make direct investments in supporting robust, open, basic scientific research into cyberbulling and trials of promising intervention approaches.

Lucy: There was an interesting discussion by the NSPCC about this recently, and it seems that people are very mixed in their opinions—some would also say parents play an important role, as well as Government. I think this reflects the fact that cyberbullying is a complex social issue. It is important that social media companies are aware, and work with government, NGOs and young people to safeguard against harm (as many are doing), but equally schools and parents play an important role in educating children about cyberbullying—how to stay safe, how to play an active role in reducing cyberbullying, and who to turn to if children are experiencing cyberbullying.

Ed.: You mention various limitations to the study; what further evidence do you think we need, in order to more completely understand this issue, and support good interventions?

Lucy: I think we need to know more about how to support children directly affected by bullying, and more work is needed in developing effective interventions for cyberbullying. There are some very good school-based interventions with a strong evidence base to suggest that they reduce the prevalence of at least traditional forms of bullying, but they are not being widely implemented in the UK, and this is a missed opportunity.

Andy: I agree—a focus on flashy cyberbullying headlines presents the real risk of distracting us from developing and implementing evidence-based interventions. The Internet cannot be turned off and there are no simple solutions.

Ed.: You say the UK is ranked 20th of 27 EU countries on the mental well-being index, and also note the link between well-being and productivity. Do you think there’s enough discussion and effort being put into well-being, generally? And is there even a general public understanding of what “well-being” encompasses?

Lucy: I think the public understanding of well-being is probably pretty close to the research definition—people have a good sense that this involves more than not having psychological difficulty for example, and that it refers to friendships, relationships, and doing well; one’s overall quality of life. Both research and policy is placing more of an emphasis on well-being—in part because large international studies have suggested that the UK may score particularly poorly on measures of well-being. This is very important if we are going to raise standards and improve people’s quality of life.

Read the full article: Andrew Przybylski and Lucy Bowes (2017) Cyberbullying and adolescent well-being in England: a population-based cross sectional study. The Lancet Child & Adolescent Health.

Andrew Przybylski is an experimental psychologist based at the Oxford Internet Institute. His research focuses on applying motivational theory to understand the universal aspects of video games and social media that draw people in, the role of game structure and content on human aggression, and the factors that lead to successful versus unsuccessful self-regulation of gaming contexts and social media use. @ShuhBillSkee

Lucy Bowes is a Leverhulme Early Career Research Fellow at Oxford’s Department of Experimental Psychology. Her research focuses on the impact of early life stress on psychological and behavioural development, integrating social epidemiology, developmental psychology and behavioural genetics to understand the complex genetic and environmental influences that promote resilience to victimization and early life stress. @DrLucyBowes

Andy Przybylski and Lucy Bowes were talking to the Oxford Internet Institute’s Managing Editor, David Sutcliffe.

In their Policy & Internet article, “Politicians and the Policy Agenda: Does Use of Twitter by the U.S. Congress Direct New York Times Content?” Matthew A. Shapiro and Libby Hemphill examine the extent to which he traditional media is influenced by politicians’ Twitter posts. They draw on indexing theory, which states that media coverage and framing of key policy issues will tend to track elite debate. To understand why the newspaper covers an issue and predict the daily New York Times content, it is modelled as a function of all of the previous day’s policy issue areas as well as all of the previous day’s Twitter posts about all of the policy issue areas by Democrats and Republicans.

They ask to what extent are the agenda-setting efforts of members of Congress acknowledged by the traditional media; what, if any, the advantages are for one party over the other, measured by the traditional media’s increased attention; and whether there is any variance across different policy issue areas? They find that Twitter is a legitimate political communication vehicle for US officials, that journalists consider Twitter when crafting their coverage, and that Twitter-based announcements by members of Congress are a valid substitute for the traditional communiqué in journalism, particularly for issues related to immigration and marginalized groups, and issues related to the economy and health care.

We caught up with the authors to discuss their findings:

Ed.: Can you give a quick outline of media indexing theory? Does it basically say that the press reports whatever the elite are talking about? (i.e. that press coverage can be thought of as a simple index, which tracks the many conversations that make up elite debate).

Matthew: Indexing theory, in brief, states that the content of media reports reflects the degree to which elites – politicians and leaders in government in particular – are in agreement or disagreement. The greater the level of agreement or consensus among elites, the less news there is to report in terms of elite conflict. This is not to say that a consensus among elites is not newsworthy; indexing theory conveys how media reporting is a function of the multiple voices that exist when there is elite debate.

Ed.: You say Twitter seemed a valid measure of news indexing (i.e. coverage) for at least some topics. Could it be that the NYT isn’t following Twitter so much as Twitter (and the NYT) are both following something else, i.e. floor debates, releases, etc.?

Matthew: We can’t test for whether the NYT is following Twitter rather than floor debates/press releases without collecting data for the latter. Perhaps If the House and Senate Press Galleries are indexing the news based on House and Senate debates, and if Twitter posts by members of Congress reflect the House and Senate discussions, we could still argue that Twitter remains significant because there are no limits on the amount of discussion – i.e. the boundaries of the House and Senate floors no longer exist – and the media are increasingly reliant on politicians’ use of Twitter to communicate to the press. In any case, the existing research shows that journalists are increasingly relying on Twitter posts for updates from elites.

Ed.: I’m guessing that indexing theory only really works for non-partisan media that follow elite debates, like the NYT? Or does it also work for tabloids? And what about things like Breitbart (and its ilk) .. which I’m guessing appeals explicitly to a populist audience, rather than particularly caring what the elite are talking about?

Matthew: If a study similar to our was done to examine the indexing tendencies of tabloids, Breitbart, or a similar type of media source, the first step would be to determine what is being discussed regularly in these outlets. Assuming, for example, that there isn’t much discussion about marginalized groups in Breitbart, in the context of indexing theory it would not be relevant to examine the pool of congressional Twitter posts mentioning marginalized groups. Those posts are effectively off of Breitbart’s radar. But, generally, indexing theory breaks down if partisanship and bias drive the reporting.

Ed.: Is there any sense in which Trump’s “Twitter diplomacy” has overturned or rendered moot the recent literature on political uses of Twitter? We now have a case where a single (personal) Twitter account can upset the stock market — how does one theorise that?

Matthew: In terms of indexing theory, we could argue that Trump’s Twitter posts themselves generate a response from Democrats and Republicans in Congress and thus muddy the waters by conflating policy issues with other issues like his personality, ties to Russia, his fact-checking problems, etc. This is well beyond our focus in the article, but we speculate that Trump’s early-dawn use of Twitter is primarily for marketing, damage control, and deflection. There are really many different ways to study this phenomenon. One could, for example, examine the function of unfiltered news from politician to the public and compare it with the news that is simultaneously reported in the media. We would also be interested in understanding why Trump and politicians like Trump frame their Twitter posts the way they do, what effect these posts have on their devoted followers as well as their fence-sitting followers, and how this mobilizes Congress both online (i.e. on Twitter) and when discussing and voting on policy options on the Senate and House floors. These areas of research would all build upon rather than render moot the extant literature on the political uses of Twitter.

Ed.: Following on: how does Indexing theory deal with Trump’s populism (i.e. avowedly anti-Washington position), hatred and contempt of the media, and apparent aim of bypassing the mainstream press wherever possible: even ditching the press pool and favouring populist outlets over the NYT in press gaggles. Or is the media bigger than the President .. will indexing theory survive Trump?

Matthew: Indexing theory will of course survive Trump. What we are witnessing in the media is an inability, however, to limit gaper’s block in the sense that the media focus on the more inflammatory and controversial aspects of Trump’s Twitter posts – unfortunately on a daily basis – rather than reporting the policy implications. The media have to report what is news, and Presidential Twitter posts are now newsworthy, but we would argue that we are reaching a point where anything but the meat of the policy implications must be effectively filtered. Until we reach a point where the NYT ignores the inflammatory nature of Trumps Twitter posts, it will be challenging to test indexing theory in the context of the policy agenda setting process.

Ed.: There are recent examples (Brexit, Trump) of the media apparently getting things wrong because they were following the elites and not “the forgotten” (or deplorable) .. who then voted in droves. Is there any sense in the media industry that it needs to rethink things a bit — i.e. that maybe the elite is not always going to be in control of events, or even be an accurate bellwether?

Matthew: This question highlights an omission from our article, namely that indexing theory marginalizes the role of non-elite voices. We agree that the media could do a better job reporting on certain things; for instance, relying extensively on weather vanes of public opinion that do not account for inaccurate self-reporting (i.e. people not accurately representing themselves when being polled about their support for Trump, Brexit, etc.) or understanding why disenfranchised voters might opt to stay home on Election Day. When it comes to setting the policy agenda, which is the focus of our article, we stand by indexing theory given our assumption that the policy process itself is typically directed from those holding power. On that point, and regardless of whether it is normatively appropriate, elites are accurate bellwethers of the policy agenda.

Read the full article: Shapiro, M.A. and Hemphill, L. (2017) Politicians and the Policy Agenda: Does Use of Twitter by the U.S. Congress Direct New York Times Content? Policy & Internet 9 (1) doi:10.1002/poi3.120.

Matthew A. Shapiro and Libby Hemphill were talking to blog editor David Sutcliffe.

However, while top-down social media communication between public administrations and citizens has been widely examined, the bottom-up side of this interaction has been largely overlooked. In their Policy & Internet article “The ‘Social Side’ of Public Policy: Monitoring Online Public Opinion and Its Mobilization During the Policy Cycle,” Andrea Ceron and Fedra Negri aim to bridge the gap between knowledge and practice, by examining how the information available on social media can support the actions of politicians and bureaucrats along the policy cycle.

Policymakers, particularly politicians, have always been interested in knowing citizens’ preferences, in measuring their satisfaction and in receiving feedback on their activities. Using the technique of Supervised Aggregated Sentiment Analysis, the authors show that meaningful information on public services, programmes, and policies can be extracted from the unsolicited comments posted by social media users, particularly those posted on Twitter. They use this technique to extract and analyse citizen opinion on two major public policies (on labour market reform and school reform) that drove the agenda of the Matteo Renzi cabinet in Italy between 2014 and 2015.

They show how online public opinion reacted to the different policy alternatives formulated and discussed during the adoption of the policies. They also demonstrate how social media analysis allows monitoring of the mobilization and de-mobilization processes of rival stakeholders in response to the various amendments adopted by the government, with results comparable to those of a survey and a public consultation that were undertaken by the government.

We caught up with the authors to discuss their findings:

Ed.: You say that this form of opinion monitoring and analysis is cheaper, faster and easier than (for example) representative surveys. That said, how commonly do governments harness this new form of opinion-monitoring (with the requirement for new data skills, as well as attitudes)? Do they recognise the value of it?

Andrea / Fedri: Governments are starting to pay attention to the world of social media. Just to give an idea, the Italian government has issued a call to jointly collect survey data together with the results of social media analysis and these two types of data are provided in a common report. The report has not been publicly shared, suggesting that the cabinet considers such information highly valuable. VOICES from the blogs, a spin-off created by Stefano Iacus, Luigi Curini and Andrea Ceron (University of Milan), has been involved in this and, for sure, we can attest that in a couple of instances the government modified its actions in line with shifts in public opinion observed both through survey polls and sentiment analysis. This happened with the law on Civil Unions and with the abolishment of the “voucher” (a flexible form of worker payment). So far these are just instances — although there are signs of enhanced responsiveness, particularly when online public opinion represents the core constituency of ruling parties, as the case of the school reform (discussed in the article) clearly indicates: teachers are in fact the core constituency of the Democratic Party.

Ed.: You mention that the natural language used by social media users evolves continuously and is sensitive to the discussed topic: resulting in error. The method you use involves scaling up of a human-coded (=accurate) ontology. Could you discuss how this might work in practice? Presumably humans would need to code the terms of interest first, as it wouldn’t be able to pick up new issues (e.g. around a completely new word: say, “Bowling Green”?) automatically.

Andrea / Fedri: Gary King says that the best technology is human empowered. There are at least two great advantages in exploiting human coders. First, with our technique coders manage to get rid of noise better than any algorithm, as often a single word can be judged to be in-topic or out of topic based on the context and on the rest of the sentence. Second, human-coders can collect deeper information by mining the real opinions expressed in the online conversations. This sometimes allows them to detect, bottom-up, some arguments that were completely ignored ex-ante by scholars or analysts.

Ed.: There has been a lot of debate in the UK around “false balance”, e.g. the BBC giving equal coverage to climate deniers (despite being a tiny, unrepresentative, and uninformed minority), in an attempt at “impartiality”: how do you get round issues of non-representativeness in social media, when tracking — and more importantly, acting on — opinion?

Andrea / Fedri: Nowadays social media are a non-representative sample of a country’s population. However, the idea of representativeness linked to the concept of “public opinion” dates back to the early days of polling. Today, by contrast, online conversations often represent an “activated public opinion” comprising stakeholders who express their voices in an attempt to build wider support around their views. In this regard, social media data are interesting precisely due to their non-representativeness. A tiny group can speak loudly and this voice can gain the support of an increasing number of people. If the activated public opinion acts as an “influencer”, this implies that social media analysis could anticipate trends and shifts in public opinion.

Ed.: As data becomes increasingly open and tractable (controlled by people like Google, Facebook, or monitored by e.g. GCHQ / NSA), and text-techniques become increasingly sophisticated: what is the extreme logical conclusion in terms of government being able to track opinion, say in 50 years, following the current trajectory? Or will the natural messiness of humans and language act as a natural upper limit on what is possible?

Andrea / Fedri: The purpose of scientific research, particularly applied research, is to improve our well-being and to make our life easier. For sure there could be issues linked with the privacy of our data and, in a sci-fi scenario, government and police will be able to read our minds — either to prevent crimes and terrorist attacks (as in the Minority Report movie) or to detect, isolate and punish dissent. However, technology is not a standalone object and we should not forget that there are humans behind it. Whether these humans are governments, activists or common citizens, can certainly make a difference. If governments try to misuse technology, they will certainly meet a reaction from citizens — which can be amplified precisely via this new technology.

Read the full article: Ceron, A. and Negri, F. (2016) The “Social Side” of Public Policy: Monitoring Online Public Opinion and Its Mobilization During the Policy Cycle. Policy & Internet 8 (2) DOI:10.1002/poi3.117

Andrea Ceron and Fedra Negri were talking to blog editor David Sutcliffe.

In her Policy & Internet article “The Case of Roshonara Choudhry: Implications for Theory on Online Radicalization, ISIS Women, and the Gendered Jihad”, Elizabeth Pearson explores how gender might have factored in Roshonara’s radicalization, in order to present an alternative to existing theoretical explanations. First, in precluding her from a real-world engagement with Islamism on her terms, gender limitations in the physical world might have pushed her to the Internet. Here, a lack of religious knowledge made her particularly vulnerable to extremist ideology; a susceptibility only increased through Internet socialization and to an active radical milieu. Finally, it might have created a dissonance between her online and multiple “real” gendered identities, resulting in violence.

As yet, there is no adequately proven link between online material and violent acts. But given the current reliance of terrorism research on the online environment, and the reliance of policy on terrorism research, the relationship between the virtual and offline domains must be better understood. So too must the process of “radicalization” — which still lacks clarity, and relies on theorizing that is rife with assumptions. Whatever the challenges, understanding how men and women become violent radicals, and the differences there might be between them, has never been more important.

We caught up with Elizabeth to discuss her findings:

Ed.: You note “the Internet has become increasingly attractive to many women extremists in recent years” — do these extremist views tend to be found on (general) social media or on dedicated websites? Presumably these sites are discoverable via fairly basic search?

Elizabeth: Yes and no. Much content is easily found online. ISIS has been very good at ‘colonizing’ popular social media platforms with supporters, and in particular, Twitter was for a period the dominant site. It was ideal as it allowed ISIS fans to find one another, share material, and build networks and communities of support. In the past 18 months Twitter has made a concerted – and largely successful – effort to ‘take down’ or suspend accounts. This may simply have pushed support elsewhere. We know that Telegram is now an important channel for information, for example. Private groups, the dark web and hidden net resources exist alongside open source material on sites such as Facebook, familiar to everyone. Given the illegality of much of this content, there has been huge pressure on companies to respond. Still there is criticism from bodies such as the Home Affairs Select Committee that they are not responding quickly or efficiently enough.

Ed.: This case seemed to represent a collision not just of “violent jihadists vs the West” but also “Salafi-Jihadists vs women” (as well as “Western assumptions of Muslim assumptions of acceptable roles for women”) .. were these the main tensions at play here?

Elizabeth: One of the key aspects of Roshonara’s violence was that it was transgressive. Violent Jihadist groups tend towards conservatism regarding female roles. Although there is no theological reason why women should not participate in the defensive Jihad, they are not encouraged to do so. ISIS has worked hard in its propaganda to keep female roles domestic – yet ideologically so. Roshonara appears to have absorbed Al Awlaki’s messaging regarding the injustices faced by Muslims, but only acted when she saw a video by Azzam, a very key scholar for Al Qaeda supporters, which she understood as justifying female violence. Hatred of western foreign policy, and support for intervention in Iraq appeared to be the motivation for her attack; a belief that women could also fight is what prompted her to carry this out herself.

Ed.: Does this struggle tend to be seen as a political struggle about land and nationhood; or a supranational religious struggle — or both? (with the added complication of Isis conflating nation and religion..)

Elizabeth: Nobody yet understands exactly why people ‘radicalize’. It’s almost impossible to profile violent radicals beyond saying they tend to be mainly male – and as we know, that is not a hard and fast rule either. What we can say is that there are complex factors, and a variety of recurrent themes cited by violent actors, and found in propaganda and messaging. One narrative is about political struggle on behalf of Muslims, who face injustice, particularly from the West. ISIS has made this struggle about the domination of land and nationhood, a development of Al Qaeda’s message. Religion is also important to this. Despite different levels of knowledge of Islam, supporters of the violent Jihad share commitment to battle as justified in the Quran. They believe that Islam is the way, the only way, and they find in their faith an answer to global issues, and whatever is happening personally to them. It is not possible, in my view, to ignore the religious component declared in this struggle. But there are other factors too. That’s what makes this so difficult and complex.

Ed.: You say that Roshonara “did not follow the path of radicalization set out in theory”. How so? But also .. how important and grounded is this “theory” in the practice of counter-radicalization? And what do exceptions like Roshonara Choudhry signify?

Elizabeth: Theory — based on empirical evidence — suggests that violence is a male preserve. Violent Jihadist groups also generally restrict their violence to men, and men only. Theory also tells us that actors rarely carry out violence alone. Belonging is an important part of the violent Jihad and ‘entrance’ to violence is generally through people you know, friends, family, acquaintances. Even where we have seen young women for example travel to join ISIS, this has tended to be facilitated through friends, or online contacts, or family. Roshanara as a female acting alone in this time before ISIS is therefore something quite unusual. She signifies – through her somewhat unique case – just how transgressive female violence is, and just how unusual solitary action is. She also throws into question the role of the internet. The internet alone is not usually sufficient for radicalization; offline contacts matter. In her case there remain some questions of what other contacts may have influenced her violence.

I’m not entirely sure how joined up counter-radicalization practices and radicalization theory are. The Prevent strategy aside, there are many different approaches, in the UK alone. The most successful that I have seen are due to committed individuals who know the communities they are based in and are trusted by them. It is relationships that seem to count, above all else.

Ed.: Do you think her case is an interesting outlier (a “lone wolf” as people commented at the time), or do you think there’s a need for more attention to be paid to gender (and women) in this area, either as potential threats, or solutions?

Elizabeth: Roshonara is a young woman, still in jail for her crime. As I wrote this piece I thought of her as a student at King’s College London, as I am, and I found it therefore all the more affecting that she did what she did. There is a connection through that shared space. So it’s important for me to think of her in human terms, in terms of what her life was like, who her friends were, what her preoccupations were and how she managed, or did not manage, her academic success, her transition to a different identity from the one her parents came from. She is interesting to me because of this, and because she is an outlier. She is an outlier who reveals certain truths about what gender means in the violent Jihad. That means women, yes, but also men, ideas about masculinity, male and female roles. I don’t think we should think of young Muslim people as either ‘threats’ or ‘solutions’. These are not the only possibilities. We should think about society, and how gender works within it, and within particular communities within it.

Ed.: And is gender specifically “relevant” to consider when it comes to Islamic radicalization, or do you see similar gender dynamics across all forms of political and religious extremism?

Elizabeth: My current PhD research considers the relationship between the violent Jihad and the counter-Jihad – cumulative extremism. To me, gender matters in all study. It’s not really anything special or extra, it’s just a recognition that if you are looking at groups you need to take into account the different ways that men and women are affected. To me that seems quite basic, because otherwise you are not really seeing a whole picture. Conservative gender dynamics are certainly also at work in some nationalist groups. The protection of women, the function of women as representative of the honour or dishonour of a group or nation – these matter to groups and ideologies beyond the violent Jihad. However, the counter-Jihad is in other ways progressive, for example promoting narratives of protecting gay rights as well as women’s rights. So women for both need to be protected – but what they need to be protected from and how differs for each. What is important is that the role of women, and of gender, matters in consideration of any ‘extremism’, and indeed in politics more broadly.

Ed.: You’re currently doing research on Boko Haram — are you also looking at gender? And are there any commonalities with the British context you examined in this article?

Elizabeth: Boko Haram interests me because of the ways in which it has transgressed some of the most fundamental gender norms of the Jihad. Since 2014 they have carried out hundreds of suicide attacks using women and girls. This is highly unusual and in fact unprecedented in terms of numbers. How this impacts on their relationship with the international Jihad, and since 2015, ISIS, to whom their leader gave a pledge of allegiance is something I have been thinking about.

There are many local aspects of the Nigerian conflict that do not translate – poverty, the terrain, oral traditions of preaching, human rights violations, Sharia in northern Nigerian states, forced recruitment.. In gender terms however, the role of women, the honour/dishonour of women, and gender-based violence translate across contexts. In particular, women are frequently instrumentalized by movements for a greater cause. Perhaps the greatest similarity is the resistance to the imposition of Western norms, including gender norms, free-mixing between men and women and gender equality. This is a recurrent theme for violent Jihadists and their supporters across geography. They wish to protect the way of life they understand in the Quran, as they believe this is the word of God, and the only true word, superseding all man-made law.

Read the full article: Pearson, E. (2016) The Case of Roshonara Choudhry: Implications for Theory on Online Radicalization, ISIS Women, and the Gendered Jihad. Policy & Internet 8 (1) doi:10.1002/poi3.101.

Elizabeth Pearson was talking to blog editor David Sutcliffe.

In their Policy & Internet article “Data Intelligence for Local Government? Assessing the Benefits and Barriers to Use of Big Data in the Public Sector“, Fola Malomo and Vania Sena examine the extent to which local governments in the UK are indeed using intelligence from big data, in light of the structural barriers they face when trying to exploit it. Their analysis suggests that the ambitions around the development of big data capabilities in local government are not reflected in actual use. Indeed, these methods have mostly been employed to develop new digital channels for service delivery, and even if the financial benefits of these initiatives are documented, very little is known about the benefits generated by them for the local communities.

While this is slowly changing as councils start to develop their big data capability, the overall impression gained from even a cursory overview is that the full potential of big data is yet to be exploited.

We caught up with the authors to discuss their findings:

Ed.: So what actually is “the full potential” that local government is supposed to be aiming for? What exactly is the promise of “big data” in this context?

Fola / Vania: Local governments seek to improve service delivery amongst other things. Big Data helps to increase the number of ways that local service providers can reach out to, and better the lives of, local inhabitants. In addition, the exploitation of Big Data allows to better target the beneficiaries of their services and emphasise early prevention which may result into a reduction of the delivery costs. Commissioners in a Council needed to understand the drivers of the demand for services across different departments and their connections: how the services are connected to each other and how changes in the provision of “upstream” services can affect the “downstream” provision. Many local governments have reams of data (both hard data and soft data) on local inhabitants and local businesses. Big Data can be used to improve services, increase quality of life and make doing business easier.

Ed.: I wonder: can the data available to a local authority even be considered to be “big data” — you mention that local government data tends to be complex, rather than “big and fast”, as in the industry understanding of “big data”. What sorts of data are we talking about?

Fola / Vania: Local governments hold data on individuals, companies, projects and other activities concerning the local community. Health data, including information on children and other at-risk individuals, forms a huge part of the data within local governments. We use the concept of the data-ecosystem to talk about Big Data within local governments. The data ecosystem consists of different types of data on different topics and units which may be used for different purposes.

Complexity within data is driven by the volume of data and the large number of data sources. One must consider the fact that public agencies address needs from communities that cross administrative boundaries of a single administrative body. Also, the choice of data collection methodology and observation unit is driven by reporting requirements which is influenced by central government. Lastly, data storage infrastructure may be designed to comply with reporting requirements rather than linking data across agencies; data is not necessarily produced to be merged The data is not always “big and fast” but requires the use of advanced storage and analytic tools to get useful information that local areas benefit from.

Ed.: Do you think local governments will ever have the capacity (budget, skill) to truly exploit “big data”? What were the three structural barriers you particularly identified?

Fola / Vania: Without funding there is no chance that local governments can fully exploit big data. With funding, Local government can benefit from Big Data in a number of ways. The improved usage of Big Data usually requires collaboration between agents. The three main structural barriers to the fruitful exploitation of big data by local governments are: data access; ethical issues; and organisational changes. In addition, skill gaps; and investment in information technology have proved problematic.

Data access can be a problem if data exists in separate locations with little communication between the housing organisations and no easy way to move the data from one place to another. The main advantage of big data technologies is their ability to merge different types of data; mine them for insights; and combine them for actionable insights. Nevertheless, while the use of big data approaches to data exploitation assumes that organisations can access all the data they need; this is not the case in the public sector. A uniform practice on what data can be shared locally has not yet emerged. Furthermore there is no solution to the fact that data can span across organisations that are not part of the public sector and that may therefore be unwilling to share data with public bodies.

De-identifying personal data is another key requirement to fulfil before personal data can be shared under the terms of the Data Protection Agreement. It is argued that this requirement is relevant when trying to merge small data sets as individuals can be easily re-identified once the data linkage is completed. As a result, the only option left to facilitate the linkage of data sets with personal information is to create a secure environment where data can be safely de-identified and then matched. Safe havens and trusted third parties have been developed exactly for` this purpose. Data warehouses, where data from local governments and from other parts of the public sector can be matched and linked, have been developed as an intermediate solution to the lack of infrastructure for matching sensitive data.

Due to the personal nature of the data, ethical issues arise concerning how to use information about individuals and whether persons should be identifiable. There is a huge debate on ethical challenges posed by the routine extraction of information from Big Data. The extraction and manipulation of personal information cannot be easily reconciled with what is perceived to be ethically acceptable in this area. Additional ethical issues related to the re-use of output from specific predictive models for other purposes within the public sector. This issue is particularly relevant given the fact that most predictive analytics algorithms only provide an estimate of the risk of an event.

Data usage is related to culture; and organisational changes can be a medium to longer term process. As long as key stakeholders in the organisation accept that insights from data will inform service delivery; big data technologies can be used as levers to introduce changes in the way services are provided. Unfortunately, it is commonly believed that the deployment of big data technologies simply implies a change in the way data are interrogated and interpreted and therefore should not have any bearing on the way internal processes are organised.

In addition, data usage can involve investment in information technology and training. It is well known that investment in IT has been very uneven between the private and public sector, and within the private sector as well. Despite the growth in information and communications technology (ICT) budgets across the private sector, the banking sector and the financial services industry spend 8 percent of their total operating expenditure on ICT, among local authorities, ICT spending makes up only 3-6% of the total budget. Furthermore, successful deployment of Big Data technologies needs to be accompanied by the development of internal skills that allow for the analysis and modelling of complex phenomena that is essential to the development of a data-driven approach to decision making within local governments. However, local governments tend to lack these skills and this skills gap may be exacerbated by the high turnover in the sector. All this, in addition to the sector’s fragmentation in terms of IT provision, reinforces the structural silos that prevent local authorities from sharing and exploiting their data.

Ed.: And do you think these big data techniques will just sort-of seep in to local government, or that there will need to be a proper step-change in terms of skills and attitudes?

Fola / Vania: The benefits of data-driven analysis are being increasingly accepted. Whilst the techniques used might seem to be steadily accepted by local governments, in order to make a real and lasting improvement public bodies should ideally have a big data strategy in place to determine how they will use the data they have available to them. Attitudes can take time to change and the provision of information can help people become more willing to use Big Data in their work.

Ed.: I suppose one solution might for local councils to buy in the services of third-party specialist “big data for local government” providers, rather than trying to develop in-house capacity: do these providers exist? I imagine local government might have data that would be attractive to commercial companies, maybe as a profit-sharing data partnership?

Fola / Vania: The truth is that providers do exist and they always charge local governments. What is underestimated is the role that data centres can play in this arena. The authors are members of the economic and social research council funded business and local government data research centre for smart analytics. This centre helps local councils use their big data better by collating data and performing analysis that is of use to local councils. The centre also provides training to public officials, giving them tools to understand and use data better. The centre is a collaboration between the Universities of Essex, Kent, East Anglia and the London School of Economics. Academics work closely with public officials to come up with solutions to problems facing local areas. In addition, commercial companies are interested in working with local government data. Working with third-party organisations is a good method to ease into the process of using Big Data solutions without having to make a huge changes to one’s organisation.

Ed.: Finally — is there anything that central Government can do (assuming it isn’t already 100% occupied with Brexit) to help local governments develop their data analytic capacity?

Fola / Vania: Central governments influence the environment in which local government operate. Despite local councils making decisions over things such as how data is stored, central government can assist by removing some of the previously-mentioned barriers to data usage. For example, government cuts are excessive and are making the sector very volatile so financial help will be useful in this area. Moreover, data access and transfer is made easier with uniformity of data storage protocols. In addition, the public will have more confidence in providing data if there is transparency in the collection, usage and provision of data. Guidelines for the use of sensitive data should be agreed upon and made known in order to improve the quality of the work. Central governments can also help change the general culture of local governments and attitudes towards Big Data. In order for Big Data to work well for all, individuals, companies, local governments and central governments should be well informed about the issues and able to effect change concerning Big Data issues.

Read the full article: Malomo, F. and Sena, V. (2107) Data Intelligence for Local Government? Assessing the Benefits and Barriers to Use of Big Data in the Public Sector. Policy & Internet 9 (1) DOI: 10.1002/poi3.141.

Fola Malomo and Vania Sena were talking to blog editor David Sutcliffe.

Changes in the ways knowledge is created and used — and how this is enabled by new information technologies — are driving economic and social development worldwide. Discussions of the “knowledge economy” see knowledge both as an economic output in itself, and as an input that strengthens economic processes; with developing countries tending to be described as planning or embarking on a journey of transformation into knowledge economies to bring about economic gain. Indeed, increasing connectivity has sparked many hopes for the democratization of knowledge production in sub-Saharan Africa.

Despite the centrality of digital connectivity to the knowledge economy, there are few studies of the geographies of digital knowledge and information. In their article “Engagement in the Knowledge Economy: Regional Patterns of Content Creation with a Focus on Sub-Saharan Africa”, published in Information Technologies & International Development, Sanna Ojanperä, Mark Graham, Ralph K. Straumann, Stefano De Sabbata, and Matthew Zook investigate the patterns of knowledge creation in the region. They examine three key metrics: spatial distributions of academic articles (i.e. traditional knowledge production), collaborative software development, and Internet domain registrations (i.e. digitally mediated knowledge production).

Contrary to expectations, they find distribution patterns of digital content (measured by collaborative coding and domain registrations) to be more geographically uneven than those of academic articles: despite the hopes for the democratizing power of the information revolution. This suggests that the factors often framed as catalysts for a knowledge economy do not relate to these three metrics uniformly.

Connectivity is an important enabler of digital content creation, but it seems to be only a necessary, not a sufficient, condition; wealth, innovation capacity, and public spending on education are also important factors. While the growth in telecommunications might be reducing the continent’s reliance on extractive industries and agriculture, transformation into a knowledge economy will require far more concentrated effort than simply increasing Internet connectivity.

We caught up with Sanna to discuss the article’s findings:

Ed.: You chose three indices (articles, domain registration, collaborative coding) to explore the question of Africa’s “readiness” to join the knowledge economy. Are these standard measures for the (digital) knowledge economy?

Sanna: Academic articles is a measure often used to estimate knowledge-rich activity, so you could consider it a traditional variable in this area. Other previous work measuring the geographies of codified knowledge have focused on particular aspects or segments of it, such as patents, citations, and innovation systems.

What we found to be an interesting gap in the estimation of knowledge economies is that even if digital connectivity is central to the knowledge economy discourse, studies of the current geographies of digital knowledge and information on online platforms are rare. We argue that digitally mediated participation in information- and knowledge-intensive activities offers a metric that closely measures human capacity and skills. An analysis of digitally mediated traces of skills and information might thus complement the knowledge economy discussion and offer a way to better detect the boundaries of contemporary knowledge economies. To address the gap of research on digital content, we examine the geography of activities in collaborative software development (using the GitHub platform), and the registration of top-level domains. While there are other indicators that we could have included in the analysis, we selected these two, as they have a global reach and because they measure two distinct, but important segments of knowledge economy.

Ed.: To what extent do the drivers commonly associated with knowledge economies (e.g., GDP, broadband Internet, education, innovation) explain the patterns you found? And what were these patterns?

Sanna: While connectivity plays a role in all three categories, it seems to have a strong effect only on digital content creation. Conversely, the production of academic articles is more strongly related to GDP than to connectivity. Innovation capacity appears to have a positive relationship to all three content types. Education as a topically narrower variable appears, perhaps unexpectedly, to be related only to variance in academic articles.

In terms of the patterns of these variables, we find that the geographies of collaborative coding and domain registrations are more uneven than the spatial distribution of academic authoring. Sub-Saharan Africa contributes the smallest share of content to all three categories, providing only 1.1% of academic articles. With 0.5% of collaborative coding and 0.7% of domain registrations, SSA produces an even smaller share of digital content.

While comparison across absolute numbers informs us of the total volume of content creation, it is useful to pair that with a standardized measure that informs us of the propensity of content creation across the populations. Considering the most productive countries in terms of their per capita content creation suggests geographies even more clustered in Europe than looking at total numbers. In SSA, the level of individual countries’ content production falls within the two lowest quintiles more often in the case of collaborative coding and domain registrations than with academic articles. This runs contrary to the expectation of contemporary digitally mediated content being more evenly geographically distributed than traditional content.

Ed.: You measured “articles” by looking at author affiliations. Could you just as well have used “universities” as the measure? Or is there an assumption that connectivity will somehow encourage international co-authorship (does it?) — or that maybe “articles” is a better measure of knowledge quality than presence of universities per se?

Sanna: We chose this indicator, because we consider scientific output in the form of academic articles to represent the progress of science. Publication of academic articles and the permanent scientific record they form are central for the codification of knowledge and are a key enabler of knowledge-intensive processes. Beyond being an indicator often included in the knowledge economy indices, we believe that academic articles offer a relatively uniform measure of knowledge-intensive output, as the process of peer-reviewed publishing and the way in which it constructs a permanent scientific record are rather similar around the world. In contrast, other systems for knowledge-intensive outputs such as registering patents and innovation systems are known to be vary greatly between countries and regions (Griliches, 1990).

We didn’t use the number of universities as an indicator of the knowledge economy, because we wanted to look at measures of knowledge-intensive content-creation. While universities educate individuals and increase the nation’s human capital, this ‘output’ is very diverse and looks very different between universities. Further, we wanted to assess whether education in fact drives the development of knowledge economy, and used a measure of enrollment rates in secondary and tertiary education as an explanatory variable in our analysis.

Ed.: There’s a lot of talk of Africa entering the “global” marketplace: but how global is the knowledge economy — particularly given differences in language and culture? I imagine most cultural and knowledge production remains pretty local?

Sanna: The knowledge economy could be seen as a new dynamic stage in the global economic restructuring, where economic processes and practices that place greater emphasis of intellectual abilities take place in the context of an increasingly interconnected world. To the extent that African information- and knowledge-intensive goods and services compete in these global markets, one could consider the region entering the global knowledge economy. While the markets for knowledge-based goods and services may be smaller in various African countries, many produce regionally or nationally and locally targeted knowledge-rich products. However, this understanding of the concept of knowledge economy tends to focus on commercial activities and scientific and technical knowledge and neglect indigenous, local or cultural knowledge. These types of knowledge have a higher tendency of being tacit rather than codifiable in nature. Unlike codified knowledge, which can be recorded and transmitted through symbols or become materialized in concrete form such as tools or machinery, tacit knowledge takes time to obtain and is not as easily diffused. While these tacit types of knowledge are prevalent and carry significant value for their users and producers, they are less easily converted to commercial value. This makes their measurement more challenging and as a result the discourse of knowledge economies tends to focus less on these types of knowledge production.

Ed.: Is the knowledge economy always going to be a “good” thing, or could it lead to (more) economic exploitation of the region — for example if it got trapped into supplying a market for low-quality work? (I guess the digital equivalent of extractive, rather than productive industries .. call centres, gig-work etc.)

Sanna: As is the case with any type of economic activity, the distributional effects of knowledge economies are affected by a myriad of factors. On one hand, many of the knowledge- and information-rich economic activities require human capital and technological resources, and tend to yield goods and services with higher value added. The investment in and the greater presence of these resources may help nations and individuals to access more opportunities to increase their welfare. However, countries don’t access the global information- and knowledge-based markets as equal players and the benefits from knowledge economies are not distributed equally. It is possible that exploitative practices exist in particular where institutions and regulatory practices are not sufficiently powerful to ensure adequate working conditions. In a previous study on the Sub-Saharan African gig economy and digital labour – both areas that could be considered to form part of the knowledge economy – some of the authors found that while a range of workers in these domains enjoy important and tangible benefits, they also face risks and costs such as low bargaining power, limited economic inclusion, intermediated value chains leading to exploitation of less experienced workers, and restrictions in upgrading skills in order to move upwards in professional roles.

Ed.: I guess it’s difficult to unpack any causation in terms of Internet connectivity, economic development, and knowledge economies — despite hopes of the Internet “transforming” Sub-Saharan African economies. Is there anything in your study (or others) to hint at an answer to the question of causality?

Sanna: In order to discuss causality, we would need to study the effects of a given intervention or treatment, as measured in an ideal randomized controlled experiment. As we’re not investigating the effect of a particular intervention, but studying descriptive trends in the three dependent variables using the Ordinary Least Squares (OLS) method of estimation in multiple linear regression framework, we cannot make strong claims about causality. However, we find that both the descriptive study of RQ1 as well as the regression modeling and residual mapping for RQ2 offer statistically significant results, which lend themselves for interpretations with relevance to our RQs and that have important implications, which we discuss in the concluding section of the article.

Read the full article: Ojanperä, S., Graham, M., Straumann, R.K., De Sabbata, S., & Zook, M. (2017). Engagement in the knowledge economy: Regional patterns of content creation with a focus on sub-Saharan Africa. Information Technologies & International Development 13: 33–51.

Sanna Ojanperä was talking to blog editor David Sutcliffe.

While much of the modern political process is now carried out digitally, ICTs have yet to bring democracies to their full utopian ideal. The drivers of involvement in digital politics from an individual perspective are well studied, but less attention has been paid to the supply-side of online engagement in politics. In his Policy & Internet article “Inequality in Local Digital Politics: How Different Preconditions for Citizen Engagement Can Be Explained,” Gustav Lidén examines the supply of channels for digital politics distributed by Swedish municipalities, in order to understand the drivers of variation in local online engagement.

He finds a positive trajectory for digital politics in Swedish municipalities, but with significant variation between municipalities when it comes to opportunities for engagement in local politics via their websites. These patterns are explained primarily by population size (digital politics is costly, and larger societies are probably better able to carry these costs), but also by economic conditions and education levels. He also find that a lack of policies and unenthusiastic politicians creates poor possibilities for development, verifying previous findings that without citizen demand — and ambitious politicians — successful provision of channels for digital politics will be hard to achieve.

We caught up with Gustav to discuss his findings:

Ed.: I guess there must be a huge literature (also in development studies) on the interactions between connectivity, education, the economy, and supply and demand for digital government: and what the influencers are in each of these relationships. Not to mention causality.. I’m guessing “everything is important, but nothing is clear”: is that fair? And do you think any “general principles” explaining demand and supply of electronic government / democracy could ever be established, if they haven’t already?

Gustav: Although the literature in this field is becoming vast the subfield that I am primarily engaged in, that is the conditions for digital policy at the subnational level, has only recently attracted greater numbers of scholars. Even if predictors of these phenomena can be highly dependent on context, there are some circumstances that we can now regard as being the ‘usual suspects’. Not surprisingly, resources of both economic and human capital appear to be important, irrespective of the empirical case. Population size also seems to be a key determinant that can influence these kind of resources.

In terms of causality, few studies that I am familiar with have succeeded in examining the interplay of both demand for and supply of digital forms of politics. In my article I try to get closer to the causal chain by examining both structural predictors as well as adding qualitative material from two cases. This makes it possible to establish better precision on causal chains since it enables judgements on how structural conditions influence key stakeholders.

Ed.: You say government-citizen interactions in Sweden “are to a larger extent digital in larger and better-off societies, while ‘analog’ methods prevail in smaller and poorer ones.” Does it particularly matter whether things are digital or analog at municipal level: as long as they all have equal access to national-level things?

Gustav: I would say so, yes. However, this could vary in relation to the responsibilities of municipalities among different countries. The municipal sector in Sweden is significant. Its general costs represent about one quarter of the country’s GDP and the sector is responsible for important parts of the welfare sector. In addition to this, municipalities also represent the most natural arena for political engagement — the typical political career starts off in the local council. Great variation in digital politics among municipalities is therefore problematic — there is a risk of inequality between municipalities if citizens from one municipality face greater possibilities for information and participation while those residing in another are more restrained.

Ed.: Sweden has areas of very low population density: are paper / telephone channels cheaper for municipalities to deliver in these areas, or might that just be an excuse for any lack of enthusiasm? i.e. what sorts of geographical constraints does Sweden face?

Gustav: This is a general problem for a large proportion of the Swedish municipalities. Due to government efforts, ambitions for assuring high-speed internet connections (including more sparsely populated areas), are under way. Yet in recent research, the importance for fast internet access in relation to municipalities’ work with digital politics has been quite ambiguous. My guess would, however, be that if the infrastructure is in place it will, sooner or later, be impossible for municipalities to refrain from working with more digital forms of politics.

Ed.: I guess a cliche of the Swedes (correct me if I’m wrong!) is that despite the welfare state / tradition of tolerance, they’re not particularly social — making it difficult, for example, for non-Swedes to integrate. How far do you think cultural / societal factors play a role in attempts to create “digital community,” in Sweden, or elsewhere?

Gustav: This cliche is perhaps most commonly related to the Swedish countryside. However, the case studies in my article illustrates a contrary image. Take the municipality of Gagnef as an example, one of my two cases, in which informants describe a vibrant civil society with associations representing a great variety of sectors. One interesting finding, though, is that local engagement is channeled through these traditional forms and not particularly through digital media. Still, from a global perspective, Sweden is rightfully described as an international leader in terms of digitalization. This is perhaps most visible in the more urban parts of the country; even if there are many good examples from the countryside in which the technology is one way to counteract great distances and low population density.

Ed.: And what is the role of the central government in all this? i.e. should they (could they? do they?) provide encouragement and expertise in providing local-level digital services, particularly for the smaller and poorer districts?

Gustav: Due to the considerable autonomy among the municipalities the government has not regulated municipalities working with this issue. However, they have encouraged and supported parts of it, primarily when it comes to the investment of technological infrastructure. My research does show that smaller and poorer municipalities have a hard time finding the right resources for developing digital forms of politics. Local political leaders find it hard to prioritize these issues when there is almost a constant need for more resources for schools and elderly care. But this is hardly unique for Sweden. In a study of the local level in the US, Norris and Reddick show how lack of financial resources is the number one constraint for the development of digital services. I think that government regulation, i.e. forcing municipalities to distribute specific digital channels, could lower inequalities between municipalities but would be unthinkable without additional government funding.

Ed.: Finally: do you see it as “inevitable” that everyone will eventually be online, or could pockets of analog government-citizen interaction persist basically indefinitely?

Gustav: Something of a countermovement opposing the digital society appears to exist in several societies. In general, I think we need to find a more balanced way to describe the consequences of digitalization. Hopefully, most people see both the value and the downsides of a digital society, but the debate tends to be dominated either by naïve optimists or complete pessimists. Policy makers need though, to start thinking of the consequences of both inequalities in relation to this technique and pay more attention to the risks related to it.

Read the full article: Lidén, G. (2016) Inequality in Local Digital Politics: How Different Preconditions for Citizen Engagement Can Be Explained. Policy & Internet 8 (3) doi:10.1002/poi3.122.

Gustav Lidén was talking to blog editor David Sutcliffe.

See his websites: https://www.miun.se/Personal/gustavliden/ and http://gustavliden.blogspot.se/

Letting your child use social media is like giving them cocaine, alcohol and cigarettes – all at once, or so we’re told. If you have been following recent press reports about the effects of social media on young people, you may well believe this. But there is no scientific evidence to support such extreme claims.

The real story is far more complex. It is very difficult to predict how social media will affect any specific individual – the effect depends on things like their personality, type of social media use and social surroundings. In reality, social media can have both positive and negative outcomes.

Media reports that compare social media to drug use are ignoring evidence of positive effects, while exaggerating and generalising the evidence of negative effects. This is scaremongering – and it does not promote healthy social media use. We would not liken giving children sweets to giving children drugs, even though having sweets for every meal could have serious health consequences. We should therefore not liken social media to drugs either.

For a claim to be proved scientifically it needs to be thoroughly tested. To fully confirm The Independent’s headline that: “Giving your child a smartphone is like giving them a gram of cocaine, says top addiction expert”, you would need to give children both a gram of cocaine and a smartphone and then compare the effects. Similarly, you would need to provide millennials with social media, drugs and alcohol to test The Conversation’s headline that: “Social media is as harmful as alcohol and drugs for millennials”. But ethical guidelines at universities were put in place so that such studies will never be done.

The diversity of social media

But maybe news headlines should be discounted – as exaggerations are often used to grab the readers’ attention. But even when ignoring these grand claims, the media coverage of social media is still misleading. For example, reports that talk about the effects of social media are often oversimplifying reality. Social media is incredibly diverse – different sites providing a host of different features. This makes it extremely difficult to generalise about social media’s effects.

A recent review of past research concluded that the effect of Facebook depends on which of the platform’s features you use. A dialog with friends over Facebook messenger can improve your mood, while comparing your life to other people’s photos on the Newsfeed can do the opposite. By treating all social media sites and features as one concept, the media is oversimplifying something that is very complex.

Focusing on the negative

Past media coverage has not only oversimplified social media, but has often only focused on social media’s negative aspects. But scientific research demonstrates that there are both positive and negative outcomes of social media use. Research has shown that Facebook increases self-esteem and promotes feeling connected to others. People’s physiological reactions also indicate they react positively to Facebook use.

By contrast, it has also been found that social media can decrease well-being and increases social anxiety. An analysis of 57 scientific studies found that social media is associated with slightly higher levels of narcissism. This array of conflicting evidence suggests that social media has both negative and positive effects. Not just one or the other.

The amount matters

The effect of social media also depends on the amount of time you spend using it. In a recent study we conducted of more than 120,000 UK teenagers, we found that moderate social media use is not harmful to mental health.

We compared the relationship between screen time and well-being. We found that those who used screens a moderate amount – between one and three hours each day – reported higher well-being compared with those who didn’t use social media at all and those who used it more than three hours a day. So, unlike drugs, those who practise abstinence do not appear to fare better.

Recent media reports may have made parents unnecessarily anxious about their child’s use of social media. A flashy quote or headline can often distract from the real challenges of parenting. It’s time the media covered not only the bad, but also the beneficial and complex sides of social media. The effects of social media cannot be summarised by comparing social media to drugs. It is just not that simple.

Andy Przybylski, Associate Professor and Senior Research Fellow, University of Oxford and Amy C Orben, College Lecturer and DPhil Candidate, University of Oxford

This article was originally published on The Conversation. Read the original article.

Social media have been part of the UK electoral landscape for a while. In 2015, many of us attributed the Conservative success in part to their massive expenditure on targeted Facebook advertising, 10 times more than Labour, whose ‘bottom-up’ Twitter campaign seemed mainly to have preached to the converted. Social media advertising was used more successfully by Leave.EU than Remain in the referendum (although some of us cautioned against blaming social media for Brexit). But in both these campaigns, the relentless attack of the tabloid press was able to strike at the heart of the Labour and Remain campaigns and was widely credited for having influenced the result, as in so many elections from the 1930s onwards.

However, in 2017 Labour’s campaign was widely regarded as having made a huge positive difference to the party’s share of the vote – unexpectedly rising by 10 percentage points on 2015 – in the face of a typically sustained and viscious attack by the Daily Mail, the Sun and the Daily Express. Why? There are (at least) three reasons.

First, increased turnout of young people is widely regarded to have driven Labour’s improved share of the vote – and young people do not in general read newspapers not even online. Instead, they spend increasing proportions of their time on social media platforms on mobile phones, particularly Instagram (with 10 million UK users, mostly under 30) and Snapchat (used by half of 18-34 year olds), both mobile-first platforms. On these platforms, although they may see individual stories that are shared or appear on their phone’s news portal, they may not even see the front page headlines that used to make politicians shake.

Meanwhile, what people do pay attention to and share on these platforms are videos and music, so popular artists amass huge followings. Some of the most popular came out in favour of Labour under the umbrella hashtag #Grime4Corbyn, with artists like Stormzy, JME (whose Facebook interview with Corbyn was viewed 2.5 million times) and Skepta with over a million followers on Instagram alone.

A leaflet from Croydon pointing out that ‘Even your Dad has more Facebook friends’ than the 2015 vote difference between Conservative and Labour and showing Stormzy saying ‘Vote Labour!’ was shared millions of times. Obviously we don’t know how much difference these endorsements made – but by sharing videos and images, they certainly spread the idea of voting for Corbyn across huge social networks.

Second, Labour have overtaken the Tories in reaching out across social platforms used by young people with an incredibly efficient advertising strategy. There is no doubt that in 2017 the Conservatives ran a relentless campaign of anti-Corbyn attack ads on Facebook and Instagram. But for the Conservatives, social media are just for elections. Instead, Labour have been using these channels for two years now – Corbyn has been active on Snapchat since becoming Labour leader in 2015 (when some of us were surprised to hear our teenage offspring announcing brightly ‘I’m friends with Jeremy Corbyn on Snapchat’).

That means that by the time of the election Corbyn and various fiercely pro-Labour online-only news outlets like the Canary had acquired a huge following among this demographic, meaning not having to pay for ads. And if you have followers to spread your message, you can be very efficient with advertising spend. While the Conservatives spent more than £1m on direct advertising with Facebook etc., nearly 10 million people watched pro-Labour videos on Facebook that cost less than £2K to make. Furthermore, there is some evidence that the relentless negativity of the Conservative advertising campaign actually put young people off particularly. After all, the advertising guidelines for Instagram advise ‘Images should tell a story/be inspirational’!

On the day before the election, the Daily Mail ran a frontpage headline ‘Apologists for Terror’, with a photo of Diane Abbot along with Corbyn and John McDonnell. But that morning Labour announced that Abbot’s standing aside due to illness. The paper circulating around the networks and sitting on news-stands was already out of date. Digital natives are used to real-time information, they are never going to be swayed by something so clearly past its sell-by-date.

Likewise, the Sun’s election day image – a grotesque image of Jeremy “Corbinned” in a dustbin was photoshopped to replace Corbyn with an equally grotesque photograph of May taking his place in the dustbin, before the first editions landed. It won’t have reached the same audience, perhaps, but it will have reached a lot of people.

It will be a long time before we can really assess the influence of social media in the 2017 election, and some things we may never know. That is because all the data that would allow us to do so is held by the platforms themselves – Facebook, Instagram, Snapchat and so on. That is a crucial issue for the future of our democracy, already bringing calls for some transparency in political advertising both by social media platforms and the parties themselves. Under current conditions the Electoral Commission is incapable of regulating election advertising effectively, or judging (for example) how much national parties spend on targeted advertising locally. This is something that urgently needs addressing in the coming months, especially given Britain’s current penchant for elections.

The secret and often dark world of personalized political advertising on social media, where strong undercurrents of support remain hidden to the outside world, is one reason why polls fail to predict election results until after the election has taken place. Having the data to understand the social media election would also explain some of the volatility in elections these days, as explored in our book Political Turbulence: How Social Media Shape Collective Action. By investigating large-scale data on political activity my co-authors and I showed that social media are injecting the same sort of instability into politics as they have into cultural markets, where most artists gain no traction at all but a (probably unpredictable) few become massively popular – the young singer Ed Sheeran’s ‘The Shape of You’ has been streamed one billion times on Spotify alone.

In 2017, Stormzy and co. provided a more direct link between political and music markets, and this kind of development will ensure that politics in the age of social media will remain turbulent and unpredictable. We can’t claim to have predicted Labour’s unexpected success in this election, but we can claim to have foreseen that it couldn’t be predicted.

The Internet is often portrayed as a disruptive equalizer, an information medium able to directly give individuals access to information and provide a platform to share their opinions unmediated. But the Internet is also a tool for surveillance, censorship, and information warfare. Often states drive such practices, but increasingly the private sector plays a role. While states have a clear obligation to protect human rights on the Internet, questions surrounding the human right accountability of the private sector are unclear. Which begs the question what the responsibility is of the private industry, which runs and owns much of the Internet, towards human rights?

During the 35th session of the United Nations (UN) Human Rights Council this month, David Kaye, UN Special Rapporteur (UNSR) for the right to freedom of expression, presented his latest report [1], which focuses on the role of the private sector in the provision of Internet and telecommunications access. The UNSR on freedom of expression is an independent expert, appointed by the Human Rights Council to analyse, document, and report on the state of freedom of expression globally [2]. The rapporteur is also expected to make recommendations towards ‘better promoting and protection of the right to freedom of expression’ [3]. In recent years, the UNSRs on freedom of expression increasingly focus on the intersection between access to information, expression, and the Internet [4].

This most recent report is a landmark document. Its focus on the role and responsibilities of the private sector towards the right to freedom of expression presents a necessary step forward in the debate about the responsibility for the realization of human rights online. The report takes on the legal difficulties surrounding the increased reliance of states on access to privately owned networks and data, whether by necessity, through cooperation, or through coercion, for surveillance, security, and service provision. It also tackles the legal responsibilities that private organizations have to respect human rights.

The first half of Kaye’s report emphasises the role of states in protecting the right to freedom of expression and access to information online, in particular in the context of state-mandated Internet shutdowns and private-public data sharing. Kaye highlights several major Internet shutdowns across the world and argues that considering ‘the number of essential activities and services they affect, shutdowns restrict expression and interfere with other fundamental rights’ [5]. In order to address this issue, he recommends that the Human Rights Council supplements and specifies resolution 32/13, on ‘the promotion, protection and enjoyment of human rights on the Internet’ [6], in which it condemns such disruptions to the network. On the interaction between private actors and the state, Kaye walks a delicate line. On the one hand, he argues that governments should not pressure or threaten companies to provide them with access to data. On the other hand, he also argues that states should not allow companies to make network management decisions that treat data differentially based on its origin.

The second half of the report focusses on the responsibility of the private sector. In this context, the UNSR highlights the responsibilities of private actors towards the right to freedom of expression. Kaye argues that this sector plays a crucial role in providing access to information and communication services to millions across the globe. He looks specifically at the role of telecommunication and Internet service providers, Internet exchange points, content delivery networks, network equipment vendors, and other private actors. He argues that four contextual factors are relevant to understanding the responsibility of private actors vis-à-vis human rights:

(1) private actors provide access to ‘a public good’,
(2) due to the technical nature of the Internet, any restrictions on access affect freedom of expression on a global level,
(3) the private sector is vulnerable to state pressure,
(4) but it is also in a unique position to respect users’ rights.

The report draws out the dilemma of the boundaries of responsibility. When should companies decide to comply with state policies that might undermine the rights of Internet end-users? What remedies should they offer end-users if they are complicit in human rights violations? How can private actors assess what impact their technologies might have on human rights?

Private actors across the spectrum, from multinational social media platforms to the garage-based start-ups are likely to run into these questions. As the Internet underpins a large part of the functioning of our societies, and will only further continue to do so as physical devices increasingly become part of the network (aka the Internet of Things), it is even more important to understand and allocate private sector responsibility for protecting human rights.

The report has a dedicated addendum [7] that specifically details the responsibility of Internet Standard Developing Organizations (SDOs). In it, Kaye relies on the article written by Corinne Cath and Luciano Floridi of the Oxford Internet Institute (OII) entitled ‘The Design of the Internet’s Architecture by the Internet Engineering Task Force (IETF) and Human Rights’ [8] to support his argument that SDOs should take on a credible approach to human rights accountability.

Overall, Kaye argues that companies should adopt the UN Guiding Principles on Business and Human Rights [9], which would provide a ‘minimum baseline for corporate human rights accountability’. To operationalize this commitment, the private sector will need to take several urgent steps. It should ensure that sufficient resources are reserved for meeting its responsibility towards human rights, and it should integrate the principles of due diligence, human rights by design, stakeholder engagement, mitigation of the harms of government-imposed restrictions, transparency, and effective remedies to complement its ‘high level commitment to human rights’.

While this report is not binding [10] on states or companies, it does set out a much-needed detailed blue print of how to address questions of corporate responsibility towards human rights in the digital age.

References

[1] https://documents-dds-ny.un.org/doc/UNDOC/GEN/G17/077/46/PDF/G1707746.pdf?OpenElement
[2] http://www.ijrcenter.org/un-special-procedures/
[3] http://www.ohchr.org/EN/Issues/FreedomOpinion/Pages/OpinionIndex.aspx
[4] http://www2.ohchr.org/english/bodies/hrcouncil/docs/17session/A.HRC.17.27_en.pdf
[5] The author of this blog has written about this issue here: https://www.cfr.org/blog-post/should-technical-actors-play-political-role-internet-age
[6] http://ap.ohchr.org/documents/dpage_e.aspx?si=A/HRC/32/L.20
[7] https://documents-dds-ny.un.org/doc/UNDOC/GEN/G17/141/31/PDF/G1714131.pdf?OpenElement
[8] https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2912308
[9] http://www.ohchr.org/Documents/Publications/GuidingPrinciplesBusinessHR_EN.pdf
[10] http://www.ohchr.org/Documents/Publications/FactSheet27en.pdf

While the online world has turned into an ecosystem of bots (by which we mean computer scripts that automatically handle repetitive and mundane tasks), our knowledge of how these automated agents interact with each other is rather poor. But being automata without capacity for emotions, meaning-making, creativity, or sociality, we might expect bot interactions to be relatively predictable and uneventful.

In their PLOS ONE article “Even good bots fight: The case of Wikipedia“, Milena Tsvetkova, Ruth García-Gavilanes, Luciano Floridi, and Taha Yasseri analyze the interactions between bots that edit articles on Wikipedia. They track the extent to which bots undid each other’s edits over the period 2001–2010, model how pairs of bots interact over time, and identify different types of interaction outcomes. Although Wikipedia bots are intended to support the encyclopaedia — identifying and undoing vandalism, enforcing bans, checking spelling, creating inter-language links, importing content automatically, mining data, identifying copyright violations, greeting newcomers, etc. — the authors find they often undid each other’s edits, with these sterile “fights” sometimes continuing for years.

They suggest that even relatively “dumb” bots may give rise to complex interactions, carrying important implications for Artificial Intelligence research. Understanding these bot-bot interactions will be crucial for managing social media, providing adequate cyber-security, and designing autonomous vehicles (that don’t crash..).

We caught up with Taha Yasseri and Luciano Floridi to discuss the implications of the findings:

Ed.: Is there any particular difference between the way individual bots interact (and maybe get bogged down in conflict), and lines of vast and complex code interacting badly, or having unforeseen results (e.g. flash-crashes in automated trading): i.e. is this just (another) example of us not always being able to anticipate how code interacts in the wild?

Taha: There are similarities and differences. The most notable difference is that here bots are not competing. They all work based on same rules and more importantly to achieve the same goal that is to increase the quality of the encyclopedia. Considering these features, the rather antagonistic interactions between the bots come as a surprise.

Ed.: Wikipedia have said that they know about it, and that it’s a minor problem: but I suppose Wikipedia presents a nice, open, benevolent system to make a start on examining and understanding bot interactions. What other bot-systems are you aware of, or that you could have looked at?

Taha: In terms of content generating bots, Twitter bots have turned out to be very important in terms of online propaganda. The crawlers bots that collect information from social media or the web (such as personal information or email addresses) are also being heavily deployed. In fact we have come up with a first typology of the Internet bots based on their type of action and their intentions (benevolent vs malevolent), that is presented in the article.

Ed.: You’ve also done work on human collaborations (e.g. in the citizen science projects of the Zooniverse) — is there any work comparing human collaborations with bot collaborations — or even examining human-bot collaborations and interactions?

Taha: In the present work we do compare bot-bot interactions with human-human interactions to observe similarities and differences. The most striking difference is in the dynamics of negative interactions. While human conflicts heat up very quickly and then disappear after a while, bots undoing each others’ contribution comes as a steady flow which might persist over years. In the HUMANE project, we discuss the co-existence of humans and machines in the digital world from a theoretical point of view and there we discuss such ecosystems in details.

Ed.: Humans obviously interact badly, fairly often (despite being a social species) .. why should we be particularly worried about how bots interact with each other, given humans seem to expect and cope with social inefficiency, annoyances, conflict and break-down? Isn’t this just more of the same?

Luciano: The fact that bots can be as bad as humans is far from reassuring. The fact that this happens even when they are programmed to collaborate is more disconcerting than what happens among humans when these compete, or fight each other. Here are very elementary mechanisms that through simple interactions generate messy and conflictual outcomes. One may hope this is not evidence of what may happen when more complex systems and interactions are in question. The lesson I learnt from all this is that without rules or some kind of normative framework that promote collaboration, not even good mechanisms ensure a good outcome.

Read the full article: Tsvetkova M, Garcia-Gavilanes R, Floridi, L, Yasseri T (2017) Even good bots fight: The case of Wikipedia. PLoS ONE 12(2): e0171774. doi:10.1371/journal.pone.0171774

Taha Yasseri and Luciano Floridi were talking to blog editor David Sutcliffe.

These applications are based on the idea of issue and proximity voting — the parties and candidates recommended by VAAs are those with the highest number of matching positions on a number of political questions and issues. Many of these questions are much more specific and detailed than party programs and electoral platforms, and show the voters exactly what the party or candidates stand for and how they will vote in parliament once elected. In his Policy & Internet article “Do VAAs Encourage Issue Voting and Promissory Representation? Evidence From the Swiss Smartvote,” Andreas Ladner examines the extent to which VAAs alter the way voters perceive the meaning of elections, and encourage them to hold politicians to account for election promises.

His main hypothesis is that VAAs lead to “promissory representation” — where parties and candidates are elected for their promises and sanctioned by the electorate if they don’t keep them. He suggests that as these tools become more popular, the “delegate model” is likely to increase in popularity: i.e. one in which politicians are regarded as delegates voted into parliament to keep their promises, rather than being voted a free mandate to act how they see fit (the “trustee model”).

We caught up with Andreas to discuss his findings:

Ed.: You found that issue-voters were more likely (than other voters) to say they would sanction a politician who broke their election promises. But also that issue voters are less politically engaged. So is this maybe a bit moot: i.e. if the people most likely to force the “delegate model” system are the least likely to enforce it?

Andreas: It perhaps looks a bit moot in the first place, but what happens if the less engaged are given the possibility to sanction them more easily or by default. Sanctioning a politician who breaks an election promise is not per se a good thing, it depends on the reason why he or she broke it, on the situation, and on the promise. VAA can easily provide information to what extent candidates keep their promises — and then it gets very easy to sanction them simply for that without taking other arguments into consideration.

Ed.: Do voting advice applications work best in complex, multi-party political systems? (I’m not sure anyone would need one to distinguish between Trump / Clinton, for example?)

Andreas: Yes, I believe that in very complex systems – like for example in the Swiss case where voters not only vote for parties but also for up to 35 different candidates – VAAs are particularly useful since they help to process a huge amount of information. If the choice is only between two parties or two candidates which are completely different, than VAAs are less helpful.

Ed.: I guess the recent elections / referendum I am most familiar with (US, UK, France) have been particularly lurid and nasty: but I guess VAAs rely on a certain quiet rationality to work as intended? How do you see your Swiss results (and Swiss elections, generally) comparing with these examples? Do VAAs not just get lost in the noise?

Andreas: The idea of VAAs is to help voters to make better informed choices. This is, of course, opposed to decisions based on emotions. In Switzerland, elections are not of outmost importance, due to specific features of our political system such as direct democracy and power sharing, but voters seem to appreciate the information provided by smartvote. Almost 20% of the voter cast their vote after having consulted the website.

Ed.: Macron is a recent example of someone who clearly sought (and received) a general mandate, rather than presenting a detailed platform of promises. Is that unusual? He was criticised in his campaign for being “too vague,” but it clearly worked for him. What use are manifesto pledges in politics — as opposed to simply making clear to the electorate where you stand on the political spectrum?

Andreas: Good VAAs combine electoral promises on concrete issues as well as more general political positions. Voters can base their decisions on either of them, or on a combination of both of them. I am not arguing in favour of one or the other, but they clearly have different implications. The former is closer to the delegate model, the latter to the trustee model. I think good VAAs should make the differences clear and should even allow the voters to choose.

Ed.: I guess Trump is a contrasting example of someone whose campaign was all about promises (while also seeking a clear mandate to “make America great again”), but who has lied, and broken these (impossible) promises seemingly faster than people can keep track of them. Do you think his supporters care, though?

Andreas: His promises were too far away from what he can possibly keep. Quite a few of his voters, I believe, do not want them to be fully realized but rather that the US move a bit more into this direction.

Ed.: I suppose another example of an extremely successful quasi-pledge was the Brexit campaign’s obviously meaningless — but hugely successful — “We send the EU £350 million a week; let’s fund our NHS instead.” Not to sound depressing, but do promises actually mean anything? Is it the candidate / issue that matters (and the media response to that), or the actual pledges?

Andreas: I agree that the media play an important role and not always into the direction they intend to do. I do not think that it is the £350 million a week which made the difference. It is much more a general discontent and a situation which was not sufficiently explained and legitimized which led to this unexpected decision. If you lose the support for your policy than it gets much easier for your opponents. It is difficult to imagine that you can get a majority built on nothing.

Ed.: I’ve read all the articles in the Policy & Internet special issue on VAAs: one thing that struck me is that there’s lots of incomplete data, e.g. no knowledge of how people actually voted in the end (or would vote in future). What are the strengths and weaknesses of VAAs as a data source for political research?

Andreas: The quality of the data varies between countries and voting systems. We have a self-selection bias in the use of VAAs and often also into the surveys conducted among the users. In general we don’t know how they voted, and we have to believe them what they tell us. In many respects the data does not differ that much from what we get from classic electoral studies, especially since they also encounter difficulties in addressing a representative sample. VAAs usually have much larger Ns on the side of the voters, generate more information about their political positions and preferences, and provide very interesting information about the candidates and parties.

Read the full article: Ladner, A. (2016) Do VAAs Encourage Issue Voting and Promissory Representation? Evidence From the Swiss Smartvote. Policy & Internet 8 (4). DOI: doi:10.1002/poi3.137.

Andreas Ladner was talking to blog editor David Sutcliffe.

However, new social media, including YouTube, provide opportunities for less-mainstream narratives of cooperation. In their Policy & Internet article “Do New Media Support New Policy Narratives? The Social Construction of the U.S.–Mexico Border on YouTube”, Donna L. Lybecker, Mark K. McBeth, Maria A. Husmann, and Nicholas Pelikan find that YouTube videos about the U.S.–Mexico border focus (perhaps unsurprisingly) on mainstream, divisive issues such as security and violence, immigration, and drugs. However, the videos appear to construct more favourable perspectives of the border region than traditional media, with around half constructing a sympathetic view of the border, and the people associated with it.

The common perceptions of the border generally take two distinct forms. One holds the U.S.–Mexico border to be the location of an annual legal flow of economic trade of $300 billion each year, a line which millions of people legally cross annually, the frontier of 100 years of peaceful coexistence between two countries, and the point of integration for the U.S.–Mexico relationship. An alternative perspective (particularly common since 9/11) focuses less on economic trade and legal crossing and more on undocumented immigration, violence and drug wars, and a U.S.-centric view of “us versus them”.

In order to garner public support for their “solutions” to these issues, politicians often define the border using one of these perspectives. Acceptance of the first view might well allow policymakers to find cooperative solutions to joint problems. Acceptance of the second creates a policy problem that is more value-laden than empirically based and that creates distrust and polarization among stakeholders and between the countries. The U.S.–Mexico border is clearly a complex region encompassing both positives and negatives — but understanding these narratives could have a real-world impact on policy along the border; possibly creating the greater cooperation we need to solve many of the urgent problems faced by border communities.

We caught up with the authors to discuss their findings:

Ed.: Who created the videos you studied: were they created by the public, or were they also produced by perhaps more progressive media outlets? i.e. were you able to disentangle the effect of the media in terms of these narratives?

Mark / Donna: For this study, we studied YouTube videos, using the “relevance” filter. Thus, the videos were ordered by most related to our topic and by most frequently viewed. With this selection method we captured videos produced by a variety of sources; some that contained embedded videos from mainstream media, others created by non-profit groups and public television groups, but also videos produced by interested citizens or private groups. The non-profit and media groups more often discuss the beneficial elements of the border (trade, shared environmental protection, etc.), while individual citizens or groups tended to post the more emotional and narrative-driven videos more likely to construct the border residents in a non-deserving sense.

Ed.: How influential do you think these videos are? In a world of extreme media concentration (where even the US President seems to get his news from Fox headlines and the 42 people he follows on Twitter) .. how significant is “home grown” content; which after all may have better, or at least more locally-representative, information than certain parts of the national media?

Mark / Donna: Today’s extreme media world supplies us with constant and fast-moving news. YouTube is part of the media mix, frequently mentioned as the second largest search engine on the web, and as such is influential. Media sources report that a large number of diverse people use YouTube, thus the videos encompass a broad swath of international, domestic and local issues. That said, as with most news sources today, some individuals gravitate to the stories that represent their point of view, and YouTube makes it possible for individuals to do just this. In other words, if a person perceives the US-Mexico border as a horrible place, they can use key words to search YouTube videos that represent that point of view.

However, we believe YouTube to be more influential than some other sources precisely because it encompasses diversity, thus, even when searching using specific terms, there will likely be a few videos included in search results that provide a different point of view. Furthermore, we did find some local, “home grown” content included in search results, again adding to the diversity presented to the individual watching YouTube. Although, we found less homegrown content than initially expected. Overall, there is selectivity bias with YouTube, like any type of media, but YouTube’s greater diversity of postings and viewers and broad distribution may increase both exposure and influence.

Ed.: Your article was published pre-Trump. How do you think things might have changed post-election, particularly given the uncertainty over “the wall“ and NAFTA — and Trump’s rather strident narratives about each? Is it still a case of “negative traditional media; equivocal social media”?

Mark / Donna: Our guess is that anti-border forces are more prominent on YouTube since Trump’s election and inauguration. Unless there is an organized effort to counter discussion of “the wall” and produce positive constructions of the border, we expect that YouTube videos posted over the past few months lean more toward non-deserving constructions.

Ed.: How significant do you think social media is for news and politics generally, i.e. its influence in this information environment — compared with (say) the mainstream press and party-machines? I guess Trump’s disintermediated tweeting might have turned a few assumptions on their heads, in terms of the relation between news, social media and politics? Or is the media always going to be bigger than Trump / the President?

Mark / Donna: Social media, including YouTube and Twitter, is interactive and thus allows anyone to bypass traditional institutions. President Trump can bypass institutions of government, media institutions, even his own political party and staff and communicate directly with people via Twitter. Of course, there are advantages to that, including hearing views that differ from the “official lines,” but there are also pitfalls, such as minimized editing of comments.

We believe people see both the strengths and the weakness with social media, and thus often read news from both traditional media sources and social media. Traditional media is still powerful and connected to traditional institutions, thus, remains a substantial source of information for many people — although social media numbers are climbing, particularly with the President’s use of Twitter. Overall, both types of media influence politics, although we do not expect future presidents will necessarily emulate President Trump’s use of social media.

Ed.: Another thing we hear a lot about now is “filter bubbles” (and whether or not they’re a thing). YouTube filters viewing suggestions according to what you watch, but still presents a vast range of both good and mad content: how significant do you think YouTube (and the explosion of smartphone video) content is in today’s information / media environment? (And are filter bubbles really a thing..?)

Mark / Donna: Yeah, we think that the filter bubbles are real. Again, we think that social media has a lot of potential to provide new information to people (and still does); although currently social media is falling into the same selectivity bias that characterizes the traditional media. We encourage our students to use online technology to seek out diverse sources; sources that both mirror their opinions and that oppose their opinions. People in the US can access diverse sources on a daily basis, but they have to be willing to seek out perspectives that differ from their own view, perspectives other than their favoured news source.

The key is getting individuals to want to challenge themselves and to be open to cognitive dissonance as they read or watch material that differs from their belief systems. Technology is advanced but humans still suffer the cognitive limitations from which they have always suffered. The political system in the US, and likely other places, encourages it. The key is for individuals to be willing to listen to views unlike their own.

Read the full article: Lybecker, D.L., McBeth, M.K., Husmann, M.A, and Pelikan, N. (2015) Do New Media Support New Policy Narratives? The Social Construction of the U.S.–Mexico Border on YouTube. Policy & Internet 7 (4). DOI: 10.1002/poi3.94.

Mark McBeth and Donna Lybecker were talking to blog editor David Sutcliffe.

A cheaper way to measure these dimensions, for example by applying predictive algorithms to existing secondary data like socioeconomic characteristics, socio-demographics, and condition of housing stock, would certainly help policy makers gain a better understanding of local communities. In their Policy & Internet article “Predicting Sense of Community and Participation by Applying Machine Learning to Open Government Data”, Alessandro Piscopo, Ronald Siebes, and Lynda Hardman employ a machine-learning technique (“Random Forests”) to evaluate an estimate of community capacity derived from open government data, and determine the most important predictive variables.

The resulting models were found to be more accurate than those based on traditional statistics, demonstrating the feasibility of the Random Forests technique for this purpose — being accurate, able to deal with small data sets and nonlinear data, and providing information about how each variable in the dataset contributes to predictive accuracy.

We caught up with the authors to discuss their findings:

Ed.: Just briefly: how did you do the study? Were you essentially trying to find which combinations of variables available in Open Government Data predicted “sense of community and participation” as already measured by surveys?

Authors: Our research stemmed from an observation of the measures of social characteristics available. These are generally obtained through expensive surveys, so we asked ourselves “how could we generate them in a more economic and efficient way?” In recent years, the UK government has openly released a wealth of datasets, which could be used to provide information for other purposes — in our case, providing measures of sense of community and participation — than those for which they had been created. We started our work by consulting papers from the social science domain, to understand which factors were associated to sense of community and participation. Afterwards, we matched the factors that were most commonly mentioned in the literature with “actual” variables found in UK Open Government Data sources.

Ed.: You say “the most determinant variables in our models were only partially in agreement with the most influential factors for sense of community and participation according to the social science literature” — which were they, and how do you account for the discrepancy?

Authors: We observed two types of discrepancy. The first was the case of variables that had roughly the same level of importance in our models and in others previously developed, but with a different rank. For instance, median age was by far the most determinant variable in our model for sense of community. This variable was not ranked among the top five variables in the literature, although it was listed among the significant variables.

The second type of discrepancy regarded variables which were highly important in our models and not influential in others, or vice versa. An example is the socioeconomic status of residents of a neighbourhood, which appeared to have no effect on participation in prior studies, but was the top-ranking variable in our participation model (operationalised as the number of people in intermediate occupation).

We believe that there are multiple explanations for these phenomena, all of which deserve further investigation. First, highly determinant predictors in conventional statistical models have been proven to have little or no importance in ensemble algorithms, such as the one we used [1]. Second, factors influencing sense of community and civic participation may vary according to the context (e.g. different countries; see [3] about sense of community in China for an example). Finally, different methods may measure different aspects related to a socially meaningful concept, leading to different partial explanations.

Ed.: What were the predictors for “lack of community” — i.e. what would a terrible community look like, according to your models?

Authors: Our work did not really focus on finding “good” and “bad” communities. However, we did notice some characteristics that were typical of communities with low sense of community or participation in our dataset. For example, sense of community had a strong negative correlation with work and stores accessibility, with ethnic fragmentation, and with the number of people living in the UK for less than 10 years. On the other hand, it was positively correlated with the age of residents. Participation, instead, was negatively correlated with household composition and occupation of its residents, whilst it had a positive relation with their level of education and the weekly worked hours. Of course, these data would require to be interpreted by a social scientist, in order to properly contextualise and understand them.

Ed.: Do you see these techniques as being more useful to highlight issues and encourage discussion, or actually being used in planning? For example, I can see it might raise issues if machine-learning models “proved” that presence of immigrant populations, or neighbourhoods of mixed economic or ethnic backgrounds, were less cohesive than homogeneous ones (not sure if they are?).

Authors: How machine learning algorithms work is not always clear, even to specialists, and this has led some people to describe them as “black boxes”. We believe that models like those we developed can be extremely useful to challenge existing perspectives based on past data available in the social science literature, e.g. they can be used to confirm or reject previous measures in the literature. Additionally, machine learning models can serve as indicators that can be more frequently consulted: they are cheaper to produce, we can use them more often, and see whether policies have actually worked.

Ed.: It’s great that existing data (in this case, Open Government Data) can be used, rather than collecting new data from scratch. In practice, how easy is it to repurpose this data and build models with it — including in countries where this data may be more difficult to access? And were there any variables you were interested in that you couldn’t access?

Authors: Identifying relevant datasets and getting hold of them was a lengthy process, even in the UK, where plenty of work has been done to make government data openly available. We had to retrieve many datasets from the pages of the government department that produced them, such as the Department for Work and Pensions or the Home Office, because we could not find them through the portal data.gov.uk. Next to this, the ONS website was another very useful resource, which we used to get census data.

The hurdles encountered in gathering the data led us to recommend the development of methods that would be able to more automatically retrieve datasets from a list of sources and select the ones that provide the best results for predictive models of social dimensions.

Ed.: The OII has done some similar work, estimating the local geography of Internet use across Britain, combining survey and national census data. The researchers said the small-area estimation technique wasn’t being used routinely in government, despite its power. What do you think of their work and discussion, in relation to your own?

Authors: One of the issues we were faced with in our research was the absence of nationwide data about sense of community and participation at a neighbourhood level. The small area estimation approach used by Blank et al., 2017 [2] could provide a suitable solution to the issue. However, the estimates produced by their approach understandably incorporate a certain amount of error. In order to use estimated values as training data for predictive models of community measures it would be key to understand how this error would be propagated to the predicted values.

[1] Berk, R. 2006. “ An Introduction to Ensemble Methods for Data Analysis.” Sociological Methods & Research 34 (3): 263–95.
[2] Blank, G., Graham, M., and Calvino, C. 2017. Local Geographies of Digital Inequality. Social Science Computer Review. DOI: 10.1177/0894439317693332.
[3] Xu, Q., Perkins, D.D. and Chow, J.C.C., 2010. Sense of community, neighboring, and social capital as predictors of local political participation in China. American journal of community psychology, 45(3-4), pp.259-271.

Read the full article: Piscopo, A., Siebes, R. and Hardman, L. (2017) Predicting Sense of Community and Participation by Applying Machine Learning to Open Government Data. Policy & Internet 9 (1) doi:10.1002/poi3.145.

Alessandro Piscopo, Ronald Siebes, and Lynda Hardman were talking to blog editor David Sutcliffe.

Some operators consider the games to be a source of additional revenue in jurisdictions where online gambling is largely illegal, or a way to attract new customers to a land-based gambling venue. Hybrid models are also emerging, with the potential for tangible rewards for playing social casino games. This merging of gaming and gambling means that many previously established boundaries are becoming blurred, and at many points, the two are indistinguishable.

However, content analysis of game content and advertising can help researchers, industry, and policymakers better understand how the two entertainment forms overlap. In their Policy & Internet article “Gambling Games on Social Platforms: How Do Advertisements for Social Casino Games Target Young Adults?”, Brett Abarbanel, Sally M. Gainsbury, Daniel King, Nerilee Hing, and Paul H. Delfabbro undertake a content analysis of 115 social casino gaming advertisements captured by young adults during their regular Internet use. They find advertisement imagery typically features images likely to appeal to young adults, with message themes including a glamorizing and normalization of gambling. Notably, nearly 90 percent of the advertisements contained no responsible or problem gambling language, despite the gambling-like content.

Gambling advertisements currently face much stricter restrictions on exposure and distribution than do social casino game advertisements: despite the latter containing much gambling-themed content designed to attract consumers. Given the receptivity of young people to messages that encourage gambling, the authors recommend that gaming companies embrace corporate social responsibility standards, including adding warning messages to advertisements for gambling-themed games. They hope that their qualitative research may complement existing quantitative findings, and facilitate discussions about appropriate policies for advertisements for social casino games and other gambling-themed games.

We caught up with Brett to discuss their findings:

Ed.: You say there are no policies related to the advertising of social casino games — why is this? And do you think this will change?

Brett: Social casino games are regulated under general consumer regulations, but there are no specific regulations for these types of games and they do not fall under gambling regulation. Although several gambling regulatory bodies have considered these games, as they do not require payment to play and prizes have no monetary value they are not considered gambling activities. Where the games include branding for gambling companies or are considered advertising, they may fall under relevant legislation. Currently it is up to individual consumers to consider if they are relevant, which includes parents considering their children’s’ use of the games.

Ed.: Is there work on whether these sorts of games actually encourage gambling behaviour? As opposed to gambling behaviour simply pre-existing — i.e. people are either gamblers or not, susceptible or not.

Brett: We have conducted previous research showing that almost one-fifth of adults who played social casino games had gambled for money as a direct result of these games. Research also found that two-thirds of adolescents who had paid money to play social casino games had gambled directly as a result of these games. This builds on other international research suggesting that there is a pathway between games and gambling. For some people, the games are perceived to be a way to ‘try out’ or practice gambling without money and most are motivated to gamble due to the possibility of winning real money. For some people with gambling problems, the games can trigger the urge to gamble, although for others, the games are used as a way to avoid gambling in an attempt to cut back. The pathway is complicated and needs further specific research, including longitudinal studies.

Ed.: Possibly a stupid question: you say social games are a huge and booming market, despite being basically free to play. Where does the revenue come from?

Brett: Not a stupid question at all! When something is free, of course it makes sense to question where the money comes from. The revenue in these business models comes from advertisements and players. The advertisement revenue model is similar to other revenue models, but the player revenue model, which is based largely on micropayments, is a major component of how these games make money. Players can typically play free, and micropayments are voluntary. However, when they run out of free chips, players have to wait to continue to play, or they can purchase additional chips.

The micropayments can also improve game experience, such as to obtain in-game items, as a temporary boost in the game, to add lives/strength/health to an avatar or game session, or unlock the next stage in the game. In social casino games, for example, micropayments can be made to acquire more virtual chips with which to play the slot game. Our research suggests that only a small fraction of the player base actually makes micropayments, and a smaller fraction of these pay very large amounts. Since many of these games are free to play, but one can pay to advance through game in certain ways, they have colloquially been referred to as “freemium” games.

Ed.: I guess social media (like Facebook) are a gift to online gambling companies: i.e. being able to target (and A/B test) their adverts to particular population segments? Are there any studies on the intersection of social media, gambling and behavioural data / economics?

Brett: There is a reasonable cross-over in social casino game players and gamblers – our Australian research found 25% of Internet and 5% of land-based gamblers used social casino games and US studies show around one-third of social casino gamers visit land-based casinos. Many of the most popular and successful social casino games are owned by companies that also operate gambling, in venues and online. Some casino companies offer social casino games to continue to engage with customers when they are not in the venue and may offer prizes that can be redeemed in venues. Games may allow gambling companies to test out how popular games will be before they put them in venues. Although, as most players do not pay to play social casino games, they may engage with these differently from gambling products.

Ed.: We’ve seen (with the “fake news” debate) social media companies claiming to simply be a conduit to others’ content, not content providers themselves. What do they say in terms of these social games: I’m assuming they would either claim that they aren’t gambling, or that they aren’t responsible for what people use social media for?

Brett: We don’t want to speak for the social media companies themselves, and they appear to leave quite a bit up to the game developers. Advertising standards have become more lax on gambling games – the example we give in our article is Google, who had a strict policy against advertisements for gambling-related content in the Google Play store but in February 2015 began beta testing advertisements for social casino games. In some markets where online gambling is restricted, online gambling sites offer ‘free’ social casino games that link to real money sites as a way to reach these markets.

Ed.: I guess this is just another example of the increasingly attention-demanding, seductive, sexualised, individually targeted, ubiquitous, behaviourally attuned, monetised environment we (and young children) find ourselves in. Do you think we should be paying attention to this trend (e.g. noticing the close link between social gaming and gambling) or do you think we’ll all just muddle along as we’ve always done? Is this disturbing, or simply people doing what they enjoy doing?

Brett: We should certainly be paying attention to this trend, but don’t think the activity of social casino games is disturbing. A big part of the goal here is awareness, followed by conscious action. We would encourage companies to take more care in controlling who accesses their games and to whom their advertisements are targeted. As you note, David, we are in such a highly-targeted, specified state of advertising. As a result, we should, theoretically, be able to avoid marketing games to young kids. Companies should also certainly be mindful of the potential effect of cartoon games. We don’t automatically assign a sneaky, underhanded motive to the industry, but at the same time there is a percentage of the population that is at risk for gambling problems and we don’t want to exacerbate the situation by inadvertently advertising to young people, who are more susceptible to this type of messaging.

Read the full article: Abarbanel, B., Gainsbury, S.M., King, D., Hing, N., and Delfabbro, P.H. (2017) Gambling Games on Social Platforms: How Do Advertisements for Social Casino Games Target Young Adults? Policy & Internet 9 (2). DOI: 10.1002/poi3.135.

Brett Abarbanel was talking to blog editor David Sutcliffe.

Although these volunteers provide useful technical assistance to humanitarian efforts (e.g. when maps and records don’t exist or are lost), their lack of affiliation with “formal” actors, such as the United Nations, and the very fact that they are volunteers, makes them a dubious data source. Indeed, concerns have been raised about the quality of amateur mapping and data efforts, and the uses to which they are put. Most of these concerns assume that volunteers have no professional training. And herein lies the contradiction: by doing the work for free and at their own will the volunteers make these efforts possible and innovative, but this is also why crisis mapping is doubted and questioned by experts.

By investigating crisis-mapping volunteers and organizations, Elizabeth Resor’s article “The Neo-Humanitarians: Assessing the Credibility of Organized Volunteer Crisis Mappers” published in Policy & Internet presents evidence of a more professional cadre of volunteers and a means to distinguish between different types of volunteer organizations. Given these organizations now play an increasingly integrated role in humanitarian responses, it’s crucial that their differences are understood and that concerns about the volunteers are answered.

We caught up with Elizabeth to discuss her findings:

Ed.: We have seen from Citizen Science (and Wikipedia) that large crowds of non-professional volunteers can produce work of incredible value, if projects are set up right. Are the fears around non-professional crisis mappers valid? For example, is this an environment where everything “must be correct”, rather than “probably mostly correct”?

Elizabeth: Much of the fears around non-professional crisis mappers comes from a lack of understanding about who the volunteers are and why they are volunteering. As these questions are answered and professional humanitarian actors become more familiar with the concept of volunteer humanitarians, I think many of these fears are diminishing.

Due to the fast-paced and resource-constrained environments of humanitarian crises, traditional actors, like the UN, are used to working with “good enough” data, or data that are “probably mostly correct”. And as you point out, volunteers can often produce very high quality data. So when you combine these two facts, it stands to reason that volunteer crisis mappers can contribute necessary data that is most likely as good as (if not better) than the data that humanitarian actors are used to working with. Moreover, in my research I found that most of these volunteers are not amateurs in the full sense because they come from related professional fields (such as GIS).

Ed.: I suppose one way of assuaging fears is to maybe set up an umbrella body of volunteer crisis mapping organisations, and maybe offer training opportunities and certification of output. But then I suppose you just end up as professionals. How blurry are the lines between useful-not useful / professional-amateur in crisis mapping?

Elizabeth: There is an umbrella group for volunteer organizations set up exactly for that reason! It’s called the Digital Humanitarian Network. At the time that I was researching this article, the DHN was very new and so I wasn’t able to ask if actors were more comfortable working with volunteers contacted through the DHN, but that would be an interesting issue to look into.

The two crisis mapping organizations I researched — the Standby Task Force and the GIS Corps — both offer training and some structure to volunteer work. They take very different approaches to the volunteer work — the Standby Task Force work can include very simple micro-tasks (like classifying photographs), whereas the GIS Corps generally provides quite specialised technical assistance (like GIS analysis). However, both of these kinds of tasks can produce useful and needed data in a crisis.

Ed.: Another article in the journal examined the effective take-over of a Russian crisis volunteer website by the Government, i.e. by professionalising (and therefore controlling) the site and volunteer details they had control over who did / didn’t turn up in disaster areas (effectively meaning nonprofessionals were kept out). How do humanitarian organisations view volunteer crisis mappers: as useful organizations to be worked with in parallel, or as something to be controlled?

Elizabeth: I have seen examples of humanitarian and international development agencies trying to lead or create crowdsourcing responses to crises (for example, USAID “Mapping to End Malaria“). I take this as a sign that these agencies understand the value in volunteer contributions — something they wouldn’t have understood without the initial examples created by those volunteers.

Still, humanitarian organizations are large bureaucracies, and even in a crisis they function as bureaucracies, while volunteer organizations take a nimble and flexible approach. This structural difference is part of the value that volunteers can offer humanitarian organizations, so I don’t believe that it would be in the best interest of the humanitarian organizations to completely co-opt or absorb the volunteer organizations.

Ed.: How does liability work? Eg if crisis workers in a conflict zone are put in danger by their locations being revealed by well-meaning volunteers? Or mistakes being being made on the ground because of incorrect data — perhaps injected by hostile actors to create confusion (thinking of our current environment of hybrid warfare..).

Elizabeth: Unfortunately, all humanitarian crises are dangerous and involve threats to “on the ground” response teams as well as affected communities. I’m not sure how liability is handled. Incorrect data or revealed locations might not be immediately traced back to the source of the problem (i.e. volunteers) and the first concern would be minimizing the harm, not penalizing the cause.

Still, this is the greatest challenge to volunteer crisis mapping that I see. Volunteers don’t want to cause more harm than good, and to do this they must understand the context of the crisis in which they are getting involved (even if it is remotely). This is where relationships with organizations “on the ground” are key. Also, while I found that most volunteers had experience related to GIS and/or data analysis, very few had experience in humanitarian work. This seems like an area where training can help volunteers understand the gravity of their work, to ensure that they take it seriously and do their best work.

Ed.: Finally, have you ever participated as a volunteer crisis mapper? And also: how do you the think the phenomenon is evolving, and what do you think researchers ought to be looking at next?

Elizabeth: I haven’t participated in any active crises, although I’ve tried some of the tools and trainings to get a sense of the volunteer activities.

In terms of future research, you mentioned hybridized warfare and it would be interesting to see how this change in the location of a crisis (i.e. in online spaces as well as physical spaces) is changing the nature of volunteer responses. For example, how can many dispersed volunteers help monitor ISIS activity on YouTube and Twitter? Or are those tasks better suited for an algorithm? I would also be curious to see how the rise of isolationist politicians in Europe and the US has influenced volunteer crisis mapping. Has this caused more people to want to reach out and participate in international crises or is it making them more inward-looking? It’s certainly an interesting field to follow!

Read the full article: Resor, E. (2016) The Neo-Humanitarians: Assessing the Credibility of Organized Volunteer Crisis Mappers. Policy & Internet 8 (1) DOI:10.1002/poi3.112.

Elizabeth Resor was talking to blog editor David Sutcliffe.

In his Policy & Internet article “Cleavage Structures and Dimensions of Ideology in English Politics: Evidence From Voting Advice Application Data”, Jonathan Wheatley argues that the cleavage that exists in many European societies between “winners” and “losers” of globalization has engendered a new ideological dimension pitting “cosmopolitans” against “communitarians” and that draws on cultural issues relating to identity — rather than economic issues.

He identifies latent dimensions from opinion data generated by two Voting Advice Applications deployed in England in 2014 and 2015 — finding that the political space in England is defined by two main ideological dimensions: an economic Left–Right dimension and a cultural communitarian–cosmopolitan dimension. While they co-vary to a significant degree, with economic rightists tending to be more communitarian and economic leftists tending to be more cosmopolitan, these tendencies do not always hold and the two dimensions should be considered as separate.

The identification of the communitarian–cosmopolitan dimension lends weight to the hypothesis of Kriesi et al. (2006) that politics is increasingly defined by a cleavage between “winners” and “losers” of globalization, with “losers” tending to adopt a position of cultural demarcation and to perceive “outsiders” such as immigrants and the EU, as a threat. If an economic dimension pitting Left against Right (or labour against capital) defined the political arena in Europe in the twentieth century, maybe it’s a cultural cleavage that pits cosmopolitans against communitarians that defines politics in the twenty-first.

We caught up with Jonathan to discuss his findings:

Ed.: The big thing that happened since your article was published was Brexit — so I guess the “communitarian–cosmopolitan” dimension (Trump!) makes obvious intuitive sense as a political cleavage plane. Will you be comparing your GE2015 VAA data with GE2017 data? And what might you expect to see?

Jonathan: Absolutely! We will be launching the WhoGetsMyVoteUK Voting Advice Application next week. This VAA will be launched by three universities: Oxford Brookes University (where I am based), Queen Mary University London and the University of Bristol. This should provide extensive data that will allow us to make a longitudinal study: before and after Brexit.

Ed.: There was a lot of talk (for the first time) after Brexit of “the left behind” — I suppose partly corresponding to your “communitarians” — but that all seems to have died down. Of course they’re still there: is there any sense of how they will affect the upcoming election — particularly the “communitarian leftists”?

Jonathan: Well this is the very group that Theresa May’s Conservative Party seems to be targeting. We should note that May has attempted to appeal directly to this group by her claim that “if you believe you’re a citizen of the world, you’re a citizen of nowhere” made at the Tory Party Conference last autumn, and by her assertion that “Liberalism and globalisation have left people behind” made at the Lord Mayor’s banquet late last year. Her (at least superficially) economically leftist proposals during the election campaign to increase the living wage and statutory rights for family care and training, and to strengthen labour laws, together with her “hard Brexit stance” and confrontational rhetoric towards European leaders seems specifically designed to appeal to this group. Many of these “communitarian leftists” have previously been tempted by UKIP, but the Conservatives seem to be winning the battle for their votes at the moment.

Ed.: Does the UK’s first-past-the-post system (resulting in a non-proportionally representative set of MPs) just hide what is happening underneath, i.e. I’m guessing a fairly constant, unchanging spectrum of political leanings? Presumably UKIP’s rise didn’t signify a lurch to the right: it was just an efficient way of labelling (for a while) people who were already there?

Jonathan: To a certain extent, yes. Superficially the UK has very much been a case of “business as usual” in terms of its party system, notwithstanding the (perhaps brief) emergence of UKIP as a significant force in around 2012. This can be contrasted with Sweden, Finland and the Netherlands, where populist right parties obtained significant representation in parliament. And UKIP may prove to be a temporary phenomenon. The first-past-the-post system provides more incentives for parties to reposition themselves to reflect the new reality than it does for new parties to emerge. In fact it is this repositioning, from a economically right-wing, mildly cosmopolitan party to an (outwardly) economically centrist, communitarian party, that seems to characterise the Tories today.

Ed.: Everything seems to be in a tremendous mess (parties imploding, Brexit horror, blackbox campaigning, the alt-right, uncertainty over tactical voting, “election hacking”) and pretty volatile. But are these exciting times for political scientists? Or are things too messy and the data (for example, on voting intensions as well as outcomes) too inaccessible to distinguish any grand patterns?

Jonathan: Exciting from a political science point of view; alarming from the point of view of a member of society.

Ed.: But talking of “grand patterns”: do you have any intuition why “the C20 might be about capital vs labour; the C21 about local vs global”? Is it simply the next obvious reaction to ever-faster technological development and economic concentration bumping against societal inertia, or something more complex and unpredictable?

Jonathan: Over generations European societies gradually developed mechanisms of accountability to constrain their leaders and ensure they did not over-reach their powers. This is how democracy became consolidated. Hoverver, given that power is increasingly accruing to transnational and multinational corporations and networks that are beyond the reach of citizens operating in the national sphere, we must learn how to do this all over again on a global scale. Until we do so, globalisation will inevitably create “winners” and “losers” and will, I think, inevitably lead to more populism and upheaval.

Read the full article: Wheatley, J. (2016) Cleavage Structures and Dimensions of Ideology in English Politics: Evidence From Voting Advice Application Data. Policy & Internet 8 (4) doi:10.1002/poi3.129

Jonathan Wheatley was talking to blog editor David Sutcliffe.

Three Trends

1. The proliferation of Wi-Fi means when children can use smart phones or tablets in variety of new contexts including on buses and trains, in hotels and restaurants, in school, libraries and health centre waiting rooms.

2. Research confirms apps on smart phones and tablets are now children’s primary gateway to the Web. This is the appification of the Web that Jonathon Zittrain predicted: the WeChat app, popular in China, is becoming its full realisation.

3. Simultaneously, the rapid expansion of the Internet of Things means everything is becoming ‘smart’ – phones, cars, toys, baby monitors, watches, toasters: we are even promised smart cities. Essentially, this means these devices have an IP address that allows to them receive, process, and transmit data on the Internet. Often these devices (including personal assistants like Alexa, game consoles and smart TVs) are picking up data produced by children. Marketing about smart toys tells us they are enhancing children’s play, augmenting children’s learning, incentivising children’s healthy habits and can even reclaim family time. Salient examples include Hello Barbie and Smart Toy Bear, which use voice and/or image recognition and connect to the cloud to analyse, process, and respond to children’s conversations and images. This sector is expanding to include app-enabled toys such as toy drones, cars, and droids (e.g. Star Wars BB-8); toys-to-life, which connect action figures to video games (e.g. Skylanders, Amiibo); puzzle and building games (e.g. Osmo, Lego Fusion); and children’s GPS-enabled wearables such as smart watches and fitness trackers. We need to look beyond the marketing to see what is making this technology ubiquitous.

The commercial incentives to collect children’s data

Service providers now use free Wi-Fi as an additional enticement to their customers, including families. Apps offer companies opportunities to contain children’s usage in a walled-garden so that they can capture valuable marketing data, or offer children and parents opportunities to make in-app purchases. Therefore, more and more companies, especially companies that have no background in technology such as bus operators and cereal manufactures, use Wi-Fi and apps to engage with children.

The smart label is also a new way for companies to differentiate their products from others in saturated markets that overwhelm consumers with choice. However, security is an additional cost that manufactures of smart technologies manufacturers are unwilling to pay. The microprocessors in smart toys often don’t have the processing power required for strong security measures and secure communication, such as encryption (e.g. an 8-bit microcontroller cannot support the industry standard SSL to encrypt communications). Therefore these devices are designed without the ability to accommodate software or firmware updates. Some smart toys transmit data in clear text (parents of course are unaware of such details when purchasing these toys).

While children are using their devices they are constantly emitting data. Because this data is so valuable to businesses it has become a cliché to frame it as an exploitable ‘natural’ resource like oil. This means every digitisable movement, transaction and interaction we make is potentially commodifiable. Moreover, the networks of specialist companies, partners and affiliates that capture, store process, broker and resell the new oil are becoming so complex they are impenetrable. This includes the involvement of commercial actors in public institutions such as schools.

Lupton & Williamson (2017) use the term ‘datafied child’ to draw attention to this creeping normalisation of harvesting data about children. As its provenance becomes more opaque the data is orphaned and vulnerable to further commodification. And when it is shared across unencrypted channels or stored using weak security (as high profile cases show) it is easily hacked. The implications of this are only beginning to emerge. In response, children’s rights, privacy and protection; the particular ethics of the capture and management of children’s data; and its potential for commercial exploitation are all beginning to receive more attention.

Refocusing on children

Apart from a ticked box, companies have no way of knowing if a parent or child has given their consent. Children, or their parents, will often sign away their data to quickly dispatch any impediment to accessing the Wi-Fi. When children use public Wi-Fi they are opening, often unencrypted, channels to their devices. We need to start mapping the range of actors who are collecting data in this way and find out if they have any provisions for protecting children’s data.

Similarly, when children use their apps, companies assume that a responsible adult has agreed to the terms and conditions. Parents are expected to be gatekeepers, boundary setters, and supervisors. However, for various reasons, there may not be an informed, (digitally) literate adult on hand. For example, parents may be too busy with work or too ill to stay on top of their children’s complex digital lives. Children are educated in year groups but they share digital networks and practices with older children and teenagers, including siblings, extended family members, and friends who may enable risky practices.

We may need to start looking at additional ways of protecting children that transfers the burden away from the family and to companies that are capturing and monetising the data. This includes being realistic about the efficacy of current legislation. Because children can simply enter a fake birthdate, application of the US Children’s Online Privacy Protection Act to restrict the collection of children’s personal data online has been fairly ineffectual (boyd et al., 2011). In Europe, the incoming General Data Protection Regulation allows EU states to set a minimum age of 16 under which children cannot consent to having their data processed, potentially encouraging and even larger population of minors to lie about their age online.

We need to ask what would data capture and management look like if it is guided by a children’s framework such as this one developed here by Sonia Livingstone and endorsed by the Children’s Commissioner here. Perhaps only companies that complied with strong security and anonymisation procedures would be licenced to trade in UK? Given the financial drivers at work, an ideal solution would possibly make better regulation a commerical incentive. We will be exploring these and other similar questions that emerge over the coming months.

This work is part of the OII project “Child safety on the Internet: looking beyond ICT actors“, which maps the range of non-ICT companies engaging digitally with children and identifying areas where their actions might affect a child’s exposure to online risks such as data theft, adverse online experiences or sexual exploitation. It is funded by the Oak Foundation.

Being excluded from the Internet economy has negative economic and social implications; it is therefore important for policymakers to ask how policy can bridge this inequality. But does policy actually have an effect on these differences? And if so, which specific policy variables? In their Policy & Internet article “Crossing the Digital Desert in Sub-Saharan Africa: Does Policy Matter?”, Robert Wentrup, Xiangxuan Xu, H. Richard Nakamura, and Patrik Ström address the dearth of research assessing the interplay between policy and Internet penetration by identifying Internet penetration-related policy variables and institutional constructs in Sub-Saharan Africa. It is a first attempt to investigate whether Internet policy variables have any effect on Internet penetration in Sub-Saharan Africa, and to shed light on them.

Based on a literature review and the available data, they examine four variables: (i) free flow of information (e.g. level of censorship); (ii) market concentration (i.e. whether or not internet provision is monopolistic); (iii) the activity level of the Universal Service Fund (a public policy promoted by some governments and international telecom organizations to address digital inclusion); and (iv) total tax on computer equipment, including import tariffs on personal computers. The results show that only the activity level of the USF and low total tax on computer equipment are significantly positively related to Internet penetration in Sub-Saharan Africa. Free flow of information and market concentration show no impact on Internet penetration. The latter could be attributed to underdeveloped competition in most Sub-Saharan countries.

The authors argue that unless states pursue an inclusive policy intended to enhance Internet access for all its citizens, there is a risk that the skewed pattern between the “haves” and the “have nots” will persist, or worse, be reinforced. They recommend that policymakers promote the policy instrument of Universal Service and USF and consider substituting tax on computer equipment with other tax revenues (i.e. introduce consumption-friendly incentives), and not to blindly trust the market’s invisible hand to fix inequality in Internet diffusion.

We caught up with Robert to discuss the findings:

Ed.: I would assume that Internet penetration is rising (or possibly even booming) across the continent, and that therefore things will eventually sort themselves out — is that generally true? Or is it already stalling / plateauing, leaving a lot of people with no apparent hope of ever getting online?

Robert: Yes, generally we see a growth in Internet penetration across Africa. But it is very heterogeneous and unequal in its character, and thus country-specific. Some rich African countries are doing quite well whereas others are lagging behind. We have also seen known that Internet connectivity is vulnerable due to the political situation. The recent shutdown of the Internet in Cameroon demonstrates this vulnerability.

Ed.: You mention that “determining the causality between Internet penetration and [various] factors is problematic” – i.e. that the relation between Internet use and economic growth is complex. This presumably makes it difficult for effective and sweeping policy “solutions” to have a clear effect. How has this affected Internet-policy in the region, if at all?.

Robert: On the one hand one can say that if there is economic growth, there will be money to invest in Internet infrastructure and devices, and on the other hand if there are investments in Internet infrastructure, there will be economic growth. This resembles the chicken and egg problem. For many African countries, which lack large public investment funds and at the same time suffer from other more important socio-economic challenges, it might be tricky to put effort into Internet policy issues. But there are some good examples of countries that have actually managed to do this, for example Kenya. As a result these efforts can lead to positive effects on the society and economy as a whole. The local context, and a focus on instruments that disseminate Internet usage in unprivileged geographic areas and social groups (like the Universal Service Fund) are very important.

Ed.: How much of the low Internet perpetration in large parts of Africa is simply due to large rural populations — and therefore something that will either never be resolved properly, or that will naturally resolve itself with the ongoing shift to urban centres?

Robert: We did not see a clear causality between rural population and low Internet on a country level, mainly due to the fact that countries with a large rural population are often quite rich and thus also have money to invest in Internet infrastructure. Africa is very dependent on agriculture. Although the Internet connectivity issue might be “self-resolved” to some degree by urban migration, other issues would emerge from such a shift such as an increased socio-economic divide in the urban areas. Hence, it is more effective to make sure that the Internet reaches rural areas at an early stage.

Ed.: And how much does domestic policy (around things like telecoms) get set internally, as opposed to externally? Presumably some things (e.g. the continent-wide cables required to connect Africa to the rest of the world) are easier to bring about if there is a strong / stable regional policy around regulation of markets and competition — whether organised internally, or influenced by outside governments and industry?

Robert: The influence of telecom ministries and telecom operators is strong, but of course they are affected by intra-regional organisations, private companies etc. In the past Africa has had difficulties in developing pan-regional trade and policies. But such initiatives are encouraged, not least in order to facilitate cost-sharing of large Internet-related investments.

Ed.: Leaving aside the question of causality, you mention the strong correlation between economic activity and Internet penetration: are there any African countries that buck this trend — at either end of the economic scale?

Robert: We have seen that Kenya and Nigeria have had quite impressive rates of Internet penetration in relation to GDP. Gabon on the other hand is a relatively rich African country, but with quite low Internet penetration.

Read the full article: Wentrup, R., Xu, X., Nakamura, H.R., and Ström, P. (2016) Crossing the Digital Desert in Sub-Saharan Africa: Does Policy Matter? Policy & Internet 8 (3). doi:10.1002/poi3.123

Robert Wentrup was talking to blog editor David Sutcliffe.

This seeming inconsistency between intent and behaviour is routinely explained with reference to the “privacy paradox”. Advertisers, retailers, and others with a vested interest in avoiding the regulation of digital data collection have pointed to this so-called paradox as an argument against government intervention. By phrasing privacy as a choice between involvement in (or isolation from) various social and economic communities, they frame information disclosure as a strategic decision made by informed consumers. Indeed, discussions on digital privacy have been dominated by the idea of the “empowered consumer” or “privacy pragmatist” — an autonomous individual who makes informed decisions about the disclosure of their personal information.

But there is increasing evidence that “control” is a problematic framework through which to operationalize privacy. In her Policy & Internet article “From Privacy Pragmatist to Privacy Resigned: Challenging Narratives of Rational Choice in Digital Privacy Debates,” Nora A. Draper examines how the figure of the “privacy pragmatist” developed by the prominent privacy researcher Alan Westin has been used to frame privacy within a typology of personal preference — a framework that persists in academic, regulatory, and commercial discourses in the United States. Those in the pragmatist group are wary about the safety and security of their personal information, but make supposedly rational decisions about the conditions under which they are comfortable with disclosure, logically calculating the costs and benefits associated with information exchange.

Academic critiques of this model have tended to focus on the methodological and theoretical validity of the pragmatist framework; however, in light of two recent studies that suggest individuals are resigned to the loss of privacy online, this article argues for the need to examine a possibility that has been overlooked as a consequence of this focus on Westin’s typology of privacy preferences: that people have opted out of the discussion altogether. Considering a theory of resignation alters how the problem of privacy is framed and opens the door to alternative discussions around policy solutions.

We caught up with Nora to discuss her findings:

Ed.: How easy is it even to discuss privacy (and people’s “rational choices”), when we know so little about what data is collected about us through a vast number of individually innocuous channels — or the uses to which it is put?

Nora: This is a fundamental challenge in current discussions around privacy. There are steps that we can take as individuals that protect us from particular types of intrusion, but in an environment where seemingly benign data flows are used to understand and predict our behaviours, it is easy for personal privacy protection to feel like an uphill battle. In such an environment, it is increasingly important that we consider resigned inaction to be a rational choice.

Ed.: I’m not surprised that there will be people who basically give up in exhaustion, when faced with the job of managing their privacy (I mean, who actually reads the Google terms that pop up every so often?). Is there a danger that this lack of engagement with privacy will be normalised during a time that we should actually be paying more, not less, attention to it?

Nora: This feeling of powerlessness around our ability to secure opportunities for privacy has the potential to discourage individual or collective action around privacy. Anthropologists Peter Benson and Stuart Kirsch have described the cultivation of resignation as a strategy to discourage collective action against undesirable corporate practices. Whether or not these are deliberate efforts, the consequences of creating a nearly unnavigable privacy landscape is that people may accept undesirable practices as inevitable.

Ed.: I suppose another irony is the difficulty of getting people to care about something that nevertheless relates so fundamentally and intimately to themselves. How do we get privacy to seem more interesting and important to the general public?

Nora: People experience the threats of unwanted visibility very differently. For those who are used to the comfortable feeling of public invisibility — the types of anonymity we feel even in public spaces — the likelihood of an unwanted privacy breach can feel remote. This is one of the problems of thinking about privacy purely as a personal issue. When people internalize the idea that if they have done nothing wrong, they have no reason to be concerned about their privacy, it can become easy to dismiss violations when they happen to others. We can become comfortable with a narrative that if a person’s privacy has been violated, it’s likely because they failed to use the appropriate safeguards to protect their information.

This cultivation of a set of personal responsibilities around privacy is problematic not least because it has the potential to blame victims rather than those parties responsible for the privacy incursions. I believe there is real value in building empathy around this issue. Efforts to treat privacy as a community practice and, perhaps, a social obligation may encourage us to think about privacy as a collective rather than individual value.

Ed.: We have a forthcoming article that explores the privacy views of Facebook / Google (companies and employees), essentially pointing out that while the public may regard privacy as pertaining to whether or not companies collect information in the first place, the companies frame it as an issue of “control” — they collect it, but let users subsequently “control” what others see. Is this fundamental discrepancy (data collection vs control) something you recognise in the discussion?

Nora: The discursive and practical framing of privacy as a question of control brings together issues addressed in your previous two questions. By providing individuals with tools to manage particular aspects of their information, companies are able to cultivate an illusion of control. For example, we may feel empowered to determine who in our digital network has access to a particular posted image, but little ability to determine how information related to that image — for example, its associated metadata or details on who likes, comments, or reposts it — is used.

The “control” framework further encourages us to think about privacy as an individual responsibility. For example, we may assume that unwanted visibility related to that image is the result of an individual’s failure to correctly manage their privacy settings. The reality is usually much more complicated than this assigning of individual blame allows for.

Ed.: How much of the privacy debate and policy making (in the States) is skewed by economic interests — i.e. holding that it’s necessary for the public to provide data in order to keep business competitive? And is the “Europe favours privacy, US favours industry” truism broadly true?

Nora: I don’t have a satisfactory answer to this question. There is evidence from past surveys I’ve done with colleagues that people in the United States are more alarmed by the collection and use of personal information by political parties than they are by similar corporate practices. Even that distinction, however, may be too simplistic. Political parties have an established history of using consumer information to segment and target particular audience groups for political purposes. We know that the U.S. government has required private companies to share information about consumers to assist in various surveillance efforts. Discussions about privacy in the U.S. are often framed in terms of tradeoffs with, for example, technological and economic innovation. This is, however, only one of the ways in which the value of privacy is undermined through the creation of false tradeoffs. Daniel Solove, for example, has written extensively on how efforts to frame privacy in opposition to safety encourages capitulation to transparency in the service of national security.

Ed.: There are some truly terrible US laws (e.g. the General Mining Act of 1872) that were developed for one purpose, but are now hugely exploitable. What is the situation for privacy? Is the law still largely fit for purpose, in a world of ubiquitous data collection? Or is reform necessary?

Nora: One example of such a law is the Electronic Communication Privacy Act (ECPA) of 1986. This law was written before many Americans had email accounts, but continues to influence the scope authorities have to access digital communications. One of the key issues in the ECPA is the differential protection for messages depending on when they were sent. The ECPA, which was written when emails would have been downloaded from a server onto a personal computer, treats emails stored for more than 180 days as “abandoned.” While messages received in the past 180 days cannot be accessed without a warrant, so-called abandoned messages require only a subpoena. Although there is some debate about whether subpoenas offer adequate privacy protections for messages stored on remote servers, the issue is that the time-based distinction created by “180-day rule” makes little sense when access to cloud storage allows people to save messages indefinitely. Bipartisan efforts to introduce the Email Privacy Act, which would extend warrant protections to digital communication that is over 180 days old has received wide support from those in the tech industry as well as from privacy advocacy groups.

Another challenge, which you alluded to in your first question, pertains to the regulation of algorithms and algorithmic decision-making. These technologies are often described as “black boxes” to reflect the difficulties in assessing how they work. While the consequences of algorithmic decision-making can be profound, the processes that lead to those decisions are often opaque. The result has been increased scholarly and regulatory attention on strategies to understand, evaluate, and regulate the processes by which algorithms make decisions about individuals.

Read the full article: Draper, N.A. (2017) From Privacy Pragmatist to Privacy Resigned: Challenging Narratives of Rational Choice in Digital Privacy Debates. Policy & Internet 9 (2). doi:10.1002/poi3.142.

Nora A. Draper was talking to blog editor David Sutcliffe.

The current dominant mechanism for public inclusion is the multistakeholder approach, i.e. one that includes governments, industry and civil society in governance debates. Despite at times being used as a shorthand for public inclusion, multistakeholder governance is implemented in many different ways and has faced criticism, with some arguing that multistakeholder discussions serve as a cover for the growth of state dominance over the Web, and enables oligarchic domination of discourses that are ostensibly open and democratic.

In her Policy & Internet article “Searching for the Public in Internet Governance: Examining Infrastructures of Participation at NETmundial”, Sarah Myers West examines the role of the public in Internet governance debates, with reference to public inclusion at the 2014 Global Multistakeholder Meeting on the Future of Internet Governance (NETmundial). NETmundial emerged at a point when public legitimacy was a particular concern for the Internet governance community, so finding ways to include the rapidly growing, and increasingly diverse group of stakeholders in the governance debate was especially important for the meeting’s success.

This is particularly significant as the Internet governance community faces problems of increasing complexity and diversity of views. The growth of the Internet has made the public central to Internet governance — but introduces problems around the growing number of stakeholders speaking different languages, with different technical backgrounds, and different perspectives on the future of the Internet.

However, the article suggests that rather than attempting to unify behind a single institution or achieve public consensus through a single, deliberative forum, the NETmundial example suggests that the Internet community may further fragment into multiple publics, further redistributing into a more networked and “agonistic” model. This doesn’t quite reflect the model of the “public sphere” Habermas may have envisioned, but it may ultimately befit the network of networks it is forged around.

We caught up with Sarah to discuss her findings:

Ed.: You say governance debates involve two levels of contestation: firstly in how we define “the Internet community”, and secondly around the actual decision-making process. How do we even start defining what “the public” means?

Sarah: This is a really difficult question, and it’s really the one that drove me throughout my research. I think that observing examples of publics ‘in the wild’ — how they are actually constituted within the Internet governance space — is one entry point. As I found in the article, there are a number of different kinds of publics that have emerged over the history of the internet, some fairly structured and centralized and others more ad hoc and decentralized. There’s also a difference between the way public inclusion is described/structured and the way things work out in practice. But better understanding what kinds of publics actually exist is only the first step to analyzing deeper questions — about the workings of power on and through the Internet.

Ed.: I know Internet governance is important but haven’t the faintest idea who represents me (as a member of “the public”) in these debates. Are my interests represented by the UK Government? Europe? NGOs? Industry? Or by self-proclaimed “public representatives”?

Sarah: All of the above — and also, maybe, none of the above. There are a number of different kinds of stakeholders representing different constituencies on the Internet — at NETmundial, this was separated into Government, Business, Civil Society, Academia and the Technical Community. In reality, there are blurred boundaries around all these categories, and each of these groups could make claims about representing the public, though which aspects of the public interest they represent is worth a closer look.

Many Internet governance fora are constituted in a way that would also allow each of us to represent ourselves: at NETmundial, there was a lot of thought put in to facilitating remote participation and bringing in questions from the Internet. But there are still barriers — it’s not the same as being in the room with decision makers, and the technical language that’s developed around Internet governance certainly makes these discussions hard for newcomers to follow.

Ed.: Is there a tension here between keeping a process fairly closed (and efficient) vs making it totally open and paralysed? And also between being completely democratic vs being run by people (engineers) who actually understand how the Internet works? i.e. what is the point of including “the public” (whatever that means) at a global level, instead of simply being represented by the governments we elect at a national (or European) level?

Sarah: There definitely is a tension there, and I think this is part of the reason why we see such different models of public inclusion in different kinds of forums. For starters, I’m not sure that, at present, there’s a forum that I can think of that is fully democratic. But I think there is still a value in trying to be more democratic, and to placing the public at the centre of these discussions. As we’ve seen in the years following the Snowden revelations, the interests of state actors are not always aligned, and sometimes are completely at odds, with those of the public.

The involvement of civil society, academia and the technical community is really critical to counterbalancing these interests — but, as many civil society members remarked after NETmundial, this can be an uphill battle. Governments and corporations have an easier time in these kinds of forums identifying and advocating for a narrow set of interests and values, whereas civil society doesn’t always come in to these discussions with as clear a consensus. It can be a messy process.

Ed.: You say that “analyzing the infrastructure of public participation makes it possible to examine the functions of Internet governance processes at a deeper level.” Having done so, are you hopeful or cynical about “Internet governance” as it is currently done?

Sarah: I’m hopeful about the attentiveness to public inclusion exhibited at NETmundial — it really was a central part of the process and the organizers made a number of investments in ensuring it was as broadly accessible as possible. That said, I’m a bit critical of whether building technological infrastructure for inclusion on its own can overcome the real resource imbalances that effect who can participate in these kinds of forums. It’s probably going to require investments in both — there’s a danger that by focusing on the appearance of being democratic, these discussions can mask the underlying power discrepancies that inhibit deliberation on an even playing field.

Read the full article: West, S.M. (2017) Searching for the Public in Internet Governance: Examining Infrastructures of Participation at NETmundial. Policy & Internet 9 (2). doi:10.1002/poi3.143

Sarah Myers West was talking to blog editor David Sutcliffe.

In many sectors, automation is seen as a threat due to the potential for job losses. By contrast, automation is seen as an opportunity in healthcare, as a way to address pressures including staff shortages, increasing demand and workloads, reduced budget, skills shortages, and decreased consultation times. Automation may address these pressures in primary care, while also reconfiguring the work of staff roles and changing the patient-doctor relationship.

In the interview below, Matt Willis discusses a project, funded by The Health Foundation, which looks at opportunities and challenges to automation in NHS England general practice services. While the main goal of the project is to classify work tasks and then calculate the probability that each task will be automated, Matt is currently conducting ethnographic fieldwork in primary care sites to understand the work practices of surgery staff and clinicians.

Since the first automated pill counting machine was introduced in 1970 the role of the pharmacist has expanded to where they now perform more patient consultations, consult with primary care physicians, and require greater technical skill (including a Pharm.D degree). While this provides one clear way in which a medical profession has responded to automation, the research team is now looking at how automation will reconfigure other professions in primary care, and how it will shape its technical and digital infrastructures.

We caught up with Matt Willis to explore the implications of automation in primary care.

Ed.: One finding from an analysis by Frey and Osborne is that most healthcare occupations (that involve things like social intelligence, caring etc.) show a remarkably low probability for computerisation. But what sorts of things could be automated, despite that?

Matt: While providing care is the most important work that happens in primary care, there are many tasks that support that care. Many of those tasks are highly structured and repetitive, ideal things we can automate. There is an incredible amount of what I call “letter work” that occurs in primary care. It’s tasks like responding to requests for information from secondary care, an information request from a medical supplier, processing a trusted assessment, and so on.

There is also generating the letters that are sent to other parts of the NHS — and letters are also triaged at the beginning of each day depending on the urgency of the request. Medical coding is another task that can be automated as well as medication orders and renewal. All of these tasks require someone working with paper or digital text documents and gathering information according to a set of criteria. Often surgeries are overwhelmed with paperwork, so automation is a potential way to make a dent in the way information is processed.

Ed.: I suppose that the increasing digitisation of sensors and data capture (e.g. digital thermometers) and patient records actually helps in this: i.e. automation sounds like the obvious next step in an increasingly digital environment? But is it really as simple as that?

Matt: Well, it’s never as simple as you think it’s going to be. The commonality of data originating in a digital format usually does make data easier to work with, manipulate, analyze, and make actionable. Even when information is entirely digital there can be barriers of interoperability between systems. Automation could even be automating the use of data from one system to the next. There are also social and policy barriers to the use of digital data for automation. Think back to the recent care.data debacle that was supposed to centralize much of the NHS data from disparate silos.

Ed.: So will automation of these tasks be driven by government / within the NHS, or by industry / the market? i.e. is there already a market for automating aspects of healthcare?

Matt: Oh yes, I think it will be a variety of those forces you mention. There is already partial automation in many little ways all over NHS. Automation of messages and notifications, blood pressure cuffs, and other medical devices. Automation is not entirely new to healthcare. The pharmacist is an exemplar health profession to look at if we want to see how automation has changed the tasks of a profession for decades. Many of the electronic health record providers in the UK have different workflow automation features or let clinicians develop workflow efficiency protocols that may automate things in specific ways.

Ed.: You say that one of the bottlenecks to automating healthcare is lack of detailed knowledge of the sorts of tasks that could actually be automated. Is this what you’re working on now?

Matt: Absolutely. The data from labour statistics is self-reported and many of the occupations were lumped together meaning all receptionists in different sectors are just listed under receptionist. One early finding I have that I have been thinking about is how a receptionist in the healthcare sector is different in their information work than a receptionist’s counterpart in another sector. I see this with occupations across health, that there are unique features that differentiate health occupations from similar occupations. This begs the need to tease out those details in the data.

Additionally, we need to understand the use of technologies in primary care and what tasks those technologies perform. One of the most important links I am trying to understand is that between the tasks of people and the tasks of technologies. I am working on not only understanding the opportunities and challenges of automation in primary care but also what are the precursors that exist that may support the implementation of automation.

Ed.: When I started in journals publishing I went to the post room every day to mail out hardcopy proofs to authors. Now everything I do is electronic. I’m not really aware of when the shift happened, or what I do with the time freed up (blog, I suppose..). Do you think it will be similarly difficult in healthcare to pin-point a moment when “things got automated”?

Matt: Well, often times with technology and the change of social practices it’s rarely something that happens overnight. You probably started to gradually send out less and less paper manuscripts over a period of time. It’s the frog sitting in a pot where the heat is slowly turned up. There is a theory that technological change comes in swarm patterns — meaning it’s not one technological change that upends everything, but the advent of numerous technologies that start to create big change.

For example, one of the many reasons that the application of automation technologies is increasing is the swarming of prior technologies like “big data” sets, advances in machine vision, machine learning, machine pattern recognition, mobile robotics, the proliferation of sensors, and further development of autonomous technologies. These kinds of things drive big advances forward.

Ed.: I don’t know if people in the publishing house I worked in lost their jobs when things like post rooms and tea trolleys got replaced by email and coffee machines — or were simply moved to different types of jobs. Do you think people will “lose their jobs“ as automation spreads through the health sector, or will it just drive a shift to people doing something else instead?

Matt: One of the justifications in the project is that in many sectors automation is seen as a threat, however, automation is seen as an opportunity in healthcare. This is in great part due to the current state of the NHS and that the smart and appropriate application of automation technologies can be a force multiplier, particularly in primary care.

I see it as not that people will be put out of jobs, but that you’ll be less likely to have to work 12 hours when you should be working 8 and to not have a pile of documents stacking up that you are three months behind in processing. The demand for healthcare is increasing, the population is aging, and people live longer. One of the ways to keep up with this trend is to implement automation technologies that support healthcare workers and management.

I think we are a long ways away from the science fiction future where a patient lays in an entirely automated medical pod that scans them and administers whatever drug, treatment, procedure, or surgery they need. A person’s tasks and the allocation of work will shift in part due to technology. But that has been happening for decades. There is also a longstanding debate about if technology creates more jobs in the long term than it destroys. It’s likely that in healthcare we will see new occupational roles, job titles, and tasks emerge that are in part automation related. Also, that tasks like filing paperwork or writing a letter will seem barbaric when a computer can, through little time and effort, do that for you.

Matthew Willis was talking to blog editor David Sutcliffe.

There is a general understanding that public decision-making could generate greater legitimacy for political decisions, greater trust in government action and a stronger sense of representation. One way of listening to citizens’ demands and improving their trust in politics is the creation of online communication channels whereby issues, problems, demands, and suggestions can be addressed. One example, participatory budgeting, is the process by which ordinary citizens are given the opportunity to make decisions regarding a municipal budget, by suggesting, discussing, and nominating projects that can be carried out within it. Considered to be a successful example of empowered democratic governance, participatory budgeting has spread among many cities in Brazil, and after being recommended by the World Bank and UN-Habitat, also implemented in various cities worldwide.

The Policy & Internet article “Do Citizens Trust Electronic Participatory Budgeting? Public Expression in Online Forums as an Evaluation Method in Belo Horizonte” by Samuel A. R. Barros and Rafael C. Sampaio examines the feelings, emotions, narratives, and perceptions of political effectiveness and political representation shared in these forums. They discuss how online messages and feelings expressed through these channels can be used to assess public policies, as well as examining some of the consequences of ignoring them.

Recognized as one of the most successful e-democracy experiences in Brazil, Belo Horizonte’s electronic participatory budgeting platform was created in 2006 to allow citizens to deliberate and vote in online forums provided by the city hall. The initiative involved around 174,000 participants in 2006 and 124,000 in 2008. However, only 25,000 participants took part in the 2011 edition, indicating significant loss of confidence in the process. It is a useful case to assess the reasons for success and failure of e-participation initiatives.

There is some consensus in the literature on participants’ need to feel that their contributions will be taken into consideration by those who promote initiatives and, ideally, that these contributions will have effects and practical consequences in the formulation of public policies. By offering an opportunity to participate, the municipality sought to improve perceptions of the quality of representation. Nonetheless, government failure to carry out the project chosen in 2008 and lack of confidence in the voting mechanism itself may have contributed to producing the opposite effect.

Moderators didn’t facilitate conversation or answer questions or demands. No indication was given as to whether these messages were being taken into consideration or even read, and the organizers never explained how or whether the messages would be used later on. In other words, the municipality took no responsibility for reading or evaluating the messages posted there. Thus, it seems to be an online forum that offers little or no citizen empowerment.

We caught up with the authors to discuss their findings:

Ed.: You say that in 2008 62.5% of the messages expressed positive feelings, but in 2011, 59% expressed negative ones. Quite a drop! Is that all attributable to the deliberation not being run properly, i.e. to the danger of causing damage (i.e. fall in trust) by failing to deliver on promises?

Samuel + Rafael: That’s the million dollar question! The truth is: it’s hard to say. Nevertheless, our research does show some evidence of this. Most negative feelings were directly connected to this failure to deliver the previously approved work. As participatory budgeting processes are very connected to practical issues, this was probably the main reason of the drop we saw. We also indicate how the type of complaint changed significantly from one edition to another. For instance, in 2008 many people asked for small adjustments in each of the proposed works, while in 2011 they were complaining about the scope or even the relevance of the works.

Ed.: This particular example aside: is participatory budgeting generally successful? And does it tend to be genuinely participatory (and deliberative?), or more like: “do you want option A or B”?

Samuel + Rafael: That’s also a very good question. In Brazil’s case, most participatory budgeting exercises achieved good levels of participation and contributed to at least minor change in the bureaucratic routines of public servants and officials. Thus, they can be considered successful. Of course, there are many cases of failure as well, since participatory budgeting can be hard to do properly and as our article indicates, a single mistake can disrupt it for good.

Regarding the second question, we would say that it’s more about choosing what you want and what you can deliver as the public power. In actual fact, most participatory budgeting exercises are not as deliberative as everyone believes — they are more about bargaining and negotiation. Nevertheless, while the daily practice of participation may not be as deliberative as we may want it, it still achieves a lot of other benefits, such as keeping the community engaged and informed, letting people know more about how the budget works — and the negotiation itself may involve a certain amount of empathy and role-taking.

Ed.: Is there any evidence that crowdsourcing decisions of this sort leads to better ones? (or at least, more popular ones). Or was this mostly done just to “keep the people happy”?

Samuel + Rafael: We shouldn’t assume that every popular decision is necessarily better, or we’ll get trapped in the caveats. On the other hand, considering how our representative system was designed, how people feel powerless and how rulers are usually set apart from their constituents, we can easily support any real attempt to give the people a greater chance of stating their minds and even deciding on things. If the process is well designed, if the managers (i.e. public servants and officials) are truly open to these inputs and if the public is informed, we can hope for better decisions.

Ed.: Is there any conflict here between “what is popular” and “what is right”? i.e. how much should be opened up to mass voting (with the inevitable skews and take-over by vested interests).

Samuel + Rafael: This is the “dark side” of participation that we mentioned before. We should not automatically consider participation to be good in and of itself. It can be misinformed, biased, and lead to worse and not better decisions. Particularly, when people are not informed enough, when the topic was not discussed enough in the public sphere, we might end up with bad popular decisions. For instance, would Brexit have occurred with a different method of voting?

Let’s imagine several months of small scale discussions between citizens (i.e. minipublics) both face-to-face and in online deliberation spaces. Maybe these groups would reach the same decision, but at least all participants would feel more confident in their decisions, because they had enough information and were confronted with different points of view and arguments before voting. Thus, we believe that mass voting can be used for big decisions, but that there is a need for greater conversation and consensus before it.

Ed.: Is there any link between participatory budgeting and public scrutiny of public budgets (which can be tremendously corrupt, e.g. when it comes to building projects) — or does participatory budgeting tend to be viewed as something very different to oversight?

Samuel + Rafael: This is actually one of the benefits of participatory budgeting that is not correlated to participation alone. It makes corruption and bribery harder to do. As there are more people discussing and monitoring the budget, the process itself needs to be more transparent and accountable. There are some studies that find a correlation between participatory budgeting and tax payment. The problem is that participatory budgeting tends to concern only a small amount of the budget, thus this public control does not reach the whole process. Still, it proves how public participation may lead to a series of benefits both for the public agents and the public itself.

Read the full article: Barros, S.A.R. and Sampaio, R.C. (2016) Do Citizens Trust Electronic Participatory Budgeting? Public Expression in Online Forums as an Evaluation Method in Belo Horizonte. Policy & Internet 8 (3). doi:10.1002/poi3.125

Samuel A. R. Barros and Rafael C. Sampaio were talking to blog editor David Sutcliffe.

Few social policy ideas are as hot today as universal basic income. Social scientists, technologists, and politicians from both ends of the political spectrum see it as a potential solution to the unemployment that automation and artificial intelligence are expected to create.

It has also been floated as a potential solution to the rise of the gig economy, where work is centred around on-demand tasks and short-term projects as opposed to regular full-time employment. This is the kind of employment that platforms like Uber and Freelancer are based on.

Automation and the gig economy are actually closely linked. Isolating and codifying a job task in such a way that it can be outsourced to a gig worker can be the first step towards automating that task. Once a task has been automated, gig workers are used to train and supervise the algorithm. Meanwhile, expert online contractors are hired to fine-tune the technology. More often than not, a finished artificial intelligence system is actually an ensemble of machines and human workers acting in concert.

Basic income is an interesting solution for the gig economy, because it addresses its problems from a new angle. One of the most problematic aspects of the gig economy has to do with its negative job characteristics. Though gig work can provide autonomy and good earnings for some, it also involves uncertainty and insecurity, and for many can entail working antisocial hours for little pay.

A sort of default policy response therefore tends to be to regulate gig work back into the mould of standard employment, consisting of things like guaranteed working hours and notice periods. Basic income takes a different angle. It provides workers with a level of security and predictability over their income that is independent of work.

Plus, by providing workers with a fallback option, a sufficiently high basic income empowers them to turn down bad gigs. So, rather than regulating employer-employee relations, basic income allows them to negotiate terms on a more level playing field. This is why the idea has found favour on both sides of the left-right divide.

Paying the cost

But is basic income viable? One of the big questions is of course its cost. Giving every citizen enough money every month to pay for their essential living costs is no mean feat. Even if it replaced needs-based benefits, it would still probably entail a largescale redistribution of income. The economics of this continue to be vigorously debated, but on a macro-level it may be basically viable.

Yet if basic income is intended as a corrective to economic inequality resulting from new technologies, then the micro-level details of how it is funded are also important. Silicon Valley technology companies, regardless of all the wonderful services they provide us with, have also been notoriously good at avoiding paying taxes. Had they paid more taxes, there would probably be less economic inequality to grapple with now in the first place.

So when some of the same technologists now suggest that states should address mounting inequality with basic income, it is pertinent to ask who will pay for it. Colleagues and I have previously looked into novel ways of taxing the data economy, but there are no easy solutions in sight.

Beyond the basics

Another frequently cited set of questions has to do with basic income’s expected effects on society. Sceptics fear that given a free income, most people would simply stay home and watch YouTube while society crumbles. After all, employment is tightly bound with people’s sense of identity and self-worth, and provides time structure for each day, week, and year.

Proponents, however, have faith that most would want to better themselves or help others, even if they were not explicitly paid to do so. The idea is that a guaranteed income would free people to pursue societally valuable activities that markets won’t pay them to pursue, and that current test-based benefits may even hinder them from pursuing.

But all of these activities require not just food and shelter that basic income can buy, but also other resources, such as skills, knowledge, connections, and self-confidence. The most important means through which many of these resources are cultivated is education. Deprived of this, people with nothing but a basic income may well end up sitting at home watching YouTube.

Research that colleagues and I have carried out looking at online gig workers in Southeast Asia and Sub-Saharan Africa suggests that it is not the most resource-poor who are able to benefit from new online work opportunities, but more typically those with a good level of education, health, and other resources.

So universal basic income is a very interesting potential solution to the rise of the gig economy and more entrepreneurial working lives in general. But whenever basic income is discussed, it is important to ask who exactly would be paying for it. And it is important to recognise that more than just money for basic necessities is needed – unless the intention is simply to store away surplus people in YouTube-enabled homes. Apart from universal basic income, we might therefore want to talk about universal basic resources, such as education as well.

Vili Lehdonvirta, Associate Professor and Senior Research Fellow, Oxford Internet Institute, University of Oxford

This article was originally published on The Conversation. Read the original article.

In an era when most transactions occur online, it’s natural for public authorities to want the vast bulk of their contacts with citizens to occur through the Internet. But they also face a minority for whom paper and face-to-face interactions are still preferred or needed — leading to fears that efforts to move services online “by default” might reinforce or even encourage exclusion. Notwithstanding these fears, it might be possible to “nudge” citizens from long-held habits by making online submission advantageous and other routes of use more difficult.

Behavioural public policy has been strongly advocated in recent years as a low-cost means to shift citizen behaviour, and has been used to reform many standard administrative processes in government. But how can we design non-obtrusive nudges to make users shift channels without them losing access to services? In their new Policy & Internet article “Nudges That Promote Channel Shift: A Randomized Evaluation of Messages to Encourage Citizens to Renew Benefits Online” Peter John and Toby Blume design and report a randomized control trial that encouraged users of a disability parking scheme to renew online.

They found that by simplifying messages and adding incentives (i.e. signalling the collective benefit of moving online) users were encouraged to switch from paper to online channels by about six percentage points. As a result of the intervention and ongoing efforts by the Council, virtually all the parking scheme users now renew online.

The finding that it’s possible to appeal to citizens’ willingness to act for collective benefit is encouraging. The results also support the more general literature that shows that citizens’ use of online services is based on trust and confidence with public services and that interventions should go with the grain of citizen preferences and norms.

We caught up with Peter John to discuss his findings, and the role of behavioural public policy in government:

Ed.: Is it fair to say that the real innovation of behavioural public policy isn’t so much Government trying to nudge us into doing things in subtle, unremarked ways, but actually using experimental techniques to provide some empirical backing for the success of any interventions? i.e. like industry has done for years with things like A/B testing?

Peter: There is some truth in this, but the late 2000s was a time when policy-makers got more interested in the findings of the behavioural sciences and in redesigning initiatives to incorporate behaviour insights. Randomised controlled trials (RCTs) have become more commonly used more generally across governments to test for the impact of public policies — these are better than A/B testing as randomisation protocols are followed and clear reports are made of the methods used. A/B testing can be dodgy — or at least, it is done in secret and we don’t know how good the methods used are. There is much better reporting of government RCTs.

Ed.: The UK Government’s much-discussed “Nudge Unit” was part-privatised a few years ago, and the Government now has to pay for its services: was this a signal of the tremendous commercial value of behavioural economics (and all the money to be made if you sell off bits of the Civil Service), or Government not really knowing what to do with it?

Peter: I think the language of privatisation is not quite right to describe what happened. The unit was spun out of government, but government still owns a share, with Nesta owning the other large portion. It is not a profit-making enterprise, but a non-profit one — the freedom allows it to access funds from foundations and other funders. The Behavioural Insights Team is still very much a public service organisation, even if it has got much bigger since moving out of direct control by Government. Where there are public funds involved there is scrutiny through ministers and other funders — it matters that people know about the nudges, and can hold policy-makers to account.

Ed.: You say that “interventions should go with the grain of citizen preferences and norms” to be successful. Which I suppose is a sort-of built-in ethical safeguard. But do you know of any behavioural pushes that make us go against our norms, or that might raise genuine ethical concerns, or calls for oversight?

Peter: I think some of the shaming experiments done on voter turnout are on the margins of what is ethically acceptable. I agree that the natural pragmatism and caution of public agencies helps them agree relatively low key interventions.

Ed.: Finally — having spent some time studying and thinking about Government nudges .. have you ever noticed or suspected that you might have been subjected to one, as a normal citizen? I mean: how ubiquitous are they in our public environment?

Peter: Indeed — a lot of our tax letters are part of an experiment. But it’s hard to tell of course, as making nudges non-obtrusive is one of the key things. It shouldn’t be a problem that I am part of an experiment of the kind I might commission.

Read the full article: John, P. and Blume, T. (2017) Nudges That Promote Channel Shift: A Randomized Evaluation of Messages to Encourage Citizens to Renew Benefits Online. Policy & Internet. DOI: 10.1002/poi3.148.

Peter John was talking to blog editor David Sutcliffe.

Easy availability of Twitter data links nicely to a key goal of computational social science. If researchers can find ways to impute user characteristics from social media, then the capabilities of computational social science would be greatly extended. However few papers consider the digital divide among Twitter users. But the question of who uses Twitter has major implications for research attempts to use the content of tweets for inference about population behaviour. Do Twitter users share identical characteristics with the population interest? For what populations are Twitter data actually appropriate?

A new article by Grant Blank published in Social Science Computer Review provides a multivariate empirical analysis of the digital divide among Twitter users, comparing Twitter users and nonusers with respect to their characteristic patterns of Internet activity and to certain key attitudes. It thereby fills a gap in our knowledge about an important social media platform, and it joins a surprisingly small number of studies that describe the population that uses social media.

Comparing British (OxIS survey) and US (Pew) data, Grant finds that generally, British Twitter users are younger, wealthier, and better educated than other Internet users, who in turn are younger, wealthier, and better educated than the offline British population. American Twitter users are also younger and wealthier than the rest of the population, but they are not better educated. Twitter users are disproportionately members of elites in both countries. Twitter users also differ from other groups in their online activities and their attitudes.

Under these circumstances, any collection of tweets will be biased, and inferences based on analysis of such tweets will not match the population characteristics. A biased sample can’t be corrected by collecting more data; and these biases have important implications for research based on Twitter data, suggesting that Twitter data are not suitable for research where representativeness is important, such as forecasting elections or gaining insight into attitudes, sentiments, or activities of large populations.

Read the full article: Blank, G. (2016) The Digital Divide Among Twitter Users and Its Implications for Social Research. Social Science Computer Review. DOI: 10.1177/0894439316671698

We caught up with Grant to explore the implications of the findings:

Ed.: Despite your cautions about lack of representativeness, you mention that the bias in Twitter could actually make it useful to study (for example) elite behaviours: for example in political communication?

Grant: Yes. If you want to study elites and channels of elite influence then Twitter is a good candidate. Twitter data could be used as one channel of elite influence, along with other online channels like social media or blog posts, and offline channels like mass media or lobbying. There is an ecology of media and Twitter is one part.

Ed.: You also mention that Twitter is actually quite successful at forecasting certain offline, commercial behaviours (e.g. box office receipts).

Grant: Right. Some commercial products are disproportionately used by wealthier or younger people. That certainly would include certain forms of mass entertainment like cinema. It also probably includes a number of digital products like smartphones, especially more expensive phones, and wearable devices like a Fitbit. If a product is disproportionately bought by the same population groups that use Twitter then it may be possible to forecast sales using Twitter data. Conversely, products disproportionately used by poorer or older people are unlikely to be predictable using Twitter.

Ed.: Is there a general trend towards abandoning expensive, time-consuming, multi-year surveys and polling? And do you see any long-term danger in that? i.e. governments and media (and academics?) thinking “Oh, we can just get it off social media now”.

Grant: Yes and no. There are certainly people who are thinking about it and trying to make it work. The ease and low cost of social media is very seductive. However, that has to be balanced against major weaknesses. First the population using Twitter (and other social media) is unclear, but it is not a random sample. It is just a population of Twitter users, which is not a population of interest to many.

Second, tweets are even less representative. As I point out in the article, over 40% of people with a Twitter account have never sent a tweet, and the top 15% of users account for 85% of tweets. So tweets are even less representative of any real-world population than Twitter users. What these issues mean is that you can’t calculate measures of error or confidence intervals from Twitter data. This is crippling for many academic and government uses.

Third, Twitter’s limited message length and simple interface tends to give it advantages on devices with restricted input capability, like phones. It is well-suited for short, rapid messages. These characteristics tend to encourage Twitter use for political demonstrations, disasters, sports events, and other live events where reports from an on-the-spot observer are valuable. This suggests that Twitter usage is not like other social media or like email or blogs.

Fourth, researchers attempting to extract the meaning of words have 140 characters to analyze and they are littered with abbreviations, slang, non-standard English, misspellings and links to other documents. The measurement issues are immense. Measurement is hard enough in surveys when researchers have control over question wording and can do cognitive interviews to understand how people interpret words.

With Twitter (and other social media) researchers have no control over the process that generated the data, and no theory of the data generating process. Unlike surveys, social media analysis is not a general-purpose tool for research. Except in limited areas where these issues are less important, social media is not a promising tool.

Ed.: How would you respond to claims that for example Facebook actually had more accurate political polling than anyone else in the recent US Election? (just that no-one had access to its data, and Facebook didn’t say anything)?

Grant: That is an interesting possibility. The problem is matching Facebook data with other data, like voting records. Facebook doesn’t know where people live. Finding their location would not be an easy problem. It is simpler because Facebook would not need an actual address; it would only need to locate the correct voting district or the state (for the Electoral College in US Presidential elections). Still, there would be error of unknown magnitude, probably impossible to calculate. It would be a very interesting research project. Whether it would be more accurate than a poll is hard to say.

Ed.: Do you think social media (or maybe search data) scraping and analysis will ever successfully replace surveys?

Grant: Surveys are such versatile, general purpose tools. They can be used to elicit many kinds information on all kinds of subjects from almost any population. These are not characteristics of social media. There is no real danger that surveys will be replaced in general.

However, I can see certain specific areas where analysis of social media will be useful. Most of these are commercial areas, like consumer sentiments. If you want to know what people are saying about your product, then going to social media is a good, cheap source of information. This is especially true if you sell a mass market product that many people use and talk about; think: films, cars, fast food, breakfast cereal, etc.

These are important topics to some people, but they are a subset of things that surveys are used for. Too many things are not talked about, and some are very important. For example, there is the famous British reluctance to talk about money. Things like income, pensions, and real estate or financial assets are not likely to be common topics. If you are a government department or a researcher interested in poverty, the effect of government assistance, or the distribution of income and wealth, you have to depend on a survey.

There are a lot of other situations where surveys are indispensable. For example, if the OII wanted to know what kind of jobs OII alumni had found, it would probably have to survey them.

Ed.: Finally .. 1400 Twitter articles in .. do we actually know enough now to say anything particularly useful or concrete about it? Are we creeping towards a Twitter revelation or consensus, or is it basically 1400 articles saying “it’s all very complicated”?

Grant: Mostly researchers have accepted Twitter data at face value. Whatever people write in a tweet, it means whatever the researcher thinks it means. This is very easy and it avoids a whole collection of complex issues. All the hard work of understanding how meaning is constructed in Twitter and how it can be measured is yet to be done. We are a long way from understanding Twitter.

Read the full article: Blank, G. (2016) The Digital Divide Among Twitter Users and Its Implications for Social Research. Social Science Computer Review. DOI: 10.1177/0894439316671698

Grant Blank was talking to blog editor David Sutcliffe.

“Self-Tracking” (MIT Press) by Gina Neff and Dawn Nafus examines how people record, analyze, and reflect on this data — looking at the tools they use and the communities they become part of, and offering an introduction to the essential ideas and key challenges of using these technologies. In considering self-tracking as a social and cultural phenomenon, they describe not only the use of data as a kind of mirror of the self but also how this enables people to connect to, and learn from, others.

They also consider what’s at stake: who wants our data and why, the practices of serious self-tracking enthusiasts, the design of commercial self-tracking technology, and how people are turning to self-tracking to fill gaps in the healthcare system. None of us can lead an entirely untracked life today, but in their book, Gina and Dawn show us how to use our data in a way that empowers and educates us.

We caught up with Gina to explore the self-tracking movement:

Ed.: Over one hundred million wearable sensors were shipped last year to help us gather data about our lives. Is the trend and market for personal health-monitoring devices ever-increasing, or are we seeing saturation of the device market and the things people might conceivably want to (pay to) monitor about themselves?

Gina: By focusing on direct-to-consumer wearables and mobile apps for health and wellness in the US we see a lot of tech developed with very little focus on impact or efficacy. I think to some extent we’ve hit the trough in the ‘hype’ cycle, where the initial excitement over digital self-tracking is giving way to the hard and serious work of figuring out how to make things that improve people’s lives. Recent clinical trial data show that activity trackers, for example, don’t help people to lose weight. What we try to do in the book is to help people figure out what self-tracking to do for them and advocate for people being able to access and control their own data to help them ask — and answer — the questions that they have.

Ed.: A question I was too shy to ask the first time I saw you speak at the OII — how do you put the narrative back into the data? That is, how do you make stories that might mean something to a person, out of the vast piles of strangely meaningful-meaningless numbers that their devices accumulate about them?

Gina: We really emphasise community. It might sound clichéd but it truly helps. When I read some scholars’ critiques of the Quantified Self meetups that happen around the world I wonder if we have actually been to the same meetings. Instead of some kind of technophilia there are people really working to make sense of information about their lives. There’s a lot of love for tech, but there are also people trying to figure out what their numbers mean, are they normal, and how to design their own ‘n of 1’ trials to figure out how to make themselves better, healthier, and happier. Putting narrative back into data really involves sharing results with others and making sense together.

Ed.: There’s already been a lot of fuss about monetisation of NHS health records: I imagine the world of personal health / wellness data is a vast Wild West of opportunity for some (i.e. companies) and potential exploitation of others (i.e. the monitored), with little law or enforcement? For a start .. is this health data or social data? And are these equivalent forms of data, or are they afforded different protections?

Gina: In an opinion piece in Wired UK last summer I asked what happens to data ownership when your smartphone is your doctor. Right now we afford different privacy protection to health-related data than other forms of personal data. But very soon trace data may be useful for clinical diagnoses. There are already in place programmes for using trace data for early detection of mood disorders, and research is underway on using mobile data for the diagnosis of movement disorders. Who will have control and access to these potential early alert systems for our health information? Will it be legally protected to the same extent as the information in our medical records? These are questions that society needs to settle.

Ed.: I like the central irony of “mindfulness” (a meditation technique involving a deep awareness of your own body), i.e. that these devices reveal more about certain aspects of the state of your body than you would know yourself: but you have to focus on something outside of yourself (i.e. a device) to gain that knowledge. Do these monitoring devices support or defeat “mindfulness”?

Gina: I’m of two minds, no pun intended. Many of the Quantified Self experiments we discuss in the book involved people playing with their data in intentional ways and that level of reflection in turn influences how people connect the data about themselves to the changes they want to make in their behaviour. In other words, the act of self-tracking itself may help people to make changes. Some scholars have written about the ‘outsourcing’ of the self, while others have argued that we can develop ‘exosenses’ outside our bodies to extend our experience of the world, bringing us more haptic awareness. Personally, I do see the irony in smartphone apps intended to help us reconnect with ourselves.

Ed.: We are apparently willing to give up a huge amount of privacy (and monetizable data) for convenience, novelty, and to interact with seductive technologies. Is the main driving force of the wearable health-tech industry the actual devices themselves, or the data they collect? i.e. are these self-tracking companies primarily device/hardware companies or software/data companies?

Gina: Sadly, I think it is neither. The drop off in engagement with wearables and apps is steep with the majority falling into disuse after six months. Right now one of the primary concerns I have as an Internet scholar is the apparent lack of empathy companies seem to have for their customers in this space. People operate under the assumption that the data generated by the devices they purchase is ‘theirs’, yet companies too often operate as if they are the sole owners of that data.

Anthropologist Bill Maurer has proposed replacing data ownership with a notion of data ‘kinship’ – that both technology companies and their customers have rights and responsibilities to the data that they produce together. Until we have better social contracts and legal frameworks for people to have control and access to their own data in ways that allow them to extract it, query it, and combine it with other kinds of data, then that problem of engagement will continue and activity trackers will sit unused on bedside tables or uncharged in the back of drawers. The ability to help people ask the next question or design the next self-tracking experiment is where most wearables fail today.

Ed.: And is this data at all clinically useful / interoperable with healthcare and insurance systems? i.e. do the companies producing self-monitoring devices work to particular data and medical standards? And is there any auditing and certification of these devices, and the data they collect?

Gina: This idea that the data is just one interoperable system away from usefulness is seductive but so, so wrong. I was recently at a panel of health innovators, the title of which was ‘No more Apps’. The argument was that we’re not going to get to meaningful change in healthcare simply by adding a new data stream. Doctors in our study said things like ‘I don’t need more data; I need more resources.’ Right now we have few protections for individuals that this data won’t be able to harm their rights to insurance, or won’t be used to discriminate against them and yet there are few results that show how the commercially available wearable devices are delivering clinical value. There’s still a lot of work needed before this can happen.

Ed.: Lastly — just as we share our music on iTunes; could you see a scenario where we start to share our self-status with other device wearers? Maybe to increase our sociability and empathy by being able to send auto-congratulations to people who’ve walked a lot that day, or to show concern to people with elevated heart rates / skin conductivity (etc.)? Given the logical next step to accumulating things is to share them..

Gina: We can see that future scenario now in groups like Patients Like Me, Cure Together, and Quantified Self meetups. What these ‘edge’ use cases teach us for more everyday self-tracking uses is that real support and community can form around people sharing their data with others. These are projects that start from individuals with information about themselves and work to build toward collective, social knowledge. Other types of ‘citizen science’ projects are underway like the Personal Genome Project where people can donate their health data for science. The Stanford-led MyHeart Counts study on iPhone and Apple Watch recruited in its first two weeks 6,000 people for its study and now has over 40,000 US participants. Those are numbers for clinical studies that we’ve just never seen before.

My co-author led the development of an interesting tool, Data Sense, that lets people without stats training visualize the relationships among variables in their own data or easily combine their data with data from other people. When people can do that they can begin asking the questions that matter for them and for their communities. What we know won’t work in the future of self-tracking data, though, are the lightweight online communities that technology brands just throw together. I’m just not going to be motivated by a random message from LovesToWalk1949, but under the right conditions I might be motivated by my mom, my best friend or my social network. There is still a lot of hard work that has to be done to get the design of self-tracking tools, practices, and communities for social support right.

Gina Neff was talking to blog editor David Sutcliffe about her book (with Dawn Naffs) “Self-Tracking” (MIT Press).

Development has always grappled with why some people and places have more than others, but much of that conversation is lost within contemporary discourses of ICTs and development. As states and organisations rush to develop policies and plans, build drones and balloons, and lay fibre-optic cables, much is said about the power of ICTs to positively transform the world’s most underprivileged people and places.

Despite the vigour of such claims, there is actually a lack of academic consensus about the impacts of digital connectivity on economic development. In their new article, Nicolas Friederici, Sanna Ojanperä and Mark Graham review claims made by African governments and large international institutions about the impacts of connectivity, showing that the evidence base to support them is thin.

It is indeed possible that contemporary grand visions of connectivity are truly reflective of a promising future, but it is equally possible that many of them are hugely overblown. The current evidence base is mixed and inconclusive. More worryingly, visions of rapid ICT-driven development might not only fail to achieve their goals — they could actively undermine development efforts in a world of scarce resources. We should therefore refuse to believe it is self-evident that ICTs will automatically bring about development, and should do more to ask the organisations and entities who produce these grand visions to justify their claims.

Read the full article: Friederici, N., Ojanperä, S., and Graham, M. (2017) The Impact of Connectivity in Africa: Grand Visions and the Mirage of Inclusive Digital Development. Electronic Journal of Information Systems in Developing Countries, 79(2), 1–20.

We caught up with the authors to discuss their findings.

Ed.: Who is paying for these IT-development projects: are they business and profit-led, or donor led: and do the donors (and businesses) attach strings?

Nicolas: Funding has become ever more mixed. Foundational infrastructure like fibre-optic cables have usually been put in place through public private partnerships, where private companies lay out the network while loans, subsidies, and policy support are provided by national governments and organizations like the World Bank. Development agencies have mostly funded more targeted connectivity projects, like health or agricultural information platforms.

Recently, philanthropic foundations and tech corporations have increased their footprint, for instance, the Rockefeller Foundation’s Digital Jobs project or Facebook’s Open Cellular Base stations. So we are seeing an increasingly complex web of financial channels. What discourse does is pave the way for funding to flow into such projects.

The problem is that, while private companies may stop investing when they don’t see returns, governments and development funders might continue to pour resources into an agenda as long as it suits their ideals or desirable and widely accepted narratives. Of course, these resources are scarce; so, at the minimum, we need to allow scrutiny and look for alternatives about how development funding could be used for maximum effect.

Ed.: Simple, aspirational messages are obviously how politicians get people excited about things (and to pay for them). What is the alternative?

Nicolas: We’re not saying that the rhetoric of politicians is the problem here. We’re saying that many of the actors who are calling the shots in development are stubbornly evading valid concerns that academics and some practitioners have brought forward. The documents that we analyze in the article — and these are very influential sources — pretend that it is an unquestionable fact that there is a causal, direct and wide-spread positive impact of Internet and ICTs on all facets of development, anywhere. This assertion is not only simplistic, it’s also problematic and maybe even dangerous to think about a complex and important topic like (human, social) development in this way.

The alternative is a more open and plural conversation where we openly admit that resources spent on one thing can’t be spent on another, and where we enable different and critical opinions to enter the fray. This is especially important when a nation’s public is disempowered or misinformed, or when regulators are weak. For example, in most countries in Europe, advocacy groups and strong telecoms regulators provide a counterforce to the interests of technology corporations. Such institutions are often absent in the Global South, so the onus is on development organizations to regulate themselves, either by engaging with people “on the ground” or with academics. For instance, the recent World Development Report by the World Bank did this, which led the report to, we think, much more reliable and balanced conclusions compared to the Bank’s earlier outputs.

Ed.: You say these visions are “modernist” and “techno-determinist” — why is that? Is it a quirk of the current development landscape, or does development policy naturally tend to attract fixers (rather than doubters and worriers..). And how do we get more doubt into policy?

Nicolas: Absolutely, development organizations are all about fixing development problems, and we do not take issue with that. However, these organizations also need to understand that “fixing development” is not like fixing a machine (that is, a device that functions according to mechanical principles). It’s not like one could input “technology” or “the Internet,” and get “development” as an output.

In a nutshell, that’s what we mean when we say that visions are modernist and techno-determinist: many development organizations, governments, and corporations make the implicit assumption that technological progress is fixing development, that this is an apolitical and unstoppable process, and that this is working out in the same way everywhere on earth. This assumption glances over contestation, political choices and trade-offs, and the cultural, economic, and social diversity of contexts.

Ed.: Presumably if things are very market-led: the market will decide if the internet “solves” everything: ie either it will, or it won’t. Has there been enough time yet to verify the outcomes of these projects (e.g. how has the one-laptop initiative worked out)?

Nicolas: I’m not sure I agree with the implication that markets can decide if the Internet solves everything. It’s us humans who are deciding, making choices, prioritizing, allocating resources, setting policies, etc. As humans, we might decide that we want a market (that is, supply and demand matched by a price mechanism) to regulate some array of transactions. This is exactly what is happening, for instance, with the spread of mobile money in Kenya or the worldwide rise of smartphones: people feel they benefit from using a product and are willing to pay money to a supplier.

The issue with technology and development is (a) that in many cases, markets are not the mechanism that achieves the best development outcomes (think about education or healthcare), (b) that even the freest of markets needs to be enabled by things like political stability, infrastructure, and basic institutions (think about contract law and property rights), and (c) that many markets need regulatory intervention or power-balancing institutions to prevent one side of the exchange to dominate and exploit the other (think about workers’ rights).

In each case, it is thus a matter of evaluating what mixture of technology, markets, and protections works best to achieve the best development outcomes, keeping in mind that development is multi-dimensional and goes far beyond economic growth. These evaluations and discussions are challenging, and it takes time to determine what works, where, and when, but ultimately we’re improving our knowledge and our practice if we keep the conversation open, critical, and diverse.

Ed.: Is there a consensus on ICT and development, or are there basically lots of camps, ranging from extreme optimists to extreme pessimists? I get the impression that basically “it’s complicated” — is that fair? And how much discussion or recognition (beyond yourselves) is there about the gap between these statements and reality?

Nicolas: ICT and development has seen a lot of soul-searching, and scholars and practitioners have spent over 20 years debating the field’s nature and purpose. There is certainly no consensus on what ICTD should do, or how ICTs effect/affect development, and maybe that is an unrealistic — and undesirable — goal. There are certainly optimistic and pessimistic voices, like you mention, but there is also a lot of wisdom that is not widely acknowledged, or not in the public domain at all. There are thousands of practitioners from the Global North and South who have been in the trenches, applied their critical and curious minds, and seen what makes an impact and what is a pipe dream.

So we’re far from the only ones who are aware that much of the ICTD rhetoric is out of touch with realities, and we’re also not the first ones to identify this problem. What we tried to point out in our article is that the currently most powerful, influential, and listened to sources tend to be the ones that are overly optimistic and overly simplistic, ignoring all the wisdom and nuance created through hard scholarly and practical work. These actors seem to be detached from the messy realities of ICTD.

This carries a risk, because it is these organizations (governments, global consultancies, multilateral development organizations, and international tech corporations) that are setting the agenda, distributing the funds, making the hiring decisions, etc. in development practice.

Read the full article: Friederici, N., Ojanperä, S., and Graham, M. (2017) The Impact of Connectivity in Africa: Grand Visions and the Mirage of Inclusive Digital Development. Electronic Journal of Information Systems in Developing Countries, 79(2), 1–20.

Nicolas Friederici was talking to blog editor David Sutcliffe.

However, a new article by Andrew Przybylski and Victoria Nash, “Internet Filtering Technology and Aversive Online Experiences in Adolescents”, published in the Journal of Pediatrics, finds equivocal to strong evidence that household-level Internet filtering does not reduce the chance of adolescents having recent aversive online experiences. The authors analysed data from 1030 in-home interviews conducted with early adolescents as part of Ofcom’s Children and Parents Media Use and Attitudes Report.

The Internet is now a central fixture of modern life, and the positives and negatives of online Internet use need to be balanced by caregivers. Internet filters have been adopted as a tool for limiting the negatives; however, evidence of their effectiveness is dubious. They are expensive to develop and maintain, and also carry significant informational costs: even sophisticated filters over-block, which is onerous for those seeking information about sexual health, relationships, or identity, and might have a disproportionate effect on vulnerable groups. Striking the right balance between protecting adolescents and respecting their rights to freedom of expression and information presents a formidable challenge.

In conducting their study to address this uncertainty, the authors found convincing evidence that Internet filters were not effective at shielding early adolescents from aversive experiences online. Given this finding, they propose that evidence derived from a randomized controlled trial and registered research designs are needed to determine how far Internet-filtering technology supports or thwarts young people online. Only then will parents and policymakers be able to make an informed decision as to whether their widespread use justifies their costs.

We caught up with Andy and Vicki to discuss the implications of their study:

Ed.: Just this morning when working from home I tried to look up an article’s author and was blocked, Virgin Media presumably having decided he might be harmful to me. Where does this recent enthusiasm for default-filtering come from? Is it just that it’s a quick, uncomplicated (technological) fix, which I guess is what politicians / policy-people like?

Vicki: In many ways this is just a typical response to the sorts of moral panic which have long arisen around the possible risks of new technologies. We saw the same concerns arise with television in the 1960s, for example, and in that case the UK’s policy response was to introduce a ‘watershed’, a daily time after which content aimed at adults could be shown. I suppose I see filtering as fulfilling the same sort of policy gap, namely recognising that certain types of content can be legally available but should not be served up ‘in front of the children’.

Andy: My reading of the psychological and developmental literature suggests that filters provide a way of creating a safe walled space in schools, libraries, and homes for young people to use the internet. This of course does not mean that reading our article will be harmful!

Ed.: I suppose that children desperate to explore won’t be stopped by a filter; those who aren’t curious probably wouldn’t encounter much anyway — what is the profile of the “child” and the “harm-filtering” scenario envisaged by policy-makers? And is Internet filtering basically just aiming at the (easy) middle of the bell-curve?

Vicki: This is a really important point. Sociologists recognised many years ago that the whole concept of childhood is socially constructed, but we often forget about this when it comes to making policy. There’s a tendency for politicians, for example, either to describe children as inherently innocent and vulnerable, or to frame them as expert ‘digital natives’, yet there’s plenty of academic research which demonstrates the extent to which children’s experiences of the Internet vary by age, education, income and skill level.

This matters because it suggests a ‘one-size-fits-all’ approach may fail. In the context of this paper, we specifically wanted to check whether children with the technical know-how to get around filters experienced more negative experiences online than those who were less tech-savvy. This is often assumed to be true, but interestingly, our analysis suggests this factor makes very little difference.

Ed.: In all these discussions and policy decisions: is there a tacit assumption that these children are all growing up in a healthy, supportive (“normal”) environment — or is there a recognition that many children will be growing up in attention-poor (perhaps abusive) environments and that maybe one blanket technical “solution” won’t fit everyone? Is there also an irony that the best protected children will already be protected, and the least protected, probably won’t be?

Andy: Yes this is ironic and somewhat tragic dynamic. Unfortunately because the evidence for filtering effectiveness is at such an early age it’s not possible to know which young people (if any) are any more or less helped by filters. We need to know how effective filters are in general before moving on to see the young people for whom they are more or less helpful. We would also need to be able to explicitly define what would constitute an ‘attention-poor’ environment.

Vicki: From my perspective, this does always serve as a useful reminder that there’s a good reason why policy-makers turn to universalistic interventions, namely that this is likely to be the only way of making a difference for the hardest-to-reach children whose carers might never act voluntarily. But admirable motives are no replacement for efficacy, so as Andy notes, it would make more sense to find evidence that household internet filtering is effective, and second that it can be effective for this vulnerable group, before imposing default-on filters on all.

Ed.: With all this talk of potential “harm” to children posed by the Internet .. is there any sense of how much (specific) harm we’re talking about? And conversely .. any sense of the potential harms of over-blocking?

Vicki: No, you are right to see that the harms of Internet use are quite hard to pin down. These typically take the form of bullying, or self-harm horror stories related to Internet use. The problem is that it’s often easier to gauge how many children have been exposed to certain risky experiences (e.g. viewing pornography) than to ascertain whether or how they were harmed by this. Policy in this area often abides by what’s known as ‘the precautionary principle’.

This means that if you lack clear evidence of harm but have good reason to suspect public harm is likely, then the burden of proof is on those who would prove it is not likely. This means that policies aimed at protecting children in many contexts are often conservative, and rightly so. But it also means that it’s important to reconsider policies in the light of new evidence as it comes along. In this case we found that there is not as much evidence that Internet filters are effective at preventing exposure to negative experiences online as might be hoped.

Ed.: Stupid question: do these filters just filter “websites”, or do they filter social media posts as well? I would have thought young teens would be more likely to find or share stuff on social media (i.e. mobile) than “on a website”?

Andy: My understanding is that there are continually updated ‘lists’ of website that contain certain kinds of content such as pornography, piracy, gambling, or drug use (see this list on Wikipedia, for example) as these categories vary by UK ISP.

Vicki: But it’s not quite true to say that household filtering packages don’t block social media. Some of the filtering options offered by the UK’s ‘Big 4’ ISPs enable parents and carers to block social media sites for ‘homework time’ for example. A bigger issue though, is that much of children’s Internet use now takes place outside the home. So, household-level filters can only go so far. And whilst schools and libraries usually filter content, public wifi or wifi in friends’ houses may not, and content can be easily exchanged directly between kids’ devices via Bluetooth or messaging apps.

Ed: Do these blocked sites (like the webpage of that journal author I was trying to access) get notified that they have been blocked and have a chance to appeal? Would a simple solution to over blocking simply be to allow (e.g. sexual health, gender-issue, minority, etc.) sites to request that they be whitelisted, or apply for some “approved” certification?

Vicki: I don’t believe so. There are whitelisted sites, indeed that was a key outcome of an early inquiry into ‘over-blocking’ by the UK Children’s Council on Internet Safety. But in order for this to be a sufficient response, it would be necessary for all sites and apps that are subject to filtering to be notified, to allow for possible appeal. The Open Rights Group provide a tool that allows site owners to check the availability of their sites, but there is no official process for seeking whitelisting or appeal.

Ed.: And what about age verification as an alternative? (however that is achieved / validated), i.e. restricting content before it is indexed, rather than after?

Andy: To evaluate this we would need to conduct a randomised controlled trial where we tested how the application of age verification for different households, selected at random, would relate (or not) to young people encountering potentially aversive content online.

Vicki: But even if such a study could prove that age verification tools were effective in restricting access to underage Internet users, it’s not clear this would be a desirable scenario. It makes most sense for content that is illegal to access below a certain age, such as online gambling or pornography. But if content is age-gated without legal requirement, then it could prove a very restrictive tool, removing the possibility of parental discretion and failing to make any allowances for the sorts of differences in ability or maturity between children that I pointed out at the beginning.

Ed: Similarly to the the arguments over Google making content-blocking decisions (e.g. over the “right to forget”): are these filtering decisions left to the discretion of ISPs / the market / the software providers, or to some government dept / NGO? Who’s ultimately in charge of who sees what?

Vicki: Obviously when it comes to content that is illegal for children or adults to access then broad decisions about the delineation of what is illegal falls to governments and is then interpreted and applied by private companies. But when it comes to material that is not illegal, but just deemed harmful or undesirable, then ISPs and social media platforms are left to decide for themselves how to draw the boundaries and then how to apply their own policies. This increasing self-regulatory role for what Jonathan Zittrain has called ‘private sherriffs’ is often seen a flexible and appropriate response, but it does bring reduced accountability and transparency.

Ed.: I guess it’s ironic with all this attention paid to children, that we now find ourselves in an information environment where maybe we should be filtering out (fake) content for adults as well (joke..). But seriously: with all these issues around content, is your instinct that we should be using technical fixes (filtering, removing from indexes, etc.) or trying to build reflexivity, literacy, resilience in users (i.e. coping strategies). Or both? Both are difficult.

Andy: It is as ironic as it is tragic. When I talk to parents (both Vicki and I are parents) I hear that they have been let down by the existing advice which often amounts to little more than ‘turn it off’. Their struggles have nuance (e.g. how do I know who is in my child’s WhatsApp groups? Is snapchat OK if they’re just using it amongst best friends?) and whilst general broad advice is heard, this more detailed information and support is hard for parents to find.

Vicki: I agree. But I think it’s inevitable that we’ll always need a combination of tools to deal with the incredible array of content that develops online. No technical tool will ever be 100% reliable in blocking content we don’t want to see, and we need to know how to deal with whatever gets through. That certainly means having a greater social and political focus on education but also a willingness to consider that building resilience may mean exposure to risk, which is hard for some groups to accept.

Every element of our strategy should be underpinned by whatever evidence is available. Ultimately, we also need to stop thinking about these problems as technology problems: fake news is just as much a feature of increasing political extremism and alienation just as online pornography is a feature of a heavily sexualised mainstream culture. And we can be certain: neither of these broader social trends will be resolved by simple efforts to block out what we don’t wish to see.

Read the full article: Przybylski, A. and Nash, V. (2017) Internet Filtering Technology and Aversive Online Experiences in Adolescents. Journal of Pediatrics. DOI: http://dx.doi.org/10.1016/j.jpeds.2017.01.063

Andy Przybylski and Vicki Nash were talking to blog editor David Sutcliffe.

However, a number of open science initiatives have been successful recently in raising awareness of the benefits of open science and encouraging public sharing of datasets. These are discussed by Malte Elson (Ruhr University Bochum) and the OII’s Andrew Przybylski in their special issue editorial: “The Science of Technology and Human Behavior: Standards, Old and New”, published in the Journal of Media Psychology. What makes this issue special is not the topic, but the scientific approach to hypothesis testing: the articles are explicitly confirmatory, that is, intended to test existing theory.

All five studies are registered reports, meaning they were reviewed in two stages: first, the theoretical background, hypotheses, methods, and analysis plans of a study were peer-reviewed before the data were collected. The studies received an “in-principle” acceptance before the researchers proceeded to conduct them. The soundness of the analyses and discussion section were reviewed in a second step, and the publication decision was not contingent on the outcome of the study: i.e. there was no bias against reporting null results. The authors made all materials, data, and analysis scripts available on the Open Science Framework (OSF), and the papers were checked using the freely available R package statcheck (see also: www.statcheck.io).

All additional (non-preregistered) analyses are explicitly labelled as exploratory. This makes it easier to see and understand what the researchers were expecting based on knowledge of the relevant literature, and what they eventually found in their studies. It also allows readers to build a clearer idea of the research process and the elements of the studies that came as inspiration after the reviews and the data collection were complete. The issue provide a clear example of how exploratory and confirmatory studies can coexist — and how science can thrive as a result. The articles published in this issue will hopefully serve as an inspiration and model for other media researchers, and encourage scientists studying media to preregister designs and share their data and materials openly.

Media research — whether concerning the Internet, video games, or film — speaks directly to everyday life in the modern world. It affects how the public forms their perceptions of media effects, and how professional groups and governmental bodies make policies and recommendations. Empirical findings disseminated to caregivers, practitioners, and educators should therefore be built on an empirical foundation with sufficient rigor. And indeed, the promise of building an empirically-based understanding of how we use, shape, and are shaped by technology is an alluring one. If adopted by media psychology researchers, this approach could support rigorous testing and development of promising theories, and retirement of theories that do not reliably account for observed data.

The authors close by noting their firm belief that incremental steps taken towards scientific transparency and empirical rigor — with changes to publishing practices to promote open, reproducible, high-quality research – will help us realize this potential.

We caught up with the editors to find out more about preregistration of studies:

Ed.: So this “crisis“ in psychology (including, for example, a lack of reproducibility of certain reported results) — is it unique to psychology, or does it extend more generally to other (social) sciences? And how much will is there in the community to do something about it?

Andy: Absolutely not. There is strong evidence in most social and medical sciences that computational reproducibility (i.e. re-running the code / data) and replicability (i.e. re-running the study) are much lower than we might expect. In psychology and medical research there is a lot of passion and expertise focused on improving the evidence base. We’re cautiously optimistic that researchers in allied fields such as computational social science will follow suit.

Malte: It’s important to understand that a failure to successfully replicate a previous finding is not a problem for scientific progress. Quite contrary, it tells us that previously held assumptions or predictions must be revisited. The number of replications in psychology’s flagship journals is still not overwhelming, but the research community has begun to value and incentivize this type of research.

Ed.: It’s really impressive not just what you’ve done with this special issue (and the intentions behind it), but also that the editor gave you free reign to do so — and also to investigate and report on the state of that journal’s previously published articles, including re-running stats, in what you describe as an act of “sincere self-reflection” on the part of the journal. How much acceptance is there in the field (psychology, and beyond) that things need to be shaken up?

Malte: I think it is uncontroversial to say that, as psychologists adapt their research practices (by preregistering their hypotheses, conducting high-powered replications, and sharing their data and materials) the reliability and quality of the scientific evidence they produce increases. However, we need to be careful not to depreciate the research generated before these changes. But that is exactly what science can help with: Meta-scientific analyses of already published research, be it in our editorial or elsewhere, provide guidance how it may (or may not) inform future studies on technology and human behavior.

Andy: We owe a lot to the editor-in-chief Nicole Krämer and the experts that reviewed submissions to the special issue. This hard work has helped us and the authors deliver a strong set of studies with respect to technology effects on behaviour. We are proud to say that registered reports is now a permanent submission track at the Journal of Media Psychology and 35 other journals. We hope this can help set an example for other areas of quantitative social science which may not yet realise they face the same serious challenges.

Ed: It’s incredibly annoying to encounter papers in review where the problem is clearly that the study should have been designed differently from the start. The authors won’t start over, of course, so you’re just left with a weak paper that the authors will be desperate to offload somewhere, but that really shouldn’t be published: i.e. a massive waste of everyone’s time. What structural changes are needed to mainstream pre-registration as a process, i.e. for design to be reviewed first, before any data is collected or analysed? And what will a tipping point towards preregistration look like, assuming it comes?

Andy: We agree that this is experience is aggravating as researchers invested in both the basic and applied aspects of science. We think this might come down to a carrot and stick approach. For quantitative science, pre-registration and replication could be a requirement for articles to be considered in the Research Exercise Framework (REF) and as part of UK and EU research council funding. For example, the Wellcome Trust now provides an open access open science portal for researchers supported by their funding (carrots). In terms of sticks, it may be the case that policy makers and the general public will become more sophisticated over time and simply will not value work that is not transparently conducted and shared.

Ed.: How aware / concerned are publishers and funding bodies of this crisis in confidence in psychology as a scientific endeavour? Will they just follow the lead of others (e.g. groups like the Center for Open Science), or are they taking a leadership role themselves in finding a way forward?

Malte: Funding bodies are arguably another source of particularly tasty carrots. It is in their vital interest that funded research is relevant and conducted rigorously, but also that it is sustainable. They depend on reliable groundwork to base new research projects on. Without it funding becomes, essentially, a gambling operation. Some organizations are quicker than others to take a lead, such as the The Netherlands Organisation for Scientific Research (NWO), who have launched a Replication Studies pilot programme. I’m optimistic we will see similar efforts elsewhere.

Andy: We are deeply concerned that the general public will see that science and scientists are missing a golden opportunity to correct itself and ourselves. Like scientists, funding bodies are adaptive and we (and others) speak directly to them about these challenges to the medical and social sciences.The public and research councils invest substantial resources in science and it is our responsibility to do our best and to deliver the best science we can. Initiatives like the Center for Open Science are key to this because they help scientists build tools to pool our resources and develop innovative methods for strengthening our work.

Ed.: I assume the end goal of this movement to embed it in the structure of science as-it-is-done? i.e. for good journals and major funding bodies to make pre-registration of studies a requirement, and for a clear distinction to be drawn between exploratory and confirmatory studies? Out of curiosity, what does (to pick a random journal) Nature make of all this? And the scientific press? Is there much awareness of preregistration as a method?

Malte: Conceptually, preregistration is just another word for how the scientific method is taught already: Hypotheses are derived from theory, and data are collected to test them. Predict, verify, replicate. Matching this concept by a formal procedure on some organizational level (such as funding bodies or journals) seems only consequential. Thanks to scientists like Chris Chambers, who is promoting the Registered Reports format, confidence that the number of journals offering this track will ever increase is warranted.

Andy: We’re excited to say that parts of these mega-journals and some science journalists are on board. Nature: Human Behavior now provides registered reports as a submission track and a number of science journalists including Ed Yong (@edyong209), Tom Chivers (@TomChivers), Neuroskeptic (@Neuro_Skeptic), and Jessie Singal (@jessesingal) are leading the way with critical and on point work that highlights the risks associated with the replication crisis and opportunities to improve reproducibility.

Ed.: Finally: what would you suggest to someone wanting to make sure they do a good study, but who is not sure where to begin with all this: what are the main things they should read and consider?

Andy: That’s a good question; the web is a great place to start. To learn more about registered reports and why they are important see this, and to learn about their place in robust science see this. To see how you can challenge yourself to do a pre-registered study and earn $1,000 see this, and to do a deep dive into open scientific practice see this.

Malte: Yeah, what Andy said. Also, I would thoroughly recommend joining social networks (Twitter, or the two sister groups Psychological Methods and PsychMAP on Facebook) where these issues are lively discussed.

Ed.: Anyway .. congratulations to you both, the issue authors, and the journal’s editor-in-chief, on having done a wonderful thing!

Malte: Thank you! We hope the research reports in this issue will serve as an inspiration and model for other psychologists.

Andy: Many thanks, we are doing our best to make the social sciences better and more reliable.

Read the full editorial: Elson, M. and Przybylski, A. (2017) The Science of Technology and Human Behavior: Standards, Old and New. Journal of Media Psychology. DOI: 10.1027/1864-1105/a000212

Malte Elson and Andrew Przybylski were talking to blog editor David Sutcliffe.

The growth of online gig work — paid work allocated and delivered by way of internet platforms without a contract for long-term employment — has been welcomed by economic development experts, and the world’s largest global development network is promoting its potential to aid human development. There are hopes that online gig work, and the platforms that support it, might catalyse new, sustainable employment opportunities by addressing a mismatch in the supply and demand of labour globally.

Some of the world’s largest gig work platforms have also framed their business models as a revolution in labour markets, suggesting that they can help lift people out of poverty. Similarly, many policymakers expect that regions like Sub-Saharan Africa and Southeast Asia can capitalise on this digitally mediated work opportunity as youth-to-adult unemployment rates hit historic peaks. More broadly, it has been suggested that online gig work will have structural benefits on the global economy, such as raising labour force participation and improving productivity.

Against this background, a new report by Mark Graham, Vili Lehdonvirta, Alex Wood, Helena Barnard, Isis Hjorth, and David Peter Simon, “The Risks and Rewards of Online Gig Work At The Global Margins” [PDF] highlights the risks alongside the rewards of online gig work. It draws on interviews and surveys, together with transaction data from one of the world’s largest online gig work platforms, to reveal the complex and sometimes problematic reality of this “new world of work”.

While there are significant rewards to online gig work, there are also significant risks. Discrimination, low pay rates, overwork, and insecurity all need to be tackled head-on. The report encourages online gig work platforms to further develop their service, policymakers to revisit regulation, and labour activists to examine organising tactics if online gig work is to truly live up to its potential for human development, and become a sustainable situation for many more workers.

The final section of the report poses questions for all stakeholders regarding how to improve the conditions and livelihoods of online gig workers, particularly given how these platforms have become disembedded from the norms and laws that normally regulate labour intermediaries. Specific questions that are discussed include:

• Is it necessary to list nationality on profile pages? Will online gig workers receive formal employment contracts in the future?
• What formal channels could exist for workers to voice their issues? Where should governments regulate online gig work in the future?
• Will governments need to limit online gig work monopolies? And how will governments support alternative forms of platform organisation?
• What online forms of voice could emerge for workers, and in what ways can existing groups be leveraged to promote solidarity?
• To what extent will companies be held accountable for poor working conditions? Do platforms need a Fairwork certification program?

The report also offers suggestions alongside the questions, drawing on relevant literature and referencing historical precedents.

Read the full report: Graham, M., Lehdonvirta, V., Wood, A., Barnard, H., Hjorth, I., Simon, D. P. (2017) The Risks and Rewards of Online Gig Work At The Global Margins [PDF]. Oxford: Oxford Internet Institute.

Read the article: Graham, M., Hjorth, I. and Lehdonvirta, V. (2017) Digital Labour and Development: Impacts of Global Digital Labour Platforms and the Gig Economy on Worker Livelihoods. Transfer. DOI: 10.1177/1024258916687250

The report is an output of the project “Microwork and Virtual Production Networks in Sub-Saharan Africa and Southeast Asia”, funded by the International Development Research Centre (IDRC), grant number: 107384-001.

As David Harvey famously noted, workers are unavoidably place-based because “labor-power has to go home every night.” But the widespread use of the Internet has changed much of that. The confluence of rapidly spreading digital connectivity, skilled but under-employed workers, the existence of international markets for labour, and the ongoing search for new outsourcing destinations, has resulted in organisational, technological, and spatial fixes for virtual production networks of services and money. Clients, bosses, workers, and users of the end-products of work can all now be located in different corners of the planet.

A new article by Mark Graham, Isis Hjorth and Vili Lehdonvirta, “Digital labour and development: impacts of global digital labour platforms and the gig economy on worker livelihoods”, published in Transfer, discusses the implications of the spatial unfixing of work for workers in some of the world’s economic margins, and reflects on some of the key benefits and costs associated with these new digital regimes of work. Drawing on a multi-year study with digital workers in Sub-Saharan Africa and South-east Asia, it highlights four key concerns for workers: bargaining power, economic inclusion, intermediated value chains, and upgrading.

As ever more policy-makers, governments and organisations turn to the gig economy and digital labour as an economic development strategy to bring jobs to places that need them, it is important to understand how this might influence the livelihoods of workers. The authors show that although there are important and tangible benefits for a range of workers, there are also a range of risks and costs that could negatively affect the livelihoods of digital workers. They conclude with a discussion of four broad strategies – certification schemes, organising digital workers, regulatory strategies and democratic control of online labour platforms — that could improve conditions and livelihoods for digital workers.

We caught up with the authors to explore the implications of the study:

Ed.: Shouldn’t increased digitisation of work also increase transparency (i.e. tracking, auditing etc.) around this work — i.e. shouldn’t digitisation largely be a good thing?

Mark: It depends. One of the goals of our research is to ask who actually wins and loses from the digitalisation of work. A good thing for one group (e.g. employers in the Global North) isn’t necessarily automatically a good thing for another group (e.g. workers in the Global South).

Ed.: You mention market-based strategies as one possible way to improve transparency around working conditions along value chains: do you mean something like a “Fairtrade” certification for digital work, i.e. creating a market for “fair work”?

Mark: Exactly. At the moment, we can make sure that the coffee we drink or the chocolate we eat is made ethically. But we have no idea if the digital services we use are. A ‘fair work’ certification system could change that.

Ed.: And what sorts of work are these people doing? Is it the sort of stuff that could be very easily replaced by advances in automation (natural language processing, pattern recognition etc.)? i.e. is it doubly precarious, not just in terms of labour conditions, but also in terms of the very existence of the work itself?

Mark: Yes, some of it is. Ironically, some of the paid work that is done is training algorithms to do work that used to be done by humans.

Ed.: You say that “digital workers have been unable to build any large-scale or effective digital labour movements” — is that because (unlike e.g. farm work which is spatially constrained), employers can very easily find someone else anywhere in the world who is willing to do it? Can you envisage the creation of any effective online labour movement?

Mark: A key part of the problem for workers here is the economic geography of this work. A worker in Kenya knows that they can be easily replaced by workers on the other side of the planet. The potential pool of workers willing to take any job is massive. For digital workers to have any sort of effective movement in this context means looking to what I call geographic bottlenecks in the system. Places in which work isn’t solely in a global digital cloud. This can mean looking to things like organising and picketing the headquarters of firms, clusters of workers in particular places, or digital locations (the web-presence of firms). I’m currently working on a new publication that deals with these issues in a bit more detail.

Ed.: Are there any parallels between the online gig work you have studied and ongoing issues with “gig work” services like Uber and Deliveroo (e.g. undercutting of traditional jobs, lack of contracts, precarity)?

Mark: A commonality in all of those cases is that platforms become intermediaries in between clients and workers. This means that rather than being employees, workers tend to be self-employed: a situation that offers workers freedom and flexibility, but also comes with significant risks to the worker (e.g. no wages if they fall ill).

Read the full article: Graham, M., Hjorth, I. and Lehdonvirta, V. (2017) Digital Labour and Development: Impacts of Global Digital Labour Platforms and the Gig Economy on Worker Livelihoods. Transfer. DOI: 10.1177/1024258916687250

Read the full report: Graham, M., Lehdonvirta, V., Wood, A., Barnard, H., Hjorth, I., Simon, D. P. (2017) The Risks and Rewards of Online Gig Work At The Global Margins [PDF]. Oxford: Oxford Internet Institute.

The article draws on findings from the research project “Microwork and Virtual Production Networks in Sub-Saharan Africa and South-east Asia”, funded by the International Development Research Centre (IDRC), grant number: 107384-001.

Mark Graham was talking to blog editor David Sutcliffe.

While the UK government has financed technological infrastructure and invested in schemes to address digital inequalities, the outcomes of these schemes are rarely uniformly positive or transformative for the people involved. This gap between expectation and reality demands theoretical attention; with more attention placed on the cultural, political and economic contexts of the digitally excluded, and the various attempts to “include” them.

Focusing on a two-year digital inclusion scheme for 30 teenagers and their families initiated by a local council in England, a qualitative study by Huw C. Davies, Rebecca Eynon, and Sarah Wilkin analyses why, despite the good intentions of the scheme’s stakeholders, it fell short of its ambitions. It also explains how the neoliberalist systems of governance that are increasingly shaping the cultures and behaviours of Internet service providers and schools — that incentivise action that is counterproductive to addressing digital inequality and practices — cannot solve the problems they create.

We caught up with the authors to discuss the study’s findings:

Ed.: It was estimated that around 10% of 13 year olds in the study area lacked dependable access to the Internet, and had no laptop or PC at home. How does this impact educational outcomes?

Huw: It’s impossible to disaggregate technology from everything else that can affect a young person’s progress through school. However, one school in our study had transferred all its homework and assessments online while the other schools were progressing to this model. The students we worked with said doing research for homework is synonymous with using Google or Wikipedia, and it’s the norm to send homework and coursework to teachers by email, upload it to Virtual Learning Environments, or print it out at home. Therefore students who don’t have access to the Internet have to spend time and effort finding work-arounds such as using public libraries. Lack of access also excludes such students from casual learning from resources online or pursuing their own interests in their own time.

Ed.: The digital inclusion scheme was designed as a collaboration between a local council in England (who provided Internet services) and schools (who managed the scheme) in order to test the effect of providing home Internet access on educational outcomes in the area. What was your own involvement, as researchers?

Huw: Initially, we were the project’s expert consultants: we were there to offer advice, guidance and training to teachers and assess the project’s efficacy on its conclusion. However, as it progressed we took on the responsibility of providing skills training to the scheme’s students and technical support to their families. When it came to assessing the scheme, by interviewing young people and their families at their homes, we were therefore able to draw on our working knowledge of each family’s circumstances.

Ed.: What was the outcome of the digital inclusion project —- i.e. was it “successful”?

Huw: As we discuss in the article, defining success in these kinds of schemes is difficult. Subconsciously many people involved in these kinds of schemes expect technology to be transformative for the young people involved yet in reality the changes you see are more nuanced and subtle. Some of the scheme’s young people found apprenticeships or college courses, taught themselves new skills, used social networks for the first time and spoke to friends and relatives abroad by video for free. These success stories definitely made the scheme worthwhile. However, despite the significant good will of the schools, local council, and the families to make the scheme a success there were also frustrations and problems. In the article we talk about these problems and argue that the challenges the scheme encountered are not just practical issues to be resolved, but are systemic issues that need to be explicitly recognised in future schemes of this kind.

Ed.: And in the article you use neoliberalism as a frame to discuss these issues..?

Huw: Yes. But we recognise in the article that this is a concept that needs to be used with care. It’s often used pejoratively and/or imprecisely. We have taken it to mean a set of guiding principles that are intended to produce a better quality of services through competition, targets, results, incentives and penalties. The logic of these principles, we argue, influences they way organisations treat individual users of their services.

For example, for Internet Service Providers (ISPs) the logic of neoliberalism is to subcontract out the constituent parts of an overall service provision to create mini internal markets that (in theory) promote efficiency through competition. Yet this logic only really works if everyone comes to the market with similar resources and abilities to make choices. If their customers are well informed and wealthy enough to remind companies that they can take their business elsewhere these companies will have a strong incentive to improve their services and reduce their costs. If customers are disempowered by lack of choice the logic of neoliberalism tends to marginalise or ignore their needs. These were low-income families with little or no experience of exercising consumer choice and rights. For them therefore these mini markets didn’t work.

In the schools we worked with the logic of neoliberalism meant staff and students felt under pressure to meet certain targets — they all had to priortise things that were measured and measurable. Failure to meet these targets would then mean they would have to account for what went wrong, face losing out on a reward or they would expect disciplinary action. It therefore becomes much more difficult for schools to devote time and energy to schemes such as this.

Ed.: Were there any obvious lessons that might lead to a better outcome if the scheme were to be repeated: or are the (social, economic, political) problems just too intractable, and therefore too difficult and expensive to sort out?

Huw: Many of the families told us that access to the Internet was becoming evermore vital. This was not just for homework but also for access to public and health services (that are being increasingly delivered online) and getting to the best deals online for consumer services. They often told us therefore that they would do whatever it took to keep their connection after the two-year scheme ended. This often meant paying for broadband out of their social security benefits or income that was too low to be taxable: income that could otherwise have been spent on, for example, food and clothing. Given its necessity, we should have a national conversation about providing this service to low income families for free.

Ed.: Some of the families included in the study could be considered “hard to reach”. What were your experiences of working with them?

Huw: There are many practical and ethical issues to address before these sorts of schemes can begin. These families often face multiple intersecting problems that involve many agencies (who don’t necessarily communicate with each other) intervening in their lives. For example, some of the scheme’s families were dealing with mental illness, disability, poor housing, and debt all at the same time. It is important that such schemes are set up with an awareness of this complexity. We are very grateful to the families that took part in the scheme and the insights they gave us for how such schemes should run in the future.

Ed.: Finally, how do your findings inform all the studies showing that “digital inclusion schemes are rarely uniformly positive or transformative for the people involved”. Are these studies gradually leading to improved knowledge (and better policy intervention), or simply showing the extent of the problem without necessarily offering “solutions”?

Huw: We have tried to put this scheme into a broader context to show such policy interventions have to be much more ambitious, intelligent, and holistic. We never assumed digital inequality is an isolated problem that can be fixed with a free broadband connection, but when people are unable to afford the Internet it is an indication of other forms of disadvantage that, in a sympathetic and coordinated way, have to be addressed simultaneously. Hopefully, we have contributed to the growing awareness that such attempts to ameliorate the symptoms may offer some relief but should never be considered a cure in itself.

Read the full article: Huw C. Davies, Rebecca Eynon, Sarah Wilkin (2017) Neoliberal gremlins? How a scheme to help disadvantaged young people thrive online fell short of its ambitions. Information, Communication & Society. DOI: 10.1080/1369118X.2017.1293131

The article is an output of the project “Tackling Digital Inequality Amongst Young People: The Home Internet Access Initiative“, funded by Google.

Huw Davies was talking to blog editor David Sutcliffe.

This is the third post in a series that will uncover great writing by faculty and students at the Oxford Internet Institute, things you should probably know, and things that deserve to be brought out for another viewing. This week: Reality, Augmented Reality and Ambient Fun!

The addictive gameplay of Pokémon GO has led to police departments warning people that they should be more careful about revealing their locations, players injuring themselves, finding dead bodies, and even the Holocaust Museum telling people to play elsewhere.. Our environments are increasingly augmented with digital information: but how do we assert our rights over how and where this information is used? And should we be paying more attention to the design of persuasive technologies in increasingly attention-scarce environments? Or should we maybe just bin all our devices and pack ourselves off to digital detox camp?

1. James Williams: Bring Your Own Boundaries: Pokémon GO and the Challenge of Ambient Fun

23 July 2016 / 2500 words / 12 min / Gross misuses of the “Poké-” prefix: 6

“The slogan of the Pokémon franchise is ‘Gotta catch ‘em all!’ This phrase has always seemed to me an apt slogan for the digital era as a whole. It expresses an important element of the attitude we’re expected to have as we grapple with the Sisyphean boulder of information abundance using our woefully insufficient cognitive toolsets.”

Pokémon GO signals the first mainstream adoption of a type of game — always on, always with you — that requires you to ‘Bring Your Own Boundaries’, says James Williams. Regulation of the games falls on the user; presenting us with a unique opportunity to advance the conversation about the ethics of self-regulation and self-determination in environments of increasingly persuasive technology.

2. James Williams: Orwell, Huxley, Banksy

24 May 2014 / 1000 words / 5 min

“Orwell worried that what we fear could ultimately come to control us: the “boot stamping on a human face—forever.” Huxley, on the other hand, felt that what we love was more likely to control us — by seducing us and engineering our compliance from within — and was therefore more deserving of a wary eye. In the age of the Internet, this dichotomy is reflected in the interplay between information and attention.”

You could say that the core challenge of the Internet (when information overload leads to scarcity of attention) is that it optimizes more for our impulses than our intentions, says James Williams, who warns that we could significantly overemphasize informational challenges to the neglect of attentional ones. In Brave New World, the defenders of freedom had “failed to take into account man’s almost infinite appetite for distractions.” In the digital era, we are making the same mistake, says James: we need better principles and processes to help designers make products more respectful of users’ attention.

3. James Williams: Staying free in a world of persuasive technologies

29 July 2013 / 1500 words / 7 min

“The explosion of media and information has made it harder for people to be intentional or reflective about their goals and priorities in life. We’re living through a crisis of distraction. The convergence of all these trends suggests that we could increasingly live our lives in environments of high persuasive power. To me, the biggest ethical questions are those that concern individual freedom and autonomy. When, exactly, does a “nudge” become a “push”?”

Technologies are increasingly being designed to change the way we think and behave: the Internet is now part of the background of human experience, and rapid advances in analytics are enabling optimisation of technologies to reach greater levels of persuasiveness. The ethical questions raised aren’t new, says James Williams, but the environment in which we’re asking them makes them much more urgent to address.

4. Mark Graham, Joe Shaw: An Informational Right to the City? [The New Internationalist]

8 February 2017 / 1000 words / 5 min

“Contemporary cities are much more than bricks and mortar; streets and pipes. They are also their digital presences – abstract presences which can reproduce and change our material reality. If you accept this premise, then we need to ask important questions about what rights citizens have to not just public and private spaces, but also their digital equivalents.”

It’s time for the struggle for more egalitarian rights to the city to move beyond a focus on material spaces and into the realm of digital ones, say Mark Graham and Joe Shaw. And we can undermine and devalue the hold of large companies over urban information by changing our own behaviour, they say: by rejecting some technologies, by adopting alternative service providers, and by supporting initiatives to develop platforms that operate on a more transparent basis.

5. Theodora Sutton: Exploring the world of digital detoxing

2 March 2017 / 2000 words / 10 min

“The people who run Camp Grounded would tell you themselves that digital detoxing is not really about digital technology. That’s just the current scapegoat for all the alienating aspects of modern life. But at the same time I think it is a genuine conversation starter about our relationship with technology and how it’s designed.”

As our social interactions become increasingly entangled with the online world, some people are insisting on the benefits of disconnecting entirely from digital technology: getting back to so-called “real life“. In this piece, Theodora Sutton explores the digital detoxing community in the San Francisco Bay Area, getting behind the rhetoric of the digital detox to understand the views and values of those wanting to re-examine the role of technology in their lives.

The Authors

James Williams is an OII doctoral student. He studies the ethical design of persuasive technology. His research explores the complex boundary between persuasive power and human freedom in environments of high technological persuasion.

Mark Graham is the Professor of Internet Geography at the OII. His research focuses on Internet and information geographies, and the overlaps between ICTs and economic development.

Joe Shaw is an OII DPhil student and Research Assistant. His research is concerned with the geography of information, property market technologies (PropTech) and critical urbanism.

Theodora Sutton is an OII DPhil student. Her research in digital anthropology examines digital detoxing and the widespread cultural narrative that sees digital sociality as inherently ‘lesser’ or less ‘natural’ than previous forms of communication.

Coming up! .. The platform economy / Power and development / Internet past and future / Government / Labour rights / The disconnected / Ethics / Staying critical

A 2016 survey by OnePoll found that 40% of respondents felt they had “not truly experienced valuable moments such as a child’s first steps or graduation” because “technology got in the way”, and OfCom’s 2016 survey showed that 15 million British Internet users (representing a third of those online), have already tried a digital detox. In recent years, America has sought to pathologise a perceived over-use of digital technology as “Internet addiction”. While the term is not recognized by the DSM, the idea is commonly used in media rhetoric and forms an important backdrop to digital detoxing.

The article Disconnect to reconnect: The food/technology metaphor in digital detoxing (First Monday) by Theodora Sutton presents a short ethnography of the digital detoxing community in the San Francisco Bay Area. Her informants attend an annual four-day digital detox and summer camp for adults in the Californian forest called Camp Grounded. She attended two Camp Grounded sessions in 2014, and followed up with semi-structured interviews with eight detoxers.

We caught up with Theodora to examine the implications of the study and to learn more about her PhD research, which focuses on the same field site.

Ed.: In your forthcoming article you say that Camp Grounded attendees used food metaphors (and words like “snacking” and “nutrition”) to understand their own use of technology and behaviour. How useful is this as an analogy?

Theodora: The food/technology analogy is an incredibly neat way to talk about something we think of as immaterial in a more tangible way. We know that our digital world relies on physical connections, but we forget that all the time. Another thing it does in lending a dietary connotation is to imply we should regulate our consumption of digital use; that there are healthy and unhealthy or inappropriate ways of using it.

I explore more pros and cons to the analogy in the paper, but the biggest con in my opinion is that while it’s neat, it’s often used to make value judgments about technology use. For example, saying that online sociality is like processed food is implying that it lacks authenticity. So the food analogy is a really useful way to understand how people are interpreting technology culturally, but it’s important to be aware of how it’s used.

Ed.: How do people rationalise ideas of the digital being somehow “less real” or “genuine” (less “nourishing”), despite the fact that it obviously is all real: just different? Is it just a peg to blame an “other” and excuse their own behaviour .. rather than just switching off their phones and going for a run / sail etc. (or any other “real” activity..).

Theodora: The idea of new technologies being somehow less real or less natural is a pretty established Western concept, and it’s been fundamental in moral panics following new technologies. That digital sociality is different, not lesser, is something we can academically agree on, but people very often believe otherwise.

My personal view is that figuring out what kind of digital usage suits you and then acting in moderation is ideal, without the need for extreme lengths, but in reality moderation can be quite difficult to achieve. And the thing is, we’re not just talking about choosing to text rather than meet in person, or read a book instead of go on Twitter. We’re talking about digital activities that are increasingly inescapable and part of life, like work e-mail or government services being moved online.

The ability to go for a run or go sailing are again privileged activities for people with free time. Many people think getting back to nature or meeting in person are really important for human needs. But increasingly, not everyone has the ability to get away from devices, especially if you don’t have enough money to visit friends or travel to a forest, or you’re just too tired from working all the time. So Camp Grounded is part of what they feel is an urgent conversation about whether the technology we design addresses human, emotional needs.

Ed.: You write in the paper that “upon arrival at Camp Grounded, campers are met with hugs and milk and cookies” .. not to sound horrible, but isn’t this replacing one type of (self-focused) reassurance with another? I mean, it sounds really nice (as does the rest of the Camp), but it sounds a tiny bit like their “problem” is being fetishised / enjoyed a little bit? Or maybe that their problem isn’t to do with technology, but rather with confidence, anxiety etc.

Theodora: The people who run Camp Grounded would tell you themselves that digital detoxing is not really about digital technology. That’s just the current scapegoat for all the alienating aspects of modern life. They also take away real names, work talk, watches, and alcohol. One of the biggest things Camp Grounded tries to do is build up attendees’ confidence to be silly and playful and have their identities less tied to their work persona, which is a bit of a backlash against Silicon Valley’s intense work ethic. Milk and cookies comes from childhood, or America’s summer camps which many attendees went to as children, so it’s one little thing they do to get you to transition into that more relaxed and childlike way of behaving.

I’m not sure about “fetishized,” but Camp Grounded really jumps on board with the technology idea, using really ironic things like an analog dating service called “embers,” a “human powered search” where you pin questions on a big noticeboard and other people answer, and an “inbox” where people leave you letters.

And you’re right, there is an aspect of digital detoxing which is very much a “middle class ailment” in that it can seem rather surface-level and indulgent, and tickets are pretty pricey, making it quite a privileged activity. But at the same time I think it is a genuine conversation starter about our relationship with technology and how it’s designed. I think a digital detox is more than just escapism or reassurance, for them it’s about testing a different lifestyle, seeing what works best for them and learning from that.

Ed.: Many of these technologies are designed to be “addictive” (to use the term loosely: maybe I mean “seductive”) in order to drive engagement and encourage retention: is there maybe an analogy here with foods that are too sugary, salty, fatty (i.e. addictive) for us? I suppose the line between genuine addiction and free choice / agency is a difficult one; and one that may depend largely on the individual. Which presumably makes any attempts to regulate (or even just question) these persuasive digital environments particularly difficult? Given the massive outcry over perfectly rational attempts to tax sugar, fat etc.

Theodora: The analogy between sugary, salty, or fatty foods and seductive technologies is drawn a lot — it was even made by danah boyd in 2009. Digital detoxing comes from a standpoint that tech companies aren’t necessarily working to enable meaningful connection, and are instead aiming to “hook” people in. That’s often compared to food companies that exist to make a profit rather than improve your individual nutrition, using whatever salt, sugar, flavourings, or packaging they have at their disposal to make you keep coming back.

There are two different ways of “fixing” perceived problems with tech: there’s technical fixes that might only let you use the site for certain amounts of time, or re-designing it so that it’s less seductive; then there’s normative fixes, which could be on an individual level deciding to make a change, or even society wide, like the French labour law giving the “right to disconnect” from work emails on evenings and weekends.

One that sort of embodies both of these is The Time Well Spent project, run by Tristan Harris and the OII’s James Williams. They suggest different metrics for tech platforms, such as how well they enable good experiences away from the computer altogether. Like organic food stickers, they’ve suggested putting a stamp on websites whose companies have these different metrics. That could encourage people to demand better online experiences, and encourage tech companies to design accordingly.

So that’s one way that people are thinking about regulating it, but I think we’re still in the stages of sketching out what the actual problems are and thinking about how we can regulate or “fix” them. At the moment, the issue seems to depend on what the individual wants to do. I’d be really interested to know what other ideas people have had to regulate it, though.

Ed.: Without getting into the immense minefield of evolutionary psychology (and whether or not we are creating environments that might be detrimental to us mentally or socially: just as the Big Mac and Krispy Kreme are not brilliant for us nutritionally) — what is the lay of the land — the academic trends and camps — for this larger question of “Internet addiction” .. and whether or not it’s even a thing?

Theodora: In my experience academics don’t consider it a real thing, just as you wouldn’t say someone had an addiction to books. But again, that doesn’t mean it isn’t used all the time as a shorthand. And there are some academics who use it, like Kimberly Young who proposed it in the 1990’s. She still runs an Internet addiction treatment centre in New York, and there’s another in Fall City, Washington state.

The term certainly isn’t going away any time soon and the centres treat people who genuinely seem to have a very problematic relationship with their technology. People like the OII’s Andrew Przybylski (@ShuhBillSkee) are working on untangling this kind of problematic digital use from the idea of addiction, which can be a bit of a defeatist and dramatic term.

Ed.: As an ethnographer working at the Camp according to its rules (hand-written notes, analogue camera) .. did it affect your thinking or subsequent behaviour / habits in any way?

Theodora: Absolutely. In a way that’s a struggle, because I never felt that I wanted or needed a digital detox, yet having been to it three times now I can see the benefits. Going to camp made a strong case for the argument to be more careful with my technology use, for example not checking my phone mid-conversation, and I’ve been much more aware of it since. For me, that’s been part of an on-going debate that I have in my own life, which I think is a really useful fuel towards continuing to unravel this topic in my studies.

Ed.: So what are your plans now for your research in this area — will you be going back to Camp Grounded for another detox?

Theodora: Yes — I’ll be doing an ethnography of the digital detoxing community again this summer for my PhD and that will include attending Camp Grounded again. So far I’ve essentially done just preliminary fieldwork and visited to touch base with my informants. It’s easy to listen to the rhetoric around digital detoxing, but I think what’s been missing is someone spending time with them to really understand their point of view, especially their values, that you can’t always capture in a survey or in interviews.

In my PhD I hope to understand things like: how digital detoxers even think about technology, what kind of strategies they have to use it appropriately once they return from a detox, and how metaphor and language work in talking about the need to “unplug.” The food analogy is just one preliminary finding that shows how fascinating the topic is as soon as you start scratching away the surface.

Read the full article: Sutton, T. (2017) Disconnect to reconnect: The food/technology metaphor in digital detoxing. First Monday 22 (6).

OII DPhil student Theodora Sutton was talking to blog editor David Sutcliffe.

In the first attempt to estimate Internet use at any small-scale level, they combine data from a sample survey, the 2013 Oxford Internet Survey (OxIS), with the 2011 UK census, employing small area estimation to estimate Internet use in small geographies in Britain. (Read the paper for more on this method, and discussion of why there has been little work on the geography of digital inequality.)

There are two major reasons to suspect that geographic differences in Internet use may be important: apparent regional differences and the urban-rural divide. The authors do indeed find a regional difference: the area with least Internet use is in the North East, followed by central Wales; the highest is in London and the South East. But interestingly, geographic differences become non-significant after controlling for demographic variables (age, education, income etc.). That is, demographics matter more than simply where you live, in terms of the likelihood that you’re an Internet user.

Britain has one of the largest Internet economies in the developed world, and the Internet contributes an estimated 8.3 percent to Britain’s GDP. By reducing a range of geographic frictions and allowing access to new customers, markets and ideas it strongly supports domestic job and income growth. There are also personal benefits to Internet use. However, these advantages are denied to people who are not online, leading to a stream of research on the so-called digital divide.

We caught up with Grant Blank to discuss the policy implications of this marked disparity in (estimated) Internet use across Britain.

Ed.: The small-area estimation method you use combines the extreme breadth but shallowness of the national census, with the relative lack of breadth (2000 respondents) but extreme richness (550 variables) of the OxIS survey. Doing this allows you to estimate things like Internet use in fine-grained detail across all of Britain. Is this technique in standard use in government, to understand things like local demand for health services etc.? It seems pretty clever..

Grant: It is used by the government, but not extensively. It is complex and time-consuming to use well, and it requires considerable statistical skills. These have hampered its spread. It probably could be used more than it is — your example of local demand for health services is a good idea..

Ed.: You say this method works for Britain because OxIS collects information based on geographic area (rather than e.g. randomly by phone number) — so we can estimate things geographically for Britain that can’t be done for other countries in the World Internet Project (including the US, Canada, Sweden, Australia). What else will you be doing with the data, based on this happy fact?

Grant: We have used a straightforward measure of Internet use versus non-use as our dependent variable. Similar techniques could predict and map a variety of other variables. For example, we could take a more nuanced view of how people use the Internet. The patterns of mobile use versus fixed-line use may differ geographically and could be mapped. We could separate work-only users, teenagers using social media, or other subsets. Major Internet activities could be mapped, including such things as entertainment use, information gathering, commerce, and content production. In addition, the amount of use and the variety of uses could be mapped. All these are major issues and their geographic distribution has never been tracked.

Ed.: And what might you be able to do by integrating into this model another layer of geocoded (but perhaps not demographically rich or transparent) data, e.g. geolocated social media / Wikipedia activity (etc.)?

Grant: The strength of the data we have is that it is representative of the UK population. The other examples you mention, like Wikipedia activity or geolocated social media, are all done by smaller, self-selected groups of people, who are not at all representative. One possibility would be to show how and in what ways they are unrepresentative.

Ed.: If you say that Internet use actually correlates to the “usual” demographics, i.e. education, age, income — is there anything policy makers can realistically do with this information? i.e. other than hope that people go to school, never age, and get good jobs? What can policy-makers do with these findings?

Grant: The demographic characteristics are things that don’t change quickly. These results point to the limits of the government’s ability to move people online. They say that 100% of the UK population will never be online. This raises the question, what are realistic expectations for online activity? I don’t know the answer to that but it is an important question that is not easily addressed.

Ed.: You say that “The first law of the Internet is that everything is related to age”. When are we likely to have enough longitudinal data to understand whether this is simply because older people never had the chance to embed the Internet in their lives when they were younger, or whether it is indeed the case that older people inherently drop out. Will this age-effect eventually diminish or disappear?

Grant: You ask an important but unresolved question. In the language of social sciences — is the decline in Internet use with age an age-effect or a cohort-effect. An age-effect means that the Internet becomes less valuable as people age and so the decline in use with age is just a reflection of the declining value of the Internet. If this explanation is true then the age-effect will persist into the indefinite future. A cohort-effect implies that the reason older people tend to use the Internet less is that fewer of them learned to use the Internet in school or work. They will eventually be replaced by active Internet-using people and Internet use will no longer be associated with age. The decline with age will eventually disappear. We can address this question using data from the Oxford Internet Survey, but it is not a small area estimation problem.

Read the full article: Blank, G., Graham, M., and Calvino, C. 2017. Local Geographies of Digital Inequality. Social Science Computer Review. DOI: 10.1177/0894439317693332.

This work was supported by the Economic and Social Research Council [grant ES/K00283X/1]. The data have been deposited in the UK Data Archive under the name “Geography of Digital Inequality”.

Grant Blank was speaking to blog editor David Sutcliffe.

A research team at the OII has already been analysing the content, and provided cleaned data to the datahack participants that could be analysed through qualitative and quantitative methods. Following an introduction to the project by Laura Bates, an outline of the dataset by Taha Yasseri, and a speed-networking session led by Kathryn Eccles we fell into two teams to work with the data.

Our own group wanted to examine the question of how people interact with the threat of public space. We were also interested in how public space is divided between online and offline, and the social perception of being online versus offline. We wanted to explore what sorts of reactions people might have to examples of assault, or strategies or things they might do in response to something happening to them — and how they might differ online and offline.

We spent the first hour collecting keywords that might indicate reactions to either online or offline harassment, including identifying a perceived threat and coping with it. We then searched the raw data for responses like “I tried to ignore it” “I felt safe / unsafe” “I identified a risk” “I was feeling worried, feeling anxious or nervous“; and also looked at online versus offline actions. So for online action we were looking for specific platforms being named, and people saying things like “comment, response, delete, remove” in relation to social media posts. For offline we were looking for things like “I carried a [specific item]” or “I hid or avoided certain areas“ or “I walked faster” (etc.).

We wanted to know if we could apply ideas of responses to offline space back to online spaces, and how these online spaces fall short. Offline responses are often very individual, whereas you might not have such a direct and individual response to something like a Facebook ad. Taking into account the important caveat that this was just a quick exploration of the data — and that the data were indicative rather than representative (so should in no way be used to extrapolate or infer anything concrete) one of the biggest things we found was that while in the offline examples of responses to harassment there was quite a lot of action, like running away, or hiding in shops and restaurants, there were very few examples to responses in the online examples.

Though it actually turned out to be difficult to identify a clear division between online/offline contexts in the data: we saw accounts of people who were online on social media encountering something sexist and logging off, and then walking in the street and getting harassed. But it seemed like people were more likely to report something offline to the police than in online forums. And this contrast is very interesting, in terms of whether you can be an active agent in response to something, or whether there’s something about being online that positions you as being passive and unable to respond — and what we can do about that.

While we found it difficult to quantify, we did wonder if people might not be giving themselves credit for the kinds of responses they have to examples of sexism online — maybe they aren’t thinking about what they do. Whereas offline they might say “I ran away, because I was so scared” perhaps when it’s online, people just read it and not respond; or at least not report responses to the same extent. There were lots of complaints about images, or hypocrisy about Facebook’s enforcement of community standards (such as allowing rape jokes, but deleting pictures of breast-feeding), and other things like that. But the accounts don’t say if they reported it or took action.

This is strange because in cases of offline harassment in the street, where it escalates into something physical like a fight, women are often at a disadvantage: whereas in the online context women ought to have more leverage — but it does’t seem like reporting is being done. When we examined the themes of how people reacted online, we further differentiated between removing the source of a sexist comment (such as unfriending, unfollowing, muting, deleting) and removing the self (such as going offline, or removing yourself from the platform). It seemed that removing the source was generally more common than removing the self.

So people might simply be normalising the idea that misogyny and sexism is going to exist in forums. In the data someone had reported someone on Twitter saying “Well if you’re on Twitter you’re asking for it” — indicative of a “short-skirt” line of thinking about engaging on social media. In this environment people might see unfollowing and unfriending as a form of management and negotiation, as opposed to a fundamental problem with the site itself. It would be interesting to explore the self-censoring that happens before anything happens: quite a few of the examples we read opened with “I wasn’t even wearing anything provocative, but [this] happened..”. And it would be interesting to know if people also think like that in the online context: “I wasn’t even participating in a controversial way, but this still happened”. It’s an interesting parallel, maybe.

Fake news, post-truth, “alternative facts”, filter bubbles — this is the news and media environment we apparently now inhabit, and that has formed the fabric and backdrop of Brexit (“£350 million a week”) and Trump (“This was the largest audience to ever witness an inauguration — period”). Do social media divide us, hide us from each other? Are you particularly aware of what content is personalised for you, what it is you’re not seeing? How much can we do with machine-automated or crowd-sourced verification of facts? And are things really any worse now than when Bacon complained in 1620 about the false notions that “are now in possession of the human understanding, and have taken deep root therein”?

1. Bernie Hogan: How Facebook divides us [Times Literary Supplement]

27 October 2016 / 1000 words / 5 minutes

“Filter bubbles can create an increasingly fractured population, such as the one developing in America. For the many people shocked by the result of the British EU referendum, we can also partially blame filter bubbles: Facebook literally filters our friends’ views that are least palatable to us, yielding a doctored account of their personalities.”

Bernie Hogan says it’s time Facebook considered ways to use the information it has about us to bring us together across political, ideological and cultural lines, rather than hide us from each other or push us into polarized and hostile camps. He says it’s not only possible for Facebook to help mitigate the issues of filter bubbles and context collapse; it’s imperative, and it’s surprisingly simple.

2. Luciano Floridi: Fake news and a 400-year-old problem: we need to resolve the ‘post-truth’ crisis [the Guardian]

29 November 2016 / 1000 words / 5 minutes

“The internet age made big promises to us: a new period of hope and opportunity, connection and empathy, expression and democracy. Yet the digital medium has aged badly because we allowed it to grow chaotically and carelessly, lowering our guard against the deterioration and pollution of our infosphere. […] some of the costs of misinformation may be hard to reverse, especially when confidence and trust are undermined. The tech industry can and must do better to ensure the internet meets its potential to support individuals’ wellbeing and social good.”

The Internet echo chamber satiates our appetite for pleasant lies and reassuring falsehoods, and has become the defining challenge of the 21st century, says Luciano Floridi. So far, the strategy for technology companies has been to deal with the ethical impact of their products retrospectively, but this is not good enough, he says. We need to shape and guide the future of the digital, and stop making it up as we go along. It is time to work on an innovative blueprint for a better kind of infosphere.

3. Philip Howard: Facebook and Twitter’s real sin goes beyond spreading fake news

3 January 2017 / 1000 words / 5 minutes

“With the data at their disposal and the platforms they maintain, social media companies could raise standards for civility by refusing to accept ad revenue for placing fake news. They could let others audit and understand the algorithms that determine who sees what on a platform. Just as important, they could be the platforms for doing better opinion, exit and deliberative polling.”

Only Facebook and Twitter know how pervasive fabricated news stories and misinformation campaigns have become during referendums and elections, says Philip Howard — and allowing fake news and computational propaganda to target specific voters is an act against democratic values. But in a time of weakening polling systems, withholding data about public opinion is actually their major crime against democracy, he says.

4. Brent Mittelstadt: Should there be a better accounting of the algorithms that choose our news for us?

7 December 2016 / 1800 words / 8 minutes

“Transparency is often treated as the solution, but merely opening up algorithms to public and individual scrutiny will not in itself solve the problem. Information about the functionality and effects of personalisation must be meaningful to users if anything is going to be accomplished. At a minimum, users of personalisation systems should be given more information about their blind spots, about the types of information they are not seeing, or where they lie on the map of values or criteria used by the system to tailor content to users.”

A central ideal of democracy is that political discourse should allow a fair and critical exchange of ideas and values. But political discourse is unavoidably mediated by the mechanisms and technologies we use to communicate and receive information, says Brent Mittelstadt. And content personalization systems and the algorithms they rely upon create a new type of curated media that can undermine the fairness and quality of political discourse.

5. Heather Ford: Verification of crowd-sourced information: is this ‘crowd wisdom’ or machine wisdom?

19 November 2013 / 1400 words / 6 minutes

“A key question being asked in the design of future verification mechanisms is the extent to which verification work should be done by humans or non-humans (machines). Here, verification is not a binary categorisation, but rather there is a spectrum between human and non-human verification work, and indeed, projects like Ushahidi, Wikipedia and Galaxy Zoo have all developed different verification mechanisms.”

‘Human’ verification, a process of checking whether a particular report meets a group’s truth standards, is an acutely social process, says Heather Ford. If code is law and if other aspects in addition to code determine how we can act in the world, it is important that we understand the context in which code is deployed. Verification is a practice that determines how we can trust information coming from a variety of sources — only by illuminating such practices and the variety of impacts that code can have in different environments can we begin to understand how code regulates our actions in crowdsourcing environments.

.. and just to prove we’re capable of understanding and acknowledging and assimilating multiple viewpoints on complex things, here’s Helen Margetts, with a different slant on filter bubbles: “Even if political echo chambers were as efficient as some seem to think, there is little evidence that this is what actually shapes election results. After all, by definition echo chambers preach to the converted. It is the undecided people who (for example) the Leave and Trump campaigns needed to reach. And from the research, it looks like they managed to do just that.”

The Authors

Bernie Hogan is a Research Fellow at the OII; his research interests lie at the intersection of social networks and media convergence.

Luciano Floridi is the OII’s Professor of Philosophy and Ethics of Information. His  research areas are the philosophy of Information, information and computer ethics, and the philosophy of technology.

Philip Howard is the OII’s Professor of Internet Studies. He investigates the impact of digital media on political life around the world.

Brent Mittelstadt is an OII Postdoc His research interests include the ethics of information handled by medical ICT, theoretical developments in discourse and virtue ethics, and epistemology of information.

Heather Ford completed her doctorate at the OII, where she studied how Wikipedia editors write history as it happens. She is now a University Academic Fellow in Digital Methods at the University of Leeds. Her forthcoming book “Fact Factories: Wikipedia’s Quest for the Sum of All Human Knowledge” will be published by MIT Press.

Helen Margetts is the OII’s Director, and Professor of Society and the Internet. She specialises in digital era government, politics and public policy, and data science and experimental methods. Her most recent book is Political Turbulence (Princeton).

Coming up! .. It’s the economy, stupid / Augmented reality and ambient fun / The platform economy / Power and development / Internet past and future / Government / Labour rights / The disconnected / Ethics / Staying critical

This was probably the nastiest Presidential election in recent memory: awash with Twitter bots and scandal, polarisation and filter bubbles, accusations of interference by Russia and the Director of the FBI, and another shock result. We have written about electoral prediction elsewhere: instead, here are five pieces that consider the interaction of social media and democracy — the problems, but also potential ways forward.

1. James Williams: The Clickbait Candidate

10 October 2016 / 2700 words / 13 minutes

“Trump is very straightforwardly an embodiment of the dynamics of clickbait: he is the logical product (though not endpoint) in the political domain of a media environment designed to invite, and indeed incentivize, relentless competition for our attention […] Like clickbait or outrage cascades, Donald Trump is merely the sort of informational packet our media environment is designed to select for.”

James Williams says that now is probably the time to have that societal conversation about the design ethics of the attention economy — because in our current media environment, attention trumps everything.

2. Sam Woolley, Philip Howard: Bots Unite to Automate the Presidential Election [Wired]

15 May 2016 / 850 words / 4 minutes

“Donald Trump understands minority communities. Just ask Pepe Luis Lopez, Francisco Palma, and Alberto Contreras […] each tweeted in support of Trump after his victory in the Nevada caucuses earlier this year. The problem is, Pepe, Francisco, and Alberto aren’t people. They’re bots.”

It’s no surprise that automated spam accounts (or bots) are creeping into election politics, say Sam Woolley and Philip Howard. Demanding bot transparency would at least help clean up social media — which, for better or worse, is increasingly where presidents get elected.

3. Phil Howard: Is Social Media Killing Democracy?

15 November 2016 / 1100 words / 5 minutes

“This is the big year for computational propaganda — using immense data sets to manipulate public opinion over social media. Both the Brexit referendum and US election have revealed the limits of modern democracy, and social media platforms are currently setting those limits […] these technologies permit too much fake news, encourage our herding instincts, and aren’t expected to provide public goods.”

Phil Howard discusses ways to address fake news, audit social algorithms, and deal with social media’s “moral pass” — social media is damaging democracy, he says, but can also be used to save it.

4. Helen Margetts: Don’t Shoot the Messenger! What part did social media play in 2016 US e­lection?

15 November 2016 / 600 words / 3 minutes

“Rather than seeing social media solely as the means by which Trump ensnared his presidential goal, we should appreciate how they can provide a wealth of valuable data to understand the anger and despair that the polls missed, and to analyse political behaviour and opinion in the times ahead.”

New social information and visibility brings change to social behaviour, says Helen Margetts — ushering in political turbulence and unpredictability. Social media made visible what could have remain a country’s dark secret (hatred of women, rampant racism, etc.), but it will also underpin any radical counter-movement that emerges in the future.

5. Helen Margetts: Of course social media is transforming politics. But it’s not to blame for Brexit and Trump

9 January 2017 / 1700 words / 8 minutes

“Even if political echo chambers were as efficient as some seem to think, there is little evidence that this is what actually shapes election results. After all, by definition echo chambers preach to the converted. It is the undecided people who (for example) the Leave and Trump campaigns needed to reach. And from the research, it looks like they managed to do just that.”

Politics is a lot messier in the social media era than it used to be, says Helen Margetts, but rather than blaming social media for undermining democracy, we should be thinking about how we can improve the (inevitably major) part that it plays.

The Authors

James Williams is an OII doctoral candidate, studying the ethics of attention and persuasion in technology design.

Sam Woolley is a Research Assistant on the OII’s Computational Propaganda project; he is interested in political bots, and the intersection of political communication and automation.

Philip Howard is the OII’s Professor of Internet Studies and PI of the Computational Propaganda project. He investigates the impact of digital media on political life around the world.

Helen Margetts is the OII’s Director, and Professor of Society and the Internet. She specialises in digital era government, politics and public policy, and data science and experimental methods. Her most recent book is Political Turbulence (Princeton).

Coming up .. Fake news and filter bubbles / It’s the economy, stupid / Augmented reality and ambient fun / The platform economy / Power and development / Internet past and future / Government / Labour rights / The disconnected / Ethics / Staying critical

#5OIIPieces

Attention has focused on echo chambers, with many arguing that social media users exist in ideological filter bubbles, narrowly focused on their own preferences, prey to fake news and political bots, reinforcing polarization and leading voters to turn away from the mainstream. Mark Zuckerberg has responded with the strange claim that his company (built on $5 billion of advertising revenue) does not influence people’s decisions.

So what role did social media play in the political events of 2016?

Political turbulence and the new populism

There is no doubt that social media has brought change to politics. From the waves of protest and unrest in response to the 2008 financial crisis, to the Arab spring of 2011, there has been a generalized feeling that political mobilization is on the rise, and that social media had something to do with it.

Our book investigating the relationship between social media and collective action, Political Turbulence, focuses on how social media allows new, “tiny acts” of political participation (liking, tweeting, viewing, following, signing petitions and so on), which turn social movement theory around. Rather than identifying with issues, forming collective identity and then acting to support the interests of that identity – or voting for a political party that supports it – in a social media world, people act first, and think about it, or identify with others later, if at all.

These tiny acts of participation can scale up to large-scale mobilizations, such as demonstrations, protests or campaigns for policy change. But they almost always don’t. The overwhelming majority (99.99%) of petitions to the UK or US governments fail to get the 100,000 signatures required for a parliamentary debate (UK) or an official response (US).

The very few that succeed do so very quickly on a massive scale (petitions challenging the Brexit and Trump votes immediately shot above 4 million signatures, to become the largest petitions in history), but without the normal organizational or institutional trappings of a social or political movement, such as leaders or political parties – the reason why so many of the Arab Spring revolutions proved disappointing.

This explosive rise, non-normal distribution and lack of organization that characterizes contemporary politics can explain why many political developments of our time seem to come from nowhere. It can help to understand the shock waves of support that brought us the Italian Five Star Movement, Podemos in Spain, Jeremy Corbyn, Bernie Sanders, and most recently Brexit and Trump – all of which have campaigned against the “establishment” and challenged traditional political institutions to breaking point.

Each successive mobilization has made people believe that challengers from outside the mainstream are viable – and that is in part what has brought us unlikely results on both sides of the Atlantic. But it doesn’t explain everything.

We’ve had waves of populism before – long before social media (indeed many have made parallels between the politics of 2016 and that of the 1930s). While claims that social media feeds are the biggest threat to democracy, leading to the “disintegration of the general will” and “polarization that drives populism” abound, hard evidence is more difficult to find.

The myth of the echo chamber

The mechanism that is most often offered for this state of events is the existence of echo chambers or filter bubbles. The argument goes that first social media platforms feed people the news that is closest to their own ideological standpoint (estimated from their previous patterns of consumption) and second, that people create their own personalized information environments through their online behaviour, selecting friends and news sources that back up their world view.

Once in these ideological bubbles, people are prey to fake news and political bots that further reinforce their views. So, some argue, social media reinforces people’s current views and acts as a polarizing force on politics, meaning that “random exposure to content is gone from our diets of news and information”.

Really? Is exposure less random than before? Surely the most perfect echo chamber would be the one occupied by someone who only read the Daily Mail in the 1930s – with little possibility of other news – or someone who just watches Fox News? Can our new habitat on social media really be as closed off as these environments, when our digital networks are so very much larger and more heterogeneous than anything we’ve had before?

Research suggests not. A recent large-scale survey (of 50,000 news consumers in 26 countries) shows how those who do not use social media on average come across news from significantly fewer different online sources than those who do. Social media users, it found, receive an additional “boost” in the number of news sources they use each week, even if they are not actually trying to consume more news. These findings are reinforced by an analysis of Facebook data, where 8.8 billion posts, likes and comments were posted through the US election.

Recent research published in Science shows that algorithms play less of a role in exposure to attitude-challenging content than individuals’ own choices and that “on average more than 20% of an individual’s Facebook friends who report an ideological affiliation are from the opposing party”, meaning that social media exposes individuals to at least some ideologically cross-cutting viewpoints: “24% of the hard content shared by liberals’ friends is cross-cutting, compared to 35% for conservatives” (the equivalent figures would be 40% and 45% if random).

In fact, companies have no incentive to create hermetically sealed (as I have heard one commentator claim) echo chambers. Most of social media content is not about politics (sorry guys) – most of that £5 billion advertising revenue does not come from political organizations. So any incentives that companies have to create echo chambers – for the purposes of targeted advertising, for example – are most likely to relate to lifestyle choices or entertainment preferences, rather than political attitudes.

And where filter bubbles do exist they are constantly shifting and sliding – easily punctured by a trending cross-issue item (anybody looking at #Election2016 shortly before polling day would have seen a rich mix of views, while having little doubt about Trump’s impending victory).

And of course, even if political echo chambers were as efficient as some seem to think, there is little evidence that this is what actually shapes election results. After all, by definition echo chambers preach to the converted. It is the undecided people who (for example) the Leave and Trump campaigns needed to reach.

And from the research, it looks like they managed to do just that. A barrage of evidence suggests that such advertising was effective in the 2015 UK general election (where the Conservatives spent 10 times as much as Labour on Facebook advertising), in the EU referendum (where the Leave campaign also focused on paid Facebook ads) and in the presidential election, where Facebook advertising has been credited for Trump’s victory, while the Clinton campaign focused on TV ads. And of course, advanced advertising techniques might actually focus on those undecided voters from their conversations. This is not the bottom-up political mobilization that fired off support for Podemos or Bernie Sanders. It is massive top-down advertising dollars.

Ironically however, these huge top-down political advertising campaigns have some of the same characteristics as the bottom-up movements discussed above, particularly sustainability. Former New York Governor Mario Cuomo’s dictum that candidates “campaign in poetry and govern in prose” may need an update. Barack Obama’s innovative campaigns of online social networks, micro-donations and matching support were miraculous, but the extent to which he developed digital government or data-driven policy-making in office was disappointing. Campaign digitally, govern in analogue might be the new mantra.

Chaotic pluralism

Politics is a lot messier in the social media era than it used to be – whether something takes off and succeeds in gaining critical mass is far more random than it appears to be from a casual glance, where we see only those that succeed.

In Political Turbulence, we wanted to identify the model of democracy that best encapsulates politics intertwined with social media. The dynamics we observed seem to be leading us to a model of “chaotic pluralism”, characterized by diversity and heterogeneity – similar to early pluralist models – but also by non-linearity and high interconnectivity, making liberal democracies far more disorganized, unstable and unpredictable than the architects of pluralist political thought ever envisaged.

Perhaps rather than blaming social media for undermining democracy, we should be thinking about how we can improve the (inevitably major) part that it plays.

Within chaotic pluralism, there is an urgent need for redesigning democratic institutions that can accommodate new forms of political engagement, and respond to the discontent, inequalities and feelings of exclusion – even anger and alienation – that are at the root of the new populism. We should be using social media to listen to (rather than merely talk at) the expression of these public sentiments, and not just at election time.

Many political institutions – for example, the British Labour Party, the US Republican Party, and the first-past-the-post electoral system shared by both countries – are in crisis, precisely because they have become so far removed from the concerns and needs of citizens. Redesign will need to include social media platforms themselves, which have rapidly become established as institutions of democracy and will be at the heart of any democratic revival.

As these platforms finally start to admit to being media companies (rather than tech companies), we will need to demand human intervention and transparency over algorithms that determine trending news; factchecking (where Google took the lead); algorithms that detect fake news; and possibly even “public interest” bots to counteract the rise of computational propaganda.

Meanwhile, the only thing we can really predict with certainty is that unpredictable things will happen and that social media will be part of our political future.

Discussing the echoes of the 1930s in today’s politics, the Wall Street Journal points out how Roosevelt managed to steer between the extremes of left and right because he knew that “public sentiments of anger and alienation aren’t to be belittled or dismissed, for their causes can be legitimate and their consequences powerful”. The path through populism and polarization may involve using the opportunity that social media presents to listen, understand and respond to these sentiments.

This piece draws on research from Political Turbulence: How Social Media Shape Collective Action (Princeton University Press, 2016), by Helen Margetts, Peter John, Scott Hale and Taha Yasseri.

It is cross-posted from the World Economic Forum, where it was first published on 22 December 2016.

The parallels between data and oil break down quickly once you start considering practicalities such as measuring and valuing data. Data is, after all, a highly heterogeneous good whose value is context-specific — very different from a commodity such as oil that can be measured and valued by the barrel. But even if the value of data can’t simply be metered and taxed, are there other ways in which the data economy could be more directly aligned with social good?

Data-intensive industries already contribute to social good by producing useful services and paying taxes on their profits (though some pay regrettably little). But are there ways in which the data economy could directly finance global causes such as climate change prevention, poverty alleviation and infrastructure? Such mechanisms should not just arbitrarily siphon off money from industry, but also contribute value back to the data economy by correcting market failures and investment gaps. The potential impacts are significant: estimates value the data economy at around seven percent of GDP in rich industrialised countries, or around ten times the value of the United Nations development aid spending goal.

Here’s where “data financing” comes in. It’s a term we coined that’s based on innovative financing, a concept increasingly used in the philanthropical world. Innovative financing refers to initiatives that seek to unlock private capital for the sake of global development and socially beneficial projects, which face substantial funding gaps globally. Since government funding towards addressing global challenges is not growing, the proponents of innovative financing are asking how else these critical causes could be funded. An existing example of innovative financing is the UNITAID air ticket levy used to advance global health.

Data financing, then, is a subset of innovative financing that refers to mechanisms that attempt to redirect a slice of the value created in the global data economy towards broader social objectives. For instance, a Global Internet Subsidy funded by large Internet companies could help to educate and and build infrastructure in the world’s marginalized regions, in the long run also growing the market for Internet companies’ services. But such a model would need well-designed governance mechanisms to avoid the pitfalls of current Internet subsidization initiatives, which risk failing because of well-founded concerns that they further entrench Internet giants’ dominance over emerging digital markets.

Besides the Global Internet Subsidy, other data financing models examined in the report are a Privacy Insurance for personal data processing, a Shared Knowledge Duty payable by businesses profiting from open and public data, and an Attention Levy to disincentivise intrusive marketing. Many of these have been considered before, and they come with significant economic, legal, political, and technical challenges. Our report considers these challenges in turn, assesses the feasibility of potential solutions, and presents rough estimates of potential financial impacts.

Some of the prevailing business models of the data economy — provoking users’ attention, extracting their personal information, and monetizing it through advertising — are more or less taken for granted today. But they are something of a historical accident, an unanticipated corollary to some of the technical and political decisions made early in the Internet’s design. Certainly they are not any inherent feature of data as such. Although our report focuses on the technical, legal, and political practicalities of the idea of data financing, it also invites a careful reader to question some of the accepted truths on how a data-intensive economy could be organized, and what business models might be possible.

Read the report: Lehdonvirta, V., Mittelstadt, B. D., Taylor, G., Lu, Y. Y., Kadikov, A., and Margetts, H. (2016) Data Financing for Global Good: A Feasibility Study. University of Oxford: Oxford Internet Institute.

A new article by Brent Mittlestadt explores the challenges of enforcing a political right to transparency in content personalization systems. Firstly, he explains the value of transparency to political discourse and suggests how content personalization systems undermine open exchange of ideas and evidence among participants: at a minimum, personalization systems can undermine political discourse by curbing the diversity of ideas that participants encounter. Second, he explores work on the detection of discrimination in algorithmic decision making, including techniques of algorithmic auditing that service providers can employ to detect political bias. Third, he identifies several factors that inhibit auditing and thus indicate reasonable limitations on the ethical duties incurred by service providers — content personalization systems can function opaquely and be resistant to auditing because of poor accessibility and interpretability of decision-making frameworks. Finally, Brent concludes with reflections on the need for regulation of content personalization systems.

He notes that no matter how auditing is pursued, standards to detect evidence of political bias in personalized content are urgently required. Methods are needed to routinely and consistently assign political value labels to content delivered by personalization systems. This is perhaps the most pressing area for future work—to develop practical methods for algorithmic auditing.

The right to transparency in political discourse may seem unusual and farfetched. However, standards already set by the U.S. Federal Communication Commission’s fairness doctrine — no longer in force — and the British Broadcasting Corporation’s fairness principle both demonstrate the importance of the idealized version of political discourse described here. Both precedents promote balance in public political discourse by setting standards for delivery of politically relevant content. Whether it is appropriate to hold service providers that use content personalization systems to a similar standard remains a crucial question.

Read the full article: Mittelstadt, B. (2016) Auditing for Transparency in Content Personalization Systems. International Journal of Communication 10(2016), 4991–5002.

We caught up with Brent to explore the broader implications of the study:

Ed: We basically accept that the tabloids will be filled with gross bias, populism and lies (in order to sell copy) — and editorial decisions are not generally transparent to us. In terms of their impact on the democratic process, what is the difference between the editorial boardroom and a personalising social media algorithm?

Brent: There are a number of differences. First, although not necessarily transparent to the public, one hopes that editorial boardrooms are at least transparent to those within the news organisations. Editors can discuss and debate the tone and factual accuracy of their stories, explain their reasoning to one another, reflect upon the impact of their decisions on their readers, and generally have a fair debate about the merits and weaknesses of particular content.

This is not the case for a personalising social media algorithm; those working with the algorithm inside a social media company are often unable to explain why the algorithm is functioning in a particular way, or determined a particular story or topic to be ‘trending’ or displayed to particular users, while others are not. It is also far more difficult to ‘fact check’ algorithmically curated news; a news item can be widely disseminated merely by many users posting or interacting with it, without any purposeful dissemination or fact checking by the platform provider.

Another big difference is the degree to which users can be aware of the bias of the stories they are reading. Whereas a reader of The Daily Mail or The Guardian will have some idea of the values of the paper, the same cannot be said of platforms offering algorithmically curated news and information. The platform can be neutral insofar as it disseminates news items and information reflecting a range of values and political viewpoints. A user will encounter items reflecting her particular values (or, more accurately, her history of interactions with the platform and the values inferred from them), but these values, and their impact on her exposure to alternative viewpoints, may not be apparent to the user.

Ed: And how is content “personalisation” different to content filtering (e.g. as we see with the Great Firewall of China) that people get very worked up about? Should we be more worried about personalisation?

Brent: Personalisation and filtering are essentially the same mechanism; information is tailored to a user or users according to some prevailing criteria. One difference is whether content is merely infeasible to access, or technically inaccessible. Content of all types will typically still be accessible in principle when personalisation is used, but the user will have to make an effort to access content that is not recommended or otherwise given special attention. Filtering systems, in contrast, will impose technical measures to make particular content inaccessible from a particular device or geographical area.

Another difference is the source of the criteria used to set the visibility of different types of content. In the case of personalisation, these criteria are typically based on the users (inferred) interests, values, past behaviours and explicit requests. Critically, these values are not necessarily apparent to the user. For filtering, criteria are typically externally determined by a third party, often a government. Some types of information are set off limits, according to the prevailing values of the third party. It is the imposition of external values, which limit the capacity of users to access content of their choosing, which often causes an outcry against filtering and censorship.

Importantly, the two mechanisms do not necessarily differ in terms of the transparency of the limiting factors or rules to users. In some cases, such as the recently proposed ban in the UK of adult websites that do not provide meaningful age verification mechanisms, the criteria that determine whether sites are off limits will be publicly known at a general level. In other cases, and especially with personalisation, the user inside the ‘filter bubble’ will be unaware of the rules that determine whether content is (in)accessible. And it is not always the case that the platform provider intentionally keeps these rules secret. Rather, the personalisation algorithms and background analytics that determine the rules can be too complex, inaccessible or poorly understood even by the provider to give the user any meaningful insight.

Ed: Where are these algorithms developed: are they basically all proprietary? i.e. how would you gain oversight of massively valuable and commercially sensitive intellectual property?

Brent: Personalisation algorithms tend to be proprietary, and thus are not normally open to public scrutiny in any meaningful sense. In one sense this is understandable; personalisation algorithms are valuable intellectual property. At the same time the lack of transparency is a problem, as personalisation fundamentally affects how users encounter and digest information on any number of topics. As recently argued, it may be the case that personalisation of news impacts on political and democratic processes. Existing regulatory mechanisms have not been successful in opening up the ‘black box’ so to speak.

It can be argued, however, that legal requirements should be adopted to require these algorithms to be open to public scrutiny due to the fundamental way they shape our consumption of news and information. Oversight can take a number of forms. As I argue in the article, algorithmic auditing is one promising route, performed both internally by the companies themselves, and externally by a government agency or researchers. A good starting point would be for the companies developing and deploying these algorithms to extend their cooperation with researchers, thereby allowing a third party to examine the effects these systems are having on political discourse, and society more broadly.

Ed: By “algorithm audit” — do you mean examining the code and inferring what the outcome might be in terms of bias, or checking the outcome (presumably statistically) and inferring that the algorithm must be introducing bias somewhere? And is it even possible to meaningfully audit personalisation algorithms, when they might rely on vast amounts of unpredictable user feedback to train the system?

Brent: Algorithm auditing can mean both of these things, and more. Audit studies are a tool already in use, whereby human participants introduce different inputs into a system, and examine the effect on the system’s outputs. Similar methods have long been used to detect discriminatory hiring practices, for instance. Code audits are another possibility, but are generally prohibitive due to problems of access and complexity. Also, even if you can access and understand the code of an algorithm, that tells you little about how the algorithm performs in practice when given certain input data. Both the algorithm and input data would need to be audited.

Alternatively, auditing can assess just the outputs of the algorithm; recent work to design mechanisms to detect disparate impact and discrimination, particularly in the Fairness, Accountability and Transparency in Machine Learning (FAT-ML) community, is a great example of this type of auditing. Algorithms can also be designed to attempt to prevent or detect discrimination and other harms as they occur. These methods are as much about the operation of the algorithm, as they are about the nature of the training and input data, which may itself be biased. In short, auditing is very difficult, but there are promising avenues of research and development. Once we have reliable auditing methods, the next major challenge will be to tailor them to specific sectors; a one-size-meets-all approach to auditing is not on the cards.

Ed: Do you think this is a real problem for our democracy? And what is the solution if so?

Brent: It’s difficult to say, in part because access and data to study the effects of personalisation systems are hard to come by. It is one thing to prove that personalisation is occurring on a particular platform, or to show that users are systematically displayed content reflecting a narrow range of values or interests. It is quite another to prove that these effects are having an overall harmful effect on democracy. Digesting information is one of the most basic elements of social and political life, so any mechanism that fundamentally changes how information is encountered should be subject to serious and sustained scrutiny.

Assuming personalisation actually harms democracy or political discourse, mitigating its effects is quite a different issue. Transparency is often treated as the solution, but merely opening up algorithms to public and individual scrutiny will not in itself solve the problem. Information about the functionality and effects of personalisation must be meaningful to users if anything is going to be accomplished.

At a minimum, users of personalisation systems should be given more information about their blind spots, about the types of information they are not seeing, or where they lie on the map of values or criteria used by the system to tailor content to users. A promising step would be proactively giving the user some idea of what the system thinks it knows about them, or how they are being classified or profiled, without the user first needing to ask.

Brent Mittelstadt was talking to blog editor David Sutcliffe.

In their article published in EPJ Data Science, Taha Yasseri and Jonathan Bright develop a theoretically informed prediction of election results from socially generated data combined with an understanding of the social processes through which the data are generated. They can thereby explore the predictive power of socially generated data while enhancing theory about the relationship between socially generated data and real world outcomes. Their particular focus is on the readership statistics of politically relevant Wikipedia articles (such as those of individual political parties) in the time period just before an election.

By applying these methods to a variety of different European countries in the context of the 2009 and 2014 European Parliament elections they firstly show that the relative change in number of page views to the general Wikipedia page on the election can offer a reasonable estimate of the relative change in election turnout at the country level. This supports the idea that increases in online information seeking at election time are driven by voters who are considering voting.

Second, they show that a theoretically informed model based on previous national results, Wikipedia page views, news media mentions, and basic information about the political party in question can offer a good prediction of the overall vote share of the party in question. Third, they present a model for predicting change in vote share (i.e., voters swinging towards and away from a party), showing that Wikipedia page-view data provide an important increase in predictive power in this context.

This relationship is exaggerated in the case of newer parties — consistent with the idea that voters don’t seek information uniformly about all parties at election time. Rather, they behave like ‘cognitive misers’, being more likely to seek information on new political parties with which they do not have previous experience and being more likely to seek information only when they are actually changing the way they vote.

In contrast, there was no evidence of a ‘media effect’: there was little correlation between news media mentions and overall Wikipedia traffic patterns. Indeed, the news media and Wikipedia appeared to be biased towards different things: with the news favouring incumbent parties, and Wikipedia favouring new ones.

Read the full article: Yasseri, T. and Bright, J. (2016) Wikipedia traffic data and electoral prediction: towards theoretically informed models. EPJ Data Science. 5 (1).

We caught up with the authors to explore the implications of the work.

Ed: Wikipedia represents a vast amount of not just content, but also user behaviour data. How did you access the page view stats — but also: is anyone building dynamic visualisations of Wikipedia data in real time?

Taha and Jonathan: Wikipedia makes its page view data available for free (in the same way as it makes all of its information available!). You can find the data here, along with some visualisations

Ed: Why did you use Wikipedia data to examine election prediction rather than (the I suppose the more fashionable) Twitter? How do they compare as data sources?

Taha and Jonathan: One of the big problems with using Twitter to predict things like elections is that contributing on social media is a very public thing and people are quite conscious of this. For example, some parties are seen as unfashionable so people might not make their voting choice explicit. Hence overall social media might seem to be saying one thing whereas actually people are thinking another.

By contrast, looking for information online on a website like Wikipedia is an essentially private activity so there aren’t these social biases. In other words, on Wikipedia we can directly have access to transactional data on what people do, rather than what they say or prefer to say.

Ed: How did these results and findings compare with the social media analysis done as part of our UK General Election 2015 Election Night Data Hack? (long title..)

Taha and Jonathan: The GE2015 data hack looked at individual politicians. We found that having a Wikipedia page is becoming increasingly important — over 40% of Labour and Conservative Party candidates had an individual Wikipedia page. We also found that this was highly correlated with Twitter presence — being more active on one network also made you more likely to be active on the other one. And we found some initial evidence that social media reaction was correlated with votes, though there is a lot more work to do here!

Ed: Can you see digital social data analysis replacing (or maybe just complementing) opinion polling in any meaningful way? And what problems would need to be addressed before that happened: e.g. around representative sampling, data cleaning, and weeding out bots?

Taha and Jonathan: Most political pundits are starting to look at a range of indicators of popularity — for example, not just voting intention, but also ratings of leadership competence, economic performance, etc. We can see good potential for social data to become part of this range of popularity indicator. However we don’t think it will replace polling just yet; the use of social media is limited to certain demographics. Also, the data collected from social media are often very shallow, not allowing for validation. In the case of Wikipedia, for example, we only know how many times each page is viewed, but we don’t know by how many people and from where.

Ed: You do a lot of research with Wikipedia data — has that made you reflect on your own use of Wikipedia?

Taha and Jonathan: It’s interesting to think about this activity of getting direct information about politicians — it’s essentially a new activity, something you couldn’t do in the pre-digital age. I know that I personally [Jonathan] use it to find out things about politicians and political parties — it would be interesting to know more about why other people are using it as well. This could have a lot of impacts. One thing Wikipedia has is a really long memory, in a way that other means of getting information on politicians (such as newspapers) perhaps don’t. We could start to see this type of thing becoming more important in electoral politics.

[Taha] .. since my research has been mostly focused on Wikipedia edit wars between human and bot editors, I have naturally become more cautious about the information I find on Wikipedia. When it comes to sensitive topics, sach as politics, Wikipedia is a good point to start, but not a great point to end the search!

Taha Yasseri and Jonathan Bright were talking to blog editor David Sutcliffe.

I recently gave a talk at the Alan Turing Institute (ATI) under the title The Problem of Governance in Distributed Ledger Technologies. The starting point of my talk was that it is frequently posited that blockchain technologies will “revolutionize industries that rely on digital record keeping”, such as financial services and government. In the talk I applied elementary institutional economics to examine what blockchain technologies really do in terms of economic organization, and what problems this gives rise to. In this essay I present an abbreviated version of the argument. Alternatively you can watch a video of the talk below.

[youtube https://www.youtube.com/watch?v=eNrzE_UfkTw&w=640&h=360]

First, it is necessary to note that there is quite a bit of confusion as to what exactly is meant by a blockchain. When people talk about “the” blockchain, they often refer to the Bitcoin blockchain, an ongoing ledger of transactions started in 2009 and maintained by the approximately 5,000 computers that form the Bitcoin peer-to-peer network. The term blockchain can also be used to refer to other instances or forks of the same technology (“a” blockchain). The term “distributed ledger technology” (DLT) has also gained currency recently as a more general label for related technologies.

In each case, I think it is fair to say that the reason that so many people are so excited about blockchain today is not the technical features as such. In terms of performance metrics like transactions per second, existing blockchain technologies are in many ways inferior to more conventional technologies. This is frequently illustrated with the point that the Bitcoin network is limited by design to process at most approximately seven transactions per second, whereas the Visa payment network has a peak capacity of 56,000 transactions per second. Other implementations may have better performance, and on some other metrics blockchain technologies can perhaps beat more conventional technologies. But technical performance is not why so many people think blockchain is revolutionary and paradigm-shifting.

The reason that blockchain is making waves is that it promises to change the very way economies are organized: to eliminate centralized third parties. Let me explain what this means in theoretical terms. Many economic transactions, such as long-distance trade, can be modeled as a game of Prisoners’ Dilemma. The buyer and the seller can either cooperate (send the shipment/payment as promised) or defect (not send the shipment/payment). If the buyer and the seller don’t trust each other, then the equilibrium solution is that neither player cooperates and no trade takes place. This is known as the fundamental problem of cooperation.

There are several classic solutions to the problem of cooperation. One is reputation. In a community of traders where members repeatedly engage in exchange, any trader who defects (fails to deliver on a promise) will gain a negative reputation, and other traders will refuse to trade with them out of self-interest. This threat of exclusion from the community acts as a deterrent against defection, and the equilibrium under certain conditions becomes that everyone will cooperate.

Reputation is only a limited solution, however. It only works within communities where reputational information spreads effectively, and traders may still defect if the payoff from doing so is greater than the loss of future trade. Modern large-scale market economies where people trade with strangers on a daily basis are only possible because of another solution: third-party enforcement. In particular, this means state-enforced contracts and bills of exchange enforced by banks. These third parties in essence force parties to cooperate and to follow through with their promises.

Besides trade, another example of the problem of cooperation is currency. Currency can be modeled as a multiplayer game of Prisoners’ Dilemma. Traders collectively have an interest in maintaining a stable currency, because it acts as a lubricant to trade. But each trader individually has an interest in debasing the currency, in the sense of paying with fake money (what in blockchain-speak is referred to as double spending). Again the classic solution to this dilemma is third-party enforcement: the state polices metal currencies and punishes counterfeiters, and banks control ledgers and prevent people from spending money they don’t have.

So third-party enforcement is the dominant model of economic organization in today’s market economies. But it’s not without its problems. The enforcer is in a powerful position in relation to the enforced: banks could extract exorbitant fees, and states could abuse their power by debasing the currency, illegitimately freezing assets, or enforcing contracts in unfair ways. One classic solution to the problems of third-party enforcement is competition. Bank fees are kept in check by competition: the enforced can switch to another enforcer if the fees get excessive.

But competition is not always a viable solution: there is a very high cost to switching to another state (i.e. becoming a refugee) if your state starts to abuse its power. Another classic solution is accountability: democratic institutions that try to ensure the enforcer acts in the interest of the enforced. For instance, the interbank payment messaging network SWIFT is a cooperative society owned by its member banks. The members elect a Board of Directors that is the highest decision making body in the organization. This way, they attempt to ensure that SWIFT does not try to extract excessive fees from the member banks or abuse its power against them. Still, even accountability is not without its problems, since it comes with the politics of trying to reconcile different members’ diverging interests as best as possible.

Into this picture enters blockchain: a technology where third-party enforcers are replaced with a distributed network that enforces the rules. It can enforce contracts, prevent double spending, and cap the size of the money pool all without participants having to cede power to any particular third party who might abuse the power. No rent-seeking, no abuses of power, no politics — blockchain technologies can be used to create “math-based money” and “unstoppable” contracts that are enforced with the impartiality of a machine instead of the imperfect and capricious human bureaucracy of a state or a bank. This is why so many people are so excited about blockchain: its supposed ability change economic organization in a way that transforms dominant relationships of power.

Unfortunately this turns out to be a naive understanding of blockchain, and the reality is inevitably less exciting. Let me explain why. In economic organization, we must distinguish between enforcing rules and making rules. Laws are rules enforced by state bureaucracy and made by a legislature. The SWIFT Protocol is a set of rules enforced by SWIFTNet (a centralized computational system) and made, ultimately, by SWIFT’s Board of Directors. The Bitcoin Protocol is a set of rules enforced by the Bitcoin Network (a distributed network of computers) made by — whom exactly? Who makes the rules matters at least as much as who enforces them. Blockchain technology may provide for completely impartial rule-enforcement, but that is of little comfort if the rules themselves are changed. This rule-making is what we refer to as governance.

Using Bitcoin as an example, the initial versions of the protocol (ie. the rules) were written by the pseudonymous Satoshi Nakamoto, and later versions are released by a core development team. The development team is not autocratic: a complex set of social and technical entanglements means that other people are also influential in how Bitcoin’s rules are set; in particular, so-called mining pools, headed by a handful of individuals, are very influential. The point here is not to attempt to pick apart Bitcoin’s political order; the point is that Bitcoin has not in any sense eliminated human politics; humans are still very much in charge of setting the rules that the network enforces.

There is, however, no formal process for how governance works in Bitcoin, because for a very long time these politics were not explicitly recognized, and many people don’t recognize them, preferring instead the idea that Bitcoin is purely “math-based money” and that all the developers are doing is purely apolitical plumbing work. But what has started to make this position untenable and Bitcoin’s politics visible is the so-called “block size debate” — a big disagreement between factions of the Bitcoin community over the future direction of the rules. Different stakeholders have different interests in the matter, and in the absence of a robust governance mechanism that could reconcile between the interests, this has resulted in open “warfare” between the camps over social media and discussion forums.

Will competition solve the issue? Multiple “forks” of the Bitcoin protocol have emerged, each with slightly different rules. But network economics teaches us that competition does not work well at all in the presence of strong network effects: everyone prefers to be in the network where other people are, even if its rules are not exactly what they would prefer. Network markets tend to tip in favour of the largest network. Every fork/split diminishes the total value of the system, and those on the losing side of a fork may eventually find their assets worthless.

If competition doesn’t work, this leaves us with accountability. There is no obvious path how Bitcoin could develop accountable governance institutions. But other blockchain projects, especially those that are gaining some kind of commercial or public sector legitimacy, are designed from the ground up with some level of accountable governance. For instance, R3 is a firm that develops blockchain technology for use in the financial services industry. It has enrolled a consortium of banks to guide the effort, and its documents talk about the “mandate” it has from its “member banks”. Its governance model thus sounds a lot like the beginnings of something like SWIFT. Another example is RSCoin, designed by my ATI colleagues George Danezis and Sarah Meiklejohn, which is intended to be governed by a central bank.

Regardless of the model, my point is that blockchain technologies cannot escape the problem of governance. Whether they recognize it or not, they face the same governance issues as conventional third-party enforcers. You can use technologies to potentially enhance the processes of governance (eg. transparency, online deliberation, e-voting), but you can’t engineer away governance as such. All this leads me to wonder how revolutionary blockchain technologies really are. If you still rely on a Board of Directors or similar body to make it work, how much has economic organization really changed?

And this leads me to my final point, a provocation: once you address the problem of governance, you no longer need blockchain; you can just as well use conventional technology that assumes a trusted central party to enforce the rules, because you’re already trusting somebody (or some organization/process) to make the rules. I call this blockchain’s ‘governance paradox’: once you master it, you no longer need it. Indeed, R3’s design seems to have something called “uniqueness services”, which look a lot like trusted third-party enforcers (though this isn’t clear from the white paper). RSCoin likewise relies entirely on trusted third parties. The differences to conventional technology are no longer that apparent.

Perhaps blockchain technologies can still deliver better technical performance, like better availability and data integrity. But it’s not clear to me what real changes to economic organization and power relations they could bring about. I’m very happy to be challenged on this, if you can point out a place in my reasoning where I’ve made an error. Understanding grows via debate. But for the time being, I can’t help but be very skeptical of the claims that blockchain will fundamentally transform the economy or government.

The governance of DLTs is also examined in this report chapter that I coauthored earlier this year:

Lehdonvirta, V. & Robleh, A. (2016) Governance and Regulation. In: M. Walport (ed.), Distributed Ledger Technology: Beyond Blockchain. London: UK Government Office for Science, pp. 40-45.

This is the big year for computational propaganda — using immense data sets to manipulate public opinion over social media. Both the Brexit referendum and US election have revealed the limits of modern democracy, and social media platforms are currently setting those limits.

Platforms like Twitter and Facebook now provide a structure for our political lives. We’ve always relied on many kinds of sources for our political news and information. Family, friends, news organizations, charismatic politicians certainly predate the internet. But whereas those are sources of information, social media now provides the structure for political conversation. And the problem is that these technologies permit too much fake news, encourage our herding instincts, and aren’t expected to provide public goods.

First, social algorithms allow fake news stories from untrustworthy sources to spread like wildfire over networks of family and friends. Many of us just assume that there is a modicum of truth-in-advertising. We expect this from advertisements for commercial goods and services, but not from politicians and political parties. Occasionally a political actor gets punished for betraying the public trust through their misinformation campaigns. But in the United States “political speech” is completely free from reasonable public oversight, and in most other countries the media organizations and public offices for watching politicians are legally constrained, poorly financed, or themselves untrustworthy. Research demonstrates that during the campaigns for Brexit and the U.S. presidency, large volumes of fake news stories, false factoids, and absurd claims were passed over social media networks, often by Twitter’s highly automated accounts and Facebook’s algorithms.

Second, social media algorithms provide very real structure to what political scientists often call “elective affinity” or “selective exposure”. When offered the choice of who to spend time with or which organizations to trust, we prefer to strengthen our ties to the people and organizations we already know and like. When offered a choice of news stories, we prefer to read about the issues we already care about, from pundits and news outlets we’ve enjoyed in the past. Random exposure to content is gone from our diets of news and information. The problem is not that we have constructed our own community silos — humans will always do that. The problem is that social media networks take away the random exposure to new, high-quality information.

This is not a technological problem. We are social beings and so we will naturally look for ways to socialize, and we will use technology to socialize each other. But technology could be part of the solution. A not-so-radical redesign might occasionally expose us to new sources of information, or warn us when our own social networks are getting too bounded.

The third problem is that technology companies, including Facebook and Twitter, have been given a “moral pass” on the obligations we hold journalists and civil society groups to.

In most democracies, the public policy and exit polling systems have been broken for a decade. Many social scientists now find that big data, especially network data, does a better job of revealing public preferences than traditional random digit dial systems. So Facebook actually got a moral pass twice this year. Their data on public opinion would have certainly informed the Brexit debate, and their data on voter preferences would certainly have informed public conversation during the US election.

Facebook has run several experiments now, published in scholarly journals, demonstrating that they have the ability to accurately anticipate and measure social trends. Whereas journalists and social scientists feel an obligation to openly analyze and discuss public preferences, we do not expect this of Facebook. The network effects that clearly were unmeasured by pollsters were almost certainly observable to Facebook. When it comes to news and information about politics, or public preferences on important social questions, Facebook has a moral obligation to share data and prevent computational propaganda. The Brexit referendum and US election have taught us that Twitter and Facebook are now media companies. Their engineering decisions are effectively editorial decisions, and we need to expect more openness about how their algorithms work. And we should expect them to deliberate about their editorial decisions.

There are some ways to fix these problems. Opaque software algorithms shape what people find in their news feeds. We’ve all noticed fake news stories (often called clickbait), and while these can be an entertaining part of using the internet, it is bad when they are used to manipulate public opinion. These algorithms work as “bots” on social media platforms like Twitter, where they were used in both the Brexit and US presidential campaign to aggressively advance the case for leaving Europe and the case for electing Trump. Similar algorithms work behind the scenes on Facebook, where they govern what content from your social networks actually gets your attention.

So the first way to strengthen democratic practices is for academics, journalists, policy makers and the interested public to audit social media algorithms. Was Hillary Clinton really replaced by an alien in the final weeks of the 2016 campaign? We all need to be able to see who wrote this story, whether or not it is true, and how it was spread. Most important, Facebook should not allow such stories to be presented as news, much less spread. If they take ad revenue for promoting political misinformation, they should face the same regulatory punishments that a broadcaster would face for doing such a public disservice.

The second problem is a social one that can be exacerbated by information technologies. This means it can also be mitigated by technologies. Introducing random news stories and ensuring exposure to high quality information would be a simple — and healthy — algorithmic adjustment to social media platforms. The third problem could be resolved with moral leadership from within social media firms, but a little public policy oversight from elections officials and media watchdogs would help. Did Facebook see that journalists and pollsters were wrong about public preferences? Facebook should have told us if so, and shared that data.

Social media platforms have provided a structure for spreading around fake news, we users tend to trust our friends and family, and we don’t hold media technology firms accountable for degrading our public conversations. The next big thing for technology evolution is the Internet of Things, which will generate massive amounts of data that will further harden these structures. Is social media damaging democracy? Yes, but we can also use social media to save democracy.

Is this really the case? At first glance, the ingredients of the Trump victory — as for Brexit — seem remarkably traditional. The Trump campaign spent more on physical souvenirs than on field data, more on Make America Great Again hats (made in China) than on polling. The Daily Mail characterisation of judges as Enemies of the People after their ruling that the triggering of Article 50 must be discussed in parliament seemed reminiscent of the 1930s. Likewise, US crowds chanting ‘Lock her up’, like lynch mobs, seemed like ghastly reminders of a pre-democratic era.

Clearly social media were a big part of the 2016 election, used heavily by the candidates themselves, and generating 8.8 billion posts, likes and commentson Facebook alone. Social media also make visible what in an earlier era could remain a country’s dark secret — hatred of women (through death and rape threats and trolling of female politicians in both the UK and US), and rampant racism.

This visibility, society’s new self-awareness, brings change to political behaviour. Social media provide social information about what other people are doing: viewing, following, liking, sharing, tweeting, joining, supporting and so on. This social information is the driver behind the political turbulence that characterises politics today. Those rustbelt Democrats feeling abandoned by the system saw on social media that they were not alone — that other people felt the same way, and that Trump was viable as a candidate. For a woman drawn towards the Trump agenda but feeling tentative, the hashtag #WomenForTrump could reassure her that there were like-minded people she could identify with. Decades of social science research shows information about the behaviour of others influences how groups behave and now it is driving the unpredictability of politics, bringing us Trump, Brexit, Corbyn, Sanders and unexpected political mobilisation across the world.

These are not echo chambers. As recent research shows, people are exposed to cross-cutting discourse on social media, across ever larger and more heterogeneous social networks. While the hypothetical #WomenForTrump tweeter or Facebook user will see like-minded behaviour, she will also see a peppering of social information showing people using opposing hashtags like #ImWithHer, or (post-election) #StillWithHer. It could be argued that a better example of an ‘echo chamber’ would be a regular Daily Mail reader or someone who only watched Fox News.

The mainstream media loved Trump: his controversial road-crash views sold their newspapers and advertising. Social media take us out of that world. They are relatively neutral in their stance on content, giving no particular priority to extreme or offensive views as on their platforms, the numbers are what matter.

Rather than seeing social media solely as the means by which Trump ensnared his presidential goal, we should appreciate how they can provide a wealth of valuable data to understand the anger and despair that the polls missed, and to analyse political behaviour and opinion in the times ahead. Social media can also shine the light of transparency on the workings of a Trump administration, as they did on his campaign. They will be critical for building networks of solidarity to confront the intolerance, sexism and racism stirred up during this bruising campaign. And social media will underpin any radical counter-movement that emerges in the coming years.

Helen Margetts is the author of Political Turbulence: How Social Media Shape Collective Action and thanks her co-authors Peter John, Scott Haleand Taha Yasseri.

Negative interactions are also rarely explicitly declared and recorded, making them hard for scientists to study. In their new article on the structural and temporal features of negative interactions in the community, Milena Tsvetkova, Ruth García-Gavilanes and Taha Yasseri use complex network methods to analyze patterns in the timing and configuration of reverts of article edits to Wikipedia. In large online collaboration communities like Wikipedia, users sometimes undo or downrate contributions made by other users; most often to maintain and improve the collaborative project. However, it is also possible that these actions are social in nature, with previous research acknowledging that they could also imply negative social interactions.

The authors find evidence that Wikipedia editors systematically revert the same person, revert back their reverter, and come to defend a reverted editor. However, they don’t find evidence that editors “pay forward” a revert, coordinate with others to revert an editor, or revert different editors serially. These interactions can be related to the status of the editors. Even though the individual reverts might not necessarily be negative social interactions, their analysis points to the existence of certain patterns of negative social dynamics within the editorial community. Some of these patterns have not been previously explored and certainly carry implications for Wikipedia’s own knowledge collection practices — and can also be applied to other large-scale collaboration networks to identify the existence of negative social interactions.

Read the full article: Milena Tsvetkova, Ruth García-Gavilanes and Taha Yasseri (2016) Dynamics of Disagreement: Large-Scale Temporal Network Analysis Reveals Negative Interactions in Online Collaboration. Scientific Reports 6 doi:10.1038/srep36333

We caught up with the authors to explore the implications of the work.

Ed: You find that certain types of negative social interactions and status considerations interfere with knowledge production on Wikipedia. What could or should Wikipedia do about it — or is it not actually a significant problem?

Taha: We believe it is an issue to consider. While the Wikipedia community might not be able to directly cope with it, as negative social interactions are intrinsic to human societies, an important consequence of our report would be to use the information in Wikipedia articles with extra care — and also to bear in mind that Wikipedia content might carry more subjectivity compared to a professionally written encyclopaedia.

Ed: Does reverting behaviour correlate with higher quality articles (i.e. with a lot of editorial attention) or simply with controversial topics — i.e. do you see reverting behaviour as generally a positive or negative thing?

Taha: In a different project we looked at the correlation between controversy and quality. We observed that controversy, up to a certain level, is correlated with higher quality of the article, specifically as far as the completeness of the article is concerned. However, the articles with very high scores of controversy, started to show less quality. In short, a certain amount of controversy helps the articles to become more complete, but too much controversy is a bad sign.

Ed: Do you think your results say more about the structure of Wikipedia, the structure of crowds, or about individuals?

Taha: Our results shed light on some of the most fundamental patterns in human behavior. It is one of the few examples in which a large dataset of negative interactions is analysed and the dynamics of negativity are studied. In this sense, this article is more about human behavior in interaction with other community members in a collaborative environment. However, because our data come from Wikipedia, I believe there are also lessons to be learnt about Wikipedia itself.

Ed: You note that by focusing on the macro-level you miss the nuanced understanding that thick ethnographic descriptions can produce. How common is it for computational social scientists to work with ethnographers? What would you look at if you were to work with ethnographers on this project?

Taha: One of the drawbacks in big data analysis in computational social science is the small depth of the analysis. We are lacking any demographic information about the individuals that we study. We can draw conclusions about the community of Wikipedia editors in a certain language, but that is by no means specific enough. An ethnographic approach, which would benefit our research tremendously, would go deeper in analyzing individuals and studying the features and attributes which lead to certain behavior. For example, we report, at a high level, that “status” determines editors’ actions to a good extend, but of course the mechanisms behind this observation can only be explained based on ethnographic analysis.

Ed: I guess Wikipedia (whether or not unfairly) is commonly associated with edit wars — while obviously also being a gigantic success: how about other successful collaborative platforms — how does Wikipedia differ from Zooniverse, for example?

Taha: There is no doubt that Wikipedia is a huge success and probably the largest collaborative project in the history of mankind. Our research mostly focuses on its dark side, but it does not question its success and value. Compared to other collaborative projects, such as Zooniverse, the main difference is in the management model. Wikipedia is managed and run by the community of editors. Very little top-down management is employed in Wikipedia. Whereas in Zooniverse for instance, the overall structure of the project is designed by a few researchers and the crowd can only act within a pre-determined framework. For more of these sort of comparisons, I suggest to look at our HUMANE project, in which we provide a typology and comparison for a wide range of Human-Machine Networks.

Ed: Finally — do you edit Wikipedia? And have you been on the receiving end of reverts yourself?

Taha: I used to edit Wikipedia much more. And naturally I have had my own share of reverts, at both ends!

Taha Yasseri was talking to blog editor David Sutcliffe.

The authors surveyed 19,000 men and women from nationally representative samples from the UK, the United States, Canada and Germany, with over half saying they had played internet games recently. Out of the total sample, 1% of young adults (18-24 year olds) and 0.5% of the general population (aged 18 or older) reported symptoms linking play to possible addictive behaviour — less than half of recently reported rates for gambling.

They warn that researchers studying the potential “darker sides” of Internet-based games must be cautious. Extrapolating from their data, as many as a million American adults might meet the proposed DSM-5 criteria for addiction to online games — representing a large cohort of people struggling with what could be clinically dysregulated behavior. However, because the authors found no evidence supporting a clear link to clinical outcomes, they warn that more evidence for clinical and behavioral effects is needed before concluding that this is a legitimate candidate for inclusion in future revisions of the DSM. If adopted, Internet gaming disorder would vie for limited therapeutic resources with a range of serious psychiatric disorders.

Read the full article: Andrew K. Przybylski, Netta Weinstein, Kou Murayama (2016) Internet Gaming Disorder: Investigating the Clinical Relevance of a New Phenomenon. American Journal of Psychiatry. Published online: November 04, 2016.

We caught up with Andy to explore the broader implications of the study:

Ed.: Is “gaming addiction” or “Internet addition” really a thing? e.g. is it something dreamed up by politicians / media people, or is it something that has been discussed and reported by psychiatrists and GPs on the ground?

Andy: Although internet addiction started as a joke about the pathologizing of everyday behaviours, popular fears have put it on the map for policymakers and researchers. In other words, thinking about potential disorders linked to the internet, gaming, and technology have taken on a life of their own.

Ed.: Two years ago the APA identified “a critical need for good research to look into whether internet gamers run a risk of becoming addicted” and asked how such an addiction might be diagnosed properly (i.e. using a checklist of symptoms). What other work or discussion has come out of that call?

Andy: In recent years two groups of researchers have emerged, one arguing there is an international consensus about the potential disorder based on the checklist, the second arguing that it is problematic to pathologize internet gaming. This second group says we don’t understand enough about gaming to know if it’s any different from other hobbies, like being a sports fan. They’re concerned that it could lead other activities to be classified as pathological. Our study set out to test if the checklist approach works, a rigorous test of the APA call for research using the symptoms proposed.

Ed.: Do fears (whether founded or not) of addiction overlap at all with fears of violent video games perhaps altering players’ behaviour? Or are they very clearly discussed and understood as very separate issues?

Andy: Although the fears do converge, the evidence does not. There is a general view that some people might be more liable to be influenced by the addictive or violent aspects of gaming but this remains an untested assumption. In both areas the quality of the evidence base needs critical improvement before the work is valuable for policymakers and mental health professionals.

Ed.: And what’s the broad landscape like in this area – i.e. who are the main players, stakeholders, and pressure points?

Andy: In addition to the American Psychiatric Association (DSM-5), the World Health Organisation is considering formalising Gaming Disorder as a potential mental health issue in the next revision of the International Classifications of Disease (ICD) tool. There is a movement among researchers (myself included based on this research) to urge caution rushing to create new behavioural addition based on gaming for the ICD-11. It is likely that including gaming addiction will do more harm than good by confusing an already complex and under developed research area.

Ed.: And lastly: asking the researcher – do we have enough data and analysis to be able to discuss this sensibly and scientifically? What would a “definitive answer” to this question look like to you — and is it achievable?

Andy: The most important thing to understand about this research area is that there is very little high quality evidence. Generally speaking there are two kinds of empirical studies in the social and clinical sciences, exploratory studies and confirmatory ones. Most of the evidence about gaming addiction to date is exploratory, that is the analyses reported represent what ‘sticks to the wall’ after the data is collected. This isn’t a good evidence for health policy.

Our studies represent the first confirmatory research on gaming addiction. We pre-registered how we were going to collect and analyse our data before we saw it. We collected large representative samples and tested a priori hypotheses. This makes a big difference in the kinds of inferences you can draw and the value of the work to policymakers. We hope our work represents the first of many studies on technology effects that put open data, open code, and a pre-registered analysis plans at the centre of science in this area. Until the research field adopts these high standards we will not have accurate definitive answers about Internet Gaming Disorder.

Read the full article: Andrew K. Przybylski, Netta Weinstein, Kou Murayama (2016) Internet Gaming Disorder: Investigating the Clinical Relevance of a New Phenomenon. American Journal of Psychiatry. Published online: November 04, 2016.

Andy was talking to David Sutcliffe, Managing Editor of the Policy blog.

A second ingredient in his success has been populism, which rails against dominant political elites (including the Republican party) and the ‘biased’ media. Populism also rests on the notion of an ‘authentic’ people — by implication excluding ‘others’ such as immigrants and foreign powers like the Chinese — to whom the leader appeals directly. The paper makes parallels with the strength of the Sweden Democrats, an anti-immigrant party which, in a similar way, has been able to appeal to its following via social media and online newspapers, again bypassing mainstream media with its populist message.

There is a difference, however: in the US, commercial media compete for audience share, so Trump’s controversial tweets have been eagerly embraced by journalists seeking high viewership and readership ratings. In Sweden, where public media dominate and there is far less of the ‘horserace’ politics of American politics, the Sweden Democrats have been more locked out of the mainstream media and of politics. In short, Twitter plus populism has led to Trump. I argue that dominating the mediated attention space is crucial. One outcome of how this story ends will be known in November. But whatever the outcome, it is already clear that the role of the media in politics, and how they can be circumvented by new media, requires fundamental rethinking.

Ralph Schroeder is Professor and director of the Master’s degree in Social Science of the Internet at the Oxford Internet Institute. Before coming to Oxford University, he was Professor in the School of Technology Management and Economics at Chalmers University in Gothenburg (Sweden). Recent books include Rethinking Science, Technology and Social Change (Stanford University Press, 2007) and, co-authored with Eric T. Meyer, Knowledge Machines: Digital Transformations of the Sciences and Humanities (MIT Press 2015).

On 23rd June 2016, a majority of the British public voted in a referendum on whether to leave the European Union. The Leave or so-called #Brexit option was victorious, with a margin of 52% to 48% across the country, although Scotland, Northern Ireland, London and some towns voted to remain. The result was a shock to both leave and remain supporters alike. US readers might note that when the polls closed, the odds on futures markets of Brexit (15%) were longer than those of Trump being elected President.

Political scientists are reeling with the sheer volume of politics that has been packed into the month after the result. From the Prime Minister’s morning-after resignation on 24th June the country was mired in political chaos, with almost every political institution challenged and under question in the aftermath of the vote, including both Conservative and Labour parties and the existence of the United Kingdom itself, given Scotland’s resistance to leaving the EU. The eventual formation of a government under a new prime minister, Teresa May, has brought some stability. But she was not elected and her government has a tiny majority of only 12 Members of Parliament. A cartoon by Matt in the Telegraph on July 2nd (which would work for almost any day) showed two students, one of them saying ‘I’m studying politics. The course covers the period from 8am on Thursday to lunchtime on Friday.’

All these events – the campaigns to remain or leave, the post-referendum turmoil, resignations, sackings and appointments – were played out on social media; the speed of change and the unpredictability of events being far too great for conventional media to keep pace. So our book, Political Turbulence: How Social Media Shape Collective Action, can provide a way to think about the past weeks. The book focuses on how social media allow new, ‘tiny acts’ of political participation (liking, tweeting, viewing, following, signing petitions and so on), which turn social movement theory around. Rather than identifying with issues, forming collective identity and then acting to support the interests of that identity – or voting for a political party that supports it – in a social media world, people act first, and think about it, or identify with others later – if at all.

These tiny acts of participation can scale up to large-scale mobilizations, such as demonstrations, protests or petitions for policy change. These mobilizations normally fail – 99.9% of petitions to the UK or US governments fail to get the 100,000 signatures required for a parliamentary debate (UK) or an official response (US). The very few that succeed usually do so very quickly on a massive scale, but without the normal organizational or institutional trappings of a social or political movement, such as leaders or political parties. When Brazilian President Dilma Rousseff asked to speak to the leaders of the mass demonstrations against the government in 2014 organised entirely on social media with an explicit rejection of party politics, she was told ‘there are no leaders’.

This explosive rise, non-normal distribution and lack of organization that characterizes contemporary politics as a chaotic system, can explain why many political mobilizations of our times seem to come from nowhere. In the US and the UK it can help to understand the shock waves of support that brought Bernie Sanders, Donald Trump, Jeremy Corbyn (elected leader of the Labour party in 2015) and Brexit itself, all of which have challenged so strongly traditional political institutions. In both countries, the two largest political parties are creaking to breaking point in their efforts to accommodate these phenomena.

The unpredicted support for Brexit by over half of voters in the UK referendum illustrates these characteristics of the movements we model in the book, with the resistance to traditional forms of organization. Voters were courted by political institutions from all sides – the government, all the political parties apart from UKIP, the Bank of England, international organizations, foreign governments, the US President himself and the ‘Remain’ or StrongerIn campaign convened by Conservative, Labour and the smaller parties. Virtually every authoritative source of information supported Remain. Yet people were resistant to aligning themselves with any of them. Experts, facts, leaders of any kind were all rejected by the rising swell of support for the Leave side. Famously, Michael Gove, one of the key leave campaigners said ‘we have had enough of experts’. According to YouGov polls, over 2/3 of Conservative voters in 2015 voted to Leave in 2016, as did over one third of Labour and Liberal Democrat voters.

Instead, people turned to a few key claims promulgated by the two Leave campaigns Vote Leave(with key Conservative Brexiteers such as Boris Johnson, Michael Gove and Liam Fox) and Leave.EU, dominated by UKIP and its leader Nigel Farage, bankrolled by the aptly named billionaire Arron Banks. This side dominated social media in driving home their simple (if largely untrue) claims and anti-establishment, anti-elitist message (although all were part of the upper echelons of both establishment and elite). Key memes included the claim (painted on the side of a bus) that the UK gave £350m a week to the EU which could instead be spent on the NHS; the likelihood that Turkey would soon join the EU; and an image showing floods of migrants entering the UK via Europe. Banks brought in staff from his own insurance companies and political campaign firms (such as Goddard Gunster) and Leave.EU created a massive database of leave supporters to employ targeted advertising on social media.

While Remain represented the status-quo and a known entity, Leave was flexible to sell itself as anything to anyone. Leave campaigners would often criticize the Government but then not offer specific policy alternatives stating, ‘we are a campaign not a government.’ This ability for people to coalesce around a movement for a variety of different (and sometimes conflicting) reasons is a hallmark of the social-media based campaigns that characterize Political Turbulence. Some voters and campaigners argued that voting Leave would allow the UK to be more global and accept more immigrants from non-EU countries. In contrast, racism and anti-immigration sentiment were key reasons for other voters. Desire for sovereignty and independence, responses to austerity and economic inequality and hostility to the elites in London and the South East have all figured in the torrent of post-Brexit analysis. These alternative faces of Leave were exploited to gain votes for ‘change,’ but the exact change sought by any two voters could be very different.

The movement‘s organization illustrates what we have observed in recent political turbulence – as in Brazil, Hong Kong and Egypt; a complete rejection of mainstream political parties and institutions and an absence of leaders in any conventional sense. There is little evidence that the leading lights of the Leave campaigns were seen as prospective leaders. There was no outcry from the Leave side when they seemed to melt away after the vote, no mourning over Michael Gove’s complete fall from grace when the government was formed – nor even joy at Boris Johnson’s appointment as Foreign Secretary. Rather, the Leave campaigns acted like advertising campaigns, driving their points home to all corners of the online and offline worlds but without a clear public face. After the result, it transpired that there was no plan, no policy proposals, no exit strategy proposed by either campaign. The Vote Leave campaign was seemingly paralyzed by shock after the vote (they tried to delete their whole site, now reluctantly and partially restored with the lie on the side of the bus toned down to £50 million), pickled forever after 23rd June. Meanwhile, Teresa May, a reluctant Remain supporter and an absent figure during the referendum itself, emerged as the only viable leader after the event, in the same way as (in a very different context) the Muslim Brotherhood, as the only viable organization, were able to assume power after the first Egyptian revolution.

In contrast, the Leave.Eu website remains highly active, possibly poised for the rebirth of UKIP as a radical populist far-right party on the European model, as Arron Banks has proposed. UKIP was formed around this single policy – of leaving the EU – and will struggle to find policy purpose, post-Brexit. A new party, with Banks’ huge resources and a massive database of Leave supporters and their social media affiliations, possibly disenchanted by the slow progress of Brexit, disaffected by the traditional parties – might be a political winner on the new landscape.

The act of voting in the referendum will define people’s political identity for the foreseeable future, shaping the way they vote in any forthcoming election. The entire political system is being redrawn around this single issue, and whichever organizational grouping can ride the wave will win. The one thing we can predict for our political future is that it will be unpredictable.

But then its leadership departed, not once or twice but three times – the latter two within the last few months. The largest government departments have begun to reassert their authority over GDS expert advice, and digital government looks likely to be dragged back towards the deeply dysfunctional old ways of doing things. GDS isn’t perfect, but to erase the progress it has put in place would be a terrible loss.

The UK government’s use of technology has previously lagged far behind other countries. Low usage of digital services rendered them expensive and inefficient. Digital operations were often handicapped by complex networks of legacy systems, some dating right back to the 1970s. The development of the long-promised “digital era governance” was mired in a series of mega contracts: huge in terms of cost, scope and timescale, bigger than any attempted by other governments worldwide, and to be delivered by the same handful of giant global computer consulting firms that rarely saw any challenge to their grip on public contracts. Departmental silos ensured there were no economies of scale, shared services failed, and the Treasury negotiated with 24 departments individually for their IT expenditure.

Some commentators (including this one) were a little sceptical on our first encounter with GDS. We had seen it before: the Office of the e-Envoy set up by Tony Blair in 1999, superseded by the E-government Unit (2004-7), and then Directgov until 2010.

Successes and failures

In many ways GDS has been a success story, with former prime minister David Cameron calling it one of the “great unsung triumphs of the last parliament” with a claimed £1.7 billion cost savings. Treasury negotiates with GDS, rather than with 24 departments, and GDS has been involved in every hiring decision for senior digital staff, raising the quality of digital expertise.

The building blocks of the GDS’ promised “government as a platform” approach have appeared: Verify, a federated identity system that doesn’t rely on ID cards or centralised identity databases, Govpay, which makes it easier to make payments to the government, and Notify, which allows government agencies to keep citizens informed of progress on services.

GDS tackled the overweening power of the huge firms that have dominated government IT in the past, and has given smaller departments and agencies the confidence to undertake some projects themselves, bringing expertise back in-house, embracing open source, and washing away some of the taint of failure from previous government IT projects.

There has even been a procession of visitors from overseas coming to investigate, and imitations have spawned across the world, from the US to Australia.

But elsewhere GDS has really only chipped away at monolithic government IT. For example, GDS and the Department for Work and Pensions failed to work together on Universal Credit. Instead, the huge Pathfindersystem that underpinned the Universal Credit trial phase was supplied by HP, Accenture, IBM and BT and ran into serious trouble at a cost of hundreds of millions of pounds. The department is now building a new system in parallel, with GDS advice, that will largely replace it.

The big systems integrators are still waiting in the wings, poised to renew their influence in government. Francis Maude, who as cabinet minister created GDS, recently admitted that if GDS had undertaken faster and more wholescale reform of legacy systems, it wouldn’t be under threat now.

The risks of centralisation

An issue GDS never tackled is one that has existed right from the start: is it an army, or is it a band of mercenaries working in other departments? Should GDS be at the centre, building and providing systems, or should it just help others to do so, building their expertise? GDS has done both, but the emphasis has been on the former, most evident through putting the government portal GOV.UK at the centre of public services.

Heading down a centralised route was always risky, as the National Audit Office observed of its forerunner direct.gov in 2007. Many departments resented the centralisation of GOV.UK, and the removal of their departmental websites, but it’s likely they’re used to it now, even relieved that it’s no longer their problem. But a staff of 700 with a budget of £112m (from 2015) was always going to look vulnerable to budget cuts.

Return of the Big Beasts

If GDS is diminished or disbanded, any hope of creating effective digital government faces two threats.

A land-grab from the biggest departments – HMRC, DWP and the Home Office, all critics of the GDS – is one possibility. There are already signs of a purge of the digital chiefs put in place by GDS, despite the National Audit Office citing continuity of leadership as critical. This looks like permanent secretaries in the civil service reasserting control over their departments’ digital operations – which will inevitably bring a return to siloed thinking and siloed data, completely at odds with the idea of government as a platform. While the big beasts can walk alone, without GDS the smaller agencies will struggle.

The other threat is the big companies, poised in the wings to renew their influence on government should GDS controls on contract size be removed. It has already begun: the ATLAS consortium led by HP has already won two Ministry of Defence contracts worth £1.5 billion since founding GDS chief Mike Bracken resigned.

It’s hard to see how government as a platform can be taken forward without expertise and capacity at the centre – no single department would have the incentive to do so. Canada’s former chief information officer recently attributed Canada’s decline as a world leader in digital government to the removal of funds dedicated to allowing departmental silos to work together. Even as the UN declares the UK to be the global leader for implementing e-government, unless the GDS can re-establish itself the UK may find the foundations it has created swept away – at a time when using digital services to do more with less is needed more than ever.

This was first posted on The Conversation.

A core topic of concern is how we should develop better principles to understand design practices. The latter surfaces when IA looks at other disciplines, like linguistics, design thinking, new media studies and architecture to develop the theoretical foundations that can back and/or inform its practice. Within the philosophy of information this need to understand general principles of (conceptual or informational) design arises in relation to the question of how we develop and adopt the right level of abstraction (what Luciano Floridi calls the logic of design). This suggests a two-way interaction between PI and IA. On the one hand, PI can become part of the theoretical background that informs Information Architecture as one of the disciplines from which it can borrow concepts and theories. The philosophy of information, on the other hand, can benefit from the rich practice of IA and the growing body of critical reflection on how, within a particular context, the access to online information is best designed.

Throughout the workshop, two themes emerged:

1. The need for more integrated ways to reason about and describe (a) informational artefacts and infrastructures, (b) the design-processes that lead to their creation, and (c) the requirements to which they should conform. This presupposes a convergence between the things we build (informational artefacts) and the conceptual apparatus we rely on (the levels of abstraction we adopt), which surfaces in IA as well as in PI. At the same time, it also calls for novel frameworks and linguistic abstractions. This need to reframe the ways that we observe informational phenomena could be discerned in several contributions to the workshop. It surfaced in the more theoretically oriented contributions of Andrew Hinton, Jason Hobbs & Terence Fenn, Dan Klyn, and Andrea Resmini, that for instance questioned the role of language and place or described frameworks to direct our thinking about designs and problems within their broader context, but also played a role in the practical challenges described by Vicky Buser and Konstantin Weiss.
2. The gap, and resulting need to negotiate, between human and computer-oriented conceptual frameworks that are used to describe and manipulate reality. Whereas this theme was explicitly brought up in Luke Church’s comparison of how end-user programming, machine-learning and interactive visualisation each address this problem, it quickly leads us back to some of the broader concerns in IA. It is, straightforwardly, an instance of how computer-oriented frameworks start to shape infrastructures that are means to be manipulated by humans (i.e. when technical requirements dictate the shape of the user-interface), but it indirectly also hints at the challenges associated with the design of cross-channel interactions and of understanding how information flows between different levels of abstraction.

A final concern that cuts across these two themes deserves to be mentioned as well, namely the need for a language for critique.

This workshop was organised by David Peter Simon, Luciano Floridi and Patrick Allo, and was part of the “Logics of Visualisation” project.

As Laura Bates, founder of the Everyday Sexism project, has recently highlighted, “it seems to be increasingly difficult to talk about sexism, equality, and women’s rights” (Everyday Sexism Project, 2015). With many theorists suggesting that we have entered a so-called “post-feminist” era in which gender equality has been achieved (cf. McRobbie, 2008; Modleski, 1991), to complain about sexism not only risks being labelled as “uptight”, “prudish”, or a “militant feminist”, but also exposes those who speak out to sustained, and at times vicious, personal attacks (Everyday Sexism Project, 2015). Despite this, thousands of women are speaking out, through Bates’ project, about their experiences of everyday sexism. Our research seeks to draw on the rich history of gender studies in the social sciences, coupling it with emerging computational methods for topic modelling, to better understand the content of reports to the Everyday Sexism Project and the lived experiences of those who post them. Here, we outline the literature which contextualizes our study.

Studies on sexism are far from new. Indeed, particularly amongst feminist theorists and sociologists, the analysis (and deconstruction) of “inequality based on sex or gender categorization” (Harper, 2008) has formed a central tenet of both academic inquiry and a radical politics of female emancipation for several decades (De Beauvoir, 1949; Friedan, 1963; Rubin, 1975; Millett, 1971). Reflecting its feminist origins, historical research on sexism has broadly focused on defining sexist interactions (cf. Glick and Fiske, 1997) and on highlighting the problematic, biologically rooted ‘gender roles’ that form the foundation of inequality between men and women (Millett, 1971; Renzetti and Curran, 1992; Chodorow, 1995).

More recent studies, particularly in the field of psychology, have shifted the focus away from whether and how sexism exists, towards an examination of the psychological, personal, and social implications that sexist incidents have for the women who experience them. As such, theorists such as Matteson and Moradi (2005), Swim et al (2001) and Jost and Kay (2005) have highlighted the damaging intellectual and mental health outcomes for women who are subject to continual experiences of sexism. Atwood, for example, argues in her study of gender bias in families, that sexism combines with other life stressors to create significant psychological distress in women, resulting in them needing to “seek therapy, most commonly for depression and anxiety” (2001, 169).

Given its increasing ubiquity in every day life, it is hardly surprising that the relationship between technology and sexism has also sparked interest from contemporary researchers in the field. Indeed, several studies have explored the intersection between gender and power online, with Susan Herring’s work on gender differences in computer-mediated communication being of particular note (cf. Herring, 2008). Theorists such as Mindi D. Foster have focused on the impact that using digital technology, and particularly Web 2.0 technologies, to talk about sexism can have on women’s well being. Foster’s study found that when women tweeted about sexism, and in particular when they used tweets to a) name the problem, b) criticise it, or c) to suggest change, they viewed their actions as effective and had enhanced life satisfaction, and therefore felt empowered (Foster, 2015: 21).

Despite this diversity of research on sexism, however, there remain some notable gaps in understanding. In particular, as this study hopes to highlight, little previous research on sexism has considered the different ‘types’ of sexism experienced by women (beyond an identification of the workplace and the education system as contexts in which sexism often manifests as per Barnett, 2005; Watkins et al., 2006; Klein, 1992). Furthermore, research focusing on sexism has thus far been largely qualitative in nature. Although a small number of studies have employed quantitative methods (cf. Brandt 2011; Becker and Wright, 2011), none have used computational approaches to analyse the wealth of available online data on sexism.

This project, which will apply a natural language processing approach to analyse data collected from the Everyday Sexism Project website, seeks to fill such a gap. By providing much needed analysis of a large-scale crowd sourced data set on sexism, it is our hope that knowledge gained from this study will advance both the sociological understanding of women’s lived experiences of sexism, and methodological understandings of the suitability of computational topic modelling for conducting this kind of research.

Find out more about the OII’s research on the Everyday Sexism project by visiting the webpage or by looking at the other Policy & Internet blog posts on the project – post 1 and post 2.

Taha Yasseri is a Research Fellow at the OII who has interests in analysis of Big Data to understand human dynamics, government-society interactions, mass collaboration, and opinion dynamics.

Kathryn Eccles is a Research Fellow at the OII who has research interests in the impact of new technologies on scholarly behaviour and research, particularly in the Humanities.

Sophie Melville is a Research Assistant working at the OII. She previously completed the MSc in the Social Science of the Internet at the OII.

References

Atwood, N. C. (2001). Gender bias in families and its clinical implications for women. Social Work, 46 pp. 23–36.

Barnett, R. C. (2005). Ageism and Sexism in the workplace. Generations. 29(3) pp. 25 30.

Bates, Laura. (2015). Everyday Sexism [online] Available at: http://everydaysexism.com [Accessed 1 May 2016].

Becker, Julia C. & Wright, Stephen C. (2011). Yet another dark side of chivalry: Benevolent sexism undermines and hostile sexism motivates collective action for social change. Journal of Personality and Social Psychology, Vol 101(1), Jul 2011, 62-77

Brandt, Mark. (2011). Sexism and Gender Inequality across 57 societies. Psychiological Science. 22(11).

Chodorow, Nancy (1995). “Becoming a feminist foremother”. In Phyllis Chesler, Esther D. Rothblum, Ellen Cole,. Feminist foremothers in women’s studies, psychology, and mental health. New York: Haworth Press. pp. 141–154.

De Beauvoir, Simone. (1949). The second sex, woman as other. London: Vintage.

Foster, M. D. (2015). Tweeting about sexism: The well-being benefits of a social media collective action. British Journal of Social Psychology.

Friedan, Betty. (1963). The Feminine Mystique. W. W. Norton and Co.

Glick, Peter. & Fiske, Susan T. (1997). Hostile and Benevolent Sexism. Psychology of Women Quarterly, 21(1) pp. 119 – 135.

Harper, Amney J. (2008). The relationship between sexism, ambivalent sexism, and relationship quality in heterosexual women. PhD Auburn University.

Herring, Susan C. (2008). Gender and Power in Online Communication. In Janet Holmes and Miriam Meyerhoff (eds) The Handbook of Language and Gender. Oxford: Blackwell.

Jost, J. T., & Kay, A. C. (2005). Exposure to benevolent sexism and complementary gender stereotypes: Consequences for specific and diffuse forms of system justification. Journal of Personality and Social Psychology, 88 pp. 498–509.

Klein, Susan Shurberg. (1992). Sex equity and sexuality in education: breaking the barriers. State University of New York Press.

Matteson, A. V., & Moradi, B. (2005). Examining the structure of the schedule of sexist events: Replication and extension. Psychology of Women Quarterly, 29 pp. 47–57.

McRobbie, Angela (2004). Post-feminism and popular culture. Feminist Media Studies, 4(3) pp. 255 – 264.

Millett, Kate. (1971). Sexual politics. UK: Virago.

Modleski, Tania. (1991). Feminism without women: culture and criticism in a “postfeminist” age. New York: Routledge.

Renzetti, C. and D. Curran, 1992, “Sex-Role Socialization”, in Feminist Philosophies, J. Kourany, J. Sterba, and R. Tong (eds.), New Jersey: Prentice Hall.

Rubin, Gayle. (1975). The traffic in women: notes on the “political economy” of sex. In Rayna R. Reiter (ed.), Toward and anthropology of women. Monthly Review Press.

Swim, J. K., Hyers, L. L., Cohen, L. L., & Ferguson, M. J. (2001). Everyday sexism: Evidence for its incidence, nature, and psychological impact from three daily diary studies. Journal of Social Issues, 57 pp. 31–53.

Watkins et al. (2006). Does it pay to be sexist? The relationship between modern sexism and career outcomes. Journal of Vocational Behaviour. 69(3) pp. 524 – 537.

The Alan Turing Institute will build on the UK’s existing academic strengths in the analysis and application of big data and algorithm research to place the UK at the forefront of world-wide research in data science. The University of Oxford is one of five university partners, and the OII is the only partnering department in the social sciences. The aim of the summit on Data Science for Government and Policy-Making was to understand how government can make better use of big data and the ATI – with the academic partners in listening mode.

We hoped that the participants would bring forward their own stories, hopes and fears regarding data science for the public good. Crucially, we wanted to work out a roadmap for how different stakeholders can work together on the distinct challenges facing government, as opposed to commercial organisations. At the same time, data science research and development has much to gain from the policy-making community. Some of the things that government does – collect tax from the whole population, or give money away at scale, or possess the legitimate use of force – it does by virtue of being government. So the sources of data and some of the data science challenges that public agencies face are unique and tackling them could put government working with researchers at the forefront of data science innovation.

During the Summit a range of stakeholders provided insight from their distinctive perspectives; the Government Chief Scientific Advisor, Sir Mark Walport; Deputy Director of the ATI, Patrick Wolfe; the National Statistician and Director of ONS, John Pullinger; Director of Data at the Government Digital Service, Paul Maltby. Representatives of frontline departments recounted how algorithmic decision-making is already bringing predictive capacity into operational business, improving efficiency and effectiveness.

Discussion revolved around the challenges of how to build core capability in data science across government, rather than outsourcing it (as happened in an earlier era with information technology) or confining it to a data science profession. Some delegates talked of being in the ‘foothills’ of data science. The scale, heterogeneity and complexity of some government departments currently works against data science innovation, particularly when larger departments can operate thousands of databases, creating legacy barriers to interoperability. Out-dated policies can work against data science methodologies. Attendees repeatedly voiced concerns about sharing data across government departments, in some case because of limitations of legal protections; in others because people were unsure what they can and cannot do.

The potential power of data science creates an urgent need for discussion of ethics. Delegates and speakers repeatedly affirmed the importance of an ethical framework and for thought leadership in this area, so that ethics is ‘part of the science’. The clear emergent option was a national Council for Data Ethics (along the lines of the Nuffield Council for Bioethics) convened by the ATI, as recommended in the recent Science and Technology parliamentary committee report The big data dilemma and the government response. Luciano Floridi (OII’s professor of the philosophy and ethics of information) warned that we cannot reduce ethics to mere compliance. Ethical problems do not normally have a single straightforward ‘right’ answer, but require dialogue and thought and extend far beyond individual privacy. There was consensus that the UK has the potential to provide global thought leadership and to set the standard for the rest of Europe. It was announced during the Summit that an ATI Working Group on the Ethics of Data Science has been confirmed, to take these issues forward.

So what happens now?

Throughout the Summit there were calls from policy makers for more data science leadership. We hope that the ATI will be instrumental in providing this, and an interface both between government, business and academia, and between separate Government departments. This Summit showed just how much real demand – and enthusiasm – there is from policy makers to develop data science methods and harness the power of big data. No-one wants to repeat with data science the history of government information technology – where in the 1950s and 60s, government led the way as an innovator, but has struggled to maintain this position ever since. We hope that the ATI can act to prevent the same fate for data science and provide both thought leadership and the ‘time and space’ (as one delegate put it) for policy-makers to work with the Institute to develop data science for the public good.

So since the Summit, in response to the clear need that emerged from the discussion and other conversations with stakeholders, the ATI has been designing a Policy Innovation Unit, with the aim of working with government departments on ‘data science for public good’ issues. Activities could include:

• Secondments at the ATI for data scientists from government
• Short term projects in government departments for ATI doctoral students and postdoctoral researchers
• Developing ATI as an accredited data facility for public data, as suggested in the current Cabinet Office consultation on better use of data in government
• ATI pilot policy projects, using government data
• Policy symposia focused on specific issues and challenges
• ATI representation in regular meetings at the senior level (for example, between Chief Scientific Advisors, the Cabinet Office, the Office for National Statistics, GO-Science).
• ATI acting as an interface between public and private sectors, for example through knowledge exchange and the exploitation of non-government sources as well as government data
• ATI offering a trusted space, time and a forum for formulating questions and developing solutions that tackle public policy problems and push forward the frontiers of data science
• ATI as a source of cross-fertilization of expertise between departments
• Reviewing the data science landscape in a department or agency, identifying feedback loops – or lack thereof – between policy-makers, analysts, front-line staff and identifying possibilities for an ‘intelligent centre’ model through strategic development of expertise.

The Summit, and a series of Whitehall Roundtables convened by GO-Science which led up to it, have initiated a nascent network of stakeholders across government, which we aim to build on and develop over the coming months. If you are interested in being part of this, please do be in touch with us

Helen Margetts, Oxford Internet Institute, University of Oxford (director@oii.ox.ac.uk)

Tom Melham, Department of Computer Science, University of Oxford

Ed: Josh, political science has long posed a distinction between public spaces and private ones. Yet it seems like many platforms on the Internet, such as Facebook, cannot really be categorized in such terms. If this correct, what does it mean for how we should police and govern the Internet?

Josh: I think that is right – many online spaces are neither public nor private. This is also an issue for some for privacy legal frameworks (especially in the US).. A lot of the covenants and agreements were written forty or fifty years ago, long before anyone had really thought about the Internet. That has now forced governments, societies and parliaments to adapt these existing rights and protocols for the online sphere. I think that we have some fairly clear laws about the use of human intelligence sources, and police law in the offline sphere. The interesting question is how we can take that online. How can the pre-existing standards, like the requirement that procedures are necessary and proportionate, or the ‘right to appeal’, be incorporated into online spaces? In some cases there are direct analogies. In other cases there needs to be some re-writing of the rule book to try figure out what we mean. And, of course, it is difficult because the internet itself is always changing!

Ed: So do you think that concepts like proportionality and justification need to be updated for online spaces?

Josh: I think that at a very basic level they are still useful. People know what we mean when we talk about something being necessary and proportionate, and about the importance of having oversight. I think we also have a good idea about what it means to be non-discriminatory when applying the law, though this is one of those areas that can quickly get quite tricky. Consider the use of online data sources to identify people. On the one hand, the Internet is ‘blind’ in that it does not automatically codify social demographics. In this sense it is not possible to profile people in the same way that we can offline. On the other hand, it is in some ways the complete opposite. It is very easy to directly, and often invisibly, create really firm systems of discrimination – and, most problematically, to do so opaquely.

This is particularly challenging when we are dealing with extremism because, as we pointed out in the report, extremists are generally pretty unremarkable in terms of demographics. It perhaps used to be true that extremists were more likely to be poor or to have had challenging upbringings, but many of the people going to fight for the Islamic State are middle class. So we have fewer demographic pointers to latch onto when trying to find these people. Of course, insofar as there are identifiers they won’t be released by the government. The real problem for society is that there isn’t very much openness and transparency about these processes.

Ed: Governments are increasingly working with the private sector to gain access to different types of information about the public. For example, in Australia a Telecommunications bill was recently passed which requires all telecommunication companies to keep the metadata – though not the content data – of communications for two years. A lot of people opposed the Bill because metadata is still very informative, and as such there are some clear concerns about privacy. Similar concerns have been expressed in the UK about an Investigatory Powers Bill that would require new Internet Connection Records about customers, online activities.  How much do you think private corporations should protect people’s data? And how much should concepts like proportionality apply to them?

Ian: To me the distinction between metadata and content data is fairly meaningless. For example, often just knowing when and who someone called and for how long can tell you everything you need to know! You don’t have to see the content of the call. There are a lot of examples like this which highlight the slightly ludicrous nature of distinguishing between metadata and content data. It is all data. As has been said by former US CIA and NSA Director Gen. Michael Hayden, “we kill people based on metadata.”

One issue that we identified in the report is the increased onus on companies to monitor online spaces, and all of the legal entanglements that come from this given that companies might not be based in the same country as the users. One of our interviewees called this new international situation a ‘very different ballgame’. Working out how to deal with problematic online content is incredibly difficult, and some huge issues of freedom of speech are bound up in this. On the one hand, there is a government-led approach where we use the law to take down content. On the other hand is a broader approach, whereby social networks voluntarily take down objectionable content even if it is permissible under the law. This causes much more serious problems for human rights and the rule of law.

Read the full report: Brown, I., and Cowls, J., (2015) Check the Web: Assessing the Ethics and Politics of Policing the Internet for Extremist Material. VOX-Pol Publications.

Ian Brown is Professor of Information Security and Privacy at the OII. His research is focused on surveillance, privacy-enhancing technologies, and Internet regulation.

Josh Cowls is a a student and researcher based at MIT, working to understand the impact of technology on politics, communication and the media.

Josh and Ian were talking to Blog Editor Bertie Vidgen.

In an unprecedented move, the American Statistical Association recently released a statement (March 7 2016) warning against how p-values are currently used. This reflects a growing concern in academic circles that whilst a lot of attention is paid to the huge impact of big data and algorithmic decision-making, there is considerably less focus on the crucial role played by statistics in enabling effective analysis of big data sets, and making sense of the complex relationships contained within them. Because much as datafication has created huge social opportunities, it has also brought to the fore many problems and limitations with current statistical practices. In particular, the deluge of data has made it crucial that we can work out whether studies are ‘significant’. In our paper, published three days before the ASA’s statement, we argued that the most commonly used tool in the social sciences for calculating significance – the p-value – is misused, misunderstood and, most importantly, doesn’t tell us what we want to know.

The basic problem of ‘significance’ is simple: it is simply unpractical to repeat an experiment an infinite number of times to make sure that what we observe is “universal”. The same applies to our sample size: we are often unable to analyse a “whole population” sample and so have to generalize from our observations on a limited size sample to the whole population. The obvious problem here is that what we observe is based on a limited number of experiments (sometimes only one experiment) and from a limited size sample, and as such could have been generated by chance rather than by an underlying universal mechanism! We might find it impossible to make the same observation if we were to replicate the same experiment multiple times or analyse a larger sample. If this is the case then we will mischaracterise what is happening – which is a really big problem given the growing importance of ‘evidence-based’ public policy. If our evidence is faulty or unreliable then we will create policies, or intervene in social settings, in an equally faulty way.

The way that social scientists have got round this problem (that samples might not be representative of the population) is through the ‘p-value’. The p-value tells you the probability of making a similar observation in a sample with the same size and in the same number of experiments, by pure chance In other words,  it is actually telling you is how likely it is that you would see the same relationship between X and Y even if no relationship exists between them. On the face of it this is pretty useful, and in the social sciences we normally say that a p-value of 1 in 20 means the results are significant. Yet as the American Statistical Association has just noted, even though they are incredibly widespread many researchers mis-interpret what p-values really mean.

In our paper we argued that p-values are misunderstood and misused because people think the p-value tells you much more than it really does. In particular, people think the p-value tells you (i) how likely it is that a relationship between X and Y really exists and (ii) the percentage of all findings that are false (which is actually something different called the False Discovery Rate). As a result, we are far too confident that academic studies are correct. Some commentators have argued that at least 30% of studies are wrong because of problems related to p-values: a huge figure. One of the main problems is that p-values can be ‘hacked’ and as such easily manipulated to show significance when none exists.

If we are going to base public policy (and as such public funding) on ‘evidence’ then we need to make sure that the evidence used is reliable. P-values need to be used far more rigorously, with significance levels of 0.01 or 0.001 seen as standard. We also need to start being more open and transparent about how results are recorded. It is a fine line between data exploration (a legitimate academic exercise) and ‘data dredging’ (where results are manipulated in order to find something noteworthy). Only if researchers are honest about what they are doing will we be able to maximise the potential benefits offered by Big Data. Luckily there are some great initiatives – like the Open Science Framework – which improve transparency around the research process, and we fully endorse researchers making use of these platforms.

Scientific knowledge advances through corroboration and incremental progress, and it is crucial that we use and interpret statistics appropriately to ensure this progress continues. As our knowledge and use of big data methods increase, we need to ensure that our statistical tools keep pace.

Read the full paper: Vidgen, B. and Yasseri, T., (2016) P-values: Misunderstood and Misused, Frontiers in Physics, 4:6. http://dx.doi.org/10.3389/fphy.2016.00006

Bertie Vidgen is a doctoral student at the Oxford Internet Institute researching far-right extremism in online contexts. He is supervised by Dr Taha Yasseri, a research fellow at the Oxford Internet Institute interested in how Big Data can be used to understand human dynamics, government-society interactions, mass collaboration, and opinion dynamics.

Online support groups are one of the major ways in which the Internet has fundamentally changed how people experience health and health care. They provide a platform for health discussions formerly restricted by time and place, enable individuals to connect with others in similar situations, and facilitate open, anonymous communication.

Previous studies have identified that individuals primarily obtain two kinds of support from online support groups: informational (for example, advice on treatments, medication, symptom relief, and diet) and emotional (for example, receiving encouragement, being told they are in others’ prayers, receiving “hugs”, or being told that they are not alone). However, existing research has been limited as it has often used hand-coded qualitative approaches to contrast both forms of support, thereby only examining relatively few posts (<1,000) for one or two conditions.

In contrast, our research employed a machine-learning approach suitable for uncovering patterns in “big data”. Using this method a computer (which initially has no knowledge of online support groups) is given examples of informational and emotional posts (2,000 examples in our study). It then “learns” what words are associated with each category (emotional: prayers, sorry, hugs, glad, thoughts, deal, welcome, thank, god, loved, strength, alone, support, wonderful, sending; informational: effects, started, weight, blood, eating, drink, dose, night, recently, taking, side, using, twice, meal). The computer then uses this knowledge to assess new posts, and decide whether they contain more emotional or informational support.

With this approach we were able to determine the emotional or informational content of 40,000 posts across 14 different health conditions (breast cancer, prostate cancer, lung cancer, depression, schizophrenia, Alzheimer’s disease, multiple sclerosis, cystic fibrosis, fibromyalgia, heart failure, diabetes type 2, irritable bowel syndrome, asthma, and chronic obstructive pulmonary disease) on the international support group forum Dailystrength.org.

Our research revealed a slight overall tendency towards emotional posts (58% of posts were emotionally oriented). Across all diseases, those who write more also tend to write more emotional posts—we assume that as people become more involved and build relationships with other users they tend to provide more emotional support, instead of simply providing information in one-off interactions. At the same time, we also observed that older people write more informational posts. This may be explained by the fact that older people more generally use the Internet to find information, that they become experts in their chronic conditions over time, and that with increasing age health conditions may have less emotional impact as they are relatively more expected.

The demographic prevalence of the condition may also be enmeshed with the disease-related tendency to write informational or emotional posts. Our analysis suggests that content differs across the 14 conditions: mental health or brain-related conditions (such as depression, schizophrenia, and Alzheimer’s disease) feature more emotionally oriented posts, with around 80% of posts primarily containing emotional support. In contrast, nonterminal physical conditions (such as irritable bowel syndrome, diabetes, asthma) rather focus on informational support, with around 70% of posts providing advice about symptoms, treatments, and medication.

Finally, there was no gender difference across conditions with respect to the amount of posts that were informational versus emotional. That said, prostate cancer forums are oriented towards informational support, whereas breast cancer forums feature more emotional support. Apart from the generally different nature of both conditions, one explanation may lie in the nature of single-gender versus mixed-gender groups: an earlier meta-study found that women write more emotional content than men when talking among others of the same gender – but interestingly, in mixed-gender discussions, these differences nearly disappeared.

Our research helped to identify factors that determine whether online content is informational or emotional, and demonstrated how posts differ across conditions. In addition to theoretical insights about patient needs, this research will help practitioners to better understand the role of online support groups for different patients, and to provide advice to patients about the value of online support.

The results also suggest that online support groups should be integrated into the digital health strategies of the UK and other nations. At present the UK plan for “Personalised Health and Care 2020” is centred around digital services provided within the health system, and does not yet reflect the value of person-generated health data from online support groups to patients. Our research substantiates that it would benefit from considering the instrumental role that online support groups can play in the healthcare process.

Read the full paper: Deetjen, U. and J. A. Powell (2016) Informational and emotional elements in online support groups: a Bayesian approach to large-scale content analysis. Journal of the American Medical Informatics Association. http://dx.doi.org/10.1093/jamia/ocv190

Ulrike Deetjen (née Rauer) is a doctoral student at the Oxford Internet Institute researching the influence of the Internet on healthcare provision and health outcomes.

At its very core, topic modelling is a technique that seeks to automatically discover the topics contained within a group of documents. ‘Documents’ in this context could refer to text items as lengthy as individual books, or as short as sentences within a paragraph. Let’s take the idea of sentences-as-documents as an example:

• Document 1: I like to eat kippers for breakfast.
• Document 2: I love all animals, but kittens are the cutest.
• Document 3: My kitten eats kippers too.

Assuming that each sentence contains a mixture of different topics (and that a ‘topic’ can be understood as a collection of words (of any part of speech) that have different probabilities of appearance in passages discussing the topic), how does the topic modelling algorithm ‘discover’ the topics within these sentences?

The algorithm is initiated by setting the number of topics that it needs to extract. Of course, it is hard to guess this number without having an insight on the topics, but one can think of this as a resolution tuning parameter. The smaller the number of topics is set, the more general the bag of words in each topic would be, and the looser the connections between them.

The algorithm loops through all of the words in each document, assigning every word to one of our topics in a temporary and semi-random manner. This initial assignment is arbitrary and it is easy to show that different initializations lead to the same results in long run. Once each word has been assigned a temporary topic, the algorithm then re-iterates through each word in each document to update the topic assignment using two criteria: 1) How prevalent is the word in question across topics? And 2) How prevalent are the topics in the document?

To quantify these two, the algorithm calculates the likelihood of the words appearing in each document assuming the assignment of words to topics and topics to documents. 

Of course words can appear in different topics and more than one topic can appear in a document. But the iterative algorithm seeks to maximize the self-consistency of the assignment by maximizing the likelihood of the observed word-document statistics. 

We can illustrate this process and its outcome by going back to our example. A topic modelling approach might use the process above to discover the following topics across our documents:

• Document 1: I like to eat kippers for breakfast. [100% Topic A]
• Document 2: I love all animals, but kittens are the cutest. [100% Topic B]
• Document 3: My kitten eats kippers too. [67% Topic A, 33% Topic B]

Topic modelling defines each topic as a so-called ‘bag of words’, but it is the researcher’s responsibility to decide upon an appropriate label for each topic based on their understanding of language and context. Going back to our example, the algorithm might classify the underlined words under Topic A, which we could then label as ‘food’ based on our understanding of what the words mean. Similarly the italicised words might be classified under a separate topic, Topic B, which we could label ‘animals’. In this simple example the word “eat” has appeared in a sentence dominated by Topic A, but also in a sentence with some association to Topic B. Therefore it can also be seen as a connector of the two topics. Of course animals eat too and they like food!

We are going to use a similar approach to first extract the main topics reflected on the reports to the Everyday Sexism Project website and extract the relation between the sexism-related topics and concepts based on the overlap between the bags of words of each topic. Finally we can also look into the co-appearance of topics in the same document.  This way we try to draw a linguistic picture of the more than 100,000 submitted reports.

As ever, be sure to check back for further updates on our progress!

Homejoy was slated to become the Uber of domestic cleaning services. It was a platform that allowed customers to summon a cleaner as easily as they could hail a ride. Regular cleanups were just as easy to schedule. Ratings from previous clients attested to the skill and trustworthiness of each cleaner. There was no need to go through a cleaning services agency, or scour local classifieds to find a cleaner directly: the platform made it easy for both customers and people working as cleaners to find each other. Homejoy made its money by taking a cut out of each transaction. Given how incredibly successful Uber and Airbnb had been in applying the same model to their industries, Homejoy was widely expected to become the next big success story. It was to be the next step in the inexorable uberization of every industry in the economy.

On 17 July 2015, Homejoy announced that it was shutting down. Usage had grown slower than expected, revenues remained poor, technical glitches hurt operations, and the company was being hit with lawsuits on contractor misclassification. Investors’ money and patience had finally ran out. Journalists wrote interesting analyses of Homejoy’s demise (Forbes, TechCrunch, Backchannel). The root causes of any major business failure (or indeed success) are complex and hard to pinpoint. However, one of the possible explanations identified in these stories stands out, because it corresponds strongly with what theory on platforms and markets could have predicted. Homejoy wasn’t growing and making money because clients and cleaners were taking their relationships off-platform: after making the initial contact through Homejoy, they would simply exchange contact details and arrange further cleanups directly, taking the platform and its revenue share out of the loop. According to Forbes, only 15-20 percent of customers came back to Homejoy within a month to arrange another cleanup.

According to the theory of platforms in economics and management studies literature, platforms solve coordination problems. Digital service platforms like Uber and Airbnb solve, in particular, the problem of finding another party to transact with. Through marketing and bootstrapping efforts they ensure that both buyers and sellers sign up to the platform, and then provide match-making mechanisms to bring them together. They also provide solutions towards the problem of opportunism, that is, how to avoid being cheated by the other party. Rating systems are their main tool in this.

Platforms must compete against the existing institutional arrangements in their chosen industry. Uber has been very successful in taking away business from government-licensed taxicabs. Airbnb has captured market share from hotels and hotel booking sites. Both have also generated lots of new business: transactions that previously didn’t happen at all. It’s not that people didn’t already occassionally pay a highschool friend to give them a ride home from a party, or rent a room for the weekend from a friend of a friend who lives in New York. It’s that platforms make similar things possible even when the highschool friend is not available, or if you simply don’t know anyone with a flat in New York. Platforms coordinate people to turn what is otherwise a thin market into a thick one. Not only do platforms help you to find a stranger to transact with, but they also help you to trust that stranger.

Now consider the market for home cleaning services. Home cleaning differs from on-demand transport and short-term accommodation in one crucial way: the service is typically repeated. Through repeated interactions, the buyer and the seller develop trust in each other. They also develop knowledge capital specific to that particular relationship. The buyer might invest time into communicating their preferences and little details about their home to the seller, while the seller will gradually become more efficient at cleaning that particular home. They have little need for the platform to discipline each individual cleanup; relationships are thus soon taken off-platform. Instead of an all-encompassing Uber-style platform, all that may be needed is a classifieds site or a conventional agency that provides the initial introduction and references. Contrast this with on-demand transport and short-term accommodation, where each transaction is unique and thus each time the counterparty is a stranger — and as such a potential cheat or deadbeat. Here the platform continues to provide security after the parties have been introduced.

The case of Homejoy and the economic theory on platforms thus suggest that there are fundamental limits to the uberization of the economy. Digital service platforms can be very successful at mediating one-off transactions, but they are much less useful in industries where the exact same service is repeated many times, and where buyers and sellers develop assets specific to the relationship. Such industries are more likely to continue to be shaped by hierarchies and networks of personal relationships.

There are probably other dimensions that are also pivotal in predicting whether an industry is susceptible to uberization. Geographical span is one: there are efficiencies to be had from particular cleaners specializing in particular neighbourhoods. Yet, at the same time, online labour platforms like Upwork cater to buyers and sellers of software development (and other digitally mediated contract work) across national boundaries. I will discuss this dimension in detail in a future blog post.

Vili Lehdonvirta is a Research Fellow at the OII. He is an economic sociologist who studies the design and socioeconomic implications of digital marketplaces and platforms, using conventional social research methods as well as novel data science approaches. Read Vili’s other Policy & Internet Blog posts on Uber and Airbnb:

Uber and Airbnb make the rules now – but to whose benefit?

Why are citizens migrating to Uber and Airbnb, and what should governments do about it?

Should we love Uber and Airbnb or protest against them?

*please note that the views given here do not necessarily reflect the content of the report, or those of the lead author, Ian Brown.

Ed: Josh, could you let us know the purpose of the report, outline some of the key findings, and tell us how you went about researching the topic?

Josh: Sure. In the report we take a step back from the ground-level question of ‘what are the police doing?’ and instead ask, ‘what are the ethical and political boundaries, rationale and justifications for policing the web for these kinds of activity?’ We used an international human rights framework as an ethical and legal basis to understand what is being done. We also tried to further the debate by clarifying a few things: what has already been done by law enforcement, and, really crucially, what the perspectives are of all those involved, including lawmakers, law enforcers, technology companies, academia and many others.

We derived the insights in the report from a series of workshops, one of which was held as part of the EU-funded VOX-Pol network. The workshops involved participants who were quite high up in law enforcement, the intelligence agencies, the tech industry civil society, and academia. We followed these up with interviews with other individuals in similar positions and conducted background policy research.

Ed: You highlight that many extremist groups (such as Isis) are making really significant use of online platforms to organize, radicalize people, and communicate their messages.

Josh: Absolutely. A large part of our initial interest when writing the report lay in finding out more about the role of the Internet in facilitating the organization, coordination, recruitment and inspiration of violent extremism. The impact of this has been felt very recently in Paris and Beirut, and many other places worldwide. This report pre-dates these most recent developments, but was written in the context of these sorts of events.

Given the Internet is so embedded in our social lives, I think it would have been surprising if political extremist activity hadn’t gone online as well. Of course, the Internet is a very powerful tool and in the wrong hands it can be a very destructive force. But other research, separate from this report, has found that the Internet is not usually people’s first point of contact with extremism: more often than not that actually happens offline through people you know in the wider world. Nonetheless it can definitely serve as an incubator of extremism and can serve to inspire further attacks.

Ed: In the report you identify different groups in society that are affected by, and affecting, issues of extremism, privacy, and governance – including civil society, academics, large corporations and governments

Josh: Yes, in the later stages of the report we do divide society into these groups, and offer some perspectives on what they do, and what they think about counter-extremism. For example, in terms of counter-speech there are different roles for government, civil society, and industry. There is this idea that ISIS are really good at social media, and that that is how they are powering a lot of their support; but one of the people that we spoke to said that it is not the case that ISIS are really good, it is just that governments are really bad!

We shouldn’t ask government to participate in the social network: bureaucracies often struggle to be really flexible and nimble players on social media. In contrast, civil society groups tend to be more engaged with communities and know how to “speak the language” of those who might be vulnerable to radicalization. As such they can enter that dialogue in a much more informed and effective way.

The other tension, or paradigm, that we offer in this report is the distinction between whether people are ‘at risk’ or ‘a risk’. What we try to point to is that people can go from one to the other. They start by being ‘at risk’ of radicalization, but if they do get radicalized and become a violent threat to society, which only happens in the minority of cases, then they become ‘a risk’. Engaging with people who are ‘at risk’ highlights the importance of having respect and dialogue with communities that are often the first to be lambasted when things go wrong, but which seldom get all the help they need, or the credit when they get it right. We argue that civil society is particularly suited for being part of this process.

Ed: It seems like the things that people do or say online can only really be understood in terms of the context. But often we don’t have enough information, and it can be very hard to just look at something and say ‘This is definitely extremist material that is going to incite someone to commit terrorist or violent acts’.

Josh: Yes, I think you’re right. In the report we try to take what is a very complicated concept – extremist material – and divide it into more manageable chunks of meaning. We talk about three hierarchical levels. The degree of legal consensus over whether content should be banned decreases as it gets less extreme. The first level we identified was straight up provocation and hate speech. Hate speech legislation has been part of the law for a long time. You can’t incite racial hatred, you can’t incite people to crimes, and you can’t promote terrorism. Most countries in Europe have laws against these things.

The second level is the glorification and justification of terrorism. This is usually more post-hoc as by definition if you are glorifying something it has already happened. You may well be inspiring future actions, but that relationship between the act of violence and the speech act is different than with provocation. Nevertheless, some countries, such as Spain and France, have pushed hard on criminalising this. The third level is non-violent extremist material. This is the most contentious level, as there is very little consensus about what types of material should be called ‘extremist’ even though they are non-violent. One of the interviewees that we spoke to said that often it is hard to distinguish between someone who is just being friendly and someone who is really trying to persuade or groom someone to go to Syria. It is really hard to put this into a legal framework with the level of clarity that the law demands.

There is a proportionality question here. When should something be considered specifically illegal? And, then, if an illegal act has been committed what should the appropriate response be? This is bound to be very different in different situations.

Ed: Do you think that there are any immediate or practical steps that governments can take to improve the current situation? And do you think that there any ethical concerns which are not being paid sufficient attention?

Josh: In the report we raised a few concerns about existing government responses. There are lots of things beside privacy that could be seen as fundamental human rights and that are being encroached upon. Freedom of association and assembly is a really interesting one. We might not have the same reverence for a Facebook event plan or discussion group as we would a protest in a town hall, but of course they are fundamentally pretty similar.

The wider danger here is the issue of mission creep. Once you have systems in place that can do potentially very powerful analytical investigatory things then there is a risk that we could just keep extending them. If something can help us fight terrorism then should we use it to fight drug trafficking and violent crime more generally? It feels to me like there is a technical-military-industrial complex mentality in government where if you build the systems then you just want to use them. In the same way that CCTV cameras record you irrespective of whether or not you commit a violent crime or shoplift, we need to ask whether the same panoptical systems of surveillance should be extended to the Internet. Now, to a large extent they are already there. But what should we train the torchlight on next?

This takes us back to the importance of having necessary, proportionate, and independently authorized processes. When you drill down into how rights privacy should be balanced with security then it gets really complicated. But the basic process-driven things that we identified in the report are far simpler: if we accept that governments have the right to take certain actions in the name of security, then, no matter how important or life-saving those actions are, there are still protocols that governments must follow. We really wanted to infuse these issues into the debate through the report.

Read the full report: Brown, I., and Cowls, J., (2015) Check the Web: Assessing the Ethics and Politics of Policing the Internet for Extremist Material. VOX-Pol Publications.

Josh Cowls is a a student and researcher based at MIT, working to understand the impact of technology on politics, communication and the media.

Josh Cowls was talking to Blog Editor Bertie Vidgen.

Collecting, storing and distributing digital data is significantly easier and cheaper now than ever before, in line with predictions from Moore, Kryder and Gilder. Organisations are incentivised to collect large volumes of data with the hope of unleashing new business opportunities or maybe even new businesses. Consider the likes of uber, Netflix, and Airbnb and the other data mongers who have built services based solely on digital assets.

The use of this new abundant data will continue to disrupt traditional business models for years to come, and there is no doubt that these large data volumes can provide value. However, they also bring associated risks (such as unplanned disclosure and hacks) and they come with constraints (for example in the form of privacy or data protection legislation). Hardly a week goes by without a data breach hitting the headlines. Even if your telecommunications provider didn’t inadvertently share your bank account and sort code with hackers, and your child wasn’t one of the hundreds of thousands of children whose birthdays, names, and photos were exposed by a smart toy company, you might still be wondering exactly how your data is being looked after by the banks, schools, clinics, utility companies, local authorities and government departments that are so quick to collect your digital details.

Then there are the companies who have invited you to sign away the rights to your data and possibly your privacy too – the ones that ask you to sign the Terms and Conditions for access to a particular service (such as a music or online shopping service) or have asked you for access to your photos. And possibly you are one of the “worried well” who wear or carry a device that collects your health data and sends it back to storage in a faraway country, for analysis.

So unless you live in a lead-lined concrete bunker without any access to internet connected devices, and you don’t have the need to pass by webcams or sensors, or use public transport or public services; then your data is being collected and shared. And for the majority of the time, you benefit from this enormously. The bus stop tells you exactly when the next bus is coming, you have easy access to services and entertainment fitted very well to your needs, and you can do most of your bank and utility transactions online in the peace and quiet of your own home. Beyond you as an individual, there are organisations “out there” sharing your data to provide you better healthcare, education, smarter city services and secure and efficient financial services, and generally matching the demand for services with the people needing them.

So we most likely all have data that is being shared and it is generally in our interest to share it, but how can we trust the organisations responsible for sharing our data? As an organisation, how can I know that my partner and supplier organisations are taking care of my client and product information?

Organisations taking these issues seriously are coming up with their own internal policy and guidelines. However, for data sharing between organisations to be straight forward, there needs to a common understanding of basic policy and practice. During my time as a visiting associate at the Oxford Internet Institute, University of Oxford, I have developed a pragmatic solution in the form of a Voluntary Code. The Code has been produced using the guidelines for voluntary code development produced by the Office of Community Affairs, Industry Canada. More importantly, the Code is anchored in the developing ISO standards for the Governance of Data (the 38505 series). These standards apply the governance principles and model from the 38500 standard and introduce the concept of a data accountability map, highlighting six focus areas for a governing body to apply governance. The early stage standard suggests considering the aspects of Value, Risk and Constraint for each area, to determine what practice and policy should be applied to maximise the value from organisational data, whilst applying constraints as set by legislation and local policy, and minimising risk.

I am Head of the New Zealand delegation to the ISO group developing IT Service Management and IT Governance standards, SC40, and am leading the development of the 38505 series of Governance of Data standards, working with a talented editorial team of industry and standards experts from Australia, China and the Netherlands. I am confident that the robust ISO consensus-led process involving subject matter experts from around the world, will result in the publication of best practice guidance for the governance of data, presented in a format that will have relevance and acceptance internationally.

In the meantime, however, I see a need to provide urgent advice to organisations struggling with policy for sharing data. I have used my time at Oxford to interview policy, ethics, smart city, open data, health informatics, education, cyber security and social science experts and users, owners and curators of large data sets, and have come up with a “Voluntary Code for Data Sharing”. The Code takes three areas from the data accountability map in the developing ISO standard 38505-1; namely Collect, Store, Distribute, and applies the aspects of Value, Risk and Constraint to provide seven maxims for sharing data. To assist with adoption and compliance, the Code provides references to best practice and examples. As the ISO standards for the Governance of Data develop, the Code will be updated. New examples of good practice will be added as they come to light.

[A permanent home for the voluntary code is currently being organised; please email me in the meantime if you are interested in it: Alison.holt@longitude174.com]

The Code is deliberately short and succinct, but it does provide links for those who need to read more to understand the underpinning practices and standards, and those tasked with implementing organisational data policy and practice. It cannot guarantee good outcomes. With new security threats arising daily, nobody can fully guarantee the safety of your information. However, if you deal with an organisation that is compliant with the Voluntary Code, then at least you can have assurance that the organisation has at least considered how it is using your data now and how it might want to reuse your data in the future, how and where your data will be stored, and then finally how your data will be distributed or discarded. And that’s a good start!

Alison Holt was an OII Academic Visitor in late 2015. She is an internationally acclaimed expert in the Governance of Information Technology and Data, heading up the New Zealand delegations to the international standards committees for IT Governance and Service Management (SC40) and Software and Systems Engineering (SC7). The British Computer Society published Alison’s first book on the Governance of IT in 2013.

To some extent the citizen-based response filled the gap left by the lack of a sufficient response from the traditional institutions.[1] This suggests that the role of ICTs in disaster response should be examined within the political context of the power relationship between members of the public who use digital tools and the traditional institutions. My experience in 2010 was the first time I was able to see that, while we would expect that in a case of natural disaster both the authorities and the citizens would be mostly concerned about the emergency, the actual situation might be different.

Apparently the emergence of independent, citizen-based collective action in response to a disaster was considered as some type of threat by the institutional actors. First, it was a threat to the image of these institutions, which didn’t want citizens to be portrayed as the leading responding actors. Second, any type of citizen-based collective action, even if not purely political, may be an issue of concern in authoritarian countries in particular. Accordingly, one can argue that, while citizens are struggling against a disaster, in some cases the traditional institutions may make substantial efforts to restrain and contain the action of citizens. In this light, the role of information technologies can include not only enhancing citizen engagement and increasing the efficiency of the response, but also controlling the digital crowd of potential volunteers.

The purpose of this paper was to conceptualize the tension between the role of ICTs in the engagement of the crowd and its resources, and the role of ICTs in controlling the resources of the crowd. The research suggests a theoretical and methodological framework that allows us to explore this tension. The paper focuses on an analysis of specific platforms and suggests empirical data about the structure of the platforms, and interviews with developers and administrators of the platforms. This data is used in order to identify how tools of engagement are transformed into tools of control, and what major differences there are between platforms that seek to achieve these two goals. That said, obviously any platform can have properties of control and properties of engagement at the same time; however the proportion of these two types of elements can differ significantly.

One of the core issues for my research is how traditional actors respond to fast, bottom-up innovation by citizens.[2]. On the one hand, the authorities try to restrict the empowerment of citizens by the new tools. On the other hand, the institutional actors also seek to innovate and develop new tools that can restore the balance of power that has been challenged by citizen-based innovation. The tension between using digital tools for the engagement of the crowd and for control of the crowd can be considered as one of the aspects of this dynamic.

That doesn’t mean that all state-backed platforms are created solely for the purpose of control. One can argue, however, that the development of digital tools that offer a mechanism of command and control over the resources of the crowd is prevalent among the projects that are supported by the authorities. This can also be approached as a means of using information technologies in order to include the digital crowd within the “vertical of power”, which is a top-down strategy of governance. That is why this paper seeks to conceptualize this phenomenon as “vertical crowdsourcing”.

The question of whether using a digital tool as a mechanism of control is intentional is to some extent secondary. What is important is that the analysis of platform structures relying on activity theory identifies a number of properties that allow us to argue that these tools are primarily tools of control. The conceptual framework introduced in the paper is used in order to follow the transformation of tools for the engagement of the crowd into tools of control over the crowd. That said, some of the interviews with the developers and administrators of the platforms may suggest the intentional nature of the development of tools of control, while crowd engagement is secondary.

[1] Asmolov G. “Natural Disasters and Alternative Modes of Governance: The Role of Social Networks and Crowdsourcing Platforms in Russia”, in Bits and Atoms Information and Communication Technology in Areas of Limited Statehood, edited by Steven Livingston and Gregor Walter-Drop, Oxford University Press, 2013.

[2] Asmolov G., “Dynamics of innovation and the balance of power in Russia”, in State Power 2.0 Authoritarian Entrenchment and Political Engagement Worldwide, edited by Muzammil M. Hussain and Philip N. Howard, Ashgate, 2013.

Read the full article: Asmolov, G. (2015) Vertical Crowdsourcing in Russia: Balancing Governance of Crowds and State–Citizen Partnership in Emergency Situations. Policy and Internet 7,3: 292–318.

Gregory Asmolov is a PhD student at the LSE, where he is studying crowdsourcing and emergence of spontaneous order in situations of limited statehood. He is examining the emerging collaborative power of ICT-enabled crowds in crisis situations, and aiming to investigate the topic drawing on evolutionary theories concerned with spontaneous action and the sustainability of voluntary networked organizations. He analyzes whether crowdsourcing practices can lead to development of bottom-up online networked institutions and “peer-to-peer” governance.

Australia’s new data retention law for telecommunications providers, comparable to extant UK and US legislation, came into effect 13 October 2015. Telecoms and ISPs are now required to retain metadata about communications for two years to assist law enforcement agencies in crime and terrorism investigation. Despite now being in effect, the extent and types of data to be collected remain unclear. The law has been widely criticised for violating Australians’ right to privacy by introducing overly broad surveillance of civilians. The Government has argued against this portrayal. They argue the content of communications will not be retained but rather the “data about the data” – location, time, date and duration of a call.

Metadata retention raises complex ethical issues often framed in terms of privacy which are relevant globally. A popular argument is that metadata offers a lower risk of violating privacy compared to primary data – the content of communication. The distinction between the “content” and “nature” of a communication implies that if the content of a message is protected, so is the privacy of the sender and receiver.

The assumption that metadata retention is more acceptable because of its lower privacy risks is unfortunately misguided. Sufficient volumes of metadata offer comparable opportunities to generate invasive information about civilians. Consider a hypothetical. I am given access to a mobile carrier’s dataset that specifies time, date, caller and receiver identity in addition to a continuous record of location constructed with telecommunication tower triangulation records. I see from this that when John’s wife Jane leaves the house, John often calls Jill and visits her for a short period from afterwards. From this I conclude that John may be having an affair with Jill. Now consider the alternative. Instead of metadata I have access to recordings of the calls between John and Jill with which I reach the same conclusion.

From a privacy perspective the method I used to infer something about John’s marriage is trivial. In both cases I am making an intrusive inference about John based on data that describes his behaviours. I cannot be certain but in both cases I am sufficiently confident that my inference is correct based on the data available. My inferences are actionable – I treat them as if they are reliable, accurate knowledge when interacting with John. It is this willingness to act on uncertainty (which is central to ‘Big Data’) that makes metadata ethically similar to primary data. While it is comparatively difficult to learn something from metadata, the potential is undeniable. Both types allow for invasive inferences to be made about the lives and behaviours of people.

Going further, some would argue that metadata can actually be more invasive than primary data. Variables such as location, time and duration are easier to assemble into a historical record of behaviour than content. These concerns are deepened by the difficulty of “opting out” of metadata surveillance. While a person can hypothetically forego all modern communication technologies, privacy suddenly has a much higher cost in terms of quality of life.

Technologies such as encrypted communication platforms, virtual private networks (VPN) and anonymity networks have all been advocated as ways to subvert metadata collection by hiding aspects of your communications. It is worth remembering that these techniques remain feasible only so long as they remain legal, one has the technical knowledge and (in some cases) ability to pay. These technologies raise a question of whether a right to anonymity exists. Perhaps privacy enhancing technologies are immoral? Headlines about digital piracy and the “dark web” show how quickly technologically hiding one’s identity and behaviours can take on a criminal and immoral tone. The status quo of privacy subtly shifts when techniques to hide aspects of one’s personal life are portrayed as necessarily subversive. The technologies to combat metadata retention are not criminal or immoral – they are privacy enhancing technologies.

Privacy is historically a fundamental human value. Individuals have a right to privacy. Violations must be justified by a competing interest. In discussing the ethics of metadata retention and anonymity technologies it is easy to forget this status quo. Privacy is not something that individuals have to justify or argue for – it should be assumed.

Brent Mittelstadt is a Postdoctoral Research Fellow at the Oxford Internet Institute working on the ‘Ethics of Biomedical Big Data‘ project with Prof. Luciano Floridi. His research interests include the ethics of information handled by medical ICT, theoretical developments in discourse and virtue ethics, and epistemology of information.

Crowdsourcing is a recent buzzword that describes efforts to use the Internet to mobilize online communities to achieve specific organizational goals. While crowdsourcing serves several purposes, the most interesting potential from a democratic perspective is the ability to crowdsource legislation. By giving citizens the means to affect the legislative process more directly, crowdsourcing legislation is an example of a democratic innovation that gives citizens a say in the legislative process. Recent years have witnessed a scholarly debate on whether such new forms of participatory governance can help cure democratic deficits such as a declining political legitimacy of the political system in the eyes of the citizenry. However, it is still not clear how taking part in crowdsourcing affects the political attitudes of the participants, and the potential impact of such democratic innovations therefore remain unclear.

In our study, we contribute to this research agenda by exploring how crowdsourcing citizens’ initiatives affected political attitudes in Finland. The non-binding Citizens’ Initiative instrument in Finland was introduced in spring 2012 to give citizens the chance to influence the agenda of the political decision making. In particular, we zoom in on people active on the Internet website Avoin Ministeriö (Open Ministry), which is a site based on the idea of crowdsourcing where users can draft citizens’ initiatives and deliberate on their contents. As is frequently the case for studies of crowdsourcing, we find that only a small portion of the users are actively involved in the crowdsourcing process. The option to deliberate on the website was used by about 7% of the users; the rest were only passive readers or supported initiatives made by others. Nevertheless, Avoin Ministeriö has been instrumental in creating support for several of the most successful initiatives during the period, showing that the website has been a key actor during the introductory phase of the Citizens’ initiative in Finland.

We study how developments in political attitudes were affected by outcome satisfaction and process satisfaction. Outcome satisfaction concerns whether the participants get their preferred outcome through their involvement, and this has been emphasized by proponents of direct democracy. Since citizens get involved to achieve a specific outcome, their evaluation of the experience hinges on whether or not they achieve this outcome. Process satisfaction, on the other hand, is more concerned with the perceived quality of decision making. According to this perspective, what matters is that participants find that their concerns are given due consideration. When people find the decision making to be fair and balanced, they may even accept not getting their preferred outcome. The relative importance of these two perspectives remains disputed in the literature.

The research design consisted of two surveys administered to the users of Avoin Ministeriö before and after the decision of the Finnish Parliament on the first citizens’ initiative in concerning a ban on the fur-farming industry in Finland. This allowed us to observe how involvement in the crowdsourcing process shaped developments in central political attitudes among the users of Avoin Ministeriö and what factors determined the developments in subjective political legitimacy. The first survey was conducted in fall 2012, when the initiators were gathering signatures in support of the initiative to ban fur-farming, while the second survey was conducted in summer 2013 when Parliament rejected the initiative. Altogether 421 persons filled in both surveys, and thus comprised the sample for the analyses.

The study yielded a number of interesting findings. First of all, those who were dissatisfied with Parliament rejecting the initiative experienced a significantly more negative development in political trust compared to those who did not explicitly support the initiative. This shows that the crowdsourcing process had a negative impact on political legitimacy among the initiative’s supporters, which is in line with previous contributions emphasizing the importance of outcome legitimacy. It is worth noting that this also affected trust in the Finnish President, even if he has no formal powers in relation to the Citizens’ initiative in Finland. This shows that negative effects on political legitimacy could be more severe than just a temporary dissatisfaction with the political actors responsible for the decision.

Nevertheless, the outcome may not be the most important factor for determining developments in political legitimacy. Our second major finding indicated that those who were dissatisfied with the way Parliament handled the initiative also experienced more negative developments in political legitimacy compared to those who were satisfied. Furthermore, this effect was more pervasive than the effect for outcome satisfaction. This implies that the procedures for handling non-binding initiatives may play a strong role in citizens’ perceptions of representative institutions, which is in line with previous findings emphasising the importance of procedural aspects and evaluations for judging political authorities.

We conclude that there is a beneficial impact on political legitimacy if crowdsourced citizens’ initiatives have broad appeal so they can be passed in Parliament. However, it is important to note that positive effects on political legitimacy do not hinge on Parliament approving citizens’ initiatives. If the MPs invest time and resources in the careful, transparent and publicly justified handling of initiatives, possible negative effects of rejecting initiatives can be diminished. Citizens and activists may accept an unfavourable decision if the procedure by which it was reached seems fair and just. Finally, the results give reason to be hopeful about the role of crowdsourcing in restoring political legitimacy, since a majority of our respondents felt that the possibility of crowdsourcing citizens’ initiatives clearly improved Finnish democracy.

While all hopes may not have been fulfilled so far, crowdsourcing legislation therefore still has potential to help rebuild political legitimacy.

Read the full article: Christensen, H., Karjalainen, M., and Nurminen, L., (2015) Does Crowdsourcing Legislation Increase Political Legitimacy? The Case of Avoin Ministeriö in Finland. Policy and Internet 7 (1) 25–45.

Henrik Serup Christensen is Academy Research Fellow at SAMFORSK, Åbo Akademi University.

Maija Karjalainen is a PhD Candidate at the Department of Political Science and Contemporary History in the University of Turku, Finland.

Laura Nurminen is a Doctoral Candidate at the Department of Political and Economic Studies at Helsinki University, Finland.

Ed: There is much discussion about a perceived “legitimacy crisis” in democracy. For example, less than half of the Finnish electorate under 40 choose to vote. In your article you argue that Finland’s 2012 Citizens’ Initiative Act aimed to address this problem by allowing for the crowdsourcing of ideas for new legislation. How common is this idea? (And indeed, how successful?)

Taneli: The idea that digital participation could counter the “legitimacy crisis” is a fairly common one. Digital utopians have nurtured that idea from the early years of the internet, and have often been disappointed. A couple of things stand out in the Finnish experiment that make it worth a closer look.

First, the digital crowdsourcing system with strong digital identification is a reliable and potentially viral campaigning tool. Most civic initiative systems I have encountered rely on manual or otherwise cumbersome, and less reliable, signature collection methods.

Second, in the Finnish model, initiatives that break the threshold of 50,000 names must be treated in the Parliament equally to an initiative from a group of MPs. This gives the initiative constitutional and political weight.

Ed: The Act led to the passage of Finland’s first equal marriage law in 2014. In this case, online platforms were created for collecting signatures as well as drafting legislation. An NGO created a well-used platform, but it subsequently had to shut it down because it couldn’t afford the electronic signature system. Crowds are great, but not a silver bullet if something as prosaic as authentication is impossible. Where should the balance lie between NGOs and centrally funded services, i.e. government?

Taneli: The crucial thing in the success of a civic initiative system is whether it gives the people real power. This question is decided by the legal framework and constitutional basis of the initiative system. So, governments have a very important role in this early stage – designing a law for truly effective citizen initiatives.

When a framework for power-making is in place, service providers will emerge. Should the providers be public, private or third sector entities? I think that is defined by local political culture and history.

In the United States, the civic technology field is heavily funded by philanthropic foundations. There is an urge to make these tools commercially viable, though no one seems to have figured out the business model. In Europe there’s less philanthropic money, and in my experience experiments are more often government funded.

Both models have their pros and cons, but I’d like to see the two continents learning more from each other. American digital civic activists tell me enviously that the radically empowering Finnish model with a government-run service for crowdsourcing for law would be impossible in the US. In Europe, civic technologists say they wish they had the big foundations that Americans have.

Ed: But realistically, how useful is the input of non-lawyers in (technical) legislation drafting? And is there a critical threshold of people necessary to draft legislation?

Taneli: I believe that input is valuable from anyone who cares to invest some time in learning an issue. That said, having lawyers in the campaign team really helps. Writing legislation is a special skill. It’s a pity that the co-creation features in Finland’s Open Ministry website were shut down due to a lack of funding. In that model, help from lawyers could have been made more accessible for all campaign teams.

In terms of numbers, I don’t think the size of the group is an issue either way. A small group of skilled and committed people can do a lot in the drafting phase.

Ed: But can the drafting process become rather burdensome for contributors, given professional legislators will likely heavily rework, or even scrap, the text?

Taneli: Professional legislators will most likely rework the draft, and that is exactly what they are supposed to do. Initiating an idea, working on a draft, and collecting support for it are just phases in a complex process that continues in the parliament after the threshold of 50,000 signatures is reached. A well-written draft will make the legislators’ job easier, but it won’t replace them.

Ed: Do you think there’s a danger that crowdsourcing legislation might just end up reflecting the societal concerns of the web-savvy – or of campaigning and lobbying groups

Taneli: That’s certainly a risk, but so far there is little evidence of it happening. The only initiative passed so far in Finland – the Equal Marriage Act – was supported by the majority of Finns and by the majority of political parties, too. The initiative system was used to bypass a political gridlock. The handful of initiatives that have reached the 50,000 signatures threshold and entered parliamentary proceedings represent a healthy variety of issues in the fields of education, crime and punishment, and health care. Most initiatives seem to echo the viewpoint of the ‘ordinary people’ instead of lobbies or traditional political and business interest groups.

Ed: You state in your article that the real-time nature of digital crowdsourcing appeals to a generation that likes and dislikes quickly; a generation that inhabits “the space of flows”. Is this a potential source of instability or chaos? And how can this rapid turnover of attention be harnessed efficiently so as to usefully contribute to a stable and democratic society?

Taneli: The Citizens’ Initiative Act in Finland is one fairly successful model to look at in terms of balancing stability and disruptive change. It is a radical law in its potential to empower the individual and affect real power-making. But it is by no means a shortcut to ‘legislation by a digital mob’, or anything of that sort. While the digital campaigning phase can be an explosive expression of the power of the people in the ‘time and space of flows’, the elected representatives retain the final say. Passing a law is still a tedious process, and often for good reasons.

Ed: You also write about the emergence of the “mediating citizen” – what do you mean by this?

Taneli: The starting point for developing the idea of the mediating citizen is Lance Bennett’s AC/DC theory, i.e. the dichotomy of the actualising and the dutiful citizen. The dutiful citizen is the traditional form of democratic citizenship – it values voting, following the mass media, and political parties. The actualising citizen, on the other hand, finds voting and parties less appealing, and prefers more flexible and individualised forms of political action, such as ad hoc campaigns and the use of interactive technology.

I find these models accurate but was not able to place in this duality the emerging typologies of civic action I observed in the Finnish case. What we see is understanding and respect for parliamentary institutions and their power, but also strong faith in one’s skills and capability to improve the system in creative, technologically savvy ways. I used the concept of the mediating citizen to describe an actor who is able to move between the previous typologies, mediating between them. In the Finnish example, creative tools were developed to feed initiatives in the traditional power-making system of the parliament.

Ed: Do you think Finland’s Citizens Initiative Act is a model for other governments to follow when addressing concerns about “democratic legitimacy”?

Taneli: It is an interesting model to look at. But unfortunately the ‘legitimacy crisis’ is probably too complex a problem to be solved by a single participation tool. What I’d really like to see is a wave of experimentation, both on-line and off-line, as well as cross-border learning from each other. And is that not what happened when the representative model spread, too?

Read the full article: Heikka, T., (2015) The Rise of the Mediating Citizen: Time, Space, and Citizenship in the Crowdsourcing of Finnish Legislation. Policy and Internet 7 (3) 268–291.

Taneli Heikka is a journalist, author, entrepreneur, and PhD student based in Washington.

Taneli Heikka was talking to Blog Editor Pamina Smith.

Simo: Over the years we’ve deployed various types of interactive interfaces on a network of public displays. In this case it was basically a network of interactive screens deployed in downtown Oulu, next to where a renovation project was happening that we wanted to collect feedback about. We deployed an app on the screens, that allowed people to type feedback direcly on the screens (on-screen soft keyboard), and submit feedback to city authorities via SMS, Twitter and email. We also had a smiley-based “rating” system there, which people could us to leave quick feedback about certain aspects of the renovation project.

We ourselves could not, and did not even want to, assess the impact — that’s why we did this in partnership with the city authorities. Then, together with the city folks we could better evaluate if what we were doing had any real-world value whatsoever. And, as we discuss, in the end it did!

Ed: How did you go about encouraging citizens to engage with touch screen technologies in a public space — particularly the non-digitally literate, or maybe people who are just a bit shy about participating?

Simo: Actually, the whole point was that we did not deliberately encourage them by advertising the deployment or by “forcing” anyone to use it. Quite to the contrary: we wanted to see if people voluntarily used it, and the technologies that are an integral part of the city itself. This is kind of the future vision of urban computing, anyway. The screens had been there for years already, and what we wanted to see is if people find this type of service on their own when exploring the screens, and if they take the opportunity to then give feedback using them. The screens hosted a variety of other applications as well: games, news, etc., so it was interesting to also gauge how appealing the idea of public civic feedback is in comparison to everything else that was being offered.

Ed: You mention that using SMS to provide citizen feedback was effective in filtering out noise since it required a minimal payment from citizens — but it also created an initial barrier to participation. How do you increase the quality of feedback without placing citizens on different-level playing fields from the outset — particularly where technology is concerned?

Simo: Yes, SMS really worked well in lowering the amount of irrelevant commentary and complete nonsense. And it is true that SMS already introduces a cost, and even if the cost is miniscule, it’s still a cost to the citizen — and just voicing one’s opinions should of course be free. So there’s no correct answer here — if the channel is public and publicly accessible to anyone, there will be a lot of noisy input. In such cases moderation is a heavy task, and to this end we have been exploring crowdsourcing as well. We can make the community moderate itself. First, we need to identify the users who are genuinely concerned or interested about the issues being explored, and then funnel those users to moderate the discussion / output. It is a win-win situation — the people who want to get involved are empowered to moderate the commentary from others, for implicit rewards.

Ed: For this experiment on citizen feedback in an urban space, your team assembled the world’s largest public display network, which was available for research purposes 24/7. In deploying this valuable research tool, how did you guarantee the privacy of the participants involved, given that some might not want to be seen submitting very negative comments? (e.g. might a form of social pressure be the cause of relatively low participation in the study?)

Simo: The display network was not built only for this experiment, but we have run hundreds of experiments on it, and have written close to a hundred academic papers about them. So, the overarching research focus, really, is on how we can benefit citizens using the network. Over the years we have been able to systematically study issues such as social pressure, group use, effects of the public space, or, one might say “stage”, etc. And yes, social pressure does affect a lot, and for this allowing people participate via e.g. SMS or email helps a lot. That way the users won’t be seen sending the input directly.

Group use is another thing: in groups people don’t feel pressure from the “outside world” so much and are willing to interact with our applications (such as the one documented in this work), but, again, it affects the feedback quality. Groups don’t necessarily tell the truth as they aim for consensus. So the individual, and very important, opinions may not become heard. Ultimately, this is all just part of the game we must deal with, and the real question becomes how to minimize those negative effects that the public space introduces. The positives are clear: everyone can participate, easily, in the heart of the city, and whenever they want.

Ed: Despite the low participation, you still believe that the experimental results are valuable. What did you learn?

Simo: The question in a way already reveals the first important point: people are just not as interested in these “civic” things as they might claim in interviews and pre-studies. When we deploy a civic feedback prototype as the “only option” on a public gizmo (a display, some kind of new tech piece, etc.), people out of curiosity use it. Now, in our case, we just deploy it “as is”, as part of the city infrastructure for people to use if, and only if, they want to use it. So, the prototype competes for attention against smartphones, other applications on the displays, the cluttered city itself… everything!

When one reads many academic papers on interactive civic engagement prototypes, the assumptions are set very high in the discussion: “we got this much participation in this short time”, etc., but that’s not the entire truth. Leave the thing there for months and see if it still interests people! We have done the same, deployed a prototype for three days, gotten tons of interaction, published it, and learned only afterwards that “oh, maybe we were a bit optimistic with the efficiency” when the use suddenly dropped to minimum. It’s just not that easy and the application require frequent updates to keep user interest longitudinally.

Also, the radical differences in the feedback channels were surprising, but we already talked about that a bit earlier.

Ed: Your team collaborated with local officials, which is obviously valuable (and laudable), but it can potentially impose an extra burden on academics. For example, you mention that instead of employing novel feedback formats (e.g. video, audio, images, interactive maps), your team used only text. But do you think working with public officials benefitted the project as a whole, and how?

Simo: The extra burden is a necessity if one wants to really claim authentic success in civic engagement. In our opinion, it only happens between citizens and the city, not between citizens and researchers. We do not wish to build these deployments for the sake of an academic article or two: the display infrastructure is there for citizens and the city, and if we don’t educate the authorities on how to use it then nobody will. Advertisers would be glad to take over the entire real estate there, so in a way this project is just a part of the bigger picture. Which is making the display infrastructure “useful” instead of just a gimmick to kill time with (games) or for advertising.

And yes, the burden is real, but also because of this we could document what we have learned about dealing with authorities: how it is first easy to sell these prototypes to them, but sometimes hard to get commitment, etc. And it is not just this prototype — we’ve done a number of other civic engagement projects where we have noticed the same issues mentioned in the paper as well.

Ed: You also mention that as academics and policymakers you had different notions of success: for example in terms of levels of engagement and feedback of citizens. What should academics aspiring to have a concrete impact on society keep in mind when working with policymakers?

Simo: It takes a lot of time to assess impact. Policymakers will not be able to say after only a few weeks (which is the typical length of studies in our field) if the prototype has actual value to it, or if it’s just a “nice experiment”. So, deploy your strategy / tech / anything you’re doing, write about it, and let it sit. Move on with the life, and then revisit it after months to see if anything has come out of it! Patience is key here.

Ed: Did the citizen feedback result in any changes to the urban renovation project they were being consulted on?

Simo: Not the project directly: the project naturally was planned years ahead and the blueprints were final at that point. The most remarkable finding for us (and the authorities) was that after moderating the noise out from the feedback, the remaining insight was pretty much the only feedback that they ever directly got from citizens. Finns tend to be a bit on the shy side, so people won’t just pick up the phone and call the local engineering department and speak out. Not sure if anyone does, really? So they complain and chat on forums and coffee tables. So it would require active work for the authorities to find and reach out to these people.

With the display infrastructure, which was already there, we were able to gauge the public opinion that did not affect the construction directly, but indirectly affected how the department could manage their press releases, which things to stress in public communications, what parts of PR to handle differently in the next stage of the renovation project etc.

Ed: Are you planning any more experiments?

Simo: We are constantly running quite a few experiments. On the civic engagement side, for example, we are investigating how to gamify environmental awareness (recycling, waste management, keeping the environment clean) for children, as well as running longer longitudinal studies to assess the engagement of specify groups of people (e.g., children and the elderly).

Read the full article: Hosio, S., Goncalves, J., Kostakos, V. and Riekki, J. (2015) Crowdsourcing Public Opinion Using Urban Pervasive Technologies: Lessons From Real-Life Experiments in Oulu. Policy and Internet 7 (2) 203–222.

Simon Hosio is a research scientist (Dr. Tech.) at the University of Oulu, in Finland. Core topics of his research are smart city tech, crowdsourcing, wisdom of the crowd, civic engagement, and all types of “mobile stuff” in general.

Simo Hosio was talking to blog editor Pamina Smith.

We examined two recent Internet governance initiatives which incorporated crowdsourcing with mixed results: the first one, the ICANN Strategy Panel on Multistakeholder Innovation, received only limited support from the online community; the second, NETmundial, had a significant number of online inputs from global stakeholders who had the opportunity to engage using a platform for political participation specifically set up for the drafting of the outcome document. The study builds on these two cases to evaluate how crowdsourcing was used as a form of public consultation aimed at bringing the online voice of the “undefined many” (as opposed to the “elected few”) into Internet governance processes.

From the two cases, it emerged that the design of the consultation processes conducted via crowdsourcing platforms is key in overcoming barriers of participation. For instance, in the NETmundial process, the ability to submit comments and participate remotely via www.netmundial.br attracted inputs from all over the world very early on, since the preparatory phase of the meeting. In addition, substantial public engagement was obtained from the local community in the drafting of the outcome document, through a platform for political participation — www.participa.br — that gathered comments in Portuguese. In contrast, the outreach efforts of the ICANN Strategy Panel on Multistakeholder Innovation remained limited; the crowdsourcing platform they used only gathered input (exclusively in English) from a small group of people, insufficient to attribute to online public input a significant role in the reform of ICANN’s multistakeholder processes.

Second, questions around how crowdsourcing should and could be used effectively to enhance the legitimacy of decision-making processes in Internet governance remain unanswered. A proper institutional setting that recognizes a role for online multistakeholder participation is yet to be defined; in its absence, the initiatives we examined present a set of procedural limitations. For instance, in the NETmundial case, the Executive Multistakeholder Committee, in charge of drafting an outcome document to be discussed during the meeting based on the analysis of online contributions, favoured more “mainstream” and “uncontroversial” contributions. Additionally, online deliberation mechanisms for different propositions put forward by a High-Level Multistakeholder Committee, which commented on the initial draft, were not in place.

With regard to ICANN, online consultations have been used on a regular basis since its creation in 1998. Its target audience is the “ICANN community,” a group of stakeholders that volunteer their time and expertise to improve policy processes within the organization. Despite the effort, initiatives such as the 2000 global election for the new At-Large Directors have revealed difficulties in reaching as broad of an audience as wanted. Our study discusses some of the obstacles of the implementation of this ambitious initiative, including limited information and awareness about the At-Large elections, and low Internet access and use in most developing countries, particularly in Africa and Latin America.

Third, there is a need for clear rules regarding the way in which contributions are evaluated in crowdsourcing efforts. When the deliberating body (or committee) is free to disregard inputs without providing any motivation, it triggers concerns about the broader transnational governance framework in which we operate, as there is no election of those few who end up determining which parts of the contributions should be reflected in the outcome document. To avoid the agency problem arising from the lack of accountability over the incorporation of inputs, it is important that crowdsourcing attempts pay particular attention to designing a clear and comprehensive assessment process.

The “wisdom of the crowd” has traditionally been explored in developing the Internet, yet it remains a contested ground when it comes to its governance. In multistakeholder set-ups, the diversity of voices and the collection of ideas and input from as many actors as possible — via online means — represent a desideratum, rather than a reality. In our exploration of empowerment through online crowdsourcing for institutional reform, we identify three fundamental preconditions: first, the existence of sufficient community interest, able to leverage wide expertise beyond a purely technical discussion; second, the existence of procedures for the collection and screening of inputs, streamlining certain ideas considered for implementation; and third, commitment to institutionalizing the procedures, especially by clearly defining the rules according to which feedback is incorporated and circumvention is avoided.

Read the full paper: Radu, R., Zingales, N. and Calandro, E. (2015), Crowdsourcing Ideas as an Emerging Form of Multistakeholder Participation in Internet Governance. Policy & Internet, 7: 362–382. doi: 10.1002/poi3.99

Roxana Radu is a PhD candidate in International Relations at the Graduate Institute of International and Development Studies in Geneva and a fellow at the Center for Media, Data and Society, Central European University (Budapest). Her current research explores the negotiation of internet policy-making in global and regional frameworks.

Nicolo Zingales is an assistant professor at Tilburg law school, a senior member of the Tilburg Law and Economics Center (TILEC), and a research associate of the Tilburg Institute for Law, Technology and Society (TILT). He researches on various aspects of Internet governance and regulation, including multistakeholder processes, data-driven innovation and the role of online intermediaries.

Enrico Calandro (PhD) is a senior research fellow at Research ICT Africa, an ICT policy think-tank based based in Cape Town. His academic research focuses on accessibility and affordability of ICT, broadband policy, and internet governance issues from an African perspective.

When barrister Charlotte Proudman recently spoke out regarding a sexist comment that she had received on the professional networking website LinkedIn, hundreds of women praised her actions in highlighting the issue of workplace sexism – and many of them began to tell similar stories of their own. It soon became apparent that Proudman was not alone in experiencing this kind of sexism, a fact further corroborated by Laura Bates of the Everyday Sexism Project, who asserted that workplace harassment is “the most reported kind of incident” on the project’s UK website.

Proudman’s experience and Bates’ comments on the number of submissions to her site concerning harassment at work provokes a conversation about the nature of sexism, not only in the UK but also at a global level. We know that since its launch in 2012, the Everyday Sexism Project has received over 100,000 submissions in more than 13 different languages, concerning a variety of topics. But what are these topics? As Bates has stated, in the UK, workplace sexism is the most commonly discussed subject on the website – but is this also the case for the Everyday Sexism sites in France, Japan, or Brazil? What are the most common types of sexism globally, and (how) do they relate to each other? Do experiences of sexism change from one country to another?

The multi-lingual reports submitted to the Everyday Sexism project are undoubtedly a gold mine of crowdsourced information with great potential for answering important questions about instances of sexism worldwide, as well as drawing an overall picture of how sexism is experienced in different societies. So far much of the research relating to the Everyday Sexism project has focused on qualitative content analysis, and has been limited to the submissions written in English. Along with Principal Investigators Taha Yasseri and Kathryn Eccles, I will be acting as Research Assistant on a new project funded by the John Fell Oxford University Press Research Fund, that hopes to expand the methods used to investigate Everyday Sexism submission data, by undertaking a large-scale computational study that will enrich existing qualitative work in this area.

Entitled “Semantic Mapping of Sexism: Topic Modelling of Everyday Sexism Content”, our project will take a Natural Language Processing approach, analysing the content of Everyday Sexism reports in different languages, and using topic-modelling techniques to extract the most commonly occurring sexism-related topics and concepts from the submissions. We will map the semantic relations between those topics within and across different languages, comparing and contrasting the ways in which sexism is experienced in everyday life in different cultures and geographies. Ultimately, we hope to create the first data-driven map of sexism on a global scale, forming a solid framework for future studies in growing fields such as online inequality, cyber bullying, and social well being.

We’re very excited about the project and will be charting our progress via the Policy and Internet Blog, so make sure to check back for further updates!

To maintain an open and working Internet, we need to make sense of how the complex and decentralised technical system operates. Research groups, governments, and companies have dedicated teams working on highly technical research and experimentation to make sense of information flows and how these can be affected by new developments, be they intentional or due to unforeseen consequences of decisions made in another domain.

These teams, composed of network engineers and computer scientists, therefore analyse Internet data transfers, typically by collecting data from devices of large groups of individuals as well as organisations. The Internet, however, has become a complex and global socio-technical information system that mediates a significant amount of our social or professional activities, relationships, as well as mental processes. Experimentation and research on the Internet therefore require ethical scrutiny in order to give useful feedback to engineers and researchers about the social impact of their work.

The organising committee of the Association of Computing Machinery (ACM) SigComm (Signal Communications) conference has regularly encountered paper submissions that can be considered dubious from an ethical point of view. A strong debate on the research ethics of the ACM was sparked by the paper entitled “Encore: Lightweight Measurement of Web Censorship with Cross-Origin Requests,” among others submitted for the 2015 conference. In the study, researchers directed unsuspecting Internet users to test potential censorship systems in their country by directing their browser to specified URLs that could be blocked in their jurisdiction. Concerns were raised about whether this could be considered ‘human subject research’ and whether the unsuspecting users could be harmed as a result of this experiment. Consider, for example, a Chinese citizen continuously requesting the Falun Gong website from their Beijing-based laptop with no knowledge of this occurring whatsoever.

As a result of these discussions, the ACM realised that there was no formal procedure or methodology in place to make informed decisions about the ethical dimensions of such research. The conference therefore hosted a one-day workshop led by the OII’s Ethics in Networked Systems Research (ENSR) project. The day brought together 55 participants from different academic disciplines, ranging from computer science to philosophy, law, sociology, and social science. As part of a broader mission to establish ethical guidelines for Internet research, the aim of the workshop was to inform participants about the pressing ethical issues of the network measurement discipline, and to exchange ideas, reasoning, and proposed solutions.

The workshop began with two interactive sessions in which participants split into small, multidisciplinary groups to debate the submitted papers. Participants recorded their thoughts on key issues that emerged in the discussions. The remaining sessions of the day concentrated on the main themes surfacing from these notes as well as the active feedback of attendees. In this manner, participants from both sides of the debate — that is, the technical researchers and the non-technical researchers — were able to continually quiz each other about the strengths and weaknesses of their approach. The workshop’s emphasis on collaboration across academic disciplines, thereby creating an interdisciplinary community of researchers interested in Internet ethics, aimed to create a more solid foundation for building functional ethical standards in this area.

The interactive discussions yielded some particularly interesting recommendations regarding both the general ethical governance of computer science research as well as particular pressing issues. The main suggestion of the workshop was to create a procedure for an iterative approach to ethical review, whereby the relevant authority (e.g. conference programme committee, institutional ethics board, journal editor, funding agencies) and the researchers could engage in a dialogue about the impact of research, rather than have these restricted by a top-down, one-time decision of the authority.

This approach could be supported by the guidelines that the OII’s ENSR project is currently drafting. Further, participants explored to what extent computer ethics can be taught as part of every module of computer science degrees, rather than the current generic ethics courses generally taught to engineering students. This adjustment would thereby allow aspiring technical researchers to develop a hands-on sense of the social and ethical implications of new technologies and methodologies. Participants agreed that this idea would take an intensive department-wide effort, but would be very worthwhile in the end.

In more practical discussions, participants exchanged views on a wide range of potential solutions or approaches to ethical issues resulting from Internet research. For example, technical researchers struggling with obtaining  informed consent were advised to focus their efforts on user-risk mitigation (with many nuances that exceed this blog post). For those studying the Internet in foreign countries, participants recommended running a few probes with the proposed methodology. This exploratory study would then serve to underpin an informed discussion on the possible social implications of the project with organizations and researchers who are more knowledgeable of the local context (e.g. anthropologists, sociologists or NGOs, among others).

Other concrete measures proposed to improve academic research included: fictionalizing rejected case studies to help researchers understand reasons for rejection without creating a ‘hall of shame’; generating a list of basic ethical questions that all papers should answer in the proposal phase; and starting a dialogue with other research communities in analogous situations concerning ethics.

The workshop comprised some high-level discussions to get participants on the same page, and deep dives into specific topics to generate some concrete solutions. As participants wrote down their thoughts on post-it notes, the next steps will be to categorise these notes, develop initial draft guidelines, and discuss these with all participants on the dedicated mailing list.

If you would like to join this mailing list, please e-mail bendert.zevenbergen [at] oii.ox.ac.uk! More detailed write-ups of the workshop outcomes will be published in due course.

Ben Zevenbergen is a student at the Oxford Internet Institute pursuing a DPhil on the intersection of privacy law, technology, social science, and the Internet. He runs a side project that aims to establish ethics guidelines for Internet research, as well as working in multidisciplinary teams such as the EU funded Network of Excellence in Internet Science. He has worked on legal, political and policy aspects of the information society for several years. Most recently he was a policy advisor to an MEP in the European Parliament, working on Europe’s Digital Agenda. Previously Ben worked as an ICT/IP lawyer and policy consultant in the Netherlands. Ben holds a degree in law, specialising in Information Law.

Pamina Smith currently serves as an Assistant Editor at the Oxford Internet Institute and recently completed an MPhil in Comparative Social Policy at the University of Oxford. She previously worked as Assistant Policy Officer at the European Commission, handling broadband policy and telecommunications regulation, and has a degree in the History and Literature of Modern Europe from Harvard College.

If you heard that a group of people were creating, editing, and maintaining Wikipedia articles related to brands, firms and individuals, you could point out, correctly, that this is the entire point of Wikipedia. It is, after all, the “encyclopedia that anyone can edit”.

But a group has been creating and editing articles for money. Wikipedia administrators banned more than 300 suspect accounts involved, but those behind the ring are still unknown.

For most Wikipedians, the editors and experts who volunteer their time and effort to develop and maintain the world’s largest encyclopedia for free, this is completely unacceptable. However, what the group was doing was not illegal – although it is prohibited by Wikipedia’s policies – and as it’s extremely hard to detect it’s difficult to stamp out entirely.

Conflicts of interest in those editing articles has been part of Wikipedia from the beginning. In the early days, a few of the editors making the most contributions wanted a personal Wikipedia entry, at least as a reward for their contribution to the project. Of course most of these were promptly deleted by the rest of the community for not meeting the notability criteria.

As Wikipedia grew and became the number one source of free-to-access information about everything, so Wikipedia entries rose up search engines rankings. Being well-represented on Wikipedia became important for any nation, organisation, firm, political party, entrepreneur, musician, and even scientists. Wikipedians have strived to prohibit self-serving editing, due to the inherent bias that this would introduce. At the same time, “organised” problematic editing developed despite their best efforts.

The glossy sheen of public relations

The first time I learned of non-Wikipedians taking an organised approach to editing articles I was attending a lecture by an “online reputation manager” in 2012. I didn’t know of her, so I pulled up her Wikipedia entry.

It was readily apparent that the article was filled with only positive things. So I did a bit of research about the individual and edited the article to try and introduce a more neutral point of view: softened language, added references and [citation needed] tags where I couldn’t find reference material to back up an important statement.

Online reputation mangers and PR firms charge celebrities and “important” people to, among other things, groom Wikipedia pages and fool search engines to push less favourable search results further down the page when their name is searched for. And they get caught doing it, againand again and again.

Separating fact from fiction

It is not that paid-for or biased editing is so problematic in itself, but the value that many associate with the information found in Wikipedia entries. For example, in academia, professors with Wikipedia entries might be considered more important than those without. Our own research has shown that scholars with Wikipedia articles have no greater statistically significant scientific impact than those without. So why do some appear on Wikipedia while others do not? The reason is clear: because many of those entries are written by themselves or their students or colleagues. It’s important that this aspect of Wikipedia should be communicated to those reading it, and remembered every single time you’re using it.

The arrival of [citation needed] tags is a good way to alert readers to the potential for statements to be unsafe, unsupported, or flat-out wrong. But these days Google has incorporated Wikipedia articles into its search results, so that an infobox at the right side of the results page will display the information – having first stripped such tags out, presenting it as referenced and reliable information.

A critical eye

Apart from self-editing that displays obvious bias, we know that Wikipedia, however amazing it is, has other shortcomings. Comparing Wikipedia’s different language versions to see the topics they find controversial reveals the attitudes and obsessions of writers from different nations. For example, English Wikipedia is obsessed with global warming, George W Bush and the World Wrestling Federation, the German language site by Croatia and Scientology, Spanish by Chile, and French by Ségolène Royal, homosexuality and UFOs. There are lots of edit warsbehind the scenes, many of which are a lot of fuss about absolutely nothing.

It’s not that I’d suggest abandoning the use of Wikipedia, but a bit of caution and awareness in the reader of these potential flaws is required. And more so, it’s required by the many organisations, academics, journalists and services of all kind including Google itself that scrape or read Wikipedia unthinkingly assuming that it’s entirely correct.

Were everyone to approach Wikipedia with a little more of a critical eye, eventually the market for paid editing would weaken or dissolve.

Though there is nothing qualitatively new about involving more people in government and policy processes, digital technologies in principle make it possible to increase the quantity of such involvement dramatically, by lowering the costs of participation (Margetts et al., 2015) and making it possible to tap into people’s free time (Shirky, 2010). This difference in quantity is arguably great enough to obtain a quality of its own. We can thus be justified in using the term “crowdsourcing for public policy and government” to refer to new digitally enabled ways of involving people in any aspect of democratic politics and government, not replacing but rather augmenting more traditional participation routes such as elections and referendums.

In this editorial, we will briefly highlight some of the key emerging issues in research on crowdsourcing for public policy and government. Our entry point into the discussion is a collection of research papers first presented at the Internet, Politics & Policy 2014 (IPP2014) conference organized by the Oxford Internet Institute (University of Oxford) and the Policy & Internet journal. The theme of this very successful conference—our third since the founding of the journal—was “crowdsourcing for politics and policy.” Out of almost 80 papers presented at the conference in September last year, 14 of the best have now been published as peer-reviewed articles in this journal, including five in this issue. A further handful of papers from the conference focusing on labor issues will be published in the next issue, but we can already now take stock of all the articles focusing on government, politics, and policy.

The growing interest in crowdsourcing for government and public policy must be understood in the context of the contemporary malaise of politics, which is being felt across the democratic world, but most of all in Europe. The problems with democracy have a long history, from the declining powers of parliamentary bodies when compared to the executive; to declining turnouts in elections, declining participation in mass parties, and declining trust in democratic institutions and politicians. But these problems have gained a new salience in the last five years, as the ongoing financial crisis has contributed to the rise of a range of new populist forces all across Europe, and to a fragmentation of the center ground. Furthermore, poor accuracy of pre- election polls in recent elections in Israel and the UK have generated considerable debate over the usefulness and accuracy of the traditional way of knowing what the public is thinking: the sample survey.

Many place hopes on technological and institutional innovations such as crowdsourcing to show a way out of the brewing crisis of democratic politics and political science. One of the key attractions of crowdsourcing techniques to governments and grass roots movements alike is the legitimacy such techniques are expected to be able to generate. For example, crowdsourcing techniques have been applied to enable citizens to verify the legality and correctness of government decisions and outcomes. A well-known application is to ask citizens to audit large volumes of data on government spending, to uncover any malfeasance but also to increase citizens’ trust in the government (Maguire, 2011).

Articles emerging from the IPP2014 conference analyze other interesting and comparable applications. In an article titled “Population as Auditor of an Election Process in Honduras: The Case of the VotoSocial Crowdsourcing Platform,” Carlos Arias, Jorge Garcia and Alejandro Corpeño (2015) describe the use of crowdsourcing for auditing election results. Dieter Zinnbauer (2015) discusses the potentials and pitfalls of the use of crowdsourcing for some other types of auditing purposes, in “Crowdsourced Corruption Reporting: What Petrified Forests, Street Music, Bath Towels, and the Taxman Can Tell Us About the Prospects for Its Future.”

Besides allowing citizens to verify the outcome of a process, crowdsourcing can also be used to lend an air of inclusiveness and transparency to a process itself. This process legitimacy can then indirectly legitimate the outcome of the process as well. For example, crowdsourcing-style open processes have been used to collect policy ideas, gather support for difficult policy decisions, and even generate detailed spending plans through participatory budgeting (Wampler & Avritzer, 2004). Articles emerging from our conference further advance this line of research. Roxana Radu, Nicolo Zingales and Enrico Calandro (2015) examine the use of crowdsourcing to lend process legitimacy to Internet governance, in an article titled “Crowdsourcing Ideas as an Emerging Form of Multistakeholder Participation in Internet Governance.” Graham Smith, Robert C. Richards Jr. and John Gastil (2015) write about “The Potential of Participedia as a Crowdsourcing Tool for Comparative Analysis of Democratic Innovations.”

An interesting cautionary tale is presented by Henrik Serup Christensen, Maija Karjalainen and Laura Nurminen (2015) in “Does Crowdsourcing Legislation Increase Political Legitimacy? The Case of Avoin Ministeriö in Finland.” They show how a citizen initiative process ended up decreasing government legitimacy, after the government failed to implement the outcome of an initiative process that was perceived as highly legitimate by its supporters. Taneli Heikka (2015) further examines the implications of citizen initiative processes to the state–citizen relationship in “The Rise of the Mediating Citizen: Time, Space and Citizenship in the Crowdsourcing of Finnish Legislation.”

In many of the contributions that touch on the legitimating effects of crowdsourcing, one can sense a third, latent theme. Besides allowing outcomes to be audited and processes to be potentially more inclusive, crowdsourcing can also increase the perceived legitimacy of a government or policy process by lending an air of innovation and technological progress to the endeavor and those involved in it. This is most explicitly stated by Simo Hosio, Jorge Goncalves, Vassilis Kostakos and Jukka Riekki (2015) in “Crowdsourcing Public Opinion Using Urban Pervasive Technologies: Lessons From Real-Life Experiments in Oulu.” They describe how local government officials collaborating with the research team to test a new public screen based polling system “expressed that the PR value boosted their public perception as a modern organization.” That some government crowdsourcing initatives are at least in part motivated by such “crowdwashing” is hardly surprising, but it encourages us to retain a critical approach and analyze actual outcomes instead of accepting dominant discourses about the nature and effects of crowdsourcing at face value.

For instance, we must continue to examine the actual size, composition, internal structures and motivations of the supposed “crowds” that make use of online platforms. Articles emerging from our conference that contributed towards this aim include “Event Prediction With Learning Algorithms—A Study of Events Surrounding the Egyptian Revolution of 2011 on the Basis of Micro Blog Data” by Benedikt Boecking, Margeret Hall and Jeff Schneider (2015) and “Cyber Hate Speech on Twitter: An Application of Machine Classification and Statistical Modeling for Policy and Decision Making” by Pete Burnap and Matthew L. Williams (2015). Anatoliy Gruzd and Ksenia Tsyganova won a best paper award at the IPP2014 conference for an article published in this journal as “Information Wars and Online Activism During the 2013/2014 Crisis in Ukraine: Examining the Social Structures of Pro- and Anti-Maidan Groups.” These articles can be used to challenge the notion that crowdsourcing contributors are simply sets of independent individuals who are neatly representative of a larger population, and instead highlight the clusters, networks, and power structures inherent within them. This has implications to the democratic legitimacy of some of the more naive crowdsourcing initiatives.

One of the most original articles to emerge out of IPP2014 turns the concept of crowdsourcing for public policy and government on its head. While most research has focused on crowdsourcing’s empowering effects (or lack thereof), Gregory Asmolov (2015) analyses crowdsourcing as a form of social control. In an article titled “Vertical Crowdsourcing in Russia: Balancing Governance of Crowds and State–Citizen Partnership in Emergency Situations,” Asmolov draws on empirical evidence and theorists such as Foucault to show how crowdsourcing platforms can be used to institutionalize volunteer resources in order to align them with state objectives and prevent independent collective action. An article by Jorge Goncalves, Yong Liu, Bin Xiao, Saad Chaudhry, Simo Hosio and Vassilis Kostakos (2015) provides a less nefarious example of strategic use of online platforms to further government objectives, under the title “Increasing the Reach of Government Social Media: A Case Study in Modeling Government–Citizen Interaction on Facebook.”

Articles emerging from the conference also include two review articles that provide useful overviews of the field from different perspectives. “A Systematic Review of Online Deliberation Research” by Dennis Friess and Christiane Eilders (2015) takes stock of the use of digital technologies as public spheres. “The Fundamentals of Policy Crowdsourcing” by John Prpić, Araz Taeihagh and James Melton (2015) situates a broad variety of crowdsourcing literature into the context of a public policy cycle framework.

It has been extremely satisfying to follow the progress of these papers from initial conference submissions to high-quality journal articles, and to see that the final product not only advances the state of the art, but also provides certain new and critical perspectives on crowdsourcing. These perspectives will no doubt provoke responses, and Policy & Internet continues to welcome high-quality submissions dealing with crowdsourcing for public policy, government, and beyond.

Read the full editorial: Vili Lehdonvirta andJonathan Bright (2015) Crowdsourcing for Public Policy and Government. Editorial. Volume 7, Issue 3, pages 263–267.

References

Arias, C.R., Garcia, J. and Corpeño, A. (2015) Population as Auditor of an Election Process in Honduras: The Case of the VotoSocial Crowdsourcing Platform. Policy & Internet 7 (2) 185–202.

Asmolov, G. (2105) Vertical Crowdsourcing in Russia: Balancing Governance of Crowds and State–Citizen Partnership in Emergency Situations. Policy & Internet 7 (3).

Brabham, D. C. (2013). Citizen E-Participation in Urban Governance: Crowdsourcing and Collaborative Creativity: Crowdsourcing and Collaborative Creativity. IGI Global.

Boecking, B., Hall, M. and Schneider, J. (2015) Event Prediction With Learning Algorithms—A Study of Events Surrounding the Egyptian Revolution of 2011 on the Basis of Micro Blog Data. Policy & Internet 7 (2) 159–184.

Burnap P. and Williams, M.L. (2015) Cyber Hate Speech on Twitter: An Application of Machine Classification and Statistical Modeling for Policy and Decision Making. Policy & Internet 7 (2) 223–242.

Christensen, H.S., Karjalainen, M. and Nurminen, L. (2015) Does Crowdsourcing Legislation Increase Political Legitimacy? The Case of Avoin Ministeriö in Finland. Policy & Internet 7 (1) 25-45.

Friess, D. and Eilders, C. (2015) A Systematic Review of Online Deliberation Research. Policy & Internet 7 (3).

Goncalves, J., Liu, Y., Xiao, B., Chaudhry, S., Hosio, S. and Kostakos, V. (2015) Increasing the Reach of Government Social Media: A Case Study in Modeling Government–Citizen Interaction on Facebook. Policy & Internet 7 (1) 80-102.

Gruzd, A. and Tsyganova, K. (2015) Information Wars and Online Activism During the 2013/2014 Crisis in Ukraine: Examining the Social Structures of Pro- and Anti-Maidan Groups. Policy & Internet 7 (2) 121–158.

Heikka, T. (2015) The Rise of the Mediating Citizen: Time, Space and Citizenship in the Crowdsourcing of Finnish Legislation. Policy & Internet 7 (3).

Hosio, S., Goncalves, J., Kostakos, V. and Riekki, J. (2015) Crowdsourcing Public Opinion Using Urban Pervasive Technologies: Lessons From Real-Life Experiments in Oulu. Policy & Internet 7 (2) 203–222.

Howe, J. (2006). The Rise of Crowdsourcing by Jeff Howe | Byliner. Retrieved from

Maguire, S. (2011). Can Data Deliver Better Government? Political Quarterly, 82(4), 522–525.

Margetts, H., John, P., Hale, S., & Yasseri, T. (2015): Political Turbulence: How Social Media Shape Collective Action. Princeton University Press.

Prpić, J., Taeihagh, A. and Melton, J. (2015) The Fundamentals of Policy Crowdsourcing. Policy & Internet 7 (3).

Radu, R., Zingales, N. and Calandro, E. (2015) Crowdsourcing Ideas as an Emerging Form of Multistakeholder Participation in Internet Governance. Policy & Internet 7 (3).

Shirky, C. (2010). Cognitive Surplus: How Technology Makes Consumers into Collaborators. Penguin Publishing Group.

Smith, G., Richards R.C. Jr. and Gastil, J. (2015) The Potential of Participedia as a Crowdsourcing Tool for Comparative Analysis of Democratic Innovations. Policy & Internet 7 (2) 243–262.

Wampler, B., & Avritzer, L. (2004). Participatory publics: civil society and new institutions in democratic Brazil. Comparative Politics, 36(3), 291–312.

Zinnbauer, D. (2015) Crowdsourced Corruption Reporting: What Petrified Forests, Street Music, Bath Towels, and the Taxman Can Tell Us About the Prospects for Its Future. Policy & Internet 7 (1) 1–24.

Despite the British government’s boasts of the steady roll-out of superfast broadband to more than four out of five homes and businesses, you needn’t be a statistician to realise that this means one out of five are still unconnected. In fact, the recent story about a farmer who was so incensed by his slow broadband that he built his own 4G mast in a field to replace it shows that for much of the country, little has improved.

The government’s Broadband Delivery UK (BDUK) programme claims that it will provide internet access of at least 24 Mbps (megabits per second) to 95% of the country by 2017 through fibre to the cabinet, where fast fibre optic networks connect BT’s exchanges to street cabinets dotted around towns and villages. The final connection to the home comes via traditional (slower) copper cables.

Those in rural communities are understandably sceptical of the government’s “huge achievement”, arguing that only a fraction of the properties included in the government’s running total can achieve reasonable broadband speeds, as signals drop off quickly with distance from BT’s street cabinets. Millions of people are still struggling to achieve even basic broadband, and not necessarily just in the remote countryside, but in urban areas such as Redditch, Lancaster and even Pimlico in central London.

Four problems to solve

Our research found four recurring problems: connection speeds, latency, contention ratios, and reliability.

Getting high-speed ADSL broadband delivered over existing copper cables is not possible in many areas, as the distance from the exchange or the street cabinet is so far that the broadband signal degrades and speeds drop. Minimum speed requirements are rising as the volume of data we use increases, so such slow connections will become more and more frustrating.

But speed is not the only limiting factor. Network delay, known as latency, can be as frustrating as it forces the user to wait for data to arrive or to be assembled into the right order to be processed. Most of our interviewees had high latency connections.

Many home users also suffer from high contention, where a connection slows as more users in the vicinity log on – for example, during evenings after work and at weekends. One respondent pointed out that the two or three large companies in the neighbouring village carried out their daily company backups between 6.30pm-8.30pm. This was obvious, he said, because during that time internet speeds “drop off the end of a cliff”.

Connection reliability is also a problem, with connections failing randomly for no clear reason, or due to weather such as heavy rain, snow or wind – not very helpful in Britain.

Three band-aid solutions

With delivery by copper cable proving inadequate for many, other alternatives have been suggested to fill the gaps.

Mobile phones are now ubiquitous devices, and mobile phone networks cover a huge proportion of the country. A 4G mobile network connection could potentially provide 100Mbps speeds. Unfortunately, the areas failed by poor fixed line broadband provision are often the same areas with poor mobile phone networks – particularly rural areas. While 2G/3G network coverage is better, it is far slower. Without unlimited data plans, users will also face monthly caps on use as part of their contract. Weather conditions can also adversely affect the service.

Satellite broadband could be the answer and can provide reasonably high speeds of up to around 20 Mbps. But despite the decent bandwidth available, satellite connections have high latency from the slow speed of transferring data to and from satellites, due to the far larger distances involvedbetween satellites and the ground. High latency connections make it very difficult or impossible to use internet telephony such as Skype, to stream films, video or music, or play online games. It’s not really an option in mountainous regions, and is a more expensive option.

A third alternative is to use fixed wireless, relaying broadband signals over radio transmitters to cover the distance from where BT’s fixed-line fibre optic network ends. These services generally provide 20Mbps, low latency connections. However, radio towers require line-of-sight access which could be a problem given obstructions from hills or woods – factors that, again, limit use where it’s most needed.

The only one that fits

All these alternatives tend to be more expensive to set up and run, come with more strict data limits, and can be affected by atmospheric conditions such as rain, wind or fog. The only true superior alternative to fibre to the cabinet is to provide fibre to the home (FTTH), in which the last vestiges of the original copper telephone network are replaced with high-speed fibre optic right to the door of the home or business premises. Fibre optic is faster, can carry signals without loss over greater distances, and is more upgradable than copper. A true fibre optic solution would future-proof Britain’s internet access network for decades to come.

Despite its expense, it is the only solution for many rural communities, which is why some have organised to provide it for themselves, such as B4RN and B4YS in the north of England, and B4RDS in the southwest. But this requires a group of volunteers with knowledge, financial means, and the necessary dedication to lay the infrastructure that could offer a 1,000 Mbps service regardless of line distance and location – which won’t be an option for all.

An angry crowd has attacked Uber cars with bars and stones outside Mexico City airport, the latest in a series of worldwide protests against the ride-hailing app. More than 1,000 taxi drivers blocked streets in Rio de Janeiro a few days ago, and the service has been restricted or banned in the likes of France, Germany, Italy and South Korea. Protests have also been staged against Airbnb, the platform for renting short-term accommodation.

Neither platform shows any signs of faltering, however. Uber is available in 57 countries and produces hundreds of millions of dollars in revenues. Airbnb is available in more than 190 countries, and boasts more than 1.5 million rooms.

Journalists and entrepreneurs have been quick to coin terms that try to capture the social and economic changes associated with such platforms: the sharing economy; the on-demand economy; the peer-to-peer economy; and so on. Each perhaps captures one aspect of the phenomenon, but doesn’t make sense of all its potentials and contradictions, including why some people love it and some would smash it into pieces.

Economic sociologists believe markets are always based on an underlying infrastructure that allows people to find out what goods and services are on offer, agree prices and terms, pay, and have a reasonable expectation that the other party will honour the agreement. The oldest example is the personal social network: traders hear what’s on offer through word of mouth and trade only with those they personally know and trust.

In the modern world we can do business with strangers, too, because we have developed institutions to make this reliable, like private property, enforceable contracts, standardised weights and measures, and consumer protection. They are part of a long historical continuum, from ancient trade routes with their customs to medieval fairs with codes of conduct to the state-enforced trade laws of the early industrial era.

Natural selection

Institutional economists and economic historians theorised in the 1980s that these have gradually been evolving towards ever more efficient forms through natural selection. People switch to cheaper, easier, more secure and more efficient institutions as new technology and organisational innovations make them possible. Old and cumbersome institutions fall into disuse, says the theory, and society becomes more efficient and economically prosperous as a result.

It is easy to frame platforms as the next step in such a process. Even if they don’t replace state institutions, they can plug gaps. For example enforcing a contract in court is expensive and unwieldy. Platforms provide cheaper and easier alternatives through reputation systems where participants rate each other’s conduct and view past ratings.

Uber does this with government-licensed taxi infrastructures, for instance, addressing everything from quality and discovery to trust and payment. Airbnb provides a similarly sweeping solution to short-term accommodation rental. The sellers on these platforms are not just consumers seeking to better use their resources, but also firms and professionals switching over from the state infrastructure. It is as if people and companies were abandoning their national institutions and emigrating en masse to Platform Nation.

Downside or upside?

The natural selection theory argues that the government shouldn’t try to stop people from using the likes of Uber and Airbnb, nor impose its evidently less efficient norms on them. Let people vote with their feet. But is that an oversimplification?

If buyers switch to new institutions, for instance, sellers may have little choice but to follow. Even if taxi drivers don’t like Uber’s rules, they may find there is little business to be had outside the platform and switch anyway. In the end, whether the market shifts can boil down to power rather than choice.

Even when everyone participates willingly, the arrangement might be bad for society. It might adversely affect third parties, for example, such as Airbnb guests annoying neighbours through noise, traffic or being unfamiliar with the local rules. In the worst case, a platform can make society less efficient by creating a “free-rider economy”.

If these kinds of conflicting interests are reconciled, it is through the political institutions that govern the markets. Social scientists can often find out more about a market by looking at its political institutions than comparative efficiency. Take the hotel industry. Local governments try to balance the interests of hoteliers and their neighbours by limiting hotel business to certain zones. Airbnb has no such mandate to address the interests of third parties on an equal footing. Perhaps because of this, 74% of Airbnb properties are not in the main hotel districts, but often in ordinary residential blocks.

Of course, government regulators are at risk of being captured by incumbents, or at the very least creating rules that benefit incumbents to the detriment of possible future participants. An example would be taxi-licensing systems that strictly limit the numbers of cab operators. Whatever quality assurance this offers customers, among the main losers are excluded would-be drivers.

Against this background, platforms can look like radical reformers. For example Uber aims to create 1m jobs for women by 2020, a pledge that would likely not be possible if it adhered to government licensing requirements, as most licences are owned by men. Having said that, Uber’s definition of a “job” is much more precarious and entrepreneurial than the conventional definition. My point here is not to take sides, but to show that their social implications are very different. Both possess flaws and redeeming qualities, many of which can be traced back to their political institutions and whom they represent.

What kind of new economic institutions are platform developers creating? How efficient are they? What other consequences do they have? Whose interests are they geared to represent? These are the questions that bureaucrats, journalists, and social scientists ought to be asking. I hope we will be able to discover ways to take what is good from the old and the new, and create infrastructure for an economy that is as fair and inclusive as it is efficient and innovative.

Ride-hailing app Uber is close to replacing government-licensed taxis in some cities, while Airbnb’s accommodation rental platform has become a serious competitor to government-regulated hotel markets. Many other apps and platforms are trying to do the same in other sectors of the economy. In my previous post, I argued that platforms can be viewed in social science terms as economic institutions that provide infrastructures necessary for markets to thrive. I explained how the natural selection theory of institutional change suggests that people are migrating from state institutions to these new code-based institutions because they provide a more efficient environment for doing business. In this article, I will discuss some of the problems with this theory, and outline a more nuanced theory of institutional change that suggests that platforms’ effects on society will be complex and influence different people in different ways.

Economic sociologists like Neil Fligstein have pointed out that not everyone is as free to choose the means through which they conduct their trade. For example, if buyers in a market switch to new institutions, sellers may have little choice but to follow, even if the new institutions leave them worse off than the old ones did. Even if taxi drivers don’t like Uber’s rules, they may find that there is little business to be had outside the platform, and switch anyway. In the end, the choice of institutions can boil down to power. Economists have shown that even a small group of participants with enough market power — like corporate buyers — may be able to force a whole market to tip in favour of particular institutions. Uber offers a special solution for corporate clients, though I don’t know if this has played any part in the platform’s success.

Even when everyone participates in an institutional arrangement willingly, we still can’t assume that it will contribute to the social good. Cambridge economic historian Sheilagh Ogilvie has pointed out that an institution that is efficient for everyone who participates in it can still be inefficient for society as a whole if it affects third parties. For example, when Airbnb is used to turn an ordinary flat into a hotel room, it can cause nuisance to neighbours in the form of noise, traffic, and guests unfamiliar with the local rules. The convenience and low cost of doing business through the platform is achieved in part at others’ expense. In the worst case, a platform can make society not more but less efficient — by creating a ‘free rider economy’.

In general, social scientists recognize that different people and groups in society often have conflicting interests in how economic institutions are shaped. These interests are reconciled — if they are reconciled — through political institutions. Many social scientists thus look not so much at efficiencies but at political institutions to understand why economic institutions are shaped the way they are. For example, a democratic local government in principle represents the interests of its citizens, through political institutions such as council elections and public consultations. Local governments consequently try to strike a balance between the conflicting interests of hoteliers and their neighbours, by limiting hotel business to certain zones. In contrast, Airbnb as a for-profit business must cater to the interests of its customers, the would-be hoteliers and their guests. It has no mechanism, and more importantly, no mandate, to address on an equal footing the interests of third parties like customers’ neighbours. Perhaps because of this, 74% of Airbnb’s properties are not in the main hotel districts, but in ordinary residential blocks.

That said, governments have their own challenges in producing fair and efficient economic institutions. Not least among these is the fact that government regulators are at a risk of capture by incumbent market participants, or at the very least they face the innovator’s dilemma: it is easier to craft rules that benefit the incumbents than rules that provide great but uncertain benefits to future market participants. For example, cities around the world operate taxi licensing systems, where only strictly limited numbers of license owners are allowed to operate taxicabs. Whatever benefits this system offers to customers in terms of quality assurance, among its biggest beneficiaries are the license owners, and among its losers the would-be drivers who are excluded from the market. Institutional insiders and outsiders have conflicting interests, and government political institutions are often such that it is easier for it to side with the insiders.

Against this background, platforms appear almost as radical reformers that provide market access to those whom the establishment has denied it. For example, Uber recently announced that it aims to create one million jobs for women by 2020, a bold pledge in the male-dominated transport industry, and one that would likely not be possible if it adhered to government licensing requirements, as most licenses are owned by men. Having said that, Uber’s definition of a ‘job’ is something much more precarious and entrepreneurial than the conventional definition. My point here is not to side with either Uber or the licensing system, but to show that their social implications are very different. Both possess at least some flaws as well as redeeming qualities, many of which can be traced back to their political institutions and whom they represent.

What kind of new economic institutions are platform developers creating? How efficient are they? What other consequences, including unintended ones, do they have and to whom? Whose interests are they geared to represent — capital vs. labour, consumer vs. producer, Silicon Valley vs. local business, incumbent vs. marginalized? These are the questions that policy makers, journalists, and social scientists ought to be asking at this moment of transformation in our economic institutions. Instead of being forced to choose one or the other between established institutions and platforms as they currently are, I hope that we will be able to discover ways to take what is good in both, and create infrastructure for an economy that is as fair and inclusive as it is efficient and innovative.

Vili Lehdonvirta is a Research Fellow and DPhil Programme Director at the Oxford Internet Institute, and an editor of the Policy & Internet journal. He is an economic sociologist who studies the social and economic dimensions of new information technologies around the world, with particular expertise in digital markets and crowdsourcing.

Cars were smashed and tires burned in France last month in protests against the ride hailing app Uber. Less violent protests have also been staged against Airbnb, a platform for renting short-term accommodation. Despite the protests, neither platform shows any signs of faltering. Uber says it has a million users in France, and is available in 57 countries. Airbnb is available in over 190 countries, and boasts over a million rooms, more than hotel giants like Hilton and Marriott. Policy makers at the highest levels are starting to notice the rise of these and similar platforms. An EU Commission flagship strategy paper notes that “online platforms are playing an ever more central role in social and economic life,” while the Federal Trade Commission recently held a workshop on the topic in Washington.

Journalists and entrepreneurs have been quick to coin terms that try to capture the essence of the social and economic changes associated with online platforms: the sharing economy; the on-demand economy; the peer-to-peer economy; and so on. Each perhaps captures one aspect of the phenomenon, but doesn’t go very far in helping us make sense of all its potentials and contradictions, including why some people love it and some would like to smash it into pieces. Instead of starting from the assumption that everything we see today is new and unprecedented, what if we dug into existing social science theory to see what it has to say about economic transformation and the emergence of markets?

Economic sociologists are adamant that markets don’t just emerge by themselves: they are always based on some kind of an underlying infrastructure that allows people to find out what goods and services are on offer, agree on prices and terms, pay, and have a reasonable expectation that the other party will honour the agreement. The oldest market infrastructure is the personal social network: traders hear what’s on offer through word of mouth and trade only with those whom they personally know and trust. But personal networks alone couldn’t sustain the immense scale of trading in today’s society. Every day we do business with strangers and trust them to provide for our most basic needs. This is possible because modern society has developed institutions — things like private property, enforceable contracts, standardized weights and measures, consumer protection, and many other general and sector specific norms and facilities. By enabling and constraining everyone’s behaviours in predictable ways, institutions constitute a robust and more inclusive infrastructure for markets than personal social networks.

Modern institutions didn’t of course appear out of nowhere. Between prehistoric social networks and the contemporary institutions of the modern state, there is a long historical continuum of economic institutions, from ancient trade routes with their customs to medieval fairs with their codes of conduct to state-enforced trade laws of the early industrial era. Institutional economists led by Oliver Williamson and economic historians led by Douglass North theorized in the 1980s that economic institutions evolve towards more efficient forms through a process of natural selection. As new institutional forms become possible thanks to technological and organizational innovation, people switch to cheaper, easier, more secure, and overall more efficient institutions out of self-interest. Old and cumbersome institutions fall into disuse, and society becomes more efficient and economically prosperous as a result. Williamson and North both later received the Nobel Memorial Prize in Economic Sciences.

It is easy to frame platforms as the next step in such an evolutionary process. Even if platforms don’t replace state institutions, they can plug gaps that remain the state-provided infrastructure. For example, enforcing a contract in court is often too expensive and unwieldy to be used to secure transactions between individual consumers. Platforms provide cheaper and easier alternatives to formal contract enforcement, in the form of reputation systems that allow participants to rate each others’ conduct and view past ratings. Thanks to this, small transactions like sharing a commute that previously only happened in personal networks can now potentially take place on a wider scale, resulting in greater resource efficiency and prosperity (the ‘sharing economy’). Platforms are not the first companies to plug holes in state-provided market infrastructure, though. Private arbitrators, recruitment agencies, and credit rating firms have been doing similar things for a long time.

What’s arguably new about platforms, though, is that some of the most popular ones are not mere complements, but almost complete substitutes to state-provided market infrastructures. Uber provides a complete substitute to government-licensed taxi infrastructures, addressing everything from quality and discovery to trust and payment. Airbnb provides a similarly sweeping solution to short-term accommodation rental. Both platforms have been hugely successful; in San Francisco, Uber has far surpassed the city’s official taxi market in size. The sellers on these platforms are not just consumers wanting to make better use of their resources, but also firms and professionals switching over from the state infrastructure. It is as if people and companies were abandoning their national institutions and emigrating en masse to Platform Nation.

From the natural selection perspective, this move from state institutions to platforms seems easy to understand. State institutions are designed by committee and carry all kinds of historical baggage, while platforms are designed from the ground up to address their users’ needs. Government institutions are geographically fragmented, while platforms offer a seamless experience from one city, country, and language area to the other. Government offices have opening hours and queues, while platforms make use of latest technologies to provide services around the clock (the ‘on-demand economy’). Given the choice, people switch to the most efficient institutions, and society becomes more efficient as a result. The policy implications of the theory are that government shouldn’t try to stop people from using Uber and Airbnb, and that it shouldn’t try to impose its evidently less efficient norms on the platforms. Let competing platforms innovate new regulatory regimes, and let people vote with their feet; let there be a market for markets.

The natural selection theory of institutional change provides a compellingly simple way to explain the rise of platforms. However, it has difficulty in explaining some important facts, like why economic institutions have historically developed differently in different places around the world, and why some people now protest vehemently against supposedly better institutions. Indeed, over the years since the theory was first introduced, social scientists have discovered significant problems in it. Economic sociologists like Neil Fligstein have noted that not everyone is as free to choose the institutions that they use. Economic historian Sheilagh Ogilvie has pointed out that even institutions that are efficient for those who participate in them can still sometimes be inefficient for society as a whole. These points suggest a different theory of institutional change, which I will apply to online platforms in my next post.

Vili Lehdonvirta is a Research Fellow and DPhil Programme Director at the Oxford Internet Institute, and an editor of the Policy & Internet journal. He is an economic sociologist who studies the social and economic dimensions of new information technologies around the world, with particular expertise in digital markets and crowdsourcing.

Work on big data for cities is increasingly incorporated under the rubric of “smart cities”. The smart city is an old(ish) idea: give urban policymakers real time information on a whole variety of indicators about their city (from traffic and pollution to park usage and waste bin collection) and they will be able to improve decision making and optimise service delivery. But the initial vision, which mostly centred around adding sensors and RFID tags to objects around the city so that they would be able to communicate, has thus far remained unrealised (big up front investment needs and the requirements of IPv6 are perhaps the most obvious reasons for this).

The rise of big data – large, heterogeneous datasets generated by the increasing digitisation of social life – has however breathed new life into the smart cities concept. If all the cars have GPS devices, all the people have mobile phones, and all opinions are expressed on social media, then do we really need the city to be smart at all? Instead, policymakers can simply extract what they need from a sea of data which is already around them. And indeed, data from mobile phone operators has already been used for traffic optimisation, Oyster card data has been used to plan London Underground service interruptions, sewage data has been used to estimate population levels … the examples go on.

However, at the moment these examples remain largely anecdotal, driven forward by a few cities rather than adopted worldwide. The big data driven smart city faces considerable challenges if it is to become a default means of policymaking rather than a conversation piece. Getting access to the right data; correcting for biases and inaccuracies (not everyone has a GPS, phone, or expresses themselves on social media); and communicating it all to executives remain key concerns. Furthermore, especially in a context of tight budgets, most local governments cannot afford to experiment with new techniques which may not pay off instantly.

This is the context of two current OII projects in the smart cities field: UrbanData2Decide (2014-2016) and NEXUS (2015-2017). UrbanData2Decide joins together a consortium of European universities, each working with a local city partner, to explore how local government problems can be resolved with urban generated data. In Oxford, we are looking at how open mapping data can be used to estimate alcohol availability; how website analytics can be used to estimate service disruption; and how internal administrative data and social media data can be used to estimate population levels. The best concepts will be built into an application which allows decision makers to access these concepts real time.

NEXUS builds on this work. A collaborative partnership with BT, it will look at how social media data and some internal BT data can be used to estimate people movement and traffic patterns around the city, joining these data into network visualisations which are then displayed to policymakers in a data visualisation application. Both projects fill an important gap by allowing city officials to experiment with data driven solutions, providing proof of concepts and showing what works and what doesn’t. Increasing academic-government partnerships in this way has real potential to drive forward the field and turn the smart city vision into a reality.

OII Resarch Fellow Jonathan Bright is a political scientist specialising in computational and ‘big data’ approaches to the social sciences. His major interest concerns studying how people get information about the political process, and how this is changing in the internet era.

Biometric technologies are on the rise. By electronically recording data about individual’s physical attributes such as fingerprints or iris patterns, security and law enforcement services can quickly identify people with a high degree of accuracy.

The latest development in this field is the scanning of irises from a distance of up to 40 feet (12 metres) away. Researchers from Carnegie Mellon University in the US demonstrated they were able to use their iris recognition technology to identify drivers from an image of their eye captured from their vehicle’s side mirror.

The developers of this technology envisage that, as well as improving security, it will be more convenient for the individuals being identified. By using measurements of physiological characteristics, people no longer need security tokens or cumbersome passwords to identify themselves.

However, introducing such technology will come with serious challenges. There are both legal issues and public anxiety around having such sensitive data captured, stored, and accessed.

Social resistance

We have researched this area by presenting people with potential future scenarios that involved biometrics. We found that, despite the convenience of long-range identification (no queuing in front of scanners), there is a considerable reluctance to accept this technology.

On a basic level, people prefer a physical interaction when their biometrics are being read. “I feel negatively about a remote iris scan because I want there to be some kind of interaction between me and this system that’s going to be monitoring me,” said one participant in our research.

But another serious concern was that of “function creep”, whereby people slowly become accustomed to security and surveillance technologies because they are introduced gradually. This means the public may eventually be faced with much greater use of these systems than they would initially agree to.

For example, implementing biometric identification in smart phones and other everyday objects such as computers or cars could make people see the technology as useful and easy to operate, This may increase their willingness to adopt such systems. “I could imagine this becoming normalised to a point where you don’t really worry about it,“ said one research participant.

Such familiarity could lead to the introduction of more invasive long-distance recognition systems. This could ultimately produce far more widespread commercial and governmental usage of biometric identification than the average citizen might be comfortable with. As one participant put it: “[A remote scan] could be done every time we walk into a big shopping centre, they could just identify people all over the place and you’re not aware of it.”

Legal barriers

The implementation of biometric systems is not just dependent on user acceptance or resistance. Before iris-scanning technology could be introduced in the EU, major data protection and privacy considerations would have to be made.

The EU has a robust legal framework on privacy and data protection. These are recognised as fundamental rights and so related laws are among the highest ranking. Biometric data, such as iris scans, are often treated as special due to the sensitivity of the information they can contain. Our respondents also acknowledged this: “I think it’s a little too invasive and to me it sounds a bit creepy. Who knows what they can find out by scanning my irises?”

Before iris technology could be deployed, certain legal steps would need to be taken. Under EU law and the European Convention on Human Rights, authorities would need to demonstrate it was a necessary and proportionate solution to a legitimate, specific problem. They would also need to prove iris recognition was the least intrusive way to achieve that goal. And a proportionality test would have to take into account the risks the technology brings along with the benefits.

The very fact that long-range iris scanners can capture data without the collaboration of their subject also creates legal issues. EU law requires individuals to be informed when such information was being collected, by whom, for what purposes, and the existence of their rights surrounding the data.

Another issue is how the data is kept secure, particularly in the case of iris-scanning by objects such as smart phones. Scans stored on the device and/or on the cloud for purposes of future authentication would legally require robust security protection. Data stored on the cloud tends to move around between different servers and countries, which makes preventing unauthorised access more difficult.

The other issue with iris scanning is that, while the technology could be precise, it is not infallible. At its current level, the technology can still be fooled (see video above). And processing data accurately is another principle of EU data protection law.

Even if we do find ourselves subject to unwanted iris-scanning from 40 feet, safeguards for individuals should always be in place to ensure that they do not bear the burden of technological imperfections.

Counts of public Facebook posts mentioning any of the party leaders’ surnames. Data generated by social media can be used to understand political behaviour and institutions on an ongoing basis.[/caption]‘Congratulations to my friend @Messina2012 on his role in the resounding Conservative victory in Britain’ tweeted David Axelrod, campaign advisor to Miliband, to his former colleague Jim Messina, Cameron’s strategy adviser, on May 8th. The former was Obama’s communications director and the latter campaign manager of Obama’s 2012 campaign. Along with other consultants and advisors and large-scale data management platforms from Obama’s hugely successful digital campaigns, Conservative and Labour used an arsenal of social media and digital tools to interact with voters throughout, as did all the parties competing for seats in the 2015 election.

The parties ran very different kinds of digital campaigns. The Conservatives used advanced data science techniques borrowed from the US campaigns to understand how their policy announcements were being received and to target groups of individuals. They spent ten times as much as Labour on Facebook, using ads targeted at Facebook users according to their activities on the platform, geo-location and demographics. This was a top down strategy that involved working out was happening on social media and responding with targeted advertising, particularly for marginal seats. It was supplemented by the mainstream media, such as the Telegraph for example, which contacted its database of readers and subscribers to services such as Telegraph Money, urging them to vote Conservative. As Andrew Cooper tweeted after the election, ‘Big data, micro-targeting and social media campaigns just thrashed “5 million conversations” and “community organizing”’.

He has a point. Labour took a different approach to social media. Widely acknowledged to have the most boots on the real ground, knocking on doors, they took a similar ‘ground war’ approach to social media in local campaigns. Our own analysis at the Oxford Internet Institute shows that of the 450K tweets sent by candidates of the six largest parties in the month leading up to the general election, Labour party candidates sent over 120,000 while the Conservatives sent only 80,000, no more than the Greens and not much more than UKIP. But the greater number of Labour tweets were no more productive in terms of impact (measured in terms of mentions generated: and indeed the final result).

Both parties’ campaigns were tightly controlled. Ostensibly, Labour generated far more bottom-up activity from supporters using social media, through memes like #votecameron out, #milibrand (responding to Miliband’s interview with Russell Brand), and what Miliband himself termed the most unlikely cult of the 21st century in his resignation speech, #milifandom, none of which came directly from Central Office. These produced peaks of activity on Twitter that at some points exceeded even discussion of the election itself on the semi-official #GE2015 used by the parties, as the figure below shows. But the party remained aloof from these conversations, fearful of mainstream media mockery.

The Brand interview was agreed to out of desperation and can have made little difference to the vote (partly because Brand endorsed Miliband only after the deadline for voter registration: young voters suddenly overcome by an enthusiasm for participatory democracy after Brand’s public volte face on the utility of voting will have remained disenfranchised). But engaging with the swathes of young people who spend increasing amounts of their time on social media is a strategy for engagement that all parties ought to consider. YouTubers like PewDiePie have tens of millions of subscribers and billions of video views – their videos may seem unbelievably silly to many, but it is here that a good chunk the next generation of voters are to be found.

Only one of the leaders had a presence on social media that managed anything like the personal touch and universal reach that Obama achieved in 2008 and 2012 based on sustained engagement with social media – Nicola Sturgeon. The SNP’s use of social media, developed in last September’s referendum on Scottish independence had spawned a whole army of digital activists. All SNP candidates started the campaign with a Twitter account. When we look at the 650 local campaigns waged across the country, by far the most productive in the sense of generating mentions was the SNP; 100 tweets from SNP local candidates generating 10 times more mentions (1,000) than 100 tweets from (for example) the Liberal Democrats.

Scottish Labour’s failure to engage with Scottish peoples in this kind of way illustrates how difficult it is to suddenly develop relationships on social media – followers on all platforms are built up over years, not in the short space of a campaign. In strong contrast, advertising on these platforms as the Conservatives did is instantaneous, and based on the data science understanding (through advertising algorithms) of the platform itself. It doesn’t require huge databases of supporters – it doesn’t build up relationships between the party and supporters – indeed, they may remain anonymous to the party. It’s quick, dirty and effective.

The pollsters’ terrible night

So neither of the two largest parties really did anything with social media, or the huge databases of interactions that their platforms will have generated, to generate long-running engagement with the electorate. The campaigns were disconnected from their supporters, from their grass roots.

But the differing use of social media by the parties could lend a clue to why the opinion polls throughout the campaign got it so wrong, underestimating the Conservative lead by an average of five per cent. The social media data that may be gathered from this or any campaign is a valuable source of information about what the parties are doing, how they are being received, and what people are thinking or talking about in this important space – where so many people spend so much of their time. Of course, it is difficult to read from the outside; Andrew Cooper labeled the Conservatives’ campaign of big data to identify undecided voters, and micro-targeting on social media, as ‘silent and invisible’ and it seems to have been so to the polls.

Many voters were undecided until the last minute, or decided not to vote, which is impossible to predict with polls (bar the exit poll) – but possibly observable on social media, such as the spikes in attention to UKIP on Wikipedia towards the end of the campaign, which may have signaled their impressive share of the vote. As Jim Messina put it to msnbc news following up on his May 8^th tweet that UK (and US) polling was ‘completely broken’ – ‘people communicate in different ways now’, arguing that the Miliband campaign had tried to go back to the 1970s.

Surveys – such as polls — give a (hopefully) representative picture of what people think they might do. Social media data provide an (unrepresentative) picture of what people really said or did. Long-running opinion surveys (such as the Ipsos MORI Issues Index) can monitor the hopes and fears of the electorate in between elections, but attention tends to focus on the huge barrage of opinion polls at election time – which are geared entirely at predicting the election result, and which do not contribute to more general understanding of voters. In contrast, social media are a good way to track rapid bursts in mobilization or support, which reflect immediately on social media platforms – and could also be developed to illustrate more long running trends, such as unpopular policies or failing services.

As opinion surveys face more and more challenges, there is surely good reason to supplement them with social media data, which reflect what people are really thinking on an ongoing basis – like, a video in rather than the irregular snapshots taken by polls. As a leading pollster João Francisco Meira, director of Vox Populi in Brazil (which is doing innovative work in using social media data to understand public opinion) put it in conversation with one of the authors in April – ‘we have spent so long trying to hear what people are saying – now they are crying out to be heard, every day’. It is a question of pollsters working out how to listen.

Political big data

Analysts of political behaviour – academics as well as pollsters — need to pay attention to this data. At the OII we gathered large quantities of data from Facebook, Twitter, Wikipedia and YouTube in the lead-up to the election campaign, including mentions of all candidates (as did Demos’s Centre for the Analysis of Social Media). Using this data we will be able, for example, to work out the relationship between local social media campaigns and the parties’ share of the vote, as well as modeling the relationship between social media presence and turnout.

We can already see that the story of the local campaigns varied enormously – while at the start of the campaign some candidates were probably requesting new passwords for their rusty Twitter accounts, some already had an ongoing relationship with their constituents (or potential constituents), which they could build on during the campaign. One of the candidates to take over the Labour party leadership, Chuka Umunna, joined Twitter in April 2009 and now has 100K followers, which will be useful in the forthcoming leadership contest.

Election results inject data into a research field that lacks ‘big data’. Data hungry political scientists will analyse these data in every way imaginable for the next five years. But data in between elections, for example relating to democratic or civic engagement or political mobilization, has traditionally been woefully short in our discipline. Analysis of the social media campaigns in #GE2015 will start to provide a foundation to understand patterns and trends in voting behaviour, particularly when linked to other sources of data, such as the actual constituency-level voting results and even discredited polls — which may yet yield insight, even having failed to achieve their predictive aims. As the OII’s Jonathan Bright and Taha Yasseri have argued, we need ‘a theory-informed model to drive social media predictions, that is based on an understanding of how the data is generated and hence enables us to correct for certain biases’

A political data science

Parties, pollsters and political analysts should all be thinking about these digital disconnects in #GE2015, rather than burying them with their hopes for this election. As I argued in a previous post, let’s use data generated by social media to understand political behaviour and institutions on an ongoing basis. Let’s find a way of incorporating social media analysis into polling models, for example by linking survey datasets to big data of this kind. The more such activity moves beyond the election campaign itself, the more useful social media data will be in tracking the underlying trends and patterns in political behavior.

And for the parties, these kind of ways of understanding and interacting with voters needs to be institutionalized in party structures, from top to bottom. On 8th May, the VP of a policy think-tank tweeted to both Axelrod and Messina ‘Gentlemen, welcome back to America. Let’s win the next one on this side of the pond’. The UK parties are on their own now. We must hope they use the time to build an ongoing dialogue with citizens and voters, learning from the success of the new online interest group barons, such as 38 degrees and Avaaz, by treating all internet contacts as ‘members’ and interacting with them on a regular basis. Don’t wait until 2020!

Helen Margetts is the Director of the OII, and Professor of Society and the Internet. She is a political scientist specialising in digital era governance and politics, investigating political behaviour, digital government and government-citizen interactions in the age of the internet, social media and big data. She has published over a hundred books, articles and major research reports in this area, including Political Turbulence: How Social Media Shape Collective Action (with Peter John, Scott Hale and Taha Yasseri, 2015).

Scott A. Hale is a Data Scientist at the OII. He develops and applies techniques from computer science to research questions in the social sciences. He is particularly interested in the area of human-computer interaction and the spread of information between speakers of different languages online and the roles of bilingual Internet users. He is also interested in collective action and politics more generally.

This may well make Twitter particularly well suited to political debate and activity. Yet important questions emerge in terms of the patterns of conduct and engagement. Chief among them: are users mainly seeking to reinforce their own viewpoints and link with likeminded persons, or is there a basis for widening and thoughtful exposure to a variety of perspectives that may improve the collective intelligence of the citizenry as a result?

Conflict and Polarization

Political polarization often occurs in a so-called ‘echo chamber’ environment, in which individuals are exposed to only information and communities that support their own viewpoints, while ignoring opposing perspectives and insights. In such isolating and self-reinforcing conditions, ideas can become more engrained and extreme due to lack of contact with contradictory views and the exchanges that could ensue as a result.

On the web, political polarization has been found among political blogs, for instance. American researchers have found that liberal and conservative bloggers in the US tend to link to other bloggers who share their political ideology. For Kingwell, a prominent Canadian philosopher, the resulting dynamic is one that can be characterized by a decline in civility and a lessening ability for political compromise to take hold. He laments the emergence of a ‘shout doctrine’ that corrodes the civic and political culture, in the sense that divisions are accentuated and compromise becomes more elusive.

Such a dynamic is not the result of social media alone – but rather it reflects for some the impacts of the Internet generally and the specific manner by which social media can lend itself to broadcasting and sensationalism, rather than reasoned debate and exchange. Traditional media and journalistic organizations have thus become further pressured to act in kind, driven less by a patient and persistent presentation of all sides of an issue and more by near-instantaneous reporting online. In a manner akin to Kingwell’s view, one prominent television news journalist in the US, Ted Koppel, has lamented this new media environment as a danger to the republic.

Nonetheless, the research is far from conclusive as to whether the Internet increases political polarization. Some studies have found that among casual acquaintances (such as those that can typically be observed on Twitter), it is common to observe connections across ideological boundaries. In one such funded by the Pew Internet and American Life Project and the National Science Foundation, findings suggest that people who often visit websites that support their ideological orientation also visit web sites that support divergent political views. As a result, greater sensitivity and empathy for alternative viewpoints could potentially ensue, improving the likelihood for political compromise – even on a modest scale that would otherwise not have been achievable without this heightened awareness and debate.

Early Evidence from Canada

The 2011 federal election in Canada was dubbed by some observers in the media as the country’s first ‘social media election’ – as platforms such as Facebook and Twitter became prominent sources of information for growing segments of the citizenry, and evermore strategic tools for political parties in terms of fundraising, messaging, and mobilizing voters. In examining Twitter traffic, our own intention was to ascertain the extent to which polarization or cross-pollinization was occurring across the portion of the electorate making use of this micro-blogging platform.

We gathered nearly 6000 tweets pertaining to the federal election made by just under 1500 people during a three-day period in the week preceding election day (this time period was chosen because it was late enough in the campaign for people to have an informed opinion, but still early enough for them to be persuaded as to how they should vote). Once the tweets were retrieved, we used social network analysis and content analysis to analyze patterns of exchange and messaging content in depth.

We found that overall people do tend to cluster around shared political views on Twitter. Supporters of each of the four major political parties identified in the study were more likely to tweet to other supporters of the same affiliation (this was particularly true of the ruling Conservatives, the most inwardly networked of the four major politically parties). Nevertheless, in a significant number of cases (36% of all interactions) we also observed a cross-ideological discourse, especially among supporters of the two most prominent left-of-centre parties, the New Democratic Party (NDP) and the Liberal Party of Canada (LPC). The cross-ideological interactions among supporters of left-leaning parties tended to be agreeable in nature, but often at the expense of the party in power, the Conservative Party of Canada (CPC). Members from the NDP and Liberal formations were also more likely to share general information and updates about the election as well as debate various issues around their party platforms with each other.

By contrast, interactions between parties that are ideologically distant seemed to denote a tone of conflict: nearly 40% of tweets between left-leaning parties and the Conservatives tended to be hostile. Such negative interactions between supporters of different parties have shown to reduce enthusiasm about political campaigns in general, potentially widening the cleavage between highly engaged partisans and less affiliated citizens who may view such forms of aggressive and divisive politics as distasteful.

For Twitter sceptics, one concern is that the short length of Twitter messages does not allow for meaningful and in-depth discussions around complex political issues. While it is certainly true that expression within 140 characters is limited, one third of tweets between supporters of different parties included links to external sources such as news stories, blog posts, or YouTube videos. Such indirect sourcing can thereby constitute a means of expanding dialogue and debate.

Accordingly, although it is common to view Twitter as largely a platform for self-expression via short tweets, there may be a wider collective dimension to both users and the population at large as a steady stream of both individual viewpoints and referenced sources drive learning and additional exchange. If these exchanges happen across partisan boundaries, they can contribute to greater collective awareness and learning for the citizenry at large.

As the next federal election approaches in 2015, with younger voters gravitating online – especially via mobile devices, and with traditional polling increasingly under siege as less reliable than in the past, all major parties will undoubtedly devote more energy and resources to social media strategies including, perhaps most prominently, an effective usage of Twitter.

Partisan Politics versus Politics 2.0

In a still-nascent era likely to be shaped by the rise of social media and a more participative Internet on the one hand, and the explosion of ‘big data’ on the other hand, the prominence of Twitter in shaping political discourse seems destined to heighten. Our preliminary analysis suggests an important cleavage between traditional political processes and parties – and wider dynamics of political learning and exchange across a changing society that is more fluid in its political values and affiliations.

Within existing democratic structures, Twitter is viewed by political parties as primarily a platform for messaging and branding, thereby mobilizing members with shared viewpoints and attacking opposing interests. Our own analysis of Canadian electoral tweets both amongst partisans and across party lines underscores this point. The nexus between partisan operatives and new media formations will prove to be an increasingly strategic dimension to campaigning going forward.

More broadly, however, Twitter is a source of information, expression, and mobilization across a myriad of actors and formations that may not align well with traditional partisan organizations and identities. Social movements arising during the Arab Spring, amongst Mexican youth during that country’s most recent federal elections and most recently in Ukraine are cases in point. Across these wider societal dimensions – especially consequential in newly emerging democracies, the tremendous potential of platforms such as Twitter may well lie in facilitating new and much more open forms of democratic engagement that challenge our traditional constructs.

In sum, we are witnessing the inception of new forms of what can be dubbed ‘Politics 2.0’ that denotes a movement of both opportunities and challenges likely to play out differently across democracies at various stages of socio-economic, political, and digital development. Whether Twitter and other likeminded social media platforms enable inclusive and expansionary learning, or instead engrain divisive polarized exchange, has yet to be determined. What is clear however is that on Twitter, in some instances, birds of a feather do flock together as they do on political blogs. But in other instances, Twitter can play an important role to foster cross parties communication in the online political arenas.

Read the full article: Gruzd, A., and Roy, J. (2014) Investigating Political Polarization on Twitter: A Canadian Perspective. Policy and Internet 6 (1) 28-48.

Also read: Gruzd, A. and Tsyganova, K. Information wars and online activism during the 2013/2014 crisis in Ukraine: Examining the social structures of Pro- and Anti-Maidan groups. Policy and Internet. Early View April 2015: DOI: 10.1002/poi3.91

Anatoliy Gruzd is Associate Professor in the Ted Rogers School of Management and Director of the Social Media Lab at Ryerson University, Canada. Jeffrey Roy is Professor in the School of Public Administration at Dalhousie University’s Faculty of Management. His most recent book was published in 2013 by Springer: From Machinery to Mobility: Government and Democracy in a Participative Age.

Yet trace data does not fit into the quantitative / qualitative binary. The trace of a tweet includes textual information, often with links or images and metadata about who sent it, when and sometimes where they were. The traces of web browsing are also largely textual with some audio/visual elements. The quantity of these textual traces often necessitates some kind of initial quantitative filtering, but it doesn’t determine the questions or approach.

The challenges are important to understand and address because the promise of new insight into social life is real. Large-scale patterns become possible to detect, for example according to one study of mobile phone location data one’s future location is 93% predictable (Song, Qu, Blum & Barabási, 2010), despite great variation in the individual patterns. This new finding opens up further possibilities for comparison and understanding the context of these patterns. Are locations more or less predictable among people with different socio-economic circumstances? What are the key differences between the most and least predictable?

Computational social science is often associated with large-scale studies of anonymized users such as the phone location study mentioned above, or participation traces of those who contribute to online discussions. Studies that focus on limited information about a large number of people are only one type, which I call horizontal trace data. Other studies that work in collaboration with informed participants can add context and depth by asking for multiple forms of trace data and involving participants in interpreting them — what I call the vertical trace data approach.

In my doctoral dissertation I took the vertical approach to examining political information gathering during an election, gathering participants’ web browsing data with their informed consent and interviewing them in person about the context (Menchen-Trevino 2012). I found that access to websites with political information was associated with self-reported political interest, but access to election-specific pages was not. The most active election-specific browsing came from those who were undecided on election day, while many of those with high political interest had already decided whom to vote for before the election began. This is just one example of how digging futher into such data can reveal that what is true for larger categories (political information in general) may not be true, and in fact can be misleading for smaller domains (election-specific browsing). Vertical trace data collection is difficult, but it should be an important component of the project of computational social science.

Read the full article: Menchen-Trevino, E. (2013) Collecting vertical trace data: Big possibilities and big challenges for multi-method research. Policy and Internet 5 (3) 328-339.

References

Menchen-Trevino, E. (2013) Collecting vertical trace data: Big possibilities and big challenges for multi-method research. Policy and Internet 5 (3) 328-339.

Menchen-Trevino, E. (2012) Partisans and Dropouts?: News Filtering in the Contemporary Media Environment. Northwestern University, Evanston, Illinois.

Song, C., Qu, Z., Blumm, N., & Barabasi, A.-L. (2010) Limits of Predictability in Human Mobility. Science 327 (5968) 1018–1021.

Erica Menchen-Trevino is an Assistant Professor at Erasmus University Rotterdam in the Media & Communication department. She researches and teaches on topics of political communication and new media, as well as research methods (quantitative, qualitative and mixed).

These projects are examples of citizen science; collaborative research undertaken by professional scientists and members of the public. Through these projects, individuals who are not necessarily knowledgeable about or familiar with science can become active participants in knowledge creation (such as in the examples listed in the Chicago Tribune: Want to aid science? You can Zooniverse).

While online citizen science is a relatively recent phenomenon, it has attracted considerable academic attention. Various studies have been undertaken to examine and understand user behaviour, motivation, and the benefits and implications of different projects for them. For instance, Sauermann and Franzoni’s analysis of seven Zooniverse projects (Solar Stormwatch, Galaxy Zoo Supernovae, Galaxy Zoo Hubble, Moon Zoo, Old Weather, The Milkyway Project, and Planet Hunters) found that 60 percent of volunteers never return to a project after finishing their first session of contribution. By comparing contributions to these projects with those of research assistants and Amazon Mechanical Turk workers, they also calculated that these voluntary efforts amounted to an equivalent of $1.5 million in human resource costs.

Our own project on the taxonomy and ecology of contributions to the Zooniverse examines the geographical, gendered and temporal patterns of contributions and contributors to 17 Zooniverse projects between 2009 and 2013. Our preliminary results show that:

• The geographical distribution of volunteers and contributions is highly uneven, with the UK and US contributing the bulk of both. Quantitative analysis of 130 countries show that of three factors – population, GDP per capita and number of Internet users – the number of Internet users is most strongly correlated with the number of volunteers and number of contributions. However, when population is controlled, GDP per capita is found to have greater correlation with numbers of users and volunteers. The correlations are positive, suggesting that wealthier (or more developed) countries are more likely to be involved in the citizen science projects.

• Female volunteers are underrepresented in most countries. Very few countries have gender parity in participation. In many other countries, women make up less than one-third of number of volunteers whose gender is known. The female ratio of participation in the UK and Australia, for instance, is 25 per cent, while the figures for US, Canada and Germany are between 27 and 30 per cent. These figures are notable when compared with the percentage of academic jobs in the sciences held by women. In the UK, women make up only 30.3 percent of full time researchers in Science, Technology, Engineering and Mathematics (STEM) departments (UKRC report, 2010), and 24 per cent in the United States (US Department of Commerce report, 2011).

• Our analysis of user preferences and activity show that in general, there is a strong subject preference among users, with two main clusters evident among users who participate in more than one project. One cluster revolves around astrophysics projects. Volunteers in these projects are more likely to take part in other astrophysics projects, and when one project ends, volunteers are more likely to start a new project within this cluster. Similarly, volunteers in the other cluster, which are concentrated around life and Earth science projects, have a higher likelihood of being involved in other life and Earth science projects than in astrophysics projects. There is less cross-project involvement between the two main clusters.

• In addition to a tendency for cross-project activity to be contained within the same clusters, there is also a gendered pattern of engagement in various projects. Females make up more than half of gender-identified volunteers in life science projects (Snapshot Serengeti, Notes from Nature and WhaleFM have more than 50 per cent of women contributors). In contrast, the proportions of women are lowest in astrophysics projects (Galaxy Zoo Supernovae and Planet Hunters have less than 20 per cent of female contributors). These patterns suggest that science subjects in general are gendered, a finding that correlates with those by the US National Science Foundation (2014). According to an NSF report, there are relatively few women in engineering (13 per cent), computer and mathematical sciences (25 per cent), but they are well-represented in the social sciences (58 per cent) and biological and medical sciences (48 per cent).

• For the 20 most active countries (led by the UK, US and Canada), the most productive hours in terms of user contributions are between 8pm and 10pm. This suggests that citizen science is an after-dinner activity (presumably, reflecting when most people have free time before bed). This general pattern corresponds with the idea that many types of online peer-production activities, such as citizen science, are driven by ‘cognitive surplus’, that is, the aggregation of free time spent on collective pursuits (Shirky, 2010).

These are just some of the results of our study, which has found that despite being informal, relatively more open and accessible, online citizen science exhibits similar geographical and gendered patterns of knowledge production as professional, institutional science. In other ways, citizen science is different. Unlike institutional science, the bulk of citizen science activity happens late in the day, after the workday has ended and people are winding down after dinner and before bed.

We will continue our investigations into the patterns of activity in citizen science and the behaviour of citizen scientists, in order to help improve ways to make science more accessible in general and to tap into the resources of the public for scientific knowledge production. It is anticipated that upcoming projects on the Zooniverse will be more diversified and include topics from the humanities and social sciences. Towards this end, we aim to continue our investigations into patterns of activity on the citizen science platform, and the implications of a wider range of projects on the user base (in terms of age, gender and geographical coverage) and on user behaviour.

References

Sauermann, H., & Franzoni, C. (2015). Crowd science user contribution patterns and their implications. Proceedings of the National Academy of Sciences, 112(3), 679-684.

Shirky, C. (2010). Cognitive surplus: Creativity and generosity in a connected age. Penguin: London.

Taha Yasseri is the Research Fellow in Computational Social Science at the OII. Prior to coming to the OII, he spent two years as a Postdoctoral Researcher at the Budapest University of Technology and Economics, working on the socio-physical aspects of the community of Wikipedia editors, focusing on conflict and editorial wars, along with Big Data analysis to understand human dynamics, language complexity, and popularity spread. He has interests in analysis of Big Data to understand human dynamics, government-society interactions, mass collaboration, and opinion dynamics.

Wikipedia has become one of the most highly linked-to websites on the internet, with countless others using it as a reference. But it can be edited by anyone, and this has led to occasions where errors have been widely repeated – or where facts have been distorted to fit an agenda.

The chairman of the UK’s Conservative Party, Grant Shapps, has been accused of editing Wikipedia pages related to him and his rivals within the party. The Guardian newspaper claims Wikipedia administrators blocked an account on suspicions that it was being used by Shapps, or someone in his employ.

Wikipedia accounts are anonymous, so what is the support for these claims? Is it a case of fair cop or, as Shapps says in his defence, a smear campaign in the run-up to the election?

Edits examined

This isn’t the first time The Guardian has directed similar accusations against Shapps around edits to Wikipedia, with similar claims emerging in September 2012. The investigation examines a list of edits by three Wikipedia user accounts: Hackneymarsh, Historyset, and Contribsx, and several other edits from users without accounts, recorded only as their IP addresses – which the article claimed to be “linked” to Shapps.

The Hackneymarsh account made 12 edits in a short period in May 2010. The Historyset account made five edits in a similar period. All the edits recorded by IP addresses date to between 2008 and 2010. Most recently, the Contribsx account has been active from August 2013 to April 2015.

First of all, it is technically impossible to conclusively link any of those accounts or IP addresses to a real person. Of course you can speculate – and in this case it’s clear that these accounts seem to demonstrate great sympathy with Shapps based on the edits they’ve made. But no further information about the three usernames can be made public by the Wikimedia Foundation, as per its privacy policies.

However, the case is different for the IP addresses. Using GeoIP or similar tools it’s possible to look up the IP addresses and locate them with a fair degree of accuracy to some region of the world. In this case London, Cleethorpes, and in the region of Manchester.

So, based on the publicly available information from ordinary channels, there is not much technical evidence to support The Guardian’s claims.

Putting a sock in sockpuppets

Even if it was possible to demonstrate that Schapps was editing his own Wikipedia page to make himself look good, this sort of self-promotion, while frowned upon, is not sufficient to result in a ban. A Wikipedia admin blocked Contribsx for a different reason regarded far more seriously: sockpuppetry.

The use of multiple Wikipedia user accounts for an improper purpose is called sockpuppetry. Improper purposes include attempts to deceive or mislead other editors, disrupt discussions, distort consensus, avoid sanctions, evade blocks or otherwise violate community standards and policies … Wikipedia editors are generally expected to edit using only one (preferably registered) account.

Certain Wikipedia admins called “check users” have limited access to the logs of IP addresses and details of users’ computer, operating system and the browser recorded by Wikipedia’s webservers. Check users use this confidential information together with other evidence of user behaviour – such as similarity of editing interests – to identify instances of sockpuppetry, and whether the intent has been to mislead.

As a former check user, I can say for the record it’s difficult to establish with complete accuracy whether two or more accounts are used by the same person. But on occasion there is enough to be drawn from the accounts’ behaviour to warrant accusations of sockpuppetry and so enforce a ban. But this only occurs if the sockpuppet accounts have violated any other rule – sockpuppetry itself is not prohibited, only when used for nefarious ends.

Limited technical evidence

In this case, the check user has speculated that Contribsx is related to the other users Hackneymarsh and Historyset – but these users have been inactive for five years, and so by definition cannot have violated any other Wikipedia rule to warrant a ban. More importantly, the technical information available to check users only goes back a couple of months in most cases, so I can’t see the basis for technical evidence that would support the claim these accounts are connected.

In fact the banning administrator admits that the decision is mainly based on behavioural similarity and not technical evidence available to them as a check user. And this has raised criticisms and requests for further investigation from their fellow editors.

In response to the government’s recent declarations that internet speeds of 100Mb/s should be available to “nearly all homes” in the UK, a great many might suggest that this is easier said than done. It would not be the first such bold claim, yet internet connections in many rural areas still languish at 20th-century speeds.

The government’s digital communications infrastructure strategycontains the intention of giving customers the “right” to a broadband connection of at least 5Mb/s in their homes.

There’s no clear indication of any timeline for introduction, nor what is meant by “nearly all homes” and “affordable prices”. But in any case, bumping the minimum speed to 5Mb/s is hardly adequate to keep up with today’s online society. It’s less than the maximum possible ADSL1speed of 8Mb/s that was common in the mid-2000s, far less than the 24Mb/s maximum speed of ADSL2+ that followed, and far, far less than the 30-60Mb/s speeds typical of fibre optic or cable broadband connections available today.

In fact a large number of rural homes still are not able to access even the previously promised 2Mb/s minimum of the Digital Britain report in 2009.

Serious implications

As part of our study of rural broadband access we interviewed 27 people from rural areas in England and Wales about the quality of their internet connection and their daily experiences with slow and unreliable internet. Only three had download speeds of up to 6Mb/s, while most had connections that barely reached 1Mb/s. Even those who reported the faster speeds were still unable to carry out basic online tasks in a reasonable amount of time. For example using Google Maps, watching online videos, or opening several pages at once would require several minutes of buffering and waiting. Having several devices share the connection at a time wasn’t even an option.

So the pledge for a “right” to 5Mb/s made by the chancellor of the exchequer, George Osborne, is as meaningless as previous promises for 2Mb/s. Nor is it close to fast enough. The advertised figure refers to download speed, of which the upload speed is typically only a fraction. This means uploads far slower even than these slow download speeds, rendering it all but unusable for those needing to send large files, such as businesses.

With constantly moving timescales for completion, the government doesn’t seem to regard adequate rural broadband connections as a matter of urgency, even while the consequences for those affected are often serious and urgent at the same time. In Snowdonia, for example, a fast and more importantly reliable broadband connection can be a matter of life and death.

The Llanberis Mountain Rescue team at the foot of Mount Snowdon receives around 200 call-outs a year to rescue mountaineers from danger. Their systems are connected to police and emergency services, all of which run online to provide a quick and precise method of locating lost or injured mountaineers. But their internet connection is below 1Mb/s and cuts out regularly, especially in bad weather, which interferes with dispatching the rescue teams quickly. With low signal or no reception at all in the mountains, neither mobile phone networks nor satellite internet connections are alternatives.

Connection interrupted

Even besides life and death situations, slow and unreliable internet can seriously affect people – their social lives, their family connections, their health and even their finances. Some of those we interviewed had to drive one-and-a-half hours to the nearest city in order to find internet connections fast enough to download large files for their businesses. Others reported losing clients because they weren’t able to maintain a consistent online presence or conduct Skype meetings. Families were unable to check up on serious health conditions of their children, while others, unable to work from home, were forced to commute long distances to an office.

Especially in poorer rural areas such as North Wales, fast and reliable internet could boost the economy by enabling small businesses to emerge and thrive. It’s not a lack of imagination and ability holding people in the region back, it’s the lack of 21st-century communications infrastructure that most of us take for granted.

The government’s strategy document explains that it “wants to support the development of the UK’s digital communications infrastructure”, yet in doing so wishes “to maintain the principle that intervention should be limited to that which is required for the market to function effectively.”

It is exactly this vagueness that is currently preventing communities from taking matters into their own hands. Many of our interviewees said they still hoped BT would deploy fast internet to their village or premises, but had been given no sense of when that might occur, if at all, or that given timescales slip. “Soon” seems to be the word that keeps those in the countryside in check, causing them to hold off on looking for alternatives – such as community efforts like the B4RN initiative in Lancashire.

If the government is serious about the country’s role as a digital nation, it needs to provide feasible solutions for all populated areas of the country, which means affordable, and future-proof, which entails fibre to the premises (FTTP) – and sooner rather than later.

Dementia affects about 44 million individuals, a number that is expected to nearly double by 2030 and triple by 2050. With an estimated annual cost of USD 604 billion, dementia represents a major economic burden for both industrial and developing countries, as well as a significant physical and emotional burden on individuals, family members and caregivers. There is currently no cure for dementia or a reliable way to slow its progress, and the G8 health ministers have set the goal of finding a cure or disease-modifying therapy by 2025. However, the underlying mechanisms are complex, and influenced by a range of genetic and environmental influences that may have no immediately apparent connection to brain health.

Of course medical research relies on access to large amounts of data, including clinical, genetic and imaging datasets. Making these widely available across research groups helps reduce data collection efforts, increases the statistical power of studies and makes data accessible to more researchers. This is particularly important from a global perspective: Swedish researchers say, for example, that they are sitting on a goldmine of excellent longitudinal and linked data on a variety of medical conditions including dementia, but that they have too few researchers to exploit its potential. Other countries will have many researchers, and less data.

‘Big data’ adds new sources of data and ways of analysing them to the repertoire of traditional medical research data. This can include (non-medical) data from online patient platforms, shop loyalty cards, and mobile phones — made available, for example, through Apple’s ResearchKit, just announced last week. As dementia is believed to be influenced by a wide range of social, environmental and lifestyle-related factors (such as diet, smoking, fitness training, and people’s social networks), and this behavioural data has the potential to improve early diagnosis, as well as allow retrospective insights into events in the years leading up to a diagnosis. For example, data on changes in shopping habits (accessible through loyalty cards) may provide an early indication of dementia.

However, there are many challenges to using and sharing big data for dementia research. The technology hurdles can largely be overcome, but there are also deep-seated issues around the management of data collection, analysis and sharing, as well as underlying people-related challenges in relation to skills, incentives, and mindsets. Change will only happen if we tackle these challenges at all levels jointly.

As data are combined from different research teams, institutions and nations — or even from non-medical sources — new access models will need to be developed that make data widely available to researchers while protecting the privacy and other interests of the data originator. Establishing robust and flexible core data standards that make data more sharable by design can lower barriers for data sharing, and help avoid researchers expending time and effort trying to establish the conditions of their use.

At the same time, we need policies that protect citizens against undue exploitation of their data. Consent needs to be understood by individuals — including the complex and far-reaching implications of providing genetic information — and should provide effective enforcement mechanisms to protect them against data misuse. Privacy concerns about digital, highly sensitive data are important and should not be de-emphasised as a subordinate goal to advancing dementia research. Beyond releasing data in a protected environments, allowing people to voluntarily “donate data”, and making consent understandable and enforceable, we also need governance mechanisms that safeguard appropriate data use for a wide range of purposes. This is particularly important as the significance of data changes with its context of use, and data will never be fully anonymisable.

We also need a favourable ecosystem with stable and beneficial legal frameworks, and links between academic researchers and private organisations for exchange of data and expertise. Legislation needs to account of the growing importance of global research communities in terms of funding and making best use of human and data resources. Also important is sustainable funding for data infrastructures, as well as an understanding that funders can have considerable influence on how research data, in particular, are made available. One of the most fundamental challenges in terms of data sharing is that there are relatively few incentives or career rewards that accrue to data creators and curators, so ways to recognise the value of shared data must be built into the research system.

In terms of skills, we need more health-/bioinformatics talent, as well as collaboration with those disciplines researching factors “below the neck”, such as cardiovascular or metabolic diseases, as scientists increasingly find that these may be associated with dementia to a larger extent than previously thought. Linking in engineers, physicists or innovative private sector organisations may prove fruitful for tapping into new skill sets to separate the signal from the noise in big data approaches.

In summary, everyone involved needs to adopt a mindset of responsible data sharing, collaborative effort, and a long-term commitment to building two-way connections between basic science, clinical care and the healthcare in everyday life. Fully capturing the health-related potential of big data requires “out of the box” thinking in terms of how to profit from the huge amounts of data being generated routinely across all facets of our everyday lives. This sort of data offers ways for individuals to become involved, by actively donating their data to research efforts, participating in consumer-led research, or engaging as citizen scientists. Empowering people to be active contributors to science may help alleviate the common feeling of helplessness faced by those whose lives are affected by dementia.

Of course, to do this we need to develop a culture that promotes trust between the people providing the data and those capturing and using it, as well as an ongoing dialogue about new ethical questions raised by collection and use of big data. Technical, legal and consent-related mechanisms to protect individual’s sensitive biomedical and lifestyle-related data against misuse may not always be sufficient, as the recent Nuffield Council on Bioethics report has argued. For example, we need a discussion around the direct and indirect benefits to participants of engaging in research, when it is appropriate for data collected for one purpose to be put to others, and to what extent individuals can make decisions particularly on genetic data, which may have more far-reaching consequences for their own and their family members’ professional and personal lives if health conditions, for example, can be predicted by others (such as employers and insurance companies).

Policymakers and the international community have an integral leadership role to play in informing and driving the public debate on responsible use and sharing of medical data, as well as in supporting the process through funding, incentivising collaboration between public and private stakeholders, creating data sharing incentives (for example, via taxation), and ensuring stability of research and legal frameworks.

Dementia is a disease that concerns all nations in the developed and developing world, and just as diseases have no respect for national boundaries, neither should research into dementia (and the data infrastructures that support it) be seen as a purely national or regional priority. The high personal, societal and economic importance of improving the prevention, diagnosis, treatment and cure of dementia worldwide should provide a strong incentive for establishing robust and safe mechanisms for data sharing.

Read the full report: Deetjen, U., E. T. Meyer and R. Schroeder (2015) Big Data for Advancing Dementia Research. Paris, France: OECD Publishing.

Before the pervasive dissemination of Information and Communication Technologies (ICTs), the use of information in war waging referred to intelligence gathering and propaganda. In the age of the information revolution things have radically changed. Information has now acquired a pivotal role in contemporary warfare, for it has become both an effective target and a viable means. These days, we use ‘cyber warfare’ to refer to the use of ICTs by state actors to disruptive (or even destructive) ends.

As contemporary societies grow increasingly dependant on ICTs, any form of attack that involves their informational infrastructures poses serious risks and raises the need for adequate defence and regulatory measures. However, such a need contrasts with the novelty of this phenomenon, with cyber warfare posing a radical shift in the paradigm within which warfare has been conceived so far. In the new paradigm, impairment of functionality, disruption, and reversible damage substitute for bloodshed, destruction, and casualties. At the same time, the intangible environment (the cyber sphere), targets, and agents substitute for beings in blood and flesh, firearms, and physical targets (at least in the non-kinetic instances of cyber warfare).

The paradigm shift raises questions about the adequacy and efficacy of existing laws and ethical theories for the regulation of cyber warfare. Military experts, strategy planners, law- and policy-makers, philosophers, and ethicists all participate in discussions around this problem. The debate is polarised around two main approaches: (1) the analogy approach, and (2) the discontinuous approach. The former stresses that the regulatory gap concerning cyber warfare is only apparent, insofar as cyber conflicts are not radically different from other forms of conflicts. As Schmitt put it “a thick web of international law norms suffuses cyber-space. These norms both outlaw many malevolent cyber-operations and allow states to mount robust responses”. The UN Charter, NATO Treaty, Geneva Conventions, the first two Additional Protocols, and Convention restricting or prohibiting the use of certain conventional weapons are more than sufficient to regulate cyber warfare; all that is needed is an in-depth analysis of such laws and an adequate interpretation. This is the approach underpinning, for example, the so-called Tallinn Manual.

The opposite position, the discontinuous approach, stresses the novelty of cyber conflicts and maintains that existing ethical principles and laws are not adequate to regulate this phenomenon. Just War Theory is the main object of contention in this case. Those defending this approach argue that Just War Theory is not the right conceptual tool to address non-kinetic forms of warfare, for it assumes bloody and violent warfare occurring in the physical domain. This view sees cyber warfare as one of the most compelling signs of the information revolution — as Luciano Floridi has put it “those who live by the digit, die by the digit”. As such, it claims that any successful attempt to regulate cyber warfare cannot ignore the conceptual and ethical changes that such a revolution has brought about.

These two approaches have proceeded in parallel over the last decade, stalling rather than fostering a fruitful debate. There is therefore a clear need to establish a coordinated interdisciplinary approach that allows for experts with different backgrounds to collaborate and find a common ground to overcome the polarisation of the discussion. This is precisely the goal of the project financed by the NATO Cooperative Cyber Defence Centre of Excellence (NATO CCD COE) and that I co-led with Lt Glorioso, a representative of the Centre. The project has convened a series of workshops gathering international experts in the fields of law, military strategies, philosophy, and ethics to discuss the ethical and regulatory problems posed by cyber warfare.

The first workshop was held in 2013 at the Centro Alti Studi Difesa in Rome and had the goal of launching an interdisciplinary and coordinated approach to the problems posed by cyber warfare. The second event was hosted in last November at Magdalen College, Oxford. It relied on the approach established in 2013 to foster an interdisciplinary discussion on issues concerning attribution, the principle of proportionality, the distinction between combatant and non-combatant, and the one between pre-emption and prevention. A report on the workshop has now been published surveying the main positions and the key discussion points that emerged during the meeting.

One of most relevant points concerned the risks that cyber warfare poses for the established political equilibrium and maintaining peace. The risk of escalation, both in the nature and in the number of conflicts, was perceived as realistic by both the speakers and the audience attending the workshop. Deterrence therefore emerged as one of the most pressing challenges posed by cyber warfare – and one that experts need to take into account in their efforts to develop new forms of regulation in support of peace and stability in the information age.

Read the full report: Corinne J.N. Cath, Ludovica Glorioso, Maria Rosaria Taddeo (2015) Ethics and Policies for Cyber Warfare [PDF, 400kb]. Report on the NATO CCD COE Workshop on ‘Ethics and Policies for Cyber Warfare’, Magdalen College, Oxford, 11-12 November 2014.

Dr Mariarosaria Taddeo is a researcher at the Oxford Internet Institute, University of Oxford. Her main research areas are information and computer ethics, philosophy of information, philosophy of technology, ethics of cyber-conflict and cyber-security, and applied ethics. She also serves as president of the International Association for Computing and Philosophy.

Greg: As I explain in the article, there is a common belief that mass media outlets, and especially online mass media outlets, often portray government in a negative light in an effort to pique the interest of readers. This tendency of media outlets to engage in ‘bureaucracy bashing’ is thought, in turn, to detract from the public’s support for their government. The basic assumption underpinning this relationship is that the more negative information on government there is, the more negative public opinion. However, in my analyses, I found evidence of a positive indirect relationship between citizens’ use of online mass media outlets and their levels of trust in government. Interestingly, however, the more frequently citizens used online mass media outlets for information about their government, the weaker this association became. These findings challenge conventional wisdom that suggests greater exposure to mass media outlets will result in more negative perceptions of the public sector.

Ed: So you find that that the particular positive or negative spin of the actual message may not be as important as the individuals’ sense that they are aware of the activities of the public sector. That’s presumably good news — both for government, and for efforts to ‘open it up’?

Greg: Yes, I think it can be. However, a few important caveats apply. First, the positive relationship between online mass media use and perceptions of government tapers off as respondents made more frequent use of online mass media outlets. In the study, I interpreted this to mean that exposure to mass media had less of an influence upon those who were more aware of public affairs, and more of an influence upon those who were less aware of public affairs. Therefore, there is something of a diminishing returns aspect to this relationship. Second, this study was not able to account for the valence (ie how positive or negative the information is) of information respondents were exposed to when using online mass media. While some attempts were made to control for valance by adding different control variables, further research drawing upon experimental research designs would be useful in substantiating the relationship between the valence of information disseminated by mass media outlets and citizens’ perceptions of their government.

Ed: Do you think governments are aware of this relationship — ie that an indirect effect of being more open and present in the media, might be increased citizen trust — and that they are responding accordingly?

Greg: I think that there is a general idea that more communication is better than less communication. However, at the same time there is a lot of evidence to suggest that some of the more complex aspects of the relationship between openness and trust in government go unaccounted for in current attempts by public sector organizations to become more open and transparent. As a result, this tool that public organizations have at their disposal is not being used as effectively as it could be, and in some instances is being used in ways that are counterproductive–that is, actually decreasing citizen trust in government. Therefore, in order for governments to translate greater openness into greater trust in government, more refined applications are necessary.

Ed: I know there are various initiatives in the UK — open government data / FoIs / departmental social media channels etc. — aimed at a general opening up of government processes. How open is the Korean government? Is a greater openness something they might adopt (or are adopting?) as part of a general aim to have a more informed and involved — and therefore hopefully more trusting — citizenry?

Greg: The South Korean Government, as well as the Seoul Metropolitan Government have gone to great lengths to enhance their openness. Their strategy has made use of different ICTs, such as e-government websites, social media accounts, non-emergency call centers, and smart phone apps. As a result, many now say that attempts by the Korean Government to become more open are more advanced than in many other areas of the developed world. However, the persistent issue in South Korea, as elsewhere, is whether these attempts are having the intended impact. A lot of empirical research has found, for example, that various attempts at becoming more open by many governments around the world have fallen short of creating a more informed and involved citizenry.

Ed: Finally — is there much empirical work or data in this area?

Greg: While there is a lot of excellent empirical research from the field of political science that has examined how mass media use relates to citizens’ perceptions of politicians, political preferences, or their levels of political knowledge, this topic has received almost no attention at all in public management/administration. This lack of discussion is surprising, given mass media has long served as a key means of enhancing the transparency and accountability of public organizations.

Read the full article: Porumbescu, G. (2013) Assessing the Link Between Online Mass Media and Trust in Government: Evidence From Seoul, South Korea. Policy & Internet 5 (4) 418-443.

Greg Porumbescu was talking to blog editor David Sutcliffe.

Gregory Porumbescu is an Assistant Professor at the Northern Illinois University Department of Public Administration. His research interests primarily relate to public sector applications of information and communications technology, transparency and accountability, and citizens’ perceptions of public service provision.

Over the years, this debate has plodded steadily along, with scholars on both ends of the spectrum fighting furiously to establish a working understanding. Then, the Internet came along and drew up new battle lines. The Internet is at its best when it provides a home for the disenfranchised, an environment where like-minded individuals can wipe free the dust of societal disassociation and connect and share content. However, the Internet brought with it a shift in power, particularly in how individuals conceptualised society and their role within it. The Internet, in addition to this role, provided a plethora of new and customisable modes of political participation. From the onset, a lot of these new forms of engagement were extensions of existing forms, broadening the everyday citizen’s participatory repertoire. There was a move from voting to e-voting, petitions to e-petitions, face-to-face communities to online communities; the Internet took what was already there and streamlined it, removing those pesky elements of time, space and identity.

Yet, as the Internet continues to develop, and we move into the ultra-heightened communicative landscape of the social web, new and unique forms of political participation take root, drawing upon those customisable environments and organic cyber migrations. The most prominent of these is clicktivism, sometimes also, unfairly, referred to as slacktivism. Clicktivism takes the fundamental features of browsing culture and turns them into a means of political expression. Quite simply, clicktivism refers to the simplification of online participatory processes: one-click online petitions, content sharing, social buttons (e.g. Facebook’s ‘Like’ button) etc.

For the most part, clicktivism is seen in derogatory terms, with the idea that the streamlining of online processes has created a societal disposition towards feel-good, ‘easy’ activism. From this perspective, clicktivism is a lazy or overly-convenient alternative to the effort and legitimacy of traditional engagement. Here, individuals engaging in clicktivism may derive some sense of moral gratification from their actions, but clicktivism’s capacity to incite genuine political change is severely limited. Some would go so far as to say that clicktivism has a negative impact on democratic systems, as it undermines an individual’s desire and need to participate in traditional forms of engagement; those established modes which mainstream political scholars understand as the backbone of a healthy, functioning democracy.

This idea that clicktivism isn’t ‘legitimate’ activism is fuelled by a general lack of understanding about what clicktivism actually involves. As a recent development in observed political action, clicktivism has received its fair share of attention in the political participation literature. However, for the most part, this literature has done a poor job of actually defining clicktivism. As such, clicktivism is not so much a contested notion, as an ill-defined one. The extant work continues to describe clicktivism in broad terms, failing to effectively establish what it does, and does not, involve. Indeed, as highlighted, the mainstream political participation literature saw clicktivism not as a specific form of online action, but rather as a limited and unimportant mode of online engagement.

However, to disregard emerging forms of engagement such as clicktivism because they are at odds with long-held notions of what constitutes meaningful ‘political’ engagement is a misguided and dangerous road to travel. Here, it is important that we acknowledge that a political act, even if it requires limited effort, has relevance for the individual, and, as such, carries worth. And this is where we see clicktivism challenging these traditional notions of political participation. To date, we have looked at clicktivism through an outdated lens; an approach rooted in traditional notions of democracy. However, the Internet has fundamentally changed how people understand politics, and, consequently, it is forcing us to broaden our understanding of the ‘political’, and of what constitutes political participation.

The Internet, in no small part, has created a more reflexive political citizen, one who has been given the tools to express dissatisfaction throughout all facets of their life, not just those tied to the political arena. Collective action underpinned by a developed ideology has been replaced by project orientated identities and connective action. Here, an individual’s desire to engage does not derive from the collective action frames of political parties, but rather from the individual’s self-evaluation of a project’s worth and their personal action frames.

Simply put, people now pick and choose what projects they participate in and feel little generalized commitment to continued involvement. And it is clicktivism which is leading the vanguard here. Clicktivism, as an impulsive, non-committed online political gesture, which can be easily replicated and that does not require any specialized knowledge, is shaped by, and reinforces, this change. It affords the project-oriented individual an efficient means of political participation, without the hassles involved with traditional engagement.

This is not to say, however, that clicktivism serves the same functions as traditional forms. Indeed, much more work is needed to understand the impact and effect that clicktivist techniques can have on social movements and political issues. However, and this is the most important point, clicktivism is forcing us to reconsider what we define as political participation. It does not overtly engage with the political arena, but provides avenues through which to do so. It does not incite genuine political change, but it makes people feel as if they are contributing. It does not politicize issues, but it fuels discursive practices. It may not function in the same way as traditional forms of engagement, but it represents the political participation aspirations of the modern citizen. Clicktivism has been bridging the dualism between the traditional and contemporary forms of political participation, and in its place establishing a participatory duality.

Clicktivism, and similar contemporary forms of engagement, are challenging how we understand political participation, and to ignore them because of what they don’t embody, rather than what they do, is to move forward with eyes closed.

Read the full article: Halupka, M. (2014) Clicktivism: A Systematic Heuristic. Policy and Internet 6 (2) 115-132.

Max Halupka is a PhD candidate at the ANZOG Institute for Governance, University of Canberra. His research interests include youth political participation, e-activism, online engagement, hacktivism, and fluid participatory structures.

Yong Jin: First, because we rely on the Internet to perform almost all types of transactions, how personal privacy is protected is perhaps one of the important issues we face in this digital age. There are many important findings: the most significant one is that the more popular sites did not necessarily provide better privacy control features for users than sites that were randomly selected. This is surprising because one might expect “the more popular, the better privacy protection” — a sort of marketplace magic that automatically solves the issue of personal privacy online. This was not the case at all, because the popular sites with more resources did not provide better privacy protection. Of course, the Internet in general is a malleable medium. This means that commercial sites can design, modify, or easily manipulate user interfaces to maximize the ease with which users can protect their personal privacy. The fact that this is not really happening for commercial websites in the U.S. is not only alarming, but also suggests that commercial forces may not have a strong incentive to provide privacy protection.

Ed: Your sample included websites oriented toward young users and sensitive data relating to health and finance: what did you find for them?

Yong Jin: Because the sample size for these websites was limited, caution is needed in interpreting the results. But what is clear is that just because the websites deal with health or financial data, they did not seem to be better at providing more privacy protection. To me, this should raise enormous concerns from those who use the Internet for health information seeking or financial data. The finding should also inform and urge policymakers to ask whether the current non-intervention policy (regarding commercial websites in the U.S.) is effective, when no consideration is given for the different privacy needs in different commercial sectors.

Ed: How do your findings compare with the first investigation into these matters by the FTC in 1998?

Yong Jin: This is a very interesting question. In fact, at least as far as the findings from this study are concerned, it seems that no clear improvement has been made in almost two decades. Of course, the picture is somewhat complicated. On the one hand, we see (on the surface) that websites have a lot more interactive features. But this does not necessarily mean improvement, because when it comes to actually informing users of what features are available for their privacy control and protection, they still tend to perform poorly. Note that today’s privacy policies are longer and are likely to carry more pages and information, which makes it even more difficult for users to understand what options they do have. I think informing people about what they can actually do is harder, but is getting more important in today’s online environment.

Ed: Is this just another example of a US market-led vs European regulation-led approach to a particular problem? Or is the situation more complicated?

Yong Jin: The answer is yes and no. Yes, it is because a US market-led approach clearly presents no strong statuary ground to mandate privacy protection in commercial websites. However, the answer is also no: even in the EU there is no regulatory mandate for websites to have certain interface-protections concerning how users should get informed about their personal data, and interact with websites to control its use. The difference is more on the fundamental principle of the “opt-in” EU approach. Although the “opt-in” is stronger than the “opt-out” approach in the U.S. this does not require websites to have certain interface-design aspects that are optimized for users’ data control. In other words, to me, the reality of the EU regulation (despite its robust policy approach) will not necessarily be rosier than the U.S., because commercial websites in the EU context also operate under the same incentive of personal data collection and uses. Ultimately, this is an empirical question that will require further studies. Interestingly, the next frontier of this debate will be on privacy in mobile platforms – and useful information concerning this can be found at the OII’s project to develop ethical privacy guidelines for mobile connectivity measurements.

Ed: Awareness of issues around personal data protection is pretty prominent in Europe — witness the recent European Court of Justice ruling about the ‘Right to Forget’ — how prominent is this awareness in the States? Who’s interested in / pushing / discussing these issues?

Yong Jin: The general public in the U.S. has an enormous concern for personal data privacy, since the Edward Snowden revelations in 2013 revealed extensive government surveillance activities. Yet my sense is that public awareness concerning data collection and surveillance by commercial companies has not yet reached the same level. Certainly, the issue such as the “Right to Forget” is being discussed among only a small circle of scholars, website operators, journalists, and policymakers, and I see the general public mostly remains left out of this discussion. In fact, a number of U.S. scholars have recently begun to weigh the pros and cons of a “Right to Forget” in terms of the public’s right to know vs the individual’s right to privacy. Given the strong tradition of freedom of speech, however, I highly doubt that U.S. policymakers will have a serious interest in pushing a similar type of approach in the foreseeable future.

My own work on privacy awareness, digital literacy, and behavior online suggests that public interest and demand for strong legislation such as a “Right to Forget” is a long shot, especially in the context of commercial websites.

Ed: Given privacy policies are notoriously awful to deal with (and are therefore generally unread) — what is the solution? You say the situation doesn’t seem to have improved in ten years, and that some aspects — such as readability of policies — might actually have become worse: is this just ‘the way things are always going to be’, or are privacy policies something that realistically can and should be addressed across the board, not just for a few sites?

Yong Jin: A great question, and I see no easy answer! I actually pondered a similar question when I conducted this study. I wonder: “Are there any viable solutions for online privacy protection when commercial websites are so desperate to use personal data?” My short answer is No. And I do think the problem will persist if the current regulatory contours in the U.S. continue. This means that there is a need for appropriate policy intervention that is not entirely dependent on market-based solutions.

My longer answer would be that realistically, to solve the notoriously difficult privacy problems on the Internet, we will need multiple approaches — which means a combination of appropriate regulatory forces by all the entities involved: regulatory mandates (government), user awareness and literacy (public), commercial firms and websites (market), and interface design (technology). For instance, it is plausible to perceive a certain level of readability of policy statement is to be required of all websites targeting children or teenagers. Of course, this will function with appropriate organizational behaviors, users’ awareness and interest in privacy, etc. In my article I put a particular emphasis on the role of the government (particularly in the U.S.) where the industry often ‘captures’ the regulatory agencies. The issue is quite complicated because for privacy protection, it is not just the FTC but also Congress who should enact to empower the FTC in its jurisdiction. The apparent lack of improvement over the years since the FTC took over online privacy regulation in the mid 1990s reflects this gridlock in legislative dynamics — as much as it reflects the commercial imperative for personal data collection and use.

I made a similar argument for multiple approaches to solve privacy problems in my article Offline Status, Online Status Reproduction of Social Categories in Personal Information Skill and Knowledge, and related, excellent discussions can be found in Information Privacy in Cyberspace Transactions (by Jerry Kang), and Exploring Identity and Identification in Cyberspace, by Oscar Gandy.

Read the full article: Park, Y.J. (2014) A Broken System of Self-Regulation of Privacy Online? Surveillance, Control, and Limits of User Features in U.S. Websites. Policy & Internet 6 (4) 360-376.

Yong Jin Park was taking to blog editor David Sutcliffe.

Yong Jin Park is an Associate Professor at the School of Communications, Howard University. His research interests center on social and policy implications of new technologies; current projects examine various dimensions of digital privacy.

While these problems could be addressed by new approaches and technologies for financing dynamism in Europe’s economies, financing of (potentially risky) innovation could also be held back by financial regulation that focuses on stability, avoiding forum shopping (i.e., looking for the most permissive regulatory environment), and preventing fraud, to the exclusion of other interests, particularly innovation and renewal. But the role of finance in enabling the development and implementation of new ideas is vital — an economy’s dynamism depends on innovative competitors challenging, and if successful, replacing complacent players in the markets.

However, newcomers obviously need capital to grow. As a reaction to the markets having priced risk too low before the financial crisis, risk is now being priced too high in Europe, starving the innovation efforts of private financing at a time when much public funding has suffered from austerity measures. Of course, complementary (non-bank) sources of finance can also help fund entrepreneurship, and without that petrol of money, the engine of the new technology economy will likely stall.

The Internet has made it possible to fund innovation in new ways like crowd funding — an innovation in finance itself — and there is no reason to think that financial institutions should be immune to disruptive innovation produced by new entrants that offer completely novel ways of saving, insuring, loaning, transferring and investing money. New approaches such as crowdfunding and other financial technology (aka “FinTech”) initiatives could provide depth and a plurality of perspectives, in order to foster innovation in financial services and in the European economy as a whole.

The time has come to integrate these financial technologies into the overall financial frameworks in a manner that does not neuter their creativity, or lower their potential to revitalize the economy. There are potential synergies with macro-prudential policies focused on mitigating systemic risk and ensuring the stability of financial systems. These platforms have great potential for cross-border lending and investment and could help to remedy the retreat of bank capital behind national borders since the financial crisis. It is time for a new perspective grounded in an “innovation-friendly” philosophy and regulatory approach to emerge.

Crowdfunding is a newcomer to the financial industry, and as such, actions (such as complex and burdensome regulatory frameworks or high levels of guaranteed compensation for losses) that could close it down or raise high barriers of entry should be avoided. Competition in the interests of the consumer and of entrepreneurs looking for funding should be encouraged. Regulators should be ready to step in if abuses do, or threaten to, arise while leaving space for new ideas around crowdfunding to gain traction rapidly, without being overburdened by regulatory requirements at an early stage.

The interests of both “financing innovation” and “innovation in the financial sector” also coincide in the FinTech entrepreneurial community. Schumpeter wrote in 1942: “[the] process of Creative Destruction is the essential fact about capitalism. It is what capitalism consists in and what every capitalist concern has got to live in.” An economy’s dynamism depends on innovative competitors challenging, and if successful, taking the place of complacent players in the markets. Keeping with the theme of Schumpeterian creative destruction, the financial sector is one seen by banking sector analysts and commentators as being particularly ripe for disruptive innovation, given its current profits and lax competition. Technology-driven disintermediation of many financial services is on the cards, for example, in financial advice, lending, investing, trading, virtual currencies and risk management.

The UK’s Financial Conduct Authority’s regulatory dialogues with FinTech developers to provide legal clarity on the status of their new initiatives are an example of good practice , as regulation in this highly monitored sector is potentially a serious barrier to entry and new innovation. The FCA also proactively addresses enabling innovation with Project Innovate, an initiative to assist both start-ups and established businesses in implementing innovative ideas in the financial services markets through an Incubator and Innovation Hub.

By its nature, FinTech is a sector that can benefit and benefit from the EU’s Digital Single Market and make Europe a sectoral global leader in this field. In evaluating possible future FinTech regulation, we need to ensure an optimal regulatory framework and specific rules. The innovation principle I discuss in my article should be part of an approach ensuring not only that regulation is clear and proportional — so that innovators can easily comply — but also ensuring that we are ready, when justified, to adapt regulation to enable innovations. Furthermore, any regulatory approaches should be “future proofed” and should not lock in today’s existing technologies, business models or processes.

Read the full article: Zilgalvis, P. (2014) The Need for an Innovation Principle in Regulatory Impact Assessment: The Case of Finance and Innovation in Europe. Policy and Internet 6 (4) 377–392.

Pēteris Zilgalvis, J.D. is a Senior Member of St Antony’s College, University of Oxford, and an Associate of its Political Economy of Financial Markets Programme. In 2013-14 he was a Senior EU Fellow at St Antony’s. He is also currently Head of Unit for eHealth and Well Being, DG CONNECT, European Commission.

Tea is a sector with well-established practices and relations in the region, so we were curious if ICT might be changing it. Of course, one cannot ignore the movements of material goods when you research the tea sector. Tea is Rwanda’s main export by value, and in 2012 it moved over 21,000 tonnes of tea, accruing around $56m in value. During our fieldwork we interviewed cooperatives in remote offices surrounded by tea plantations in the temperate Southern highlands, tea processors in noisy tea factories heavy with the overpowering smell of fermenting tea leaves, and tea buyers and sellers surrounded by corridors piled high with sacks of tea.

But behind the material movement that takes tea from the slopes of Rwanda’s ‘thousand hills’ to a box on a shelf in Tesco, is a growing set of less visible digital data flows. Whilst the adoption of digital technologies is not comprehensive in the Rwandan tea sector (with, for example, very low Internet use among tea growers), we did find growing use of the Internet and ICTs. More importantly, where they were present, digital flows of information (such as tea-batch tracking, logistics and sales prices) were increasingly important to the ability of firms to improve production and ultimately to increase their profit share from tea. We have termed this a ‘data-driven value chain’ to highlight that these new digital information flows are becoming as important as the flows of material goods.

So why is tea production becoming increasingly ‘data-driven’? We found two principal drivers at work. Firstly, production of commodities like tea has shifted to private ownership. In Rwanda, tea processing factories are no longer owned by the government (as they were a decade ago) but by private firms, including several multinational tea firms. Prices for buying and selling tea are also no longer fixed by the government, but depend on the market — flat rate prices stopped at the end of 2012. Data on everything from international prices, tea quality and logistics has become increasingly important as Rwandan tea firms look to be part of the global market, by better coordinating production and improving the prices of their tea. For instance, privately owned tea factories (often in remote locations) connect via satellite or microwave Internet links to head offices, and systems integration allows multi-national tea firms the ability to track and monitor production at the touch of a button.

Secondly, we need to understand new product innovation in the tea sector. In recent years new products have particularly revolved around growing demand in the retail market for differentiated products — such as ‘environmental’, fair trade or high quality teas — for which the consumer is willing to pay more. This relates most obviously to the activities in the fields and tea processors, but digital information is also crucial in order to allow for ‘traceability’ of tea. As this guarantees that tea batches have satisfied conditions around location, food safety, chemical use, fair labour (etc.) a key component of new product innovation is therefore data — because it is integral to firms’ abilities to prove their value-added production or methods.

The idea of agricultural value chains — of analysing agricultural production from the perspective of a fragmented network of interconnected firms — has become increasingly influential in strategies and policy making supported by large donors such as the World Bank and the International Fund for Agriculture Development (IFAD), an agency of the UN.

These value chain approaches explore the amount of economic ‘value’ that different actors in the supply chain are able to capture in production. For instance, Rwandan tea farmers are only able to capture very small proportions of the final retail prices — we estimate they are paid less than 6% of the cost of the eventual retail product, and only 22% of the cost of the raw tea that is sold to retailers. Value chain analysis has been popular for policy makers and donors in that it helps them to formulate policies to support how firms in countries like Rwanda improve their value through innovation, improving processes of production, or reaching new customers.

Yet, at the moment it appears that the types of analysis being done by policy makers and donors pay very little attention to the importance of digital data, and so they are presenting an unclear picture of the ways to improve — with a tendency to focus on material matters such as machinery or business models.

Our research particularly highlighted the importance of considering how to adapt digital data flows. The ways that digital information is codified, digitised and accessed can be exclusionary, reducing the ability for smaller actors in Rwanda to compete. For instance, we found that lack of access to clear information about prices, tea quality and wider market information means that smallholders, small processors and cooperatives may not compete as well as they could, or be missing on wider innovations in tea production.

While we have focused here only on tea production, our discussions with those working in other agricultural sectors — and in other countries — suggest that our observations have significance across other agricultural sectors. In agricultural production, strategy, policy and researchers mainly focus on the material elements of production — those which are more visible and quantifiable. However, we suggest that often underlying such actions is a growing layer of digital data activity. It is only through more coherent analysis of the role of digital technologies and data that we can better analyse production — and build appropriate policy and strategies to support commodity producers in sectors like Rwandan tea.

Read the full report: Foster, C., and Graham, M. (2015) Connectivity and the Tea Sector in Rwanda. Value Chains and Networks of Connectivity-Based Enterprises in Rwanda. Project Report, Oxford Internet Institute, University of Oxford.

Chris Foster is a researcher at the Oxford Internet Institute. His research focus is on technologies and innovation in developing and emerging markets, with a particular interest on how ICTs can support development of low income groups.

One of the great hopes for new Internet connectivity in the developing world is that it will allow those in developing countries who offer products and services to link to and profit from global customers. With the landing of undersea Internet infrastructure in East Africa, there have been hopes that as firms begin to use the Internet more extensively that improved links to markets will positively impact them.

Central to enabling new customer transactions is the emergence of platforms — digital services, websites and online exchanges — that allow more direct customer-producer interactions to occur. As part of our work exploring the impacts of growing internet connectivity and digital ICTs in East Africa, we wanted to explore how digital platforms were affecting Rwandan firms. Have Rwandan firms been able to access online platforms? What impact has access to these platforms had on firms?

Tourism is becoming an increasingly important contributor to Rwanda’s economy, with 3.1% direct contribution to GDP, and representing 7% of employment. Tourism is typically focused on affluent international tourists who come to explore the wildlife of the country, most notably as the most accessible location to see the mountain gorilla. Rwandan policy makers see tourism as a potential area for expansion, and new connectivity could be one key driver in making the country more accessible to customers.

Tourist service providers in Rwanda have a very high Internet adoption, and even the smallest hotel or tour agency is likely to have at least one mobile Internet-connected laptop. Many of the global platforms also have a presence in the region: online travel agents such as Expedia and Hotels.com work with Rwandan hotels, common social media used by tourists such as TripAdvisor and Facebook are also well-known, and firms have been encouraged by the government to integrate into payment platforms like Visa.

So, in the case of Rwandan tourism, Internet connectivity, Internet access and sector-wide platforms are certainly available for tourism firms. During our fieldwork, however (and to our surprise) we found adoption of digital tourism platforms to be low, and the impact on Rwandan tourism minimal. Why? This came down to three mismatches – essentially to do with integration, with fit, and with interactions.

Global tourism platforms offer the potential for Rwandan firms to seamlessly reach a wider range of potential tourists around the globe. However, we found that the requirements for integration into global platforms were often unclear for Rwandan firms, and there was a poor fit with the existing systems and skills. For example, hotels and lodges normally integrate into online travel agencies through integration of internal information systems, which track bookings and availability within hotels. However, in Rwanda, whilst a few larger hotels used booking systems, even the medium-sized hotels lacked internal booking systems, with booking based on custom Excel spreadsheets, or even paper diaries. When tourism firms attempted to integrate into online services they thus ran into problems, and only the large (international) hotel chains tended to be fully integrated.

Integration of East African tourism service providers into global platforms was also limited by the nature of the activities in the region. Global platforms have typically focused on providing facilities for online information, booking and payment for discrete tourism components — a hotel, a flight, a review of an attraction. However, in East Africa much international tourism is ‘packaged’, meaning a third-party (normally a tour operator) will build an itinerary and make all the bookings for customers. This means that online tourism platforms don’t provide a particularly good fit, either for tourists or Rwandan service providers. A tourist will not want the complication of booking a full itinerary online, and a small lodge that gets most of its bookings through tour operators will see little potential in integrating into a global online platform.

Interaction of Rwandan tourism service providers with online platforms is inevitably undertaken over digital networks, based on remote interactions, payments and information flows. This arms-length relationship often becomes problematic where the skills and ability of service providers are lower. For example, Rwandan tourism service providers often require additional information, help or even training on how best to use platforms which are frequently changing. In contexts where lower cost Internet can at times be inconsistent, and payment systems can be busy, having the ability to connect to local help and discuss issues is important. Yet, this is the very element that global platforms like online travel agents are often trying to remove.

So in general, we found that tourism platforms supported the large international hotels and resorts where systems and structures were already in place for seamless integration into platforms. Indeed, as the Rwandan government looks to expand the tourism sector (such as through new national parks and regional integration), there is a risk that the digital domain will support generic international chains entering the country — over the expansion of local firms.

There are potential ways forward, though. Ironically, the most successful online travel agency in Rwanda is one that has contracted a local firm in the capital Kigali to allow for ‘thicker’ interactions between Rwandan service providers and platform providers. There are also a number of South African and Kenyan online platforms in the early stages of development that are more attuned to the regional contexts of tourism (for example Safari Now, a dynamic Safari scheduling platform; Nights Bridge, an online platform for smaller hotels; and WETU, an itinerary sharing platform for service providers), and these may eventually offer a better solution for Rwandan tourism service providers.

We came to similar conclusions in the other sectors we examined as part of our research in East Africa (looking at tea production and Business Process Outsourcing) — that is, that use of online platforms faces limitations in the region. Even as firms find themselves able to access the Internet, the way these global platforms are designed presents a poor fit to the facilities, activities and needs of firms in developing countries. Indeed, in globalised sectors (such as tourism and business outsourcing) platforms can be actively exclusionary, aiding international firms entering developing countries over those local firms seeking to expand outwards.

For platform owners and developers focusing on such developing markets, the impacts of greater access to the Internet are therefore liable to come when platforms are able to balance between global reach and standards — while also being able to integrate some of the specific needs and contexts of developing countries.

Read the full report: Foster, C., and Graham, M. (2015) The Internet and Tourism in Rwanda. Value Chains and Networks of Connectivity-Based Enterprises in Rwanda. Project Report, Oxford Internet Institute, University of Oxford.

Chris Foster is a researcher at the Oxford Internet Institute. His research focus is on technologies and innovation in developing and emerging markets, with a particular interest on how ICTs can support development of low income groups.

When Jike, the Chinese state-run search engine, launched in 2011, its efforts received a mixed response. The Chinese government pulled out all the stops to promote it, including placing Deng Yaping, one of China’s most successful athletes at the helm. Jike strategically branded itself as friendly, high-tech, and patriotic to appeal to national pride, competition, and trust. It also signaled a serious attempt by a powerful authoritarian state to nationalize the Internet within its territory, and to extend its influence in the digital sphere. However, plagued by technological inferiority, management deficiencies, financial woes and user indifference, Jike failed in terms of user adoption, pointing to the limits of state influence in the marketplace.

Users and critics remain skeptical of state-run search engines. While some news outlets referred to Jike as “the little search engine that couldn’t,” Chinese propaganda was busy at work rebranding, recalibrating, and reimagining its efforts. The result? The search engine formally known as Jike has now morphed into a new enterprise known as “ChinaSo”. This transformation is not new — Jike originally launched in 2010 under the name Goso, rebranding itself as Jike a year later. The March 2014 unveiling of ChinaSo was the result of the merging of the two state-run search engines Jike and Panguso.

Only time will tell if this new (ad)venture will prove more fruitful. However, several things are worthy of note here. First, despite repeated trials, the Chinese state has not given up on its efforts to expand its digital toolbox and weave a ‘China Wide Web’. Rather, state media have pooled their resources to make their collective, strategic bets. The merging of Jike and Panguso into ChinaSo was backed by several state media giants, including People’s Daily, Xinhua News Agency, and China Central Television. Branded explicitly as “China Search: Authoritative National Search,” ChinaSo reinforces a sense of national identity. How does it perform? ChinaSo now ranks 225th in China and 2139th globally (Alexa.com, 8 February 2015), up from Jike’s ranking of 376th in China and 3,174th globally that we last recorded in May 2013. While ChinaSo’s rankings have increased over time, a low adoption rate continues to haunt the state search engine. Compared to China’s homegrown commercial search giant Baidu that ranks first in China and fifth globally (Alexa.com, 8 February 2015), ChinaSo has a long way to go.

Second, in terms of design, ChinaSo has adopted a mixture of general and vertical search to increase its appeal to a wide range of potential users. Its general search, similar to Google’s and Baidu’s, allows users to query through a search box to receive results in a combination of text, image and video formats based on ChinaSo’s search engine that archives, ranks, and presents information to users. In addition, ChinaSo incorporates vertical search focusing on a wide range of categories such as transportation, investment, education and technology, health, food, tourism, shopping, real estate and cars, and sports and entertainment. Interestingly, ChinaSo also guides searchers by highlighting “top search topics today” as users place their cursor in the search box. Currently, various “anti-corruption” entries appear prominently which correspond to the central government’s high-profile anti-corruption campaigns. Given the opaqueness of search engine operation, it is unclear whether the “top searches” are ChinaSo’s editorial choices or search terms based on user queries. We suspect ChinaSo strategically prioritizes this list to direct user attention.

Third, besides improved functionality that enhances ChinaSo’s priming and agenda-setting abilities, it continues to practice (as did Jike) sophisticated information filtering and presentation. For instance, a search of “New York Times” returns not a single result directing users to the paper’s website — as it is banned in China. Instead, on the first page of results, ChinaSo directs users to several Chinese online encyclopedia entries for New York Times, stock information of NYT, and sanctioned news stories relating to the NYT that have appeared in such official media outlets as People’s Net, China Daily, and Global Times. All information appears in Chinese, which has acted as a natural barrier to the average Chinese user who seeks information outside China. Although Chinese language versions of foreign new organizations such as NYT Chinese, WSJ Chinese, and BBC Chinese exist, they are invariably blocked in China.

Last, ChinaSo’s long-term impact on China’s search market and users remains unclear. While many believe ChinaSo to be a “waste of taxpayer money” due to its persistent inability to carve out its market share in competition, others are willing to give it a shot, especially with regard to queries for official policies and statements, remarking that “[there] is nothing wrong with creating a state-run search engine service” and that ChinaSo’s results are better than those of its commercial counterparts. It seems that users either do not care or remain largely unaware of the surveillance capacities of search engines. Although recent scholarship (for instance here and here) has started to probe the Chinese notion and practices of privacy in social networking sites, no research has been conducted with regard to search-related privacy concerns in the Chinese context.

The idea of a state-sponsored search engine is not new, however. As early as 2005, a few European countries proposed a Euro-centric search engine “Project Quaero” to compete against Google and Yahoo! in what was perceived to be the “threat of Anglo-Saxon cultural imperialism.” In the post-Snowden world, not only are powerful authoritarian countries—China, Russia, Iran, and Turkey—interested in building their own national search engines, democratic countries like Germany and Brazil have also condemned the U.S. government and vowed to create their own “national Internets.”

The changing international political landscape compels researchers, policy makers and the public to re-evaluate previous assumptions of internationalism and confront the reality of the role of the Internet as an extension of state power and national identity instead. In the near future, the “the return of the state”, reflected in various trends to re-nationalize communication networks, will likely go hand in hand with social, economic and cultural changes that cross national and international borders. ChinaSo is part and parcel of the “geopolitical turn” in policy and Internet studies that should command more scholarly and public attention.

Read the full article: Jiang, M. & Okamoto, K. (2014) National identity, ideological apparatus, or panopticon? A case study of the Chinese national search engine Jike. Policy and Internet 6 (1) 89-107.

Min Jiang is an Associate Professor, in the department of Communication Studies, UNC Charlotte. Kristen Okamoto is a Ph.D. Student in the school of Communication Studies, University of Ohio.

Advocates of Open Government Data (OGD) – that is, data produced or commissioned by government or government-controlled entities that can be freely used, reused and redistributed by anyone – talk about the potential of such data to increase government transparency, catalyse economic growth, address social and environmental challenges and boost democratic participation. This heady mix of potential benefits has proved persuasive to the UK Government (and governments around the world). Over the past decade, since the emergence of the OGD agenda, the UK Government has invested extensively in making more of its data open. This investment has included £10 million to establish the Open Data Institute and a £7.5 million fund to support public bodies overcome technical barriers to releasing open data.

Yet the transformative impacts claimed by OGD advocates, in government as well as NGOs such as the Open Knowledge Foundation, still seem a rather distant possibility. Even the more modest goal of integrating the creation and use of OGD into the mainstream practices of government, businesses and citizens remains to be achieved. In my recent article Barriers to the Open Government Data Agenda: Taking a Multi-Level Perspective (Policy & Internet 6:3) I reflect upon the barriers preventing the OGD agenda from making a breakthrough into the mainstream. These reflections centre on the five key finds of a survey exploring where key stakeholders within the UK OGD community perceive barriers to the OGD agenda. The key messages from the UK OGD community are that:

1. Barriers to the OGD agenda are perceived to be widespread 

Unsurprisingly, given the relatively limited impact of OGD to date, my research shows that barriers to the OGD agenda are perceived to be widespread and numerous in the UK’s OGD community. What I find rather more surprising is the expectation, amongst policy makers, that these barriers ought to just melt away when exposed to the OGD agenda’s transparently obvious value and virtue. Given that the breakthrough of the OGD agenda (in actual fact) will require changes across the complex socio-technical structures of government and society, many teething problems should be expected, and considerable work will be required to overcome them.

2. Barriers on the demand side are of great concern

Members of the UK OGD community are particularly concerned about the wide range of demand-side barriers, including the low level of demand for OGD across civil society and the public and private sectors. These concerns are likely to have arisen as a legacy of the OGD community’s focus on the supply of OGD (such as public spending, prescription and geospatial data), which has often led the community to overlook the need to nurture initiatives that make use of OGD: for example innovators such as Carbon Culture who use OGD to address environmental challenges.

Adopting a strategic approach to supporting niches of OGD use could help overcome some of the demand-side barriers. For example, such an approach could foster the social learning required to overcome barriers relating to the practices and business models of data users. Whilst there are encouraging signs that the UK’s Open Data Institute (a UK Government-supported not-for-profit organisation seeking to catalyse the use of open data) is supporting OGD use in the private sector, there remains a significant opportunity to improve the support offered to potential OGD users across civil society. It is also important to recognise that increasing the support for OGD users is not guaranteed to result in increased demand. Rather the possibility remains that demand for OGD is limited for many other reasons – including the possibility that the majority of businesses, citizens and community organisations find OGD of very little value.

3. The structures of government continue to act as barriers

Members of the UK OGD community are also concerned that major barriers remain on the supply side, particularly in the form of the established structures and institutions of government. For example, barriers were perceived in the forms of the risk-adverse cultures of government organisations and the ad hoc funding of OGD initiatives. Although resilient, these structures are dynamic, so proponents of OGD need to be aware of emerging ‘windows of opportunity’ as they open up. Such opportunities may take the form of tensions within the structures of government (e.g. where restrictions on data sharing between different parts of government present an opportunity for OGD to create efficiency savings); and external pressures on government (e.g. the pressure to transition to a low carbon economy could create opportunities for OGD initiatives and demand for OGD).

4. There are major challenges to mobilising resources to support the open government data agenda

The research results also showed that members of the UK’s OGD community see mobilising the resources required to support the OGD as a major challenge. Concerns around securing funding are predictably prominent, but concerns also extend to developing the skills and knowledge required to use OGD across civil society, government and the private sector. These challenges are likely to persist whilst the post-financial crisis narrative of public deficit reduction through public spending reduction dominates the political agenda. This leaves OGD advocates to consider the politics and ethics of calling for investment in OGD initiatives, whilst spending reductions elsewhere are leading to the degradation of public services provision to vulnerable and socially excluded individuals.

5. The nature of some barriers remains contentious within the OGD community

OGD is often presented by advocates as a neutral, apolitical public good. However, my research highlights the important role that values and politics plays in how individuals within the OGD community perceive the agenda and the barriers it faces. For example, there are considerable differences in opinion, within the OGD community, on whether or not a private sector focus on exploiting financial value from OGD is crowding out the creation of social and environmental value. So benefits may arise from advocates being more open about the values and politics that underpin and shape the agenda. At the same time, OGD-related policy and practice could create further opportunities for social learning that brings together the diverse values and perspectives that coexist within the OGD community.

Having considered the wide range of barriers to the breakthrough of OGD agenda, and some approaches to overcoming these barriers, these discussions need setting in a broader political context. If the agenda does indeed make a breakthrough into the mainstream, it remains unclear what form this will take. Will the OGD agenda make a breakthrough by conforming with, and reinforcing, prevailing neoliberal interests? Or will the agenda stretch the fabric of government, the economy and society, and transform the relationship between citizens and the state?

Read the full article: Martin, C. (2014) Barriers to the Open Government Data Agenda: Taking a Multi-Level Perspective. Policy & Internet 6 (3) 217-240.

Ed: Firstly, what is a ‘virtual’ economy? And what exactly are people earning or exchanging in these online environments?

Vili: A virtual economy is an economy that revolves around artificially scarce virtual markers, such as Facebook likes or, in this case, virtual items and currencies in an online game. A lot of what we do online today is rewarded with such virtual wealth instead of, say, money.

Ed: In terms of ‘virtual earning power’ what was the relationship between character gender and user gender?

Vili: We know that in national economies, men and women tend to be rewarded differently for the same amount of work; men tend to earn more than women. Since online economies are such a big part of many people’s lives today, we wanted to know if this holds true in those economies as well. Looking at the virtual economies of two massively-multiplayer online games (MMOG), we found that there are indeed some gender differences in how much virtual wealth players accumulate within the same number of hours played. In one game, EVE Online, male players were on average 11 percent wealthier than female players of the same age, character skill level, and time spent playing. We believe that this finding is explained at least in part by the fact that male and female players tend to favour different activities within the game worlds, what we call “virtual pink and blue collar occupations”. In national economies, this is called occupational segregation: jobs perceived as suitable for men are rewarded differently from jobs perceived as suitable for women, resulting in a gender earnings gap.

However, in another game, EverQuest II, we found that male and female players were approximately equally wealthy. This reflects the fact that games differ in what kind of activities they reward. Some provide a better economic return on fighting and exploring, while others make it more profitable to engage in trading and building social networks. In this respect games differ from national economies, which all tend to be biased towards rewarding male-type activities. Going beyond this particular study, fantasy economies could also help illuminate the processes through which particular occupations come to be regarded as suitable for men or for women, because game developers can dream up new occupations with no prior gender expectations attached.

Ed: You also discussed the distinction between user gender and character gender…

Vili: Besides occupational segregation, there are also other mechanisms that could explain economic gender gaps, like differences in performance or outright discrimination in pay negotiations. What’s interesting about game economies is that people can appear in the guise of a gender that differs from their everyday identity: men can play female characters and vice versa. By looking at player gender and character gender separately, we can distinguish between how “being” female and “appearing to be” female are related to economic outcomes.

We found that in EVE Online, using a female character was associated with slightly less virtual wealth, while in EverQuest II, using a female character was associated with being richer on average. Since in our study the players chose the characters themselves instead of being assigned characters at random, we don’t know what the causal relationship between character gender and wealth in these games was, if any. But it’s interesting to note that again the results differed completely between games, suggesting that while gender does matter, its effect has more to do with the mutable “software” of the players and/or the coded environments rather than our immutable “hardware”.

Ed: The dataset you worked with could be considered to be an example of ‘big data’ (ie you had full transactional trace data people interacting in two games) — what can you discover with this sort of data (as opposed to eg user surveys, participant observation, or ethnographies); and how useful or powerful is it?

Vili: Social researchers are used to working with small samples of data, and then looking at measures of statistical significance to assess whether the findings are generalizable to the overall population or whether they’re just a fluke. This focus on statistical significance is sometimes so extreme that people forget to consider the practical significance of the findings: even if the effect is real, is it big enough to make any difference in practice? In contrast, when you are working with big data, almost any relationship is statistically significant, so that becomes irrelevant. As a result, people learn to focus more on practical significance — researchers, peer reviewers, journal editors, funders, as well as the general public. This is a good thing, because it can increase the impact that social research has in society.

In this study, we spent a lot of time thinking about the practical significance of the findings. In any national economy, a 11 percent gap between men and women would be huge. But in virtual economies, overall wealth inequality tends to be orders of magnitude greater than in national economies, so that a 11 percent gap is in fact relatively minuscule. Other factors, like whether one is a casual participant in the economy or a semi-professional, have a much bigger effect, so much so that I’m not sure if participants notice a gender gap themselves. Thus one of the key conclusions of the study was that we also need to look beyond traditional sociodemographic categories like gender to see what new social divisions may be appearing in virtual economies.

Ed: What do you think are the hot topics and future directions in research (and policy) on virtual economies, gaming, microwork, crowd-sourcing etc.?

Vili: Previously, ICT adoption resulted in some people’s jobs being eliminated and others being enhanced. This shift had uneven impacts on men’s and women’s jobs. Today, we are seeing an Internet-fuelled “volunterization” of some types of work — moving the work from paid employees and contractors to crowds and fans compensated with points, likes, and badges rather than money. Social researchers should keep track of how this shift impacts different social categories like men and women: whose work ends up being compensated in play money, and who gets to keep the conventional rewards.

Read the full article: Lehdonvirta, V., Ratan, R. A., Kennedy, T. L., and Williams, D. (2014) Pink and Blue Pixel$: Gender and Economic Disparity in Two Massive Online Games. The Information Society 30 (4) 243-255.

Vili Lehdonvirta is a Research Fellow and DPhil Programme Director at the Oxford Internet Institute, and an editor of the Policy & Internet journal. He is an economic sociologist who studies the social and economic dimensions of new information technologies around the world, with particular expertise in digital markets and crowdsourcing.

Vili Lehdonvirta was talking to blog editor David Sutcliffe.

Drones create headlines. Like AI, their unfettered use plays on our most sci-fi induced fears. Military deployment both intrigues us and serves to increase our suspicions. Commerce enthusiastically explores their value to meet consumers ‘on-demand’ expectations. Natural history film-makers experiment with drone technology to give us rare access to the natural world. In June 2014, the US National Park Service banned them from 401 parks while it worked out a new management policy and this week a pilot reported sighting a UAV near the flight path of a passenger jet. It’s clear that the increasing use of drones presents complex challenges.

UAVs or Unmanned Aerial Vehicles offer intriguing possibilities for nature conservation. One dominant focus of experimentation is their use for data capture and monitoring alongside data analytics and other spatial and reporting tools. The potential of integrated digital capabilities such GPS / satellite tagging and geo-mapping, cloud services, mobile devices, camera-traps, radio telemetry, LiDAR and data from field observation, to better understand and respond to nature conservation concerns may be significant.

Suggestive of this promise, is the facility to assess biodiversity in difficult or rapidly changing terrain, to track rehabilitated species and gather data to refine reintroduction programmes or to pick-up real-time changes in animal behaviour that may indicate imminent threat of poaching. The need has never been greater. The findings of the WWF Living Planet Report 2014 are sobering: ‘Species populations worldwide have declined by 52% since 1970’. Many digitally enabled conservation projects are now underway, and hopes are high.

Professor Serge Wich, Professor in Primate Biology, Liverpool John Moores University and Lian Pin Koh (Founding Directors of Conservationdrones.org), have developed drone technology to support tracking of orangutans and to assess their habitat loss. This work produces 3d geometrically accurate computer representations of the forest in near real-time that can help for example, to detect forest fires and illegal logging activity. In the course of this work they have continued to innovate and refine their model. The orangutan drone is more robust, it employs a Google maps interface and the photo data now uses automatic object recognition to detect orangutan nests. Integrating such technology with radio collars (and in some cases small sensors implanted into newly released animals), camera-traps, spy microphones and wifi data collection, can build a far more detailed picture of the behaviour and range of endangered species. This when overlaid with other data-sets, is likely to prove a valuable tool for conservation planners, if integration challenges can be resolved.

While use of digital capabilities is broadly embraced by academics and field researchers, drones do however present some very particular issues. A number of academics working in drone research for nature conservation have for example, stressed the need for caution in their rapid deployment to support anti-poaching initiatives: the concern being to avoid creating a perception of ‘fortress conservation’. Organisations are urged to consider how on-the-ground relationships may be affected by fear of ‘sinister technologies of surveillance’, thereby undoing the significant strides made through local engagement.

Academics and field-researchers also point out that drone technology for conservation purposes is very new, and its cost effectiveness — when compared with other kinds of intervention, such as training field observers — not yet proven. Due to their use in remote environments, drones (and similar tracking technologies) are also subject to issues such as battery life, range and GPS coverage, data consistency and analytics systems management. The validity of drone data in securing poaching convictions is another area of consideration and, as the US National Park Service decision illustrates, the broader legal and political impacts are still to be thought through.

Nature conservation initiatives are often, due to their hard to navigate, large scale operating context, costly and resource-intensive. They have to overcome issues associated with prevailing political unrest, lack of economic support and natural sensitivities to local customs and concerns. Innovation in such environments requires far more thought than the simple application of technologies demonstrated to work elsewhere. Every environment and each species presents particular challenges. Digital technologies, data interpretation and local participation require a precise set of conditions to work optimally.

And there is also a danger of reinventing the wheel; solutions to many of the problems nature conservationists seek to solve might be achieved, for example, by harnessing lessons from the rapid iteration of digital health technologies (device innovation remains critical for many nature conservation projects) or by surveying solutions already in use by the military and extraction industries. Many NGOs have worked hard to establish collaborations that facilitate such valuable knowledge exchange.

In 2011 one consortium created the SMART tool (spatial monitoring and reporting software). This helps local rangers using GPS to collect data, which is analysed automatically to support the swift diversion of resources to areas of need. It’s simple, quick, and visual — using maps to present findings — and the integration of low-cost robust mobile devices enables triangulation for better navigation and synching with cameras. It will also support tracking even when turned off to preserve battery life.

Another collective, Global Forest Watch established in 2012 and led by Lilian Pintea, VP Conservation Science, has developed a platform for different groups to record and share research such as deforestation alerts. Nature conservation groups can access a common cloud-based mapping system with shared variables that also supports integration with other data sets and overlay of hi-resolution images, such as those gathered by drones.

The Jane Goodall Institute is working with local partners to exploit these advances in remote sensing for global land cover maps for chimpanzee and gorilla surveying. Many other organisations and governments are experimenting with drones in efforts to protect other particularly fragile environments. In Belize for example conservation drones now monitor the health of marine ecosystems.

It’s a significant task but recent projects of this kind are yielding valuable results. Other work that employs digital innovation and UAV capabilities to support nature conservation – beyond monitoring and data capture – includes the development of robot insects at the Harvard Robotics Lab (including robot bees which could act as a ‘stop gap’ while populations recover) and ‘Robirds’ built at the University of Twente (which connects simple digital technologies with an understanding of predator-prey relationships to keep raptors away from areas of danger such as airfields).

Digital innovation for nature conservation will benefit from cross-disciplinary creativity. The marriage of digital media, technology, on-the-ground engagement and research expertise has great potential to address concerns and improve opportunities to collaborate. The questions that persist are how best to share knowledge and harness new digital technologies and innovation? How to build on the hard work already done on the ground with policy-makers and across boundaries? How to ensure new technologies are used appropriately, are cost-effective and integrated with sensitivity to local needs and resource constraints? And most importantly of all…how can we best to employ such capabilities to protect and share the wonder of the natural world?

Lisa Sargood is director of digital strategy at Horton Wolfe and Academic Visitor at the OII. Prior to this she was Exec Producer and Commissioner for digital output across BBC Nature and BBC Science. Her projects include Spring/Autumn-watch, Blue Planet, Planet Earth, Stargazing Live, Horizon, LabUK (Brain Test Britain etc.), Big Cat Live and Virtual Revolution, which won a BAFTA and an International Emmy®. Her research focuses on the potential for digital media, technology and public engagement to support nature conservation and drive pro-environment behaviours.

Contact: lisa.sargood@oii.ox.ac.uk Twitter: @lisasargood

Today’s parliamentary decision is also a milestone for another reason: it is the first piece of “crowdsourced” legislation on its way to becoming law in Finland. A 2012 constitutional change made it possible for 50,000 citizens or more to propose a bill to the parliament, through a mechanism known as the citizen initiative. Citizens can develop bills on a website maintained by the Open Ministry, a government-supported citizen association. The Open Ministry aims to be the deliberative version of government ministries that do the background work for government bills. Once the text of a citizen bill is finalised, citizens can also endorse it on a website maintained by the Ministry of Justice. If a bill attracts more than 50,000 endorsements within six months, it is delivered to the parliament.

A significant reason behind the creation of the citien initiative system was to increase citizen involvement in decision making and thus enhance the legitimacy of Finland’s political system: to make people feel that they can make a difference. Finland, like most Western democracies, is suffering from dwindling voter turnout rates (though in the last parliamentary elections, domestic voter turnout was a healthy 70.5 percent). However, here lies one of the potential pitfalls of the citizen initiative system. Of the six citizen bills delivered to the parliament so far, parliamentarians have outright rejected most proposals. According to research presented by Christensen and his colleagues at our Internet, Politics & Policy conference in Oxford in September (and to be published in issue 7:1 of Policy and Internet, March 2015), there is a risk that the citizen iniative system ends up having an effect that is opposite from what was intended:

“[T]hose who supported [a crowdsourced bill rejected by the parliament] experienced a drop in political trust as a result of not achieving this outcome. This shows that political legitimacy may well decline when participants do not get the intended result (cf. Budge, 2012). Hence, if crowdsourcing legislation in Finland is to have a positive impact on political legitimacy, it is important that it can help produce popular Citizens’ initiatives that are subsequently adopted by Parliament.”

One reason why citizen initiatives have faced a rough time in the parliament is that they are a somewhat odd addition to the parliament’s existing ways of working. The Finnish parliament, like most parliaments in representative democracies, is used to working in a government-opposition arrangement, where the government proposes bills, and parliamentarians belonging to government parties are expected to support those bills and resist bills originating from the opposition. Conversely, opposition leaders expect their members to be loyal to their own initiatives. In this arrangement, citizen initiatives have fallen into a no-man’s land where they are endorsed by neither government nor opposition members. Thanks to the party whip system, their only hope of passing has been in being adopted by the government. But the whole point of citizen initiatives is that they would allow bills not proposed by the government to reach parliament, making the exercise rather pointless.

The marriage equality citizen initiative was able to break this pattern not only because it enjoyed immense popular support, but also because many parliamentarians saw marriage equality as a matter of conscience, where the party whip system wouldn’t apply. Parliamentarians across party lines voted in support and against the initiative, in many cases ignoring their party leaders’ instructions.

Prime Minister Alexander Stubb commented immediately after the vote that the outcome “shows the power of citizen initiatives”, “citizen democracy and direct democracy”. Now that a precedent has been set, it is possible that subsequent citizen initiatives, too, get judged more on their merits than on who proposed them. Today’s decision on marriage equality may thus turn out to be historic not only for advancing equality and fairness, but also for helping to define crowdsourcing’s role in Finnish parliamentary decision making.

Vili Lehdonvirta is a Research Fellow and DPhil Programme Director at the Oxford Internet Institute, and an editor of the Policy & Internet journal. He is an economic sociologist who studies the social and economic dimensions of new information technologies around the world, with particular expertise in digital markets and crowdsourcing.

The explicit goal of the conference was twofold. On the one hand, we tried to take stock of European achievements in science, engineering, technology and innovation (SETI) during the last 10 years. On the other hand, we looked into potential future opportunities that SETI may bring to Europe, both in economic terms (growth, jobs, new business opportunities) and in terms of wellbeing (individual welfare and higher social standards).

One of the most interesting aspects of the meeting was the presentation of the latest report on “The Future of Europe is Science” by the President’s Science and Technology Advisory Council (STAC). The report addresses some very big questions: How will we keep healthy? How will we live, learn, work and interact in the future? How will we produce and consume and how will we manage resources? It also seeks to outline some key challenges that will be faced by Europe over the next 15 years. It is well written, clear, evidence-based and convincing. I recommend reading it. In what follows, I wish to highlight three of its features that I find particularly significant.

First, it is enormously refreshing and reassuring to see that the report treats science and technology as equally important and intertwined. The report takes this for granted, but anyone stuck in some Greek dichotomy between knowledge (episteme, science) and mere technique (techne, technology) will be astonished. While this divorcing of the two has always been a bad idea, it is still popular in contexts where applied science, e.g. applied physics or engineering, is considered a Cinderella. During my talk, I referred to Galileo as a paradigmatic scientist who had to be innovative in terms of both theories and instruments.

Today, technology is the outcome of innovative science and there is almost no science that is independent of technology, in terms of reliance on digital data and processing or (and this is often an inclusive or) in terms of investigations devoted to digital phenomena, e.g. in the social sciences. Of course, some Fields Medallists may not need computers to work, and may not work on computational issues, but they represent an exception. This year, Hiroshi Amano, Shuji Nakamura and Isamu Akasaki won the Nobel in physics “for the invention of efficient blue light-emitting diodes which has enabled bright and energy-saving white light sources”. Last year, François Englert and Peter Higgs were awarded the Nobel in physics “for the theoretical discovery of a mechanism that contributes to our understanding of the origin of mass of subatomic particles, and which recently was confirmed through the discovery of the predicted fundamental particle, by the ATLAS and CMS experiments at CERN’s Large Hadron Collider”. Without the technologically sophisticated work done at CERN, their theoretical discovery would have remained unsupported. The hope is that universities, research institutions, R&D centres as well as national research agencies will follow the approach espoused by STAC and think strategically in terms of technoscience.

The second point concerns some interesting statistics. The report uses several sources—especially the 2014 Eurobarometer survey of “Public perception of science, research and innovation”—to analyse and advise about the top priorities for SETI over the next 15 years, as identified by EU respondents. The picture that emerges is an ageing population worried, first of all, about its health, then about its children’s jobs, and only after that about the environment: 55 % of respondents identified “health and medical care” as among what they thought should be the main priorities for science and technological development over the next 15 years; 49 % opted for “job creation”; 33 % privileged “education and skills”. So we spent most of the meeting in Lisbon discussing these three areas. Other top priorities include “protection of the environment” (30 %), “energy supply” (25 %) and the “fight against climate change” (22 %).

So far so predictable, although it is disappointing to see such a low concern about the environment, a clear sign that even educated Europeans (with the exception of Danish and Swedish respondents) may not be getting the picture: there is no point in being healthy and employed in a desert. Yet this is not what I wish to highlight. Rather, on p. 14 of the report, the authors themselves admit that: “Contrary to our expectations, citizens do not consider the protection of personal data to be a high priority for SET in the next 15 years (11 %)”. This is very interesting. As a priority, data protection ranks as low as quality of housing: nice, but very far from essential. The authors quickly add that “but this might change in the future if citizens are confronted with serious security problems”.

They are right, but the point remains that, at the moment, all the fuss about privacy in the EU is a political rather than a social priority. Recall that this is an ageing population of grown-ups, not a bunch of teenagers in love with pictures of cats and friends online, allegedly unable to appreciate what privacy means (a caricature increasingly unbelievable anyway). Perhaps we “do not get it” when we should (a bit like the environmental issues) and need to be better informed. Or perhaps we are informed and still think that other issues are much more pressing. Either way, our political representatives should take notice.

Finally, and most importantly, the report contains a recommendation that I find extremely wise and justified. On p. 19, the Advisory Council acknowledges that, among the many foresight activities to be developed by the Commission, one in particular “should also be a priority”: ethical foresight. This must be one of the first times that ethical foresight is theorised as a top priority in the development of science and technology. The recommendation is based on the crucial and correct realisation that ethical choices, values, options and constraints influence the world of SETI much more than any other force. The evaluation of what is morally good, right or necessary shapes public opinion, hence the socially acceptable and the politically feasible and so, ultimately, the legally enforceable.

In the long run, business is constrained by law, which is constrained by ethics. This essential triangle means that—in the context of technoscientific research, development and innovation—ethics cannot be a mere add-on, an afterthought, a latecomer or an owl of Minerva that takes its flight only when the shades of night are gathering, once bad solutions have been implemented and mistakes have been made. Ethics must sit at the table of policy-making and decision-taking procedures from day one. It must inform our strategies about SETI especially at the beginning, when changing the course of action is easier and less costly, in terms of resources and impact. We must think twice but above all we must think before taking important steps, in order to avoid wandering into what Galileo defined as the dark labyrinth of ignorance.

As I stressed at the end of my keynote, the future of Europe is science, and this is why our priority must be ethics now.

Read the editorial: Floridi, L. (2014) Technoscience and Ethics Foresight. Editorial, Philosophy & Technology 27 (4) 499-501.

Luciano Floridi is the OII’s Professor of Philosophy and Ethics of Information. His research areas are the philosophy of Information, information and computer ethics, and the philosophy of technology. His most recent book is The Fourth Revolution – How the infosphere is reshaping human reality (2014, Oxford University Press).

The excitement over the potentially transformative effects of the internet in low-income countries is nowhere more evident than in East Africa – the last major populated region of the world to gain a wired connection to the internet.

Before 2009, there wasn’t a single fibre-optic cable connecting the region to the rest of the world. After hundreds of millions of dollars of investment, cables were laid to connect the region to the global network. Prices for internet access went down, speeds went up, and the number of internet users in the region skyrocketed.

Politicians, journalists and academics all argued that better connectivity would lead to a blossoming of economic, social, and political activity – and a lot of influential people in the region made grand statements. For instance, former Kenyan president Mwai Kibai stated:

I am gratified to be with you today at an event of truly historic proportions. The landing of this fibre-optic undersea cable project in Mombasa is one of the landmark projects in Kenya’s national development story.

Indeed some have compared this to the completion of the Kenya-Uganda railway more than a century ago. This comparison is not far-fetched, because while the economies of the last century were driven by railway connections, the economies of today are largely driven by internet.

The president of Rwanda, Paul Kagame, also spoke about the revolutionary potentials of these changes in connectivity. He claimed:

In Africa, we have missed both the agricultural and industrial revolutions and in Rwanda we are determined to take full advantage of the digital revolution. This revolution is summed up by the fact that it no longer is of utmost importance where you are but rather what you can do – this is of great benefit to traditionally marginalised regions and geographically isolated populations.

As many who have studied politics have long since noted, proclamations like these can have an important impact: they frame how scarce resources can be spent and legitimise actions in certain areas while excusing inaction in others.

Two moments of change

Because the internet is so frequently talked about in revolutionary terms, colleagues Casper Andersen and Laura Mann and I decided to compare in a paper the many hopes, expectations and fears written about the internet with those from another transformational moment in East Africa’s history: the construction of the Uganda Railway.

The Uganda Railway was built from 1896 to 1903 between Mombasa and Lake Victoria, connecting parts of East Africa to each other and the region to the wider world. There were strong views at the time of what this could bring. The journalist and explorer Henry Morten Stanley claimed:

I seemed to see in a vision what was to happen in the years to come. I saw steamers trailing their dark smoke over the waters of the lake; I saw passengers arriving and disembarking; I saw the natives of the east making blood brotherhood with the natives of the west. And I seemed to hear the sound of church bells ringing at great distance afar off.

A young Winston Churchill waxed lyrical on the new railway:

What a road it is! Everything is apple-pie order. The track is smoothed and weeded and ballasted as if it were London and North-Western. Every telegraph post has its number; every mile, every hundred yards, every change of gradient, has its mark … Here and there, at intervals which will become shorter every year, are plantations of rubber, fibre and cotton, the beginnings of those inexhaustible supplies which will one day meet the yet unmeasured demand of Europe for those indispensable commodities… In brief, one slender thread of scientific civilisation, of order, authority, and arrangement, drawn across the primeval chaos of the world.

Learning from expectations

After a full analysis of the historical and contemporary texts, we can make two key points.

The hopes and fears people hold about changes to how they connect with other people and places are surprisingly similar across generations. But there are notable differences between these two moments, a century apart.

The arrival of the railway revolved around the use of technology to integrate an empire and open up new lands to imperial ambitions. By framing the arrival of the railway as allowing the core to extend its dominion over the periphery, what was said and written at the time served to legitimise the extension of colonialism.

The arrival of fibre-optic cables, however, presents a different story. Instead of a world of shrinking space between the core and periphery, it tends to lean more on the idea of a “global village.” The need to connect everyone to the global economy overrides concepts of self sufficiency, local economies, or trade outside the global marketplace.

These visions matter because they leave little room for alternatives. Just as dominant narratives around the arrival of the railway presented a worldview amenable to colonialism, contemporary dominant narratives offer a convenient justification of globalised capitalism and neo-liberalism.

How people imagine they are connected to the world matters. They shape how we make sense of the world and ultimately what steps we take to re-shape the world. We should therefore look to the past, and not just the future, when we examine the effects of the changing ways in which we are connected.

Ed: Does research on MOOCs differ in any way from existing research on online learning?

Rebecca: Despite the hype around MOOCs to date, there are many similarities between MOOC research and the breadth of previous investigations into (online) learning. Many of the trends we’ve observed (the prevalence of forum lurking; community formation; etc.) have been studied previously and are supported by earlier findings. That said, the combination of scale, global-reach, duration, and “semi-synchronicity” of MOOCs have made them different enough to inspire this work. In particular, the optional nature of participation among a global-body of lifelong learners for a short burst of time (e.g. a few weeks) is a relatively new learning environment that, despite theoretical ties to existing educational research, poses a new set of challenges and opportunities.

Ed: The MOOC forum networks you modelled seemed to be less efficient at spreading information than randomly generated networks. Do you think this inefficiency is due to structural constraints of the system (or just because inefficiency is not selected against); or is there something deeper happening here, maybe saying something about the nature of learning, and networked interaction?

Rebecca: First off, it’s important to not confuse the structural “inefficiency” of communication with some inherent learning “inefficiency”. The inefficiency in the sub-forums is a matter of information diffusion—i.e., because there are communities that form in the discussion spaces, these communities tend to “trap” knowledge and information instead of promoting the spread of these ideas to a vast array of learners. This information diffusion inefficiency is not necessarily a bad thing, however. It’s a natural human tendency to form communities, and there is much education research that says learning in small groups can be much more beneficial / effective than large-scale learning. The important point that our work hopes to make is that the existence and nature of these communities seems to be influenced by the types of topics that are being discussed (and vice versa)—and that educators may be able to cultivate more isolated or inclusive network dynamics in these course settings by carefully selecting and presenting these different discussion topics to learners.

Ed: Drawing on surveys and learning outcomes you could categorise four ‘learner types’, who tend to behave differently in the network. Could the network be made more efficient by streaming groups by learning objective, or by type of interaction (eg learning / feedback / social)?

Rebecca: Given our network vulnerability analysis, it appears that discussions that focus on problems or issues that are based in real life examples –e.g., those that relate to case studies of real companies and analyses posted by learners of these companies—tend to promote more inclusive engagement and efficient information diffusion. Given that certain types of learners participate in these discussions, one could argue that forming groups around learning preferences and objectives could promote more efficient communications. Still, it’s important to be aware of the potential drawbacks to this, namely, that promoting like-minded / similar people to interact with those they are similar to could further prevent “learning through diverse exposures” that these massive-scale settings can be well-suited to promote.

Ed: In the classroom, the teacher can encourage participation and discussion if it flags: are there mechanisms to trigger or seed interaction if the levels of network activity fall below a certain threshold? How much real-time monitoring tends to occur in these systems?

Rebecca: Yes, it appears that educators may be able to influence or achieve certain types of network patterns. While each MOOC is different (some course staff members tend to be much more engaged than others, learners may have different motivations, etc.), on the whole, there isn’t much real-time monitoring in MOOCs, and MOOC platforms are still in early days where there is little to no automated monitoring or feedback (beyond static analytics dashboards for instructors).

Ed: Does learner participation in these forums improve outcomes? Do the most central users in the interaction network perform better? And do they tend to interact with other very central people?

Rebecca: While we can’t infer causation, we found that when compared to the entire course, a significantly higher percentage of high achievers were also forum participants. The more likely explanation for this is that those who are committed to completing the course and performing well also tend to use the forums—but the plurality of forum participants (44% in one of the courses we analyzed) are actually those that “fail” by traditional marks (receive below 50% in the course). Indeed, many central users tend to be those that are simply auditing the course or who are interested in communicating with others without any intention of completing course assignments. These central users tend to communicate with other central users, but also, with those whose participation is much sparser / “on the fringes”.

Ed: Slightly facetiously: you can identify ‘central’ individuals in the network who spark and sustain interaction. Can you also find people who basically cause interaction to die? Who will cause the network to fall apart? And could you start to predict the strength of a network based on the profiles and proportions of the individuals who make it up?

Rebecca: It is certainly possible to further explore how different people seem. One way this can be achieved is by exploring the temporal dynamics at play—e.g., by visualizing the communication network at any point in time and creating network “snapshots” at every hour or day, or perhaps, with every new participant, to observe how the trends and structures evolve. While this method still doesn’t allow us to identify the exact influence of any given individual’s participation (since there are so many other confounding factors, for example, how far into the course it is, peoples’ schedules / lives outside of the MOOC, etc.), it may provide some insight into their roles. We could of course define some quantitative measure(s) to measure “network strength” based on learner profiles, but caution against overarching or broad claims in doing so due to confounding forces would be essential.

Ed: The majority of my own interactions are mediated by a keyboard: which is actually a pretty inefficient way of communicating, and certainly a terrible way of arguing through a complex point. Is there any sense from MOOCs that text-based communication might be a barrier to some forms of interaction, or learning?

Rebecca: This is an excellent observation. Given the global student body, varying levels of comfort in English (and written language more broadly), differing preferences for communication, etc., there is much reason to believe that a lack of participation could result from a lack of comfort with the keyboard (or written communication more generally). Indeed, in the MOOCs we’ve studied, many learners have attempted to meet up on Google Hangouts or other non-text based media to form and sustain study groups, suggesting that many learners seek to use alternative technologies to interact with others and achieve their learning objectives.

Ed: Based on this data and analysis, are there any obvious design points that might improve interaction efficiency and learning outcomes in these platforms?

Rebecca: As I have mentioned already, open-ended questions that focus on real-life case studies tend to promote the least vulnerable and most “efficient” discussions, which may be of interest to practitioners looking to cultivate these sorts of environments. More broadly, the lack of sustained participation in the forums suggests that there are a number of “forces of disengagement” at play, one of them being that the sheer amount of content being generated in the discussion spaces (one course had over 2,700 threads and 15,600 posts) could be contributing to a sense of “content overload” and helplessness for learners. Designing platforms that help mitigate this problem will be fundamental to the vitality and effectiveness of these learning spaces in the future.

Ed: I suppose there is an inherent tension between making the online environment very smooth and seductive, and the process of learning; which is often difficult and frustrating: the very opposite experience aimed for (eg) by games designers. How do MOOCs deal with this tension? (And how much gamification is common to these systems, if any?)

Rebecca: To date, gamification seems to have been sparse in most MOOCs, although there are some interesting experiments in the works. Indeed, one study (Anderson et al., 2014) used a randomized control trial to add badges (that indicate student engagement levels) next to the names of learners in MOOC discussion spaces in order to determine if and how this affects further engagement. Coursera has also started to publicly display badges next to the names of learners that have signed up for the paid Signature Track of a specific course (presumably, to signal which learners are “more serious” about completing the course than others). As these platforms become more social (and perhaps career advancement-oriented), it’s quite possible that gamification will become more popular. This gamification may not ease the process of learning or make it more comfortable, but rather, offer additional opportunities to mitigate the challenges massive-scale anonymity and lack of information about peers to facilitate more social learning.

Ed: How much of this work is applicable to other online environments that involve thousands of people exploring and interacting together: for example deliberation, crowd production and interactive gaming, which certainly involve quantifiable interactions and a degree of negotiation and learning?

Rebecca: Since MOOCs are so loosely structured and could largely be considered “informal” learning spaces, we believe the engagement dynamics we’ve found could apply to a number of other large-scale informal learning/interactive spaces online. Similar crowd-like structures can be found in a variety of policy and practice settings.

Ed: This project has adopted a mixed methods approach: what have you gained by this, and how common is it in the field?

Rebecca: Combining computational network analysis and machine learning with qualitative content analysis and in-depth interviews has been one of the greatest strengths of this work, and a great learning opportunity for the research team. Often in empirical research, it is important to validate findings across a variety of methods to ensure that they’re robust. Given the complexity of human subjects, we knew computational methods could only go so far in revealing underlying trends; and given the scale of the dataset, we knew there were patterns that qualitative analysis alone would not enable us to detect. A mixed-methods approach enabled us to simultaneously and robustly address these dimensions. MOOC research to date has been quite interdisciplinary, bringing together computer scientists, educationists, psychologists, statisticians, and a number of other areas of expertise into a single domain. The interdisciplinarity of research in this field is arguably one of the most exciting indicators of what the future might hold.

Ed: As well as the network analysis, you also carried out interviews with MOOC participants. What did you learn from them that wasn’t obvious from the digital trace data?

Rebecca: The interviews were essential to this investigation. In addition to confirming the trends revealed by our computational explorations (which revealed the what of the underlying dynamics at play), the interviews, revealed much of the why. In particular, we learned people’s motivations for participating in (or disengaging from) the discussion forums, which provided an important backdrop for subsequent quantitative (and qualitative) investigations. We have also learned a lot more about people’s experiences of learning, the strategies they employ to their support their learning and issues around power and inequality in MOOCs.

Ed: You handcoded more than 6000 forum posts in one of the MOOCs you investigated. What findings did this yield? How would you characterise the learning and interaction you observed through this content analysis?

Rebecca: The qualitative content analysis of over 6,500 posts revealed several key insights. For one, we confirmed (as the network analysis suggested), that most discussion is insignificant “noise”—people looking to introduce themselves or have short-lived discussions about topics that are beyond the scope of the course. In a few instances, however, we discovered the different patterns (and sometimes, cycles) of knowledge construction that can occur within a specific discussion thread. In some cases, we found that discussion threads grew to be so long (with over hundreds of posts), that topics were repeated or earlier posts disregarded because new participants didn’t read and/or consider them before adding their own replies.

Ed: How are you planning to extend this work?

Rebecca: As mentioned already, feelings of helplessness resulting from sheer “content overload” in the discussion forums appear to be a key force of disengagement. To that end, as we now have a preliminary understanding of communication dynamics and learner tendencies within these sorts of learning environments, we now hope to leverage this background knowledge to develop new methods for promoting engagement and the fulfilment of individual learning objectives in these settings—in particular, by trying to mitigate the “content overload” issues in some way. Stay tuned for updates

References

Anderson, A., Huttenlocher, D., Kleinberg, J. & Leskovec, J., Engaging with Massive Open Online Courses.  In: WWW ’14 Proceedings of the 23rd International World Wide Web Conference, Seoul, Korea. New York: ACM (2014).

Read the full paper: Gillani, N., Yasseri, T., Eynon, R., and Hjorth, I. (2014) Structural limitations of learning in a crowd – communication vulnerability and information diffusion in MOOCs. Scientific Reports 4.

Rebecca Eynon was talking to blog editor David Sutcliffe.

Rebecca Eynon holds a joint academic post between the Oxford Internet Institute (OII) and the Department of Education at the University of Oxford. Her research focuses on education, learning and inequalities, and she has carried out projects in a range of settings (higher education, schools and the home) and life stages (childhood, adolescence and late adulthood).

In the realm of education and technology, a central question that researchers and policymakers alike have been grappling with has been: why does there continue to be such vast amounts of resources invested in education technology and related initiatives without substantial evidence to suggest that the promises of such technologies and related initiatives are being fulfilled? By adopting a political economy approach, which examines the social, political and economic processes shaping the production, consumption, and distribution of resources including information and communication technologies (Mosco, 2009), we can begin to understand why and how the considerable zeal surrounding education technologies and the sustained investments persist.

An exemplar case for this type of analysis, giving us a deeper understanding of the structural forces shaping the K-12 institutional circuits, would be the recent tech-centered incidents riddling the Los Angeles Unified School District.

iPad-for-all and the MiSiS CriSiS

Last month the Los Angeles Unified School District Superintendent, John Deasy, and Chief Technology Officer, Ron Chandler, both resigned due to the $1 billion iPad initiative and what is being called the MiSiS CriSiS. Underpinning these initiatives are idealistic beliefs in the powers of technology and the trend towards the standardization and corporatization of the US K-12 education.

Despite the dire need for classroom upgrades and recovery from the recession-induced mass teacher layoffs and library closures, this past year John Deasy announced the plan to direct the district’s resources toward an initiative that places iPads in all 640,000 LAUSD students’ hands. Perpetuating the idealistic promise that technology acts as a leveling tool in society, Deasy pledged that this initiative would afford equal educational opportunities across the board regardless of race or socioeconomic background of students. He stated that this would allow low-income students to have access to the same technological tools as their middle class counterparts. Commendable as the effort was, this overly idealized sentiment that technology will ameliorate the deeply rooted systemic inequities facing society is partly responsible for the furthering of misdirected investments and ineffective policies in the education technology realm.

The My Integrated Student Information System was meant to streamline the course registration process and centralize the storage of all student records. For reasons that haven’t been entirely unearthed yet, the software was pushed by Deasy and was launched a couple months ago despite various warnings from administrators and teachers that it wasn’t ready. Leaving many students disenfranchised without the necessary courses needed for college and unverified accuracy of senior transcripts for college applications, the MiSiS CriSiS brings to light one of the main concerns with these technological integration projects in schools and the interests involved — accountability. Who is accountable for ensuring there is a back up of records or to get students into the classes they need? Who is accountable for ensuring the most reliable software is chosen? While there has been heightened accountability measures in the form of high-stakes testing directed towards teacher effectiveness, there still remains little accountability regarding the process of choosing specific technology services, their plans for implementation, and overall effectiveness of the services or initiatives.

These incidents are direct results of the broader political-economic structure of public education in the United States. This is a structure characterized by interrelationships between the federal, state, and local governments and the private sector. Central to this institutional structure and the proliferation of ICT-related education initiatives are the workings of digital capitalism[1].

Digital Capitalism and the American Educational-Industrial Complex[2]

Federal, state, and local governments all contribute funding to K-12 public education in the U.S. but according to the U.S. constitution, states are ultimately responsible for their public schools. The bulk of funding for schools comes from local taxes, which creates vast inequalities across the country in terms of educational resources, infrastructure, and teaching. There has been sustained effort from the federal level to ameliorate these inequities in education, from the Elementary and Secondary Education Act of 1965 and its subsequent amendments to the highly contentious Race to the Top initiative that has built-in incentives for underachieving schools to increase student performance. However, these efforts are exceptionally limited and riddled with problems. This has only been complicated further with the economic downturn in the US, which has resulted in massive layoffs in public education resulting in an unrelenting and growing dependence on private sector resources.

Accountability, as mentioned above, is a major theme discussed in the context of education and digital capitalism. Again, while initiatives like No Child Left Behind and Race to the Top are meant to hold teachers accountable, there is still a lack of accountability measures for private sector involvement in education. Another force of digital capitalism that is responsible for the sustained proliferation of ICT-driven initiatives in education is the shift in the perceived goals of education from serving to ensure an enlightened citizenry to being valued for its vocational outputs. This is being fueled by global competitiveness discourses presented under the veil of “21^st century skills” rhetoric in order to keep the U.S. economically competitive. This has made the circular relationship between government and the corporate technology sector more salient in education. Simply put, the government is putting pressure on the public to ensure new generations are primed with the necessary 21^st century skills in order to participate in the labor market while also enhancing the position of the US in the global economy and the private sector is pushing this discourse further because they have products to sell to fulfill this elusive goal. This is further exemplified in the new standardized curriculum project rolling out in K-12.

Technology Driven Corporatization of American Public Education

This past year 45 states adopted the Common Core State Standards, which is meant to standardize curriculum across the country under the assumption that it will place all students regardless of race or class at the same level across all subjects. One major technological implication of this standardization includes the standardization of delivery systems, signaled by the iPads with Pearson education software project in LAUSD. This creates a direct line of entry for private companies to become even further entrenched in education. In many ways, these developments are making the privatization efforts more concrete and foreshadowing the evolving structure of the public K-12 system. Privatization doesn’t necessarily mean that schools are going to be under direct control of private companies (although this is already happening in certain parts of the country; you can read about it in my forthcoming article) but it does represent the transformation of education as a public good into a profit center for private interests, as demonstrated in LAUSD.

In the LAUSD situation, it is no coincidence that John Deasy has an extensive background in private industry and specifically education technology industry. Deasy came from the Gates Foundation, one of the leading education partners. Former Deputy Superintendent Jamie Aquino came from Pearson, the curriculum developers that were to provide the software for the iPad initiative. What’s more significant about these close ties and the iPad for all project is that before the bidding went public, Aquino and Deasy had already begun a backdoor deal with both Pearson and Apple to carry out the initiative thus illustrating the conflicts of interests between government, industry, and education.

Conclusion

Perhaps the recent incidents that have been riddling the Los Angeles Unified School District will bring more public attention to these issues and a push for more evidenced-based policies will emerge. Nonetheless, the issues arising in LA Unified represent broader structural, political-economic forces that shed light on the answer to the question posed earlier. Attention to these larger structural processes being propelled by such forces is what drives my own research, which aims to extend digital exclusion scholarship and provide evidence-based suggestions for more sustainable policies that maximize benefits for the populations they seek to serve. In this vein, posing a couple of preliminary policy suggestions might be appropriate.

In a nutshell, it would be naïve to assume that the private sector has nothing to offer the public sector and that public schools are not in a position to benefit from the resources they bring. However, the decision-making power needs to be more balanced among all stakeholders in order for these benefits to be realized. Several suggestions for policymakers are made in an article based on my previous research that is forthcoming but can similarly be applied here. Overall, there is a need for impact assessment measurements for these interventions that would provide valuable insight into the effectiveness of the ICT-driven initiatives. Additionally, a recommendation for more accountability measures in each stage of these projects is needed in order to ensure that the benefits are being realized and promises fulfilled. Ultimately, while perhaps a bit idealistic at this point, a shift from an economic focus to a social rights based approach to policymaking in this realm would help to create more sustainable policies that maximize the benefits for groups they’re meant to serve.

Admittedly, this is a simplified overview of the forces at play in the current restructuring of K-12 but hopefully it has provided useful insight into how technology’s role in society is not determined by the technology itself but rather by a complex ecosystem of networks and power relations that shape larger social structures. It is, of course, much more complex with many layers of discourses and sociopolitical entanglements but my goal is that this snapshot has highlighted the importance for understanding the social, political, and economic underpinnings in order to grasp the larger picture of technology’s role in society and, more specifically, education.

References

Mosco, V. (2009). The Political Economy of Communication. London. Sage Publishing.

Picciano, A.G., & Spring, J.H. (2013). The Great American Education-Industrial Complex: Ideology, technology, and profit. Routledge.

Schiller, D. (1999) Digital Capitalism. Cambridge: The MIT Press.

[1] For more on Digital Capitalism, see Dan Schiller (1999) Digital Capitalism.

[2] This concept was drawn from Picciano and Spring’s (2014) The Great American Education-Industrial Complex: Ideology, Technology, and profit.

Paige Mustain is a DPhil student at the Oxford Internet Institute. Her research lies at the intersection of education and digital exclusion. More specifically, she focuses on the political economy of information and communication technology (ICT) development initiatives in the realm of education.

Mark: We are studying online freelancing. In other words this is digital or digitised work for which professional certification or formal training is usually not required. The work is monetised or monetisable, and can be mediated through an online marketplace.

Freelancing is a very old format of work. What is new is the fact that we have almost three billion people connected to a global network: many of those people are potential workers in virtual production networks. This mass connectivity has been one crucial ingredient for some significant changes in how work is organised, divided, outsourced, and rewarded. What we plan to do in this project is better map the contours of some of those changes and understand who wins and who doesn’t in this new world of work.

Ed: Are you able to define what comprises an individual contribution to a ‘virtual production network’ — or to find data on it? How do you define and measure value within these global flows and exchanges?

Mark: It is very far from easy. Much of what we are studying is immaterial and digitally-mediated work. We can find workers and we can find clients, but the links between them are often opaque and black-boxed. Some of the workers that we have spoken to operate under non-disclosure agreements, and many actually haven’t been told what their work is being used for.

But that is precisely why we felt the need to embark on this project. With a combination of quantitative transaction data from key platforms and qualitative interviews in which we attempt to piece together parts of the network, we want to understand who is (and isn’t) able to capture and create value within these networks.

Ed: You note that “within virtual production networks, are we seeing a shift in the boundaries of firms” — to what extend to you think we seeing the emergence of new forms of organisation?

Mark: There has always been a certain spatial stickiness to some activities carried out by firms (or within firms). Some activities required the complex exchanges of knowledge that were difficult to digitally mediate. But digitisation and better connectivity in low-wage countries has now allowed many formerly ‘in-house’ business processes to be outsourced to third-parties. In an age of cloud computing, cheap connectivity, and easily accessible collaboration tools, geography has become less sticky. One task that we are engaged in is looking at the ways that some kinds of tacit knowledge that are difficult to transmit digitally offer some people and firms (in different places) competitive advantages and disadvantages.

This proliferation of digitally mediated work could also be seen as a new form of organisation. The organisations that control key work marketplaces (like oDesk) make decisions that shape both who buyers and sellers are able to connect with, and the ways in which they are able to transact.

Ed: Does ‘virtual work’ add social or economic value to individuals in low-income countries? ie are we really dealing with a disintermediated, level surface on a global playing field, or just a different form of old exploitation (ie a virtual rather than physical extraction industry)?

Mark: That is what we aim to find out. Many have pointed to the potentials of online freelancing to create jobs and bring income to workers in low-income countries. But many others have argued that such practices are creating ‘digital sweatshops’ and facilitating a race to the bottom.

We undoubtedly are not seeing a purely disintermediated market, or a global playing field. But what we want to understand is who exactly benefits from these new networks of work, and how.

Ed: Will you be doing any network analysis of the data you collect, ie of actual value-flows? And will they be geolocated networks?

Mark: Yes! I am actually preparing a post that contains a geographic network of all work conducted over the course of a month via oDesk (see the website of the OII’s Connectivity, Inclusion, and Inequality Group for more..).

Mark Graham was talking to blog editor David Sutcliffe.

Mark Graham is a Senior Research Fellow at the OII. His research focuses on Internet and information geographies, and the overlaps between ICTs and economic development.

But what constitutes a “significant” learning interaction? In large-scale MOOC forums, with socio-culturally diverse learners with different motivations for participating, this is a non-trivial problem. MOOCs are best defined as “non-formal” learning spaces, where learners pick and choose how (and if) they interact. This kind of group membership, together with the short-term nature of these courses, means that relatively weak inter-personal relationships are likely. Many of the tens of thousands of interactions in the forum may have little relevance to the learning process. So can we actually define the underlying network of significant interactions? Only once we have done this can we explore firstly how information flows through the forums, and secondly the robustness of those interaction networks: in short, the effectiveness of the platform design for supporting group learning at scale.

To explore these questions, we analysed data from 167,000 students registered on two business MOOCs offered on the Coursera platform. Almost 8000 students contributed around 30,000 discussion posts over the six weeks of the courses; almost 30,000 students viewed at least one discussion thread, totalling 321,769 discussion thread views. We first modelled these communications as a social network, with nodes representing students who posted in the discussion forums, and edges (ie links) indicating co-participation in at least one discussion thread. Of course, not all links will be equally important: many exchanges will be trivial (‘hello’, ‘thanks’ etc.). Our task, then, was to derive a “true” network of meaningful student interactions (ie iterative, consistent dialogue) by filtering out those links generated by random encounters (Figure 1; see also full paper for methodology).

Network vulnerability is interesting because it indicates how integrated and inclusive the communication flow is. Discussion forums with fleeting participation will have only a very few vocal participants: removing these people from the network will markedly reduce the information flow between the other participants — as the network falls apart, it simply becomes more difficult for information to travel across it via linked nodes. Conversely, forums that encourage repeated engagement and in-depth discussion among participants will have a larger ‘critical set’, with discussion distributed across a wide range of learners.

To understand the structure of group communication in the two courses, we looked at how quickly our modelled communication network fell apart when: (a) the most central nodes were iteratively disconnected (Figure 2; blue), compared with when (b) nodes were removed at random (ie the ‘neutral’ case; green). In the random case, the network degrades evenly, as expected. When we selectively remove the most central nodes, however, we see rapid disintegration: indicating the presence of individuals who are acting as important ‘bridges’ across the network. In other words, the network of student interactions is not random: it has structure.

Of course, the structure of participant interactions will reflect the purpose and design of the particular forum. We can see from Figure 3 that different forums in the courses have different vulnerability thresholds. Forums with high levels of iterative dialogue and knowledge construction — with learners sharing ideas and insights about weekly questions, strategic analyses, or course outcomes — are the least vulnerable to degradation. A relatively high proportion of nodes have to be removed before the network falls apart (rightmost-blue line). Forums where most individuals post once to introduce themselves and then move their discussions to other platforms (such as Facebook) or cease engagement altogether tend to be more vulnerable to degradation (left-most blue line). The different vulnerability thresholds suggest that different topics (and forum functions) promote different levels of forum engagement. Certainly, asking students open-ended questions tended to encourage significant discussions, leading to greater engagement and knowledge construction as they read analyses posted by their peers and commented with additional insights or critiques.

Understanding something about the vulnerability of a communication or interaction network is important, because it will tend to affect how information spreads across it. To investigate this, we simulated an information diffusion model similar to that used to model social contagion. Although simplistic, the SI model (‘susceptible-infected’) is very useful in analyzing topological and temporal effects on networked communication systems. While the model doesn’t account for things like decaying interest over time or peer influence, it allows us to compare the efficiency of different network topologies.

We compared our (real-data) network model with a randomized network in order to see how well information would flow if the community structures we observed in Figure 2 did not exist. Figure 4 shows the number of ‘infected’ (or ‘reached’) nodes over time for both the real (solid lines) and randomized networks (dashed lines). In all the forums, we can see that information actually spreads faster in the randomised networks. This is explained by the existence of local community structures in the real-world networks: networks with dense clusters of nodes (i.e. a clumpy network) will result in slower diffusion than a network with a more even distribution of communication, where participants do not tend to favor discussions with a limited cohort of their peers.

Overall, these results reveal an important characteristic of student discussion in MOOCs: when it comes to significant communication between learners, there are simply too many discussion topics and too much heterogeneity (ie clumpiness) to result in truly global-scale discussion. Instead, most information exchange, and by extension, any knowledge construction in the discussion forums occurs in small, short-lived groups: with information “trapped” in small learner groups. This finding is important as it highlights structural limitations that may impact the ability of MOOCs to facilitate communication amongst learners that look to learn “in the crowd”.

These insights into the communication dynamics motivate a number of important questions about how social learning can be better supported, and facilitated, in MOOCs. They certainly suggest the need to leverage intelligent machine learning algorithms to support the needs of crowd-based learners; for example, in detecting different types of discussion and patterns of engagement during the runtime of a course to help students identify and engage in conversations that promote individualized learning. Without such interventions the current structural limitations of social learning in MOOCs may prevent the realization of a truly global classroom.

The next post addresses qualitative content analysis and how machine-learning community detection schemes can be used to infer latent learner communities from the content of forum posts.

Read the full paper: Gillani, N., Yasseri, T., Eynon, R., and Hjorth, I. (2014) Structural limitations of learning in a crowd – communication vulnerability and information diffusion in MOOCs. Scientific Reports 4.

Rebecca Eynon holds a joint academic post between the Oxford Internet Institute (OII) and the Department of Education at the University of Oxford. Her research focuses on education, learning and inequalities, and she has carried out projects in a range of settings (higher education, schools and the home) and life stages (childhood, adolescence and late adulthood).

The quality of rural internet access in the UK, or lack of it, has long been a bone of contention. The government says “fast, reliable broadband” is essential, but the disparity between urban and rural areas is large and growing, with slow and patchy connections common outside towns and cities.

The main reason for this is the difficulty and cost of installing the infrastructure necessary to bring broadband to all parts of the countryside – certainly to remote villages, hamlets, homes and farms, but even to areas not classified as “deep rural” too.

A countryside unplugged

As part of our project Access Denied, we are interviewing people in rural areas, both very remote and less so, to hear their experiences of slow and unreliable internet connections and the effects on their personal and professional lives. What we’ve found so far is that even in areas less than 20 miles away from big cities, the internet connection slows to far below the minimum of 2Mb/s identified by the government as “adequate”. Whether this is fast enough to navigate today’s data-rich Web 2.0 environment is questionable.

Our interviewees could attain speeds between 0.1Mb/s and 1.2Mb/s, with the latter being a positive outlier among the speed tests we performed. Some interviewees also reported that the internet didn’t work in their homes at all, in some cases for 60% of the time. This wasn’t related to time of day; the dropped connection appeared to be random, and not something they could plan for.

The result is that activities that those in cities and towns would see as entirely normal are virtually impossible in the country – online banking, web searches for information, even sending email. One respondent explained that she was unable to pay her workers’ wages for a full week because the internet was too slow and kept cutting out, causing her online banking session to reset.

Linking villages

So poor quality internet is a major problem for some. The question is what the government and BT – which won the bid to deploy broadband to all rural UK areas – are doing about it.

The key factor affecting the speed and quality of the connection is the copper telephone lines used to connect homes to the street cabinet. While BT is steadily upgrading cabinets with high-speed fibre optic connections that connect them to the local exchange, known as fibre to the cabinet (FTTC), the copper lines slow the connection speed considerably as line quality degrades with distance from the cabinet. While some homes within a few hundred metres of the cabinet in a village centre may enjoy speedier access, for homes that are perhaps several miles away FTTC brings no improvement.

One solution is to leave out cables of any kind, and use microwave radio links, similar to those used by mobile phone networks. BT has recently installed an 80Mb/s microwave link spanning the 4km necessary to connect the village of Northlew, in Devon, to the network – significantly cheaper and easier than laying the same length of fibre optic cable.

Connecting homes

Microwave links require line-of-sight between antennas, so it’s not a solution that will work everywhere. And in any case, while this is another step toward connecting remote villages, it doesn’t solve the problem of connecting individual homes which are still fed by copper cables and which could be miles away from the cabinet, with their internet speeds falling with every metre.

An alternative approach, championed by some community initiatives such as the Broadband For the Rural North (B4RN) project in Lancashire, is fibre-to-the-home (FTTH). This is regarded as future-proof because it provides a huge increase in speed – up to 1,000Mb/s – and because, even as minimum acceptable speeds continue to rise over the following years and decades, fibre can be easily upgraded. Copper cables simply cannot provide rural areas with the internet speeds needed today.

However FTTH is expensive – and BT will opt for the cheapest option or nothing at all. This needs to be addressed more assertively by the government as the UK’s internet speeds are falling behind other countries. According to Akamai’s latest State of the Internet report for 2014, peak and average speeds in the UK lag behind. The UK ranks 16th in Europe, behind others usually perceived as less connected and competitive such as Latvia or Romania.

If the government is serious about staying competitive in the global market this isn’t good enough, which means the government and BT need to get serious about putting some speed into getting Britain online.

Data is collected about us as we interact with digital technology, directly and via organisations. Many people volunteer data to social networking sites, and sensors – in smartphones, CCTV cameras, and “Internet of Things” objects – are making the physical world as trackable as the virtual. People are very often unaware of how much data is gathered about them – let alone the purposes for which it can be used. Also, most privacy risks are highly probabilistic, cumulative, and difficult to calculate. A student sharing a photo today might not be thinking about a future interview panel; or that the heart rate data shared from a fitness gadget might affect future decisions by insurance and financial services (Brown 2014).

Rather than organisations waiting for something to go wrong, then spending large amounts of time and money trying (and often failing) to fix privacy problems, computer scientists have been developing methods for designing privacy directly into new technologies and systems (Spiekermann and Cranor 2009). One of the most important principles is data minimization; that is, limiting the collection of personal data to that needed to provide a service – rather than storing everything that can be conveniently retrieved. This limits the impact of data losses and breaches, for example by corrupt staff with authorised access to data – a practice that the UK Information Commissioner’s Office (2006) has shown to be widespread.

Privacy by design also protects against function creep (Gürses et al. 2011). When an organisation invests significant resources to collect personal data for one reason, it can be very tempting to use it for other purposes. While this is limited in the EU by data protection law, government agencies are in a good position to push for changes to national laws if they wish, bypassing such “purpose limitations”. Nor do these rules tend to apply to intelligence agencies.

Another key aspect of putting users in control of their personal data is making sure they know what data is being collected, how it is being used – and ideally being asked for their consent. There have been some interesting experiments with privacy interfaces, for example helping smartphone users understand who is asking for their location data, and what data has been recently shared with whom.

Smartphones have enough storage and computing capacity to do some tasks, such as showing users adverts relevant to their known interests, without sharing any personal data with third parties such as advertisers. This kind of user-controlled data storage and processing has all kinds of applications – for example, with smart electricity meters (Danezis et al. 2013), and congestion charging for roads (Balasch et al. 2010).

What broader lessons can be drawn about shaping technologies for the public good? What is the public good, and who gets to define it? One option is to look at opinion polling about public concerns and values over long periods of time. The European Commission’s Eurobarometer polls reveal that in most European countries (including the UK), people have had significant concerns about data privacy for decades.

A more fundamental view of core social values can be found at the national level in constitutions, and between nations in human rights treaties. As well as the protection of private life and correspondence in the European Convention on Human Rights’ Article 8, the freedom of thought, expression, association and assembly rights in Articles 9-11 (and their equivalents in the US Bill of Rights, and the International Covenant on Civil and Political Rights) are also relevant.

This national and international law restricts how states use technology to infringe human rights – even for national security purposes. There are several US legal challenges to the constitutionality of NSA communications surveillance, with a federal court in Washington DC finding that bulk access to phone records is against the Fourth Amendment [1] (but another court in New York finding the opposite [2]). The UK campaign groups Big Brother Watch, Open Rights Group, and English PEN have taken a case to the European Court of Human Rights, arguing that UK law in this regard is incompatible with the Human Rights Convention.

Can technology development be shaped more broadly to reflect such constitutional values? One of the best-known attempts is the European Union’s data protection framework. Privacy is a core European political value, not least because of the horrors of the Nazi and Communist regimes of the 20th century. Germany, France and Sweden all developed data protection laws in the 1970s in response to the development of automated systems for processing personal data, followed by most other European countries. The EU’s Data Protection Directive (95/46/EC) harmonises these laws, and has provisions that encourage organisations to use technical measures to protect personal data.

An update of this Directive, which the European parliament has been debating over the last year, more explicitly includes this type of regulation by technology. Under this General Data Protection Regulation, organisations that are processing personal data will have to implement appropriate technical measures to protect Regulation rights. By default, organisations should only collect the minimum personal data they need, and allow individuals to control the distribution of their personal data. The Regulation would also require companies to make it easier for users to download all of their data, so that it could be uploaded to a competitor service (for example, one with better data protection) – bringing market pressure to bear (Brown and Marsden 2013).

This type of technology regulation is not uncontroversial. The European Commissioner responsible until July for the Data Protection Regulation, Viviane Reding, said that she had seen unprecedented and “absolutely fierce” lobbying against some of its provisions. Legislators would clearly be foolish to try and micro-manage the development of new technology. But the EU’s principles-based approach to privacy has been internationally influential, with over 100 countries now having adopted the Data Protection Directive or similar laws (Greenleaf 2014).

If the EU can find the right balance in its Regulation, it has the opportunity to set the new global standard for privacy-protective technologies – a very significant opportunity indeed in the global marketplace.

[1] Klayman v. Obama, 2013 WL 6571596 (D.D.C. 2013)

[2] ACLU v. Clapper, No. 13-3994 (S.D. New York December 28, 2013)

References

Balasch, J., Rial, A., Troncoso, C., Preneel, B., Verbauwhede, I. and Geuens, C. (2010) PrETP: Privacy-preserving electronic toll pricing. 19th USENIX Security Symposium, pp. 63–78.

Brown, I. (2014) The economics of privacy, data protection and surveillance. In J.M. Bauer and M. Latzer (eds.) Research Handbook on the Economics of the Internet. Cheltenham: Edward Elgar.

Brown, I. and Marsden, C. (2013) Regulating Code: Good Governance and Better Regulation in the Information Age. Cambridge, MA: MIT Press.

Danezis, G., Fournet, C., Kohlweiss, M. and Zanella-Beguelin, S. (2013) Smart Meter Aggregation via Secret-Sharing. ACM Smart Energy Grid Security Workshop.

Greenleaf, G. (2014) Sheherezade and the 101 data privacy laws: Origins, significance and global trajectories. Journal of Law, Information & Science.

Gürses, S., Troncoso, C. and Diaz, C. (2011) Engineering Privacy by Design. Computers, Privacy & Data Protection.

Haddadi, H, Hui, P., Henderson, T. and Brown, I. (2011) Targeted Advertising on the Handset: Privacy and Security Challenges. In Müller, J., Alt, F., Michelis, D. (eds) Pervasive Advertising. Heidelberg: Springer, pp. 119-137.

Information Commissioner’s Office (2006) What price privacy? HC 1056.

Spiekermann, S. and Cranor, L.F. (2009) Engineering Privacy. IEEE Transactions on Software Engineering 35 (1).

Read the full article: Keeping our secrets? Designing Internet technologies for the public good, European Human Rights Law Review 4: 369-377. This article is adapted from Ian Brown’s 2014 Oxford London Lecture, given at Church House, Westminster, on 18 March 2014, supported by Oxford University’s Romanes fund.

Professor Ian Brown is Associate Director of Oxford University’s Cyber Security Centre and Senior Research Fellow at the Oxford Internet Institute. His research is focused on information security, privacy-enhancing technologies, and Internet regulation.

The question of how much influence the audience has in these decisions has always been ambiguous. While in theory we might expect journalists to be attentive to readers, journalism has also been characterized as a profession with a “deliberate…ignorance of audience wants” (Anderson, 2011b). This ‘anti-populism’ is still often portrayed as an important journalistic virtue, in the context of telling people what they need to hear, rather than what they want to hear. Recently, however, attention has been turning to the potential impact that online audience metrics are having on journalism’s “deliberate ignorance”. Online publishing provides a huge amount of information to editors about visitor numbers, visit frequency, and what visitors choose to read and how long they spend reading it. Online editors now have detailed information about what articles are popular almost as soon as they are published, with these statistics frequently displayed prominently in the newsroom.

The rise of audience metrics has created concern both within the journalistic profession and academia, as part of a broader set of concerns about the way journalism is changing online. Many have expressed concern about a ‘culture of click’, whereby important but unexciting stories make way for more attention grabbing pieces, and editorial judgments are overridden by traffic statistics. At a time when media business models are under great strain, the incentives to follow the audience are obvious, particularly when business models increasingly rely on revenue from online traffic and advertising. The consequences for the broader agenda-setting function of the news media could be significant: more prolific or earlier readers might play a disproportionate role in helping to select content; particular social classes or groupings that read news online less frequently might find their issues being subtly shifted down the agenda.

The extent to which such a populist influence exists has attracted little empirical research. Many ethnographic studies have shown that audience metrics are being captured in online newsrooms, with anecdotal evidence for the importance of traffic statistics on an article’s lifetime (Anderson 2011b, MacGregor, 2007). However, many editors have emphasised that popularity is not a major determining factor (MacGregor, 2007), and that news values remain significant in terms of placement of news articles.

In order to assess the possible influence of audience metrics on decisions made by political news editors, we undertook a systematic, large-scale study of the relationship between readership statistics and article lifetime. We examined the news cycles of five major UK news outlets (the BBC, the Daily Telegraph, the Guardian, the Daily Mail and the Mirror) over a period of six weeks, capturing their front pages every 15 minutes, resulting in over 20,000 front-page captures and more than 40,000 individual articles. We measure article readership by capturing information from the BBC’s “most read” list of news articles (twelve percent of the articles were featured at some point on the ‘most read’ list, with a median time to achieving this status of two hours, and an average article life of 15 hours on the front page). Using the Cox Proportional Hazards model (which allows us to quantify the impact of an article’s appearance on the ‘most read’ list on its chance of survival) we asked whether an article’s being listed in a ‘most read’ column affected the length of time it remained on the front page.

We found that ‘most read’ articles had, on average, a 26% lower chance of being removed from the front page than equivalent articles which were not on the most read list, providing support for the idea that online editors are influenced by readership statistics. In addition to assessing the general impact of readership statistics, we also wanted to see whether this effect differs between ‘political’ and ‘entertainment’ news. Research on participatory journalism has suggested that online editors might be more willing to allow audience participation in areas of soft news such as entertainment, arts, sports, etc. We find a small amount of evidence for this claim, though the difference between the two categories was very slight.

Finally, we wanted to assess whether there is a ‘quality’ / ‘tabloid’ split. Part of the definition of tabloid style journalism lies precisely in its willingness to follow the demands of its audience. However, we found the audience ‘effect’ (surprisingly) to be most obvious in the quality papers. For tabloids, ‘most read’ status actually had a slightly negative effect on article lifetime. We wouldn’t argue that tabloid editors actively reject the wishes of their audience; however we can say that these editors are no more likely to follow their audience than the typical ‘quality’ editor, and in fact may be less so. We do not have a clear explanation for this difference, though we could speculate that, as tabloid publications are already more tuned in to the wishes of their audience, the appearance of readership statistics makes less practical difference to the overall product. However it may also simply be the case that the online environment is slowly producing new journalistic practices for which the tabloid / quality distinction will be of less usefulness.

So on the basis of our study, we can say that high-traffic articles do in fact spend longer in the spotlight than ones that attract less readership: audience readership does have a measurable impact on the lifespan of political news. The audience is no longer the unknown quantity it was in offline journalism: it appears to have a clear impact on journalistic practice. The question that remains, however, is whether this constitutes evidence of a new ‘populism’ in journalism; or whether it represents (as editors themselves have argued) the simple striking of a balance between audience demands and news values.

Read the full article: Bright, J., and Nicholls, T. (2014) The Life and Death of Political News: Measuring the Impact of the Audience Agenda Using Online Data. Social Science Computer Review 32 (2) 170-181.

References

Anderson, C. W. (2011) Between creative and quantified audiences: Web metrics and changing patterns of newswork in local US newsrooms. Journalism 12 (5) 550-566.

MacGregor, P. (2007) Tracking the Online Audience. Journalism Studies 8 (2) 280-298.

OII Resarch Fellow Jonathan Bright is a political scientist specialising in computational and ‘big data’ approaches to the social sciences. His major interest concerns studying how people get information about the political process, and how this is changing in the internet era.

Tom Nicholls is a doctoral student at the Oxford Internet Institute. His research interests include the impact of technology on citizen/government relationships, the Internet’s implications for public management and models of electronic public service delivery.

The geography of knowledge has always been uneven. Some people and places have always been more visible and had more voices than others. But the internet seemed to promise something different: a greater diversity of voices, opinions and narratives from more places. Unfortunately, this has not come to pass in quite the manner some expected it to. Many parts of the world remain invisible or under-represented on important websites and services.

All of this matters because as geographic information becomes increasingly integral to our lives, places that are not represented on platforms like Wikipedia will be absent from many of our understandings of, and interactions with, the world.

Mapping the differences

Until now, there has been no large-scale analysis of the factors that explain the wide geographical spread of online information. This is something we have aimed to address in our research project on the geography of Wikipedia. Our focus areas were the Middle East and North Africa.

Using statistical models of geotagged Wikipedia data, we identified the necessary conditions to make countries “visible”. This allowed us to map the countries that fare considerably better or worse than expected. We found that a large part of the variation between countries could be explained by just three factors: population, availability of broadband internet, and the number of edits originating in that country.

While these three variables help to explain the sparse amount of content written about much of sub-Saharan Africa, most of the Middle East and North Africa have much less geographic information than might be expected. For example, despite high levels of wealth and connectivity, Qatar and the United Arab Emirates have far fewer articles than we might expect.

Constraints to creating content

These three factors matter independently, but they will also be subject to other constraints. A country’s population will probably affect the number of activities, places, and practices of interest (that is, the number of things one might want to write about). The size of the potential audience might also be influential, encouraging editors in more densely populated regions and those writing in major languages. And social attitudes towards information sharing will probably also change how some people contribute content.

We might also be seeing a principle of increasing informational poverty. Not only is a broad base of source material, such as books, maps, and images, needed to generate any Wikipedia article, but it is also likely that having content online will lead to the production of more content.

There are strict guidelines on how knowledge can be created and represented in Wikipedia, including the need to source key assertions. Editing incentives and constraints probably also encourage work around existing content – which is relatively straightforward to edit – rather than creating entirely new material. So it may be that the very policies and norms that govern the encyclopedia’s structure make it difficult to populate the white space with new content.

We need to recognise that none of the three conditions can ever be sufficient for generating geographic knowledge. As well as highlighting the presences and absences on Wikipedia, we also need to ask what factors encourage or limit production of that content.

Because of the constraints of the Wikipedia model, increasing representation on pages can’t occur in a linear manner. Instead it accelerates in a virtuous cycle, benefiting those with strong cultures of collecting and curating information in local languages. That is why, even after adjusting for their levels of connectivity, population and editors, Britain, Sweden, Japan and Germany are extensively referenced on Wikipedia, but the Middle East and North Africa haven’t kept pace.

If this continues, then those on the periphery might fail to reach a critical mass of editors, needed to make content. Worse still, they may even dismiss Wikipedia as a legitimate site for user-generated geographic content. This is a problem that will need to be addressed if Wikipedia is indeed to take steps towards its goal of being the “sum of all human knowledge”.

We know that Wikipedia is important to the construction of geographical imaginations of place, and that it has immense power to augment our spatial understandings and interactions (Graham et al. 2013). In other words, the presences and absences in Wikipedia matter. If a person’s primary free source of information about the world is the Persian or Arabic or Hebrew Wikipedia, then the world will look fundamentally different from the world presented through the lens of the English Wikipedia. The capacity to represent oneself to outsiders is especially important in those parts of the world that are characterized by highly uneven power relationships: Brunn and Wilson (2013) and Graham and Zook (2013) have already demonstrated the power of geospatial content to reinforce power in a South African township and Jerusalem, respectively.

Until now, there has been no large-scale empirical analysis of the factors that explain information geographies at the global scale; this is something we have aimed to address in this research project on Mapping and measuring local knowledge production and representation in the Middle East and North Africa. Using regression models of geolocated Wikipedia data we have identified what are likely to be the necessary conditions for representation at the country level, and have also identified the outliers, i.e. those countries that fare considerably better or worse than expected. We found that a large part of the variation could be explained by just three factors: namely, (1) country population, (2) availability of broadband Internet, and (3) the number of edits originating in that country. [See the full paper for an explanation of the data and the regression models.]

But how do we explain the significant inequalities in the geography of user-generated information that remain after adjusting for differing conditions using our regression model? While these three variables help to explain the sparse amount of content written about much of Sub-Saharan Africa, most of the Middle East and North Africa have quantities of geographic information below their expected values. For example, despite high levels of wealth and connectivity, Qatar and the United Arab Emirates have far fewer articles than we might expect from the model.

These three factors independently matter, but they will also be subject to a number of constraints. A country’s population will probably affect the number of human sites, activities, and practices of interest; ie the number of things one might want to write about. The size of the potential audience might also be influential, encouraging editors in denser-populated regions and those writing in major languages. However, societal attitudes towards learning and information sharing will probably also affect the propensity of people in some places to contribute content. Factors discouraging the number of edits to local content might include a lack of local Wikimedia chapters, the attractiveness of writing content about other (better-represented) places, or contentious disputes in local editing communities that divert time into edit wars and away from content generation.

We might also be seeing a principle of increasing informational poverty. Not only is a broader base of traditional source material (such as books, maps, and images) needed for the generation of any Wikipedia article, but it is likely that the very presence of content itself is a generative factor behind the production of further content. This makes information produced about information-sparse regions most useful for people in informational cores — who are used to integrating digital information into their everyday practices — rather than those in informational peripheries.

Various practices and procedures of Wikipedia editing likely amplify this effect. There are strict guidelines on how knowledge can be created and represented in Wikipedia, including a ban on original research, and the need to source key assertions. Editing incentives and constraints probably also encourage work around existing content (which is relatively straightforward to edit) rather than creation of entirely new material. In other words, the very policies and norms that govern the encyclopedia’s structure make it difficult to populate the white space with new geographic content. In addressing these patterns of increasing informational poverty, we need to recognize that no one of these three conditions can ever be sufficient for the generation of geographic knowledge. As well as highlighting the presences and absences in user-generated content, we also need to ask what factors encourage or limit production of that content.

In interpreting our model, we have come to a stark conclusion: increasing representation doesn’t occur in a linear fashion, but it accelerates in a virtuous cycle, benefitting those with strong editing cultures in local languages. For example, Britain, Sweden, Japan and Germany are extensively georeferenced on Wikipedia, whereas much of the MENA region has not kept pace, even accounting for their levels of connectivity, population, and editors. Thus, while some countries are experiencing the virtuous cycle of more edits and broadband begetting more georeferenced content, those on the periphery of these information geographies might fail to reach a critical mass of editors, or even dismiss Wikipedia as a legitimate site for user-generated geographic content: a problem that will need to be addressed if Wikipedia is indeed to be considered as the “sum of all human knowledge”.

Read the full paper: Graham, M., Hogan, B., Straumann, R.K., and Medhat, A. (2014) Uneven Geographies of User-Generated Information: Patterns of Increasing Informational Poverty. Annals of the Association of American Geographers.

References

Brunn S. D., and M. W. Wilson. 2013. Cape Town’s million plus black township of Khayelitsha: Terrae incognitae and the geographies and cartographies of silence, Habitat International. 39 284-294.

Graham M., and M. Zook. (2013) Augmented Realities and Uneven Geographies: Exploring the Geolinguistic Contours of the Web. Environment and Planning A 45(1): 77–99.

Graham M, M. Zook, and A. Boulton. 2013. Augmented Reality in the Urban Environment: Contested Content and the Duplicity of Code. Transactions of the Institute of British Geographers. 38(3) 464-479.

Mark Graham is a Senior Research Fellow at the OII. His research focuses on Internet and information geographies, and the overlaps between ICTs and economic development.

Wikipedia is often seen as a great equaliser. Every day, hundreds of thousands of people collaborate on a seemingly endless range of topics by writing, editing and discussing articles, and uploading images and video content. But it’s starting to look like global coverage on Wikipedia is far from equal. This now ubiquitous source of information offers everything you could want to know about the US and Europe but far less about any other parts of the world.

This structural openness of Wikipedia is one of its biggest strengths. Academic and activist Lawrence Lessig even describes the online encyclopedia as “a technology to equalise the opportunity that people have to access and participate in the construction of knowledge and culture, regardless of their geographic placing”.

But despite Wikipedia’s openness, there are fears that the platform is simply reproducing the most established worldviews. Knowledge created in the developed world appears to be growing at the expense of viewpoints coming from developing countries. Indeed, there are indications that global coverage in the encyclopedia is far from “equal”, with some parts of the world heavily represented on the platform, and others largely left out.

For a start, if you look at articles published about specific places such as monuments, buildings, festivals, battlefields, countries, or mountains, the imbalance is striking. Europe and North America account for a staggering 84% of these “geotagged” articles. Almost all of Africa is poorly represented in the encyclopedia, too. In fact, there are more Wikipedia articles written about Antarctica (14,959) than any country in Africa. And while there are just over 94,000 geotagged articles related to Japan, there are only 88,342 on the entire Middle East and North Africa region.

When you think of the spread in terms of the way the world’s population is spread, the picture is equally startling. Even though 60% of the world’s population is concentrated in Asia, less than 10% of Wikipedia articles relate to the region. The same is true in reverse for Europe, which is home to around 10% of the world’s population but accounts for nearly 60% of geotagged Wikipedia articles.

There is an imbalance in the languages used on Wikipedia too. Most articles written about European and East Asian countries are written in their dominant languages. Articles about the Czech Republic, for example, are mostly written in Czech. But for much of the Global South we see a dominance of articles written in English. English dominates across much of Africa and the Middle East and even parts of South and Central America.

There more Wikipedia articles in English than Arabic about almost every Arabic speaking country in the Middle East. And there are more English articles about North Korea than there are Arabic articles about either Saudi Arabia, Libya, or the United Arab Emirates. In total, there are more than 928,000 geotagged articles written in English, but only 3.23% of them are about Africa and 1.67% are about the Middle East and North Africa.

All this matters because fundamentally different narratives can be, and are, created about places and topics in different languages.

Beyond English

Even on the Arabic Wikipedia, there are geographical imbalances. There are a relatively high number of articles about Algeria and Syria, as well as about the US, Italy, Spain, Russia and Greece but substantially fewer about a number of Arabic speaking countries, including Egypt, Morocco, and Saudi Arabia. Indeed, there are only 433 geotagged articles about Egypt on the Arabic Wikipedia, but 2,428 about Italy and 1,988 about Spain.

By mapping the geography of Wikipedia articles in both global and regional languages, we can begin to examine the layers of representation that “augment” the world we live in. Some parts of the world, including the Middle East, are massively underrepresented – not just in major world languages, but their own. We like to think of Wikipedia as an opportunity for anyone, anywhere to contribute information about our world but that doesn’t seem to be happening in practice. Wikipedia might not just be reflecting the world, but also reproducing new, uneven, geographies of information.

Standing on a stage in San Francisco in early 2010, Facebook founder Mark Zuckerberg, partly responding to the site’s decision to change the privacy settings of its 350 million users, announced that as Internet users had become more comfortable sharing information online, privacy was no longer a “social norm”. Of course, he had an obvious commercial interest in relaxing norms surrounding online privacy, but this attitude has nevertheless been widely echoed in the popular media. Young people are supposed to be sharing their private lives online — and providing huge amounts of data for commercial and government entities — because they don’t fully understand the implications of the public nature of the Internet.

There has actually been little systematic research on the privacy behaviour of different age groups in online settings. But there is certainly evidence of a growing (general) concern about online privacy (Marwick et al., 2010), with a 2013 Pew study finding that 50 percent of Internet users were worried about the information available about them online, up from 30 percent in 2009. Following the recent revelations about the NSA’s surveillance activities, a Washington Post-ABC poll reported 40 percent of its U.S. respondents as saying that it was more important to protect citizens’ privacy even if it limited the ability of the government to investigate terrorist threats. But what of young people, specifically? Do they really care less about their online privacy than older users?

Privacy concerns an individual’s ability to control what personal information about them is disclosed, to whom, when, and under what circumstances. We present different versions of ourselves to different audiences, and the expectations and norms of the particular audience (or context) will determine what personal information is presented or kept hidden. This highlights a fundamental problem with privacy in some SNSs: that of ‘context collapse’ (Marwick and boyd 2011). This describes what happens when audiences that are normally kept separate offline (such as employers and family) collapse into a single online context: such a single Facebook account or Twitter channel. This could lead to problems when actions that are appropriate in one context are seen by members of another audience; consider for example, the US high school teacher who was forced to resign after a parent complained about a Facebook photo of her holding a glass of wine while on holiday in Europe.

SNSs are particularly useful for investigating how people handle privacy. Their tendency to collapse the “circles of social life” may prompt users to reflect more about their online privacy (particularly if they have been primed by media coverage of people losing their jobs, going to prison, etc. as a result of injudicious postings). However, despite SNS being an incredibly useful source of information about online behaviour practices, few articles in the large body of literature on online privacy draw on systematically collected data, and the results published so far are probably best described as conflicting (see the literature review in the full paper). Furthermore, they often use convenience samples of college students, meaning they are unable to adequately address either age effects, or potentially related variables such as education and income. These ambiguities certainly provide fertile ground for additional research; particularly research based on empirical data.

The OII’s own Oxford Internet Surveys (OxIS) collect data on British Internet users and non-users through nationally representative random samples of more than 2,000 individuals aged 14 and older, surveyed face-to-face. One of the (many) things we are interested in is online privacy behaviour, which we measure by asking respondents who have an SNS profile: “Thinking about all the social network sites you use, … on average how often do you check or change your privacy settings?” In addition to the demographic factors we collect about respondents (age, sex, location, education, income etc.), we can construct various non-demographic measures that might have a bearing on this question, such as: comfort revealing personal data; bad experiences online; concern with negative experiences; number of SNSs used; and self-reported ability using the Internet.

So are young people completely unconcerned about their privacy online, gaily granting access to everything to everyone? Well, in a word, no. We actually find a clear inverse relationship: almost 95% of 14-17-year-olds have checked or changed their SNS privacy settings, with the percentage steadily dropping to 32.5% of respondents aged 65 and over. The strength of this effect is remarkable: between the oldest and youngest the difference is over 62 percentage points, and we find little difference in the pattern between the 2013 and 2011 surveys. This immediately suggests that the common assumption that young people don’t care about — and won’t act on — privacy concerns is probably wrong.

Comparing our own data with recent nationally representative surveys from Australia (OAIC 2013) and the US (Pew 2013) we see an amazing similarity: young people are more, not less, likely to have taken action to protect the privacy of their personal information on social networking sites than older people. We find that this age effect remains significant even after controlling for other demographic variables (such as education). And none of the five non-demographic variables changes the age effect either (see the paper for the full data, analysis and modelling). The age effect appears to be real.

So in short, and contrary to the prevailing discourse, we do not find young people to be apathetic when it comes to online privacy. Barnes (2006) outlined the original ‘privacy paradox’ by arguing that “adults are concerned about invasion of privacy, while teens freely give up personal information (…) because often teens are not aware of the public nature of the Internet.” This may once have been true, but it is certainly not the case today.

Existing theories are unable to explain why young people are more likely to act to protect privacy, but maybe the answer lies in the broad, fundamental characteristics of social life. It is social structure that creates context: people know each other based around shared life stages, experiences and purposes. Every person is the center of many social circles, and different circles have different norms for what is acceptable behavior, and thus for what is made public or kept private. If we think of privacy as a sort of meta-norm that arises between groups rather than within groups, it provides a way to smooth out some of the inevitable conflicts of the varied contexts of modern social life.

This might help explain why young people are particularly concerned about their online privacy. At a time when they’re leaving their families and establishing their own identities, they will often be doing activities in one circle (e.g. friends) that they do not want known in other circles (e.g. potential employers or parents). As an individual enters the work force, starts to pay taxes, and develops friendships and relationships farther from the home, the number of social circles increases, increasing the potential for conflicting privacy norms. Of course, while privacy may still be a strong social norm, it may not be in the interest of the SNS provider to cater for its differentiated nature.

The real paradox is that these sites have become so embedded in the social lives of users that to maintain their social lives they must disclose information on them despite the fact that there is a significant privacy risk in disclosing this information; and often inadequate controls to help users to meet their diverse and complex privacy needs.

Read the full paper: Blank, G., Bolsover, G., and Dubois, E. (2014) A New Privacy Paradox: Young people and privacy on social network sites. Prepared for the Annual Meeting of the American Sociological Association, 16-19 August 2014, San Francisco, California.

References

Barnes, S. B. (2006). A privacy paradox: Social networking in the United States. First Monday,11(9).

Marwick, A. E., Murgia-Diaz, D., & Palfrey, J. G. (2010). Youth, Privacy and Reputation (Literature Review). SSRN Scholarly Paper No. ID 1588163. Rochester, NY: Social Science Research Network.

Marwick, A. E., & boyd, D. (2011). I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience. New Media & Society, 13(1), 114–133. doi:10.1177/1461444810365313

Grant Blank is a Survey Research Fellow at the OII. He is a sociologist who studies the social and cultural impact of the Internet and other new communication media.

根据相关法律法规和政策，部分搜索结果未予显示 could be a warning message we will see displayed more often on the Internet; but likely translations thereof. In Chinese, this means “according to the relevant laws, regulations, and policies, a portion of search results have not been displayed.” The control of information flows on the Internet is becoming more commonplace, in authoritarian regimes as well as in liberal democracies, either via technical or regulatory means. Such information controls can be defined as “[…] actions conducted in or through information and communications technologies (ICTs), which seek to deny (such as web filtering), disrupt (such as denial-of-service attacks), shape (such as throttling), secure (such as through encryption or circumvention) or monitor (such as passive or targeted surveillance) information for political ends. Information controls can also be non-technical and can be implemented through legal and regulatory frameworks, including informal pressures placed on private companies. […]” Information controls are not intrinsically good or bad, but much is to be explored and analysed about their use, for political or commercial purposes.

The University of Toronto’s Citizen Lab organised a one-week summer institute titled “Monitoring Internet Openness and Rights” to inform the global discussions on information control research and practice in the fields of censorship, circumvention, surveillance and adherence to human rights. A week full of presentations and workshops on the intersection of technical tools, social science research, ethical and legal reflections and policy implications was attended by a distinguished group of about 60 community members, amongst whom were two OII DPhil students; Jon Penney and Ben Zevenbergen. Conducting Internet measurements may be considered to be a terra incognita in terms of methodology and data collection, but the relevance and impacts for Internet policy-making, geopolitics or network management are obvious and undisputed.

The Citizen Lab prides itself in being a “hacker hothouse”, or an “intelligence agency for civil society” where security expertise, politics, and ethics intersect. Their research adds the much-needed geopolitical angle to the deeply technical and quantitative Internet measurements they conduct on information networks worldwide. While the Internet is fast becoming the backbone of our modern societies in many positive and welcome ways, abundant (intentional) security vulnerabilities, the ease with which human rights such as privacy and freedom of speech can be violated, threats to the neutrality of the network and the extent of mass surveillance threaten to compromise the potential of our global information sphere. Threats to a free and open internet need to be uncovered and explained to policymakers, in order encourage informed, evidence-based policy decisions, especially in a time when the underlying technology is not well-understood by decision makers.

Participants at the summer institute came with the intent to make sense of Internet measurements and information controls, as well as their social, political and ethical impacts. Through discussions in larger and smaller groups throughout the Munk School of Global Affairs – as well as restaurants and bars around Toronto – the current state of the information controls, their regulation and deployment became clear, and multi-disciplinary projects to measure breaches of human rights on the Internet or its fundamental principles were devised and coordinated.

The outcomes of the week in Toronto are impressive. The OII DPhil students presented their recent work on transparency reporting and ethical data collection in Internet measurement.

Jon Penney gave a talk on “the United States experience” with Internet-related corporate transparency reporting, that is, the evolution of existing American corporate practices in publishing “transparency reports” about the nature and quantity of government and law enforcement requests for Internet user data or content removal. Jon first began working on transparency issues as a Google Policy Fellow with the Citizen Lab in 2011, and his work has continued during his time at Harvard’s Berkman Center for Internet and Society. In this talk, Jon argued that in the U.S., corporate transparency reporting largely began with the leadership of Google and a few other Silicon Valley tech companies like Twitter, but in the Post-Snowden era, has been adopted by a wider cross section of not only technology companies, but also established telecommunications companies like Verizon and AT&T previously resistant to greater transparency in this space (perhaps due to closer, longer term relationships with federal agencies than Silicon Valley companies). Jon also canvassed evolving legal and regulatory challenges facing U.S. transparency reporting and means by which companies may provide some measure of transparency— via tools like warrant canaries— in the face of increasingly complex national security laws.

Ben Zevenbergen has recently launched ethical guidelines for the protection of privacy with regards to Internet measurements conducted via mobile phones. The first panel of the week on “Network Measurement and Information Controls” called explicitly for more concrete ethical and legal guidelines for Internet measurement projects, because the extent of data collection necessarily entails that much personal data is collected and analyzed. In the second panel on “Mobile Security and Privacy”, Ben explained how his guidelines form a privacy impact assessment for a privacy-by-design approach to mobile network measurements. The iterative process of designing a research in close cooperation with colleagues, possibly from different disciplines, ensures that privacy is taken into account at all stages of the project development. His talk led to two connected and well-attended sessions during the week to discuss the ethics of information controls research and Internet measurements. A mailing list has been set up for engineers, programmers, activists, lawyers and ethicists to discuss the ethical and legal aspects of Internet measurements. A data collection has begun to create a taxonomy of ethical issues in the discipline to inform forthcoming peer-reviewed papers.

The Citizen Lab will host its final summer institute of the series in 2015.

Photo credits: Ben Zevenbergen, Jon Penney. Writing Credits: Ben Zevenbergen, with small contribution from Jon Penney.

Ben Zevenbergen is an OII DPhil student and Research Assistant working on the EU Internet Science project. He has worked on legal, political and policy aspects of the information society for several years. Most recently he was a policy advisor to an MEP in the European Parliament, working on Europe’s Digital Agenda.

Jon Penney is a legal academic, doctoral student at the Oxford Internet Institute, and a Research Fellow / Affiliate of both The Citizen Lab an interdisciplinary research lab specializing in digital media, cyber-security, and human rights, at the University of Toronto’s Munk School for Global Affairs, and at the Berkman Center for Internet & Society, Harvard University.

Wikipedia has famously been described as a project that “ works great in practice and terrible in theory”. One of the ways in which it succeeds is through its extensive consensus-based governance structure. While this has led to spectacular success –over 4.5 million articles in the English Wikipedia alone — the governance structure is neither obvious nor immediately accessible, and can present a barrier for those seeking entry. Editing Wikipedia can be a tough challenge – an often draining and frustrating task, involving heated disputes and arguments where it is often the most tenacious, belligerent, or connected editor who wins out in the end.

Broadband access and literacy are not the only pre-conditions for editing Wikipedia; ‘digital literacy’ is also crucial. This includes the ability to obtain and critically evaluate online sources, locate Wikipedia’s editorial and governance policies, master Wiki syntax, and confidently articulate and assert one’s views about an article or topic. Experienced editors know how to negotiate the rules, build a consensus with some editors to block others, and how to influence administrators during dispute resolution. This strict adherence to the word (if not the spirit) of Wikipedia’s ‘law’ can lead to marginalization or exclusion of particular content, particularly when editors are scared off by unruly mobs who ‘weaponize’ policies to fit a specific agenda.

Governing such a vast collaborative platform as Wikipedia obviously presents a difficult balancing act between being open enough to attract volume of contributions, and moderated enough to ensure their quality. Many editors consider Wikipedia’s governance structure (which varies significantly between the different language versions) essential to ensuring the quality of its content, even if it means that certain editors can (for example) arbitrarily ban other users, lock down certain articles, and exclude moderate points of view. One of the editors we spoke to noted that: “A number of articles I have edited with quality sources, have been subjected to editors cutting information that doesn’t fit their ideas […] I spend a lot of time going back to reinstate information. Today’s examples are in the ‘Battle of Nablus (1918)’ and the ‘Third Transjordan attack’ articles. Bullying does occur from time to time […] Having tried the disputes process I wouldn’t recommend it.” Community building might help support MENA editors faced with discouragement or direct opposition as they try to build content about the region, but easily locatable translations of governance materials would also help. Few of the extensive Wikipedia policy discussions have been translated into Arabic, leading to replication of discussions or ambiguity surrounding correct dispute resolution.

Beyond arguments with fractious editors over minutiae (something that comes with the platform), negotiating the wider politics of Wikipedia can be a daunting task, particularly when in it comes to content about the MENA region. It would be an understatement to say that the Middle East is a politically sensitive region, with more than its fair share of apparently unresolvable disputes, competing ideologies (it’s the birthplace of three world religions…), repressive governments, and ongoing and bloody conflicts. Editors shared stories with us about meddling from state actors (eg Tunisia, Iran) and a lack of trust with a platform that is generally considered to be a foreign, and sometimes explicitly American, tool. Rumors abound that several states (eg Israel, Iran) have concerted efforts to work on Wikipedia content, creating a chilling effect for new editors who might feel that editing certain pages might prove dangerous, or simply frustrating or impossible. Some editors spoke of being asked by Syrian government officials for advice on how to remove critical content, or how to identify the editors responsible for putting it there. Again: the effect is chilling.

A lack of locally produced and edited content about the region clearly can’t be blamed entirely on ‘outsiders’. Many editors in the Arabic Wikipedia have felt snubbed by the creation of an explicitly “Egyptian Arabic” Wikipedia, which has not only forked the content and editorial effort, but also stymied any ‘pan-Arab’ identity on the platform. There is a culture of administrators deleting articles they do not think are locally appropriate; often relating to politically (or culturally) sensitive topics. Due to Arabic Wikipedia’s often vicious edit wars, it is heavily moderated (unlike for example the English version), and anonymous edits do not appear instantly.

Some editors at the workshops noted other systemic and cultural issues, for example complaining of an education system that encourages rote learning, reinforcing the notion that only experts should edit (or moderate) a topic, rather than amateurs with local familiarity. Editors also noted the notable gender disparities on the site; a longstanding issue for other Wikipedia versions as well. None of these discouragements are helped by what some editors noted as a larger ‘image problem’ with editing in the Arabic Wikipedia, given it would always be overshadowed by the dominant English Wikipedia, one editor commenting that: “the English Wikipedia is vastly larger than its Arabic counterpart, so it is not unthinkable that there is more content, even about Arab-world subjects, in English. From my (unscientific) observation, many times, content in Arabic about a place or a tribe is not very encyclopedic, but promotional, and lacks citations”. Translating articles into Arabic might be seen as menial and unrewarding work, when the exciting debates about an article are happening elsewhere.

When we consider the coming-together of all of these barriers, it might be surprising that Wikipedia is actually as large as it is. However, the editors we spoke with were generally optimistic about the site, considering it an important activity that serves the greater good. Wikipedia is without doubt one of the most significant cultural and political forces on the Internet. Wikipedians are remarkably generous with their time, and it’s their efforts that are helping to document, record, and represent much of the world – including places where documentation is scarce. Most of the editors at our workshop ultimately considered Wikipedia a path to a more just society; through not just consensus, voting, and an aspiration to record certain truths — seeing it not just as a site of conflict, but also a site of regional (and local) pride. When asked why he writes geographic content, one editor simply replied: “It’s my own town”.

Mark Graham is a Senior Research Fellow at the OII. His research focuses on Internet and information geographies, and the overlaps between ICTs and economic development.

Of course, the focus on risk rather than harm is understandable from an ethical and methodological perspective. It wouldn’t be ethical, for example, to conduct a trial in which one group of children was deliberately exposed to very violent or sexual content to observe whether any harms resulted. Similarly, surveys can ask respondents to self-report harms experienced online, perhaps through the lens of upsetting images or experiences. But again, there are ethical concerns about adding to children’s distress by questioning them extensively on difficult experiences, and in a survey context it’s also difficult to avoid imposing adult conceptions of ‘harm’ through the wording of the questions.

Despite these difficulties, there are many research projects that aim to measure and understand the relationship between various types of physical, emotional or psychological harm and activities online, albeit often outside the social sciences. With support from the OUP Fell Fund, I worked with colleagues Vera Slavtcheva-Petkova and Monica Bulger to review the extent of evidence available across these other disciplines. Looking at journal articles published between 1997 and 2012, we aimed to identify any empirical evidence detailing Internet-related harms experienced by children and adolescents and to gain a sense of the types of harm recorded, their severity and frequency.

Our findings demonstrate that there are many good studies out there which do address questions of harm, rather than just risk. The narrowly drawn search found 148 empirical studies which either clearly delineated evidence of very specific harms, or offered some evidence of less well-defined harms. Further, these studies offer rich insights into three broad types of harm: health-related (including harms relating to the exacerbation of eating disorders, self-harming behaviour and suicide attempts); sex-related (largely focused on studies of online solicitation and child abuse); and bullying-related (including the effects on mental health and behaviour). Such a range of coverage would come as no surprise to most researchers focusing on children’s Internet use – these are generally well-documented areas, albeit with the focus more normally on risk rather than harm. Perhaps more surprising was the absence in our search of evidence of harm in relation to privacy violations or economic well-being, both of which are increasingly discussed as significant concerns or risks for minors using the Internet. This gap might have been a factor of our search terms, of course, but given the policy relevance of both issues, more empirical study of not just risk but actual harm would seem to be merited in these areas.

Another important gap in the literature concerned the absence of literature demonstrating that severe harms often befall those without prior evidence of vulnerability or risky behaviour. For example, in relation to websites promoting self-harm or eating disorders, there is little evidence that young people previously unaffected by self-harm or eating disorders are influenced by these websites. This isn’t unexpected – other researchers have shown that harm more often befalls those who display riskier behaviour, but this is important to bear in mind when devising treatment or policy strategies for reducing such harms.

It’s also worth noting how difficult it is to determine the prevalence of harms. The best-documented cases are often those where medical, police or court records provide great depth of qualitative detail about individual suffering in cases of online grooming and abuse, eating disorders or self-harm. Yet these cases provide little insight into prevalence. And whilst survey research offers more sense of scale, we found substantial disparities in the levels of harm reported on some issues, with the prevalence of cyber-bullying, for example, varying from 9% to 72% across studies with similar age groups of children. It’s also clear that we quite simply need much more research and policy attention on certain issues. The studies relating to the online grooming of children and production of abuse images are an excellent example of how a broad research base can make an important contribution to our understanding of online risks and harms. Here, journal articles offered a remarkably rich understanding, drawing on data from police reports, court records or clinical files as well as surveys and interviews with victims, perpetrators and carers. There would be real benefits to taking a similarly thorough approach to the study of users of pro-eating disorder, self-harm and pro-suicide websites.

Our review flagged up some important lessons for policy-makers. First, whilst we (justifiably) devote a wealth of resources to the small proportion of children experiencing severe harms as a result of online experiences, the number of those experiencing more minor harms such as those caused by online bullying is likely much higher and may thus deserve more attention than currently received. Second, the diversity of topics discussed and types of harm identified seems to suggest that a one-size-fits-all solution will not work when it comes to online protection of minors. Simply banning or filtering all potentially harmful websites, pages or groups might be more damaging than useful if it drives users to less public means of communicating. Further, whilst some content such as child sexual abuse images are clearly illegal and generate great harms, other content and sites is less easy to condemn if the balance between perpetuating harmful behavior and provide valued peer support is hard to call. It should also be remembered that the need to protect young people from online harms must always be balanced against the need to protect their rights (and opportunities) to freely express themselves and seek information online.

Finally, this study makes an important contribution to public debates about child online safety by reminding us that risk and harm are not equivalent and should not be conflated. More children and young people are exposed to online risks than are actually harmed as a result and our policy responses should reflect this. In this context, the need to protect minors from online harms must always be balanced against their rights and opportunities to freely express themselves and seek information online.

A more detailed account of our findings can be found in this Information, Communication and Society journal article: Evidence on the extent of harms experienced by children as a result of online risks: implications for policy and research. If you can’t access this, please e-mail me for a copy.

Victoria Nash is a Policy and Research Fellow at the Oxford Internet Institute (OII), responsible for connecting OII research with policy and practice. Her own particular research interests draw on her background as a political theorist, and concern the theoretical and practical application of fundamental liberal values in the Internet era. Recent projects have included efforts to map the legal and regulatory trends shaping freedom of expression online for UNESCO, analysis of age verification as a tool to protect and empower children online, and the role of information and Internet access in the development of moral autonomy.

These second-generation digital divides are not merely divides of Internet access (so discussed in the late 1990s), but gaps in representation and participation (Hargittai and Walejko 2008). Whereas most Wikipedia articles written about most European and East Asian countries are written in their dominant languages, for much of the Global South we see a dominance of articles written in English. These geographic differences in the coverage of different language versions of Wikipedia matter, because fundamentally different narratives can be (and are) created about places and topics in different languages (Graham and Zook 2013; Graham 2014).

If we undertake a ‘global analysis’ of this pattern by examining the number of geocoded articles (ie about a specific place) across Wikipedia’s main language versions (Figure 1), the first thing we can observe is the incredible human effort that has gone into describing ‘place’ in Wikipedia. The second is the clear and highly uneven geography of information, with Europe and North America home to 84% of all geolocated articles. Almost all of Africa is poorly represented in the encyclopaedia — remarkably, there are more Wikipedia articles written about Antarctica (14,959) than any country in Africa, and more geotagged articles relating to Japan (94,022) than the entire MENA region (88,342). In Figure 2 it is even more obvious that Europe and North America lead in terms of representation on Wikipedia.

Knowing how many articles describe a place only tells a part of the ‘representation story’. Figure 3 adds the linguistic element, showing the dominant language of Wikipedia articles per country. The broad pattern is that some countries largely define themselves in their own languages, and others appear to be largely defined from outside. For instance, almost all European countries have more articles about themselves in their dominant language; that is, most articles about the Czech Republic are written in Czech. Most articles about Germany are written in German (not English).

We do not see this pattern across much of the South, where English dominates across much of Africa, the Middle East, South and East Asia, and even parts of South and Central America. French dominates in five African countries, and German is dominant in one former German colony (Namibia) and a few other countries (e.g. Uruguay, Bolivia, East Timor).

The scale of these differences is striking. Not only are there more Wikipedia articles in English than Arabic about almost every Arabic speaking country in the Middle East, but there are more English articles about North Korea than there are Arabic articles about Saudi Arabia, Libya, and the UAE. Not only do we see most of the world’s content written about global cores, but it is largely dominated by a relatively few languages.

Figure 4 shows the total number of geotagged Wikipedia articles in English per country. The sheer density of this layer of information over some parts of the world is astounding (with 928,542 articles about places in English), nonetheless, in this layer of geotagged English content, only 3.23% of the articles are about Africa, and 1.67% are about the MENA region.

We see a somewhat different pattern when looking at the global geography of the 22,548 geotagged articles of the Arabic Wikipedia (Figure 5). Algeria and Syria are both defined by a relatively high number of articles in Arabic (as are the US, Italy, Spain, Russia and Greece). These information densities are substantially greater than what we see for many other MENA countries in which Arabic is an official language (such as Egypt, Morocco, and Saudi Arabia). This is even more surprising when we realise that the Italian and Spanish populations are smaller than the Egyptian, but there are nonetheless far more geotagged articles in Arabic about Italy (2,428) and Spain (1,988) than about Egypt (433).

By mapping the geography of Wikipedia articles in both global and regional languages, we can begin to examine the layers of representation that ‘augment’ the world we live in. We have seen that, notable exceptions aside (e.g. ‘Iran’ in Farsi and ‘Israel’ in Hebrew) the MENA region tends to be massively underrepresented — not just in major world languages, but also in its own: Arabic. Clearly, much is being left unsaid about that part of the world. Although we entered the project anticipating that the MENA region would be under-represented in English, we did not anticipate the degree to which it is under-represented in Arabic.

References

Ford, H. (2011) The Missing Wikipedians. In Critical Point of View: A Wikipedia Reader, ed. G. Lovink and N. Tkacz, 258-268. Amsterdam: Institute of Network Cultures.

Graham, M. (2014) The Knowledge Based Economy and Digital Divisions of Labour. In Companion to Development Studies, 3rd edition, eds v. Desai, and R. Potter. Hodder, pp. 189-195.

Graham, M. (2013) The Virtual Dimension. In Global City Challenges: Debating a Concept, Improving the Practice. Eds. Acuto, M. and Steele, W. London: Palgrave.

Graham, M. (2011) Wiki Space: Palimpsests and the Politics of Exclusion. In Critical Point of View: A Wikipedia Reader. Eds. Lovink, G. and Tkacz, N. Amsterdam: Institute of Network Cultures, pp. 269-282.

Graham M., and M. Zook (2013) Augmented Realities and Uneven Geographies: Exploring the Geolinguistic Contours of the Web. Environment and Planning A 45 (1) 77–99.

Hargittai, E. and G. Walejko (2008) The Participation Divide: Content Creation and Sharing in the Digital Age. Information, Communication and Society 11 (2) 239–256.

Hecht B., and D. Gergle (2009) Measuring self-focus bias in community-maintained knowledge repositories. In Proceedings of the 4th International Conference on Communities and Technologies, Penn State University, 2009, pp. 11–20. New York: ACM.

Lessig, L. (2003) An Information Society: Free or Feudal. Talk given at the World Summit on the Information Society, Geneva, 2003.

Mark Graham is a Senior Research Fellow at the OII. His research focuses on Internet and information geographies, and the overlaps between ICTs and economic development.

Wikipedia currently contains over 9 million articles in 272 languages, far surpassing any other publicly available information repository. Being the first point of contact for most general topics (therefore an effective site for framing any subsequent representations) it is an important platform from which we can learn whether the Internet facilitates increased open participation across cultures — or reinforces existing global hierarchies and power dynamics. Because the underlying political, geographic and social structures of Wikipedia are hidden from users, and because there have not been any large scale studies of the geography of these structures and their relationship to online participation, entire groups of people (and regions) may be marginalized without their knowledge.

This process is important to understand, for the simple reason that Wikipedia content has begun to form a central part of services offered elsewhere on the Internet. When you look for information about a place on Facebook, the description of that place (including its geographic coordinates) comes from Wikipedia. If you want to “check in” to a museum in Doha to signify you were there to their friends, the place you check in to was created with Wikipedia data. When you Google “House of Saud” you are presented not only with a list of links (with Wikipedia at the top) but also with a special ‘card’ summarising the House. This data comes from Wikipedia. When you look for people or places, Google now has these terms inside its ‘knowledge graph’, a network of related concepts with data coming directly from Wikipedia. Similarly, on Google maps, Wikipedia descriptions for landmarks are presented as part of the default information.

Ironically, Wikipedia editorship is actually on a slow and steady decline, even as its content and readership increases year on year. Since 2007 and the introduction of significant devolution of administrative powers to volunteers, Wikipedia has not been able to effectively retain newcomers, something which has been noted as a concern by many at the Wikimedia Foundation. Some think Wikipedia might be levelling off because there’s only so much to write about. This is extremely far from the truth; there are still substantial gaps in geographic content in English and overwhelming gaps in other languages. Wikipedia often brands itself as aspiring to contain “the sum of human knowledge”, but behind this mantra lie policy pitfalls, tedious editor debates and delicate sourcing issues that hamper greater representation of the region. Of course these challenges form part of Wikipedia’s continuing evolution as the de facto source for online reference information, but they also (disturbingly) act to entrench particular ways of “knowing” — and ways of validating what is known.

There are over 260,000 articles in Arabic, receiving 240,000 views per hour. This actually translates as one of the least represented major world languages on Wikipedia: few languages have more speakers and fewer articles than Arabic. This relative lack of MENA voice and representation means that the tone and content of this globally useful resource, in many cases, is being determined by outsiders with a potential misunderstanding of the significance of local events, sites of interest and historical figures. In an area that has seen substantial social conflict and political upheaval, greater participation from local actors would help to ensure balance in content about contentious issues. Unfortunately, most research on MENA’s Internet presence has so far been drawn from anecdotal evidence, and no comprehensive studies currently exist.

In this project we wanted to understand where place-based content comes from, to explain reasons for the relative lack of Wikipedia articles in Arabic and about the MENA region, and to understand which parts of the region are particularly underrepresented. We also wanted to understand the relationship between Wikipedia’s administrative structure and the treatment of new editors; in particular, we wanted to know whether editors from the MENA region have less of a voice than their counterparts from elsewhere, and whether the content they create is considered more or less legitimate, as measured through the number of reverts; ie the overriding of their work by other editors.

Our practical objectives involved a consolidation of Middle Eastern Wikipedians though a number of workshops focusing on how to create more equitable and representative content, with the ultimate goal of making Wikipedia a more generative and productive site for reference information about the region. Capacity building among key Wikipedians can create greater understanding of barriers to participation and representation and offset much of the (often considerable) emotional labour required to sustain activity on the site in the face of intense arguments and ideological biases. Potential systematic structures of exclusion that could be a barrier to participation include such competitive practices as content deletion, indifference to content produced by MENA authors, and marginalization through bullying and dismissal.

However, a distinct lack of sources — owing both to a lack of legitimacy for MENA journalism and a paucity of open access government documents — is also inhibiting further growth of content about the region. When inclusion of a topic is contested by editors it is typically because there is not enough external source material about it to establish “notability”. As Ford (2011) has already discussed, notability is often culturally mediated. For example, a story in Al Jazeera would not have been considered a sufficient criterion of notability a couple of years ago. However, this has changed dramatically since its central role in reporting on the Arab Spring.

Unfortunately, notability can create a feedback loop. If an area of the world is underreported, there are no sources. If there are no sources, then journalists do not always have enough information to report about that part of the world. ‘Correct’ sourcing trumps personal experience on Wikipedia; even if an author is from a place, and is watching a building being destroyed, their Wikipedia edit will not be accepted by the community unless the event is discussed in another ‘official’ medium. Often the edit will either be branded with a ‘citation needed’ tag, eliminated, or discussed in the talk page. Particularly aggressive editors and administrators will nominate the page for ‘speedy deletion’ (ie deletion without discussion), a practice that makes responses from an author difficult

Why does any of this matter in practical terms? For the simple reason that biases, absences and contestations on Wikipedia spill over into numerous other domains that are in regular and everyday use (Graham and Zook, 2013). If a place is not on Wikipedia, this might have a chilling effect on business and stifle journalism; if a place is represented poorly on Wikipedia this can lead to misunderstandings about the place. Wikipedia is not a legislative body. However, in the court of public opinion, Wikipedia represents one of the world’s strongest forces, as it quietly inserts itself into representations of place worldwide (Graham et. al 2013; Graham 2013).

Wikipedia is not merely a site of reference information, but is rapidly becoming the de facto site for representing the world to itself. We need to understand more about that representation.

Further Reading

Allagui, I., Graham, M., and Hogan, B. 2014. Wikipedia Arabe et la Construction Collective du Savoir In Wikipedia, objet scientifique non identifie. eds. Barbe, L., and Merzeau, L. Paris: Presses Universitaries du Paris Ouest (in press).

Graham, M., Hogan, B., Straumann, R. K., and Medhat, A. 2014. Uneven Geographies of User-Generated Information: Patterns of Increasing Informational Poverty. Annals of the Association of American Geographers (forthcoming).

Graham, M. 2012. Die Welt in Der Wikipedia Als Politik der Exklusion: Palimpseste des Ortes und selective Darstellung. In Wikipedia. eds. S. Lampe, and P. Bäumer. Bundeszentrale für politische Bildung/bpb, Bonn.

Graham, M. 2011. Wiki Space: Palimpsests and the Politics of Exclusion. In Critical Point of View: A Wikipedia Reader. Eds. Lovink, G. and Tkacz, N. Amsterdam: Institute of Network Cultures, 269-282.

References

Ford, H. (2011) The Missing Wikipedians. In Geert Lovink and Nathaniel Tkacz (eds), Critical Point of View: A Wikipedia Reader, Amsterdam: Institute of Network Cultures, 2011. ISBN: 978-90-78146-13-1.

Graham, M., M. Zook., and A. Boulton. 2013. Augmented Reality in the Urban Environment: contested content and the duplicity of code. Transactions of the Institute of British Geographers. 38(3), 464-479.

Graham, M and M. Zook. 2013. Augmented Realities and Uneven Geographies: Exploring the Geo-linguistic Contours of the Web. Environment and Planning A 45(1) 77-99.

Graham, M. 2013. The Virtual Dimension. In Global City Challenges: debating a concept, improving the practice. eds. M. Acuto and W. Steele. London: Palgrave. 117-139.

Mark Graham is a Senior Research Fellow at the OII. His research focuses on Internet and information geographies, and the overlaps between ICTs and economic development.

Digital gaming, once a stigmatized hobby, is now a mainstream cultural activity. According to the Oxford Internet Survey, more than half of British Internet users play games online; more in fact, than watch films or pornography online. Most new games today contain some kind of a virtual economy: that is, a set of processes for the production, allocation, and consumption of artificially scarce virtual goods. Often the virtual economy is very simple; sometimes, as in massively multiplayer online game EVE Online, it starts to approach the scale and complexity of a small national economy.

Just like national economies, virtual economies incentivize certain behaviours and discourage others; they ask people to make choices between mutually exclusive options; they ask people to coordinate. They can also propagate value systems setting out what modes of participation are considered valuable. These virtual economies are now built into many of the most popular areas of the Internet, including social media sites and knowledge commons — with their systems of artificially scarce likes, stars, votes, and badges. Understanding these economies is therefore crucial to anyone who is interested in the social dynamics and power relations of digital media today.

But a question I am asked a lot is: what can ‘real’ economies and the economists who run them learn from these virtual economies? We might start by imagining how a textbook economist would approach the economy of an online game. In EVE Online, hundreds of thousands of players trade minerals, spaceship components and other virtual commodities on a number of regional marketplaces. These marketplaces are very sophisticated, resembling real commodity spot markets.

Our economist would doubtless point out several ways its efficiency could be radically improved. For example, EVE players can only see prices quoted in their current region, likely missing a better deal available elsewhere. (In physical commodity markets, prices are instantly broadcast worldwide: you wouldn’t pay more for gold in Tokyo than you would in New York.) Our economist knows that providing more information to market participants increases the market’s efficiency, and might therefore suggest modifying the game such that all players gain instant and galaxy-wide access to the same price information. This would improve the overall efficiency of the galactic market.

This change would obviously be a blow to those players who have specialized in gathering and trading this price information. It would also reduce the opportunities for arbitrageurs: players who rummage the galaxy for underpriced goods, transporting them to regions where they will fetch a profit. Of course, these players could always turn themselves into haulers, the space equivalent of truck drivers. Increased efficiency would probably increase cross-regional trade, meaning a boom-time for haulers.

But wait – realizing the infinite malleability of virtual economies, the textbook economist might decide to eliminate regions altogether. Distance is what economists refer to as a transaction cost: the economy would run much more efficiently without the need to transport things around. In a virtual environment goods and characters could be instantly teleported, or the galaxy simply collapsed into a single, dimensionless point. The efficiency of the virtual economy would certainly be greatly improved. But who would pay a subscription fee to participate in such a boring economy!

Why did our strawman economist make such a horrible mess of the game economy? Conventional economic laws are work equally well in virtual environments: the equilibrium price of a commodity in a competitive market is determined by the interaction of supply and demand, regardless of whether you are in the market for magic swords or soya beans. The crucial difference is in the objectives the economy is intended to fulfil. When conventional economists design and analyse economies, they take it as read that the purpose of the economy and its institutions is to solve the so-called economic problem: the allocation of limited resources so as to best satisfy human needs. Microeconomists do this by designing mechanisms that are as efficient as possible, while macroeconomists are concerned with maximizing economic output.

But in game economies, the economic problem doesn’t really exist. The needs that players experience are contrived, created by positioning otherwise useless goods (magic swords) as desirable status items. The scarcity of resources is likewise artificial, enforced through programme code. If games designers wanted to solve the economic problem, they could do it with a few keystrokes; no markets or other economic institutions are required for this purpose.

Different multiplayer game economies have different aims, but one key objective stands out: the economy helps create and hold together the social fabric of the game. Regular interaction generates interpersonal ties and trust. Having people consume the fruits of one’s digital labour generates a sense of meaning, a sense of a role to play in the community. Division of labour and the resulting mutual interdependence moreover creates solidarity and social cohesion. In short, the economy can act as a wonderful glue holding people together.

The social fabric is important to game developers, because the stronger the ties between players, the longer the players will keep playing (and paying fees). Some games developers expend considerable resources in their own style of economic research, experimenting with different exchange mechanisms and institutions to find the designs that really strengthen the social fabric. When we examine the resulting virtual economies we can see that their design choices are often very different from the choices that a conventional economist would make.

I will give an example. One aspect of designing a market is designing an exchange mechanism: the concrete mechanism through which the buyer and the seller meet, settle on a price and quantity, and execute the transaction. The simplest exchange mechanism is two people meeting face to face to negotiate a trade, and then exchanging the goods on the spot. A more sophisticated mechanism is an online auction, like eBay. Stock markets use an even more sophisticated mechanism, where participants submit buy and sell offers, these are matched by an algorithm, and trades are executed automatically.

Given that many exchange mechanisms are possible, what kind of an exchange mechanism should be build into your market? When governments and companies create markets they usually turn to microeconomists specializing in this kind of mechanism design. The microeconomist’s answer is that you should choose the exchange mechanism that is most efficient, in the sense of allocating goods optimally and minimizing all transaction costs: in the best case it may not even be necessary for the buyer and the seller to know each others’ identities.

Games economists, in contrast, tend to favour exchange mechanisms that involve social interaction; often through a virtual face-to-face meeting, where the tedious parts (explaining item characteristics) are automated, but negotiation over prices and quantities is conducted manually. Some locations in the virtual world often spontaneously emerge as sort of bazaars, where buyers and sellers congregate to search for deals. These double as social hubs where people come to meet friends and put on performances and displays, thereby building social capital. One might later consider one’s trading acquaintances when putting together a team for some quest.

More sophisticated exchange mechanisms, such as auction houses and the commodity spot markets in EVE Online, are also common in games, but they also avoid completely displacing social trade networks. In EVE Online, players must either move around in space or use their social networks to obtain price information from neighboring localities. This way, EVE Online’s developers have struck a balance between efficiency and social ties. One thing that virtual economies can teach is to look for other objectives besides efficiency and output as variables that need to be maximized in an economic system.

I would argue that a focus on social fabric — rather than just on efficiency and output – can usefully inform national economies. First, in today’s affluent societies, we are close to solving the economic problem: in the United Kingdom or the United States the need for life-sustaining material basics is all but fulfilled. Keynes predicted 90 years ago that the economic problem will be solved within 100 years; in the affluent parts of the world, it looks like he may have been right. The greatest problem faced by the UK and US today is not the economic problem, but the disintegration of the social fabric. Virtual economies show how economic institutions could be arranged so as to strengthen it.

Second, even in that greater part of the world where the economic problem still remains acute, it is not the case that we should focus on it exclusively. Poor countries should not have to go through social disintegration to reach economic affluence. Third, as I have already mentioned, games and virtual economies have become significant phenomena in their own right. Their creators are smart people who have developed many economic insights of their own. They are eager for knowledge on how to better design and operate these economies, but conventional economic advice that focuses solely on efficiency fails to address their needs. Economists and economic sociologists should widen their research to develop answers that satisfy the needs of virtual economy designers – and also of a more ‘social’ national economy.

Now, to be fair, the fact that markets and other modern economic institutions can serve important social functions has been known to sociologists since Émile Durkheim. But this has been regarded as something of a side effect, and certainly not the purpose for which these institutions are created. Game economies are radical in this respect – that they are created entirely to serve these other functions, rather than any material function. Economic anthropologist Karl Polanyi argued in The Great Transformation that in the transition from a traditional to a market society, social structure was rearranged to serve the needs of the economy. What game economies do is in some ways the opposite: they rearrange the economy to serve the needs of the social structure. And that would seem to be a very worthwhile endeavor.

Read more: Vili Lehdonvirta and Edward Castronova (2014) Virtual Economies: Design and Analysis. MIT Press.

Vili Lehdonvirta is a Research Fellow at OII. He is an economic sociologist who studies the social and economic dimensions of new information technologies around the world. His particular areas of expertise are virtual goods, virtual currencies, and digital labour. Vili’s book Virtual Economies: Design and Analysis (with Edward Castronova) is published by MIT Press.

This way of thinking about the study has a serious defect, because there are three issues raised by this research: The first is the legality of the study, which, as the authors correctly point out, falls within Facebook users’ giving informed consent when they sign up to the service. Laws or regulation may be required here to prevent this kind of manipulation, but may also be difficult, since it will be hard to draw a line between this experiment and other forms of manipulating peoples’ responses to media. However, Facebook may not want to lose users, for whom this way of manipulating them via their service may ‘cause anxiety’ (as the first author of the study, Adam Kramer, acknowledged in a blog post response to the outcry). In short, it may be bad for business, and hence Facebook may abandon this kind of research (but we’ll come back to this later). But this – companies using techniques that users don’t like, so they are forced to change course – is not new.

The second issue is academic research ethics. This study was carried out by two academic researchers (the other two authors of the study). In retrospect, it is hard to see how this study would have received approval from an institutional review board (IRB), the boards at which academic institutions check the ethics of studies. Perhaps stricter guidelines are needed here since a) big data research is becoming much more prominent in the social sciences and is often based on social media like Facebook, Twitter, and mobile phone data, and b) much – though not all (consider Wikipedia) – of this research therefore entails close relations with the social media companies who provide access to these data, and to being able to experiment with the platforms, as in this case. Here, again, the ethics of academic research may need to be tightened to provide new guidelines for academic collaboration with commercial platforms. But this is not new either.

The third issue, which is the new and important one, is the increasing power that social research using big data has over our lives. This is of course even more difficult to pin down than the first two points. Where does this power come from? It comes from having access to data of a scale and scope that is a leap or step change from what was available before, and being able to perform computational analysis on these data. This is my definition of ‘big data’ (see note 1), and clearly applies in this case, as in other cases we have documented: almost 700000 users’ Facebook newsfeeds were changed in order to perform this experiment, and more than 3 million posts containing more than 122 million words were analysed. The result: it was found that more positive words in Facebook Newsfeeds led to more positive posts by users, and the reverse for negative words.

What is important here are the implications of this powerful new knowledge. To be sure, as the authors point, this was a study that is valuable for social science in showing that emotions may be transmitted online via words, not just in face-to-face situations. But secondly, it also provides Facebook with knowledge that it can use to further manipulate users’ moods; for example, making their moods more positive so that users will come to its – rather than a competitor’s – website. In other words, social science knowledge, produced partly by academic social scientists, enables companies to manipulate peoples’ hearts and minds.

This not the Orwellian world of the Snowden revelations about phone tapping that have been in the news recently. It’s the Huxleyan Brave New World where companies and governments are able to play with peoples’ minds, and do so in a way whereby users may buy into it: after all, who wouldn’t like to have their experience on Facebook improved in a positive way? And of course that’s Facebook’s reply to criticisms of the study: the motivation of the research is that we’re just trying to improve your experience, as Kramer says in his blogpost response cited above. Similarly, according to The Guardian newspaper, ‘A Facebook spokeswoman said the research…was carried out “to improve our services and to make the content people see on Facebook as relevant and engaging as possible”’. But improving experience and services could also just mean selling more stuff.

This is scary, and academic social scientists should think twice before producing knowledge that supports this kind of impact. But again, we can’t pinpoint this impact without understanding what’s new: big data is a leap in how data can be used to manipulate people in more powerful ways. This point has been lost by those who criticize big data mainly on the grounds of the epistemological conundrums involved (as with boy and Crawford’s widely cited paper, see note 2). No, it’s precisely because knowledge is more scientific that it enables more manipulation. Hence, we need to identify the point or points at which we should put a stop to sliding down a slippery slope of increasing manipulation of our behaviours. Further, we need to specify when access to big data on a new scale enables research that affects many people without their knowledge, and regulate this type of research.

Which brings us back to the first point: true, Facebook may stop this kind of research, but how would we know? And have academics therefore colluded in research that encourages this kind of insidious use of data? We can only hope for a revolt against this kind of Huxleyan conditioning, but as in Brave New World, perhaps the outlook is rather gloomy in this regard: we may come to like more positive reinforcement of our behaviours online…

Notes

1. Schroeder, R. 2014. ‘Big Data: Towards a More Scientific Social Science and Humanities?’, in Graham, M., and Dutton, W. H. (eds.), Society and the Internet. Oxford: Oxford University Press, pp.164-76.

2. boyd, D. and Crawford, K. (2012). ‘Critical Questions for big data: Provocations for a cultural, technological and scholarly phenomenon’, Information, Communication and Society, 15(5), 662-79.

Professor Ralph Schroeder has interests in virtual environments, social aspects of e-Science, sociology of science and technology, and has written extensively about virtual reality technology. He is a researcher on the OII project Accessing and Using Big Data to Advance Social Science Knowledge, which follows ‘big data’ from its public and private origins through open and closed pathways into the social sciences, and documents and shapes the ways they are being accessed and used to create new knowledge about the social world.

A problem with national sample surveys (the usual source of data about Internet use and non-use), is that the sample sizes become too small to allow accurate generalization at smaller, sub-national areas. No one knows, for example, the proportion of Internet users in Glasgow, because national surveys simply won’t have enough respondents to make reliable city-level estimates. We know that Internet use is not evenly distributed at the regional level; Ofcom reports on broadband speeds and penetration at the county level (Ofcom 2011), and we know that London and the southeast are the most wired part of the country (Dean et al. 2012). But given the importance of the Internet, the lack of knowledge about local patterns of access and use in Britain is surprising. This is a problem because without detailed information about small areas we can’t identify where would benefit most from policy intervention to encourage Internet use and improve access.

We have begun to address this lack of information by combining two important but separate datasets — the 2011 national census, and the 2013 OxIS surveys — using the technique of small area estimation. By definition, census data are available for very small areas, and because it reaches (basically) everyone, there will be no sampling issues. Unfortunately, it is extremely expensive to collect this data, so it doesn’t collect many variables (it has no data on Internet use, for example). The second dataset, the OII’s Oxford Internet Survey (OxIS), is a very rich dataset of all kinds of Internet activity, measured with a random sample of more than 2,000 individuals across Britain. Because OxIS is unable to survey everyone in Britain, it is based on a random sample of people living in geographical ‘Output Areas’ (OAs). These areas (generally of 40-250 households) represent the fundamental building block of the national census, being the smallest geographical area for which it reports data.

Because OxIS and the census (happily) use the same OAs, we can combine national-level data on Internet use (from OxIS) with local-level demographic information (from the census) to map estimated Internet use across Britain for the first time. We can do this because we can estimate from OxIS the likelihood of an individual using the Internet just from basic demographic data (age, income, education etc.). And because the census records these demographics for everyone in each OA, we can go on to estimate the likely proportion of Internet users in each of these areas. By combining the richness of OxIS survey data with the comprehensive small area coverage of the census we can use the strengths of one to offset the gaps in the other.

Of course, this procedure assumes that people in small areas will generally match national patterns of Internet use; ie that those who are better educated, employed, and young, are more likely to use the Internet. We assume that this pattern isn’t affected by cultural or social factors (e.g. ‘Northerners just like the Internet more’), or by anything unusual about a particular group of households that makes it buck national trends (eg ‘the young people of Wytham Street, Oxford just prefer not to use the Internet’).

So what do we see when we combine the two datasets? What are the local-level patterns of Internet use across Britain? We can see from the figure that the highest estimated Internet use (88-89%) is concentrated in the south east, with London dominating. Bristol, Southampton, and Nottingham also have high levels of use, as well as the rest of the south (interestingly, including rural Cornwall) with estimated usage levels of 78-83%. Leeds, York and Manchester are also in this category. In the lowest category (59-70% use) we find the entire North East region. Cities show much the same pattern, with southern cities having the highest estimated Internet use, and Newcastle and Middlesbrough having the lowest.

There isn’t room in this post to explore and discuss all the patterns (or to speculate on the underlying reasons), but there are clear policy implications from this work. The Internet has made an enormous difference in our social life, culture, and economy; this is why it is important to bring people online, to encourage them all to participate and benefit. However, despite the importance of the Internet in Britain today, we still know very little about who is, and isn’t connected. We hope this approach (and this data) can help pinpoint the areas of greatest need. For example, the North East is striking — even the cities don’t seem to stand out from the surrounding rural areas. Allocating resources to improve use in the North East would probably be valuable, with rural areas as a secondary priority. Interestingly, Cornwall (despite being very rural) is actually above average in terms of likely Internet users, and is also the recipient of a major European Regional Development Fund effort to extend their broadband.

Actually getting access via fibre-optic cable is just one part of the story of Internet use (and one we don’t cover in this post); but this is the first time we have been estimate the likely use at a local level, based on the known characteristics of the people who live there. Using these small area estimation techniques opens a whole new area for social media research and policy-making around local patterns of digital participation. Going forward, we intend to expand the model to include urban-rural differences, the index of multiple deprivation, occupation, and socio-economic status. But there’s already much more we can do with these data.

References

Dean, D., DiGrande, S., Field, D., Lundmark, A., O’Day, J., Pineda, J., Zwillenberg, P. (2012) The connected world: The Internet economy in the G-20. Boston: Boston Consulting Group.

Malecki, E.J. & Moriset, B. (2008) The digital economy: Business organization, production processes and regional developments. London: Routledge.

Ofcom (2011) Communications infrastructure report: Fixed broadband data. [accessed on 23/9/2013 from http://stakeholders.ofcom.org.uk/binaries/research/broadband-research/Fixed_Broadband_June_2011.pdf ]

Read the full paper: Blank, G., Graham, M., and Calvino, C. (2014) Mapping the Local Geographies of Digital Inequality. [contact the authors for the paper and citation details]

Grant Blank is a Survey Research Fellow at the OII. He is a sociologist who studies the social and cultural impact of the Internet and other new communication media. He is principal investigator on the OII’s Geography of Digital Inequality project, which combines OxIS and census data to produce the first detailed geographic estimates of Internet use across the UK.

In the journal’s inaugural issue, founding Editor-in-Chief Helen Margetts outlined what are essentially two central premises behind Policy & Internet’s launch. The first is that “we cannot understand, analyze or make public policy without understanding the technological, social and economic shifts associated with the Internet” (Margetts 2009, 1). It is simply not possible to consider public policy today without some regard for the intertwining of information technologies with everyday life and society. The second premise is that the rise of the Internet is associated with shifts in how policy itself is made. In particular, she proposed that impacts of Internet adoption would be felt in the tools through which policies are effected, and the values that policy processes embody.

The purpose of the Policy and Internet journal was to take up these two challenges: the public policy implications of Internet-related social change, and Internet-related changes in policy processes themselves. In recognition of the inherently multi-disciplinary nature of policy research, the journal is designed to act as a meeting place for all kinds of disciplinary and methodological approaches. Helen predicted that methodological approaches based on large-scale transactional data, network analysis, and experimentation would turn out to be particularly important for policy and Internet studies. Driving the advancement of these methods was therefore the journal’s third purpose. Today, the journal has reached a significant milestone: over one hundred high-quality peer-reviewed articles published. This seems an opportune moment to take stock of what kind of research we have published in practice, and see how it stacks up against the original vision.

At the most general level, the journal’s articles fall into three broad categories: the Internet and public policy (48 articles), the Internet and policy processes (51 articles), and discussion of novel methodologies (10 articles). The first of these categories, “the Internet and public policy,” can be further broken down into a number of subcategories. One of the most prominent of these streams is fundamental rights in a mediated society (11 articles), which focuses particularly on privacy and freedom of expression. Related streams are children and child protection (six articles), copyright and piracy (five articles), and general e-commerce regulation (six articles), including taxation. A recently emerged stream in the journal is hate speech and cybersecurity (four articles). Of course, an enduring research stream is Internet governance, or the regulation of technical infrastructures and economic institutions that constitute the material basis of the Internet (seven articles). In recent years, the research agenda in this stream has been influenced by national policy debates around broadband market competition and network neutrality (Hahn and Singer 2013). Another enduring stream deals with the Internet and public health (eight articles).

Looking specifically at “the Internet and policy processes” category, the largest stream is e-participation, or the role of the Internet in engaging citizens in national and local government policy processes, through methods such as online deliberation, petition platforms, and voting advice applications (18 articles). Two other streams are e-government, or the use of Internet technologies for government service provision (seven articles), and e-politics, or the use of the Internet in mainstream politics, such as election campaigning and communications of the political elite (nine articles). Another stream that has gained pace during recent years, is online collective action, or the role of the Internet in activism, ‘clicktivism,’ and protest campaigns (16 articles). Last year the journal published a special issue on online collective action (Calderaro and Kavada 2013), and the next forthcoming issue includes an invited article on digital civics by Ethan Zuckerman, director of MIT’s Center for Civic Media, with commentary from prominent scholars of Internet activism. A trajectory discernible in this stream over the years is a movement from discussing mere potentials towards analyzing real impacts—including critical analyses of the sometimes inflated expectations and “democracy bubbles” created by digital media (Shulman 2009; Karpf 2012; Bryer 2012).

The final category, discussion of novel methodologies, consists of articles that develop, analyze, and reflect critically on methodological innovations in policy and Internet studies. Empirical articles published in the journal have made use of a wide range of conventional and novel research methods, from interviews and surveys to automated content analysis and advanced network analysis methods. But of those articles where methodology is the topic rather than merely the tool, the majority deal with so-called “big data,” or the use of large-scale transactional data sources in research, commerce, and evidence-based public policy (nine articles). The journal recently devoted a special issue to the potentials and pitfalls of big data for public policy (Margetts and Sutcliffe 2013), based on selected contributions to the journal’s 2012 big data conference: Big Data, Big Challenges? In general, the notion of data science and public policy is a growing research theme.

This brief analysis suggests that research published in the journal over the last five years has indeed followed the broad contours of the original vision. The two challenges, namely policy implications of Internet-related social change and Internet-related changes in policy processes, have both been addressed. In particular, research has addressed the implications of the Internet’s increasing role in social and political life. The journal has also furthered the development of new methodologies, especially the use of online network analysis techniques and large-scale transactional data sources (aka ‘big data’).

As expected, authors from a wide range of disciplines have contributed their perspectives to the journal, and engaged with other disciplines, while retaining the rigor of their own specialisms. The geographic scope of the contributions has been truly global, with authors and research contexts from six continents. I am also pleased to note that a characteristic common to all the published articles is polish; this is no doubt in part due to the high level of editorial support that the journal is able to afford to authors, including copyediting. The justifications for the journal’s establishment five years ago have clearly been borne out, so that the journal now performs an important function in fostering and bringing together research on the public policy implications of an increasingly Internet-mediated society.

And what of my own research interests as an editor? In the inaugural editorial, Helen Margetts highlighted work, finance, exchange, and economic themes in general as being among the prominent areas of Internet-related social change that are likely to have significant future policy implications. I think for the most part, these implications remain to be addressed, and this is an area that the journal can encourage authors to tackle better. As an editor, I will work to direct attention to this opportunity, and welcome manuscript submissions on all aspects of Internet-enabled economic change and its policy implications. This work will be kickstarted by the journal’s 2014 conference (26-27 September), which this year focuses on crowdsourcing and online labor.

Our published articles will continue to be highlighted here in the journal’s blog. Launched last year, we believe this blog will help to expand the reach and impact of research published in Policy and Internet to the wider academic and practitioner communities, promote discussion, and increase authors’ citations. After all, publication is only the start of an article’s public life: we want people reading, debating, citing, and offering responses to the research that we, and our excellent reviewers, feel is important, and worth publishing.

Read the full editorial:  Lehdonvirta, V. (2014) Past and Emerging Themes in Policy and Internet Studies. Policy & Internet 6(2): 109-114.

References

Bryer, T.A. (2011) Online Public Engagement in the Obama Administration: Building a Democracy Bubble? Policy & Internet 3 (4).

Calderaro, A. and Kavada, A. (2013) Challenges and Opportunities of Online Collective Action for Policy Change. Policy & Internet (5) 1.

Hahn, R. and Singer, H. (2013) Is the U.S. Government’s Internet Policy Broken? Policy & Internet 5 (3) 340-363.

Karpf, D. (2012) Online Political Mobilization from the Advocacy Group’s Perspective: Looking Beyond Clicktivism. Policy & Internet 2 (4) 7-41.

Margetts, H. (2009) The Internet and Public Policy. Policy and Internet 1 (1).

Margetts, H. and Sutcliffe, D. (2013) Addressing the Policy Challenges and Opportunities of ‘Big Data.’ Policy & Internet 5 (2) 139-146.

Shulman, S.W. (2009) The Case Against Mass E-mails: Perverse Incentives and Low Quality Public Participation in U.S. Federal Rulemaking. Policy & Internet 1 (1) 23-53.

Ed: You have been looking at “networked cultural production” — ie the creation of cultural goods like films through crowdsourcing platforms — specifically in the ‘wreckamovie’ community. What is wreckamovie?

Isis: Wreckamovie is an open online platform that is designed to facilitate collaborate film production. The main advantage of the platform is that it encourages a granular and modular approach to cultural production; this means that the whole process is broken down into small, specific tasks. In doing so, it allows a diverse range of geographically dispersed, self-selected members to contribute in accordance with their expertise, interests and skills. The platform was launched by a group of young Finnish filmmakers in 2008, having successfully produced films with the aid of an online forum since the late 1990s. Officially, there are more than 11,000 Wreckamovie members, but the active core, the community, consists of fewer than 300 individuals.

Ed: You mentioned a tendency in the literature to regard production systems as being either ‘market driven’ (eg Hollywood) or ‘not market driven’ (eg open or crowdsourced things); is that a distinction you recognised in your research?

Isis: There’s been a lot of talk about the disruptive and transformative powers nested in networked technologies, and most often Wikipedia or open source software are highlighted as examples of new production models, denoting a discontinuity from established practices of the cultural industries. Typically, the production models are discriminated based on their relation to the market: are they market-driven or fuelled by virtues such as sharing and collaboration? This way of explaining differences in cultural production isn’t just present in contemporary literature dealing with networked phenomena, though. For example, the sociologist Bourdieu equally theorized cultural production by drawing this distinction between market and non-market production, portraying the irreconcilable differences in their underlying value systems, as proposed in his The Rules of Art. However, one of the key findings of my research is that the shaping force of these productions is constituted by the tensions that arise in an antagonistic interplay between the values of social networked production and the production models of the traditional film industry. That is to say, the production practices and trajectories are equally shaped by the values embedded in peer production virtues and the conventions and drivers of Hollywood.

Ed: There has also been a tendency to regard the participants of these platforms as being either ‘professional’ or ‘amateur’ — again, is this a useful distinction in practice?

Isis: I think it’s important we move away from these binaries in order to understand contemporary networked cultural production. The notion of the blurring of boundaries between amateurs and professionals, and associated concepts such as user-generated content, peer production, and co-creation, are fine for pointing to very broad trends and changes in the constellations of cultural production. But if we want to move beyond that, towards explanatory models, we need a more fine-tuned categorisation of cultural workers. Based on my ethnographic research in the Wreckamovie community, I have proposed a typology of crowdsourcing labour, consisting of five distinct orientations. Rather than a priori definitions, the orientations are defined based on the individual production members’ interaction patterns, motivations and interpretation of the conventions guiding the division of labour in cultural production.

Ed: You mentioned that the social capital of participants involved in crowdsourcing efforts is increasingly quantifiable, malleable, and convertible: can you elaborate on this?

Isis: A defining feature of the online environment, in particular social media platforms, is its quantification of participation in the form of lists of followers, view counts, likes and so on. Across the Wreckamovie films I researched, there was a pronounced implicit understanding amongst production leaders of the exchange value of social capital accrued across the extended production networks beyond the Wreckamovie platform (e.g. Facebook, Twitter, YouTube). The quantified nature of social capital in the socio-technical space of the information economy was experienced as a convertible currency; for example, when social capital was used to drive YouTube views (which in turn constituted symbolic capital when employed as a bargaining tool in negotiating distribution deals). For some productions, these conversion mechanisms enabled increased artistic autonomy.

Ed: You also noted that we need to understand exactly where value is generated on these platforms to understand if some systems of ‘open/crowd’ production might be exploitative. How do we determine what constitutes exploitation?

Isis: The question of exploitation in the context of voluntary cultural work is an extremely complex matter, and remains an unresolved debate. I argue that it must be determined partially by examining the flow of value across the entire production networks, paying attention to nodes on both micro and macro level. Equally, we need to acknowledge the diverse forms of value that volunteers might gain in the form of, for example, embodied cultural or symbolic capital, and assess how this corresponds to their motivation and work orientation. In other words, this isn’t a question about ownership or financial compensation alone.

Ed: There were many movie-failures on the platform; but movies are obviously tremendously costly and complicated undertakings, so we would probably expect that. Was there anything in common between them, or any lessons to be learned form the projects that didn’t succeed?

Isis: You’ll find that the majority of productions on Wreckamovie are virtual ghosts; created on a whim with the expectation that production members will flock to take part and contribute. The projects that succeed in creating actual cultural goods (such as the 2010 movie Snowblind) were those that were lead by engaged producers actively promoting the building of genuine social relationships amongst members, and providing feedback to submitted content in a constructive and supportive manner to facilitate learning. The production periods of the movies I researched spanned between two and six years – it requires real dedication! Crowdsourcing does not make productions magically happen overnight.

Ed: Crowdsourcing is obviously pretty new and exciting, but are the economics (whether monetary, social or political) of these platforms really understood or properly theorised? ie is this an area where there genuinely does need to be ‘more work’?

Isis: The economies of networked cultural production are under-theorised; this is partially an outcome of the dichotomous framing of market vs. non-market led production. When conceptualized as divorced from market-oriented production, networked phenomena are most often approached through the scope of gift exchanges (in a somewhat uninformed manner). I believe Bourdieu’s concepts of alternative capital in their various guises can serve as an appropriate analytical lens for examining the dynamics and flows of the economics underpinning networked cultural production. However, this requires innovation within field theory. Specifically, the mechanisms of conversion of one form capital to another must be examined in greater detail; something I have focused on in my thesis, and hope to develop further in the future.

Isis Hjorth was speaking to blog editor David Sutcliffe.

Isis Hjorth is a cultural sociologist focusing on emerging practices associated with networked technologies. She is currently researching microwork and virtual production networks in Sub-Saharan Africa and Southeast Asia.

Read more: Hjorth, I. (2014) Networked Cultural Production: Filmmaking in the Wreckamovie Community. PhD thesis. Oxford Internet Institute, University of Oxford, UK.

Chris: Yes, at the end of the 2000s when the first fibre cables landed in East Africa, there was much anticipation about what this new connectivity would mean for the region. I remember I was in Tanzania at the time, and people were very excited about this development – being tired of the slow and expensive satellite connections where even simple websites could take a minute to load. The perception, both in the international press and from East African politicians was that the cables would be a game changer. Firms would be able to market and sell more directly to customers and reduce inefficient ‘intermediaries’. Connectivity would allow new types of digital-driven business, and it would provide opportunity for small and medium firms to become part of the global economy. We wanted to revisit this discussion. Were firms adopting internet, as it became cheaper? Had this new connectivity had the effects that were anticipated, or was it purely hype?

Ed:  So what is the current level and quality of broadband access in Rwanda? ie how connected are people on the ground?

Chris: Internet access has greatly improved over the previous few years, and the costs of bandwidth have declined markedly. The government has installed a ‘backbone’ fibre network and in the private sector there has also been a growth in the number of firms providing Internet service. There are still some problems though. Prices are still are quite high, particularly for dedicated broadband connections, and in the industries we looked at (tea and tourism) many firms couldn’t afford it. Secondly, we heard a lot of complaints that lower bandwidth connections – WiMax and mobile internet – are unreliable and become saturated at peak times. So, Rwanda has come a long way, but we expect there will be more improvements in the future.

Ed: How much impact has the Internet had on Rwanda’s economy generally? And who is it actually helping, if so?

Chris: Economists in the World Bank have calculated that in developing economies a 10% improvement in Internet access leads to an increase in growth of 1.3%, so the effects should be taken seriously. In Rwanda, it’s too early to concretely see the effects in bottom line economic growth. In Rwanda, it’s too early to concretely see the effects in bottom line economic growth. In this work we wanted to examine the effect on already established sectors to get insight on Internet adoption and use. In general, we can say that firms are increasingly adopting Internet connectivity in some form, and that firms have been able take advantage and improve operations. However, it seems that wider transformational effects of connectivity have so far been limited.

Ed: And specifically in terms of the Rwandan tea and tourism industries: has the Internet had much effect?

Chris: The global tourism industry is driven by Internet use, and so tour firms, guides and hotels in Rwanda have been readily adopting it. We can see that the Internet has been beneficial, particularly for those firms coordinating tourism in Rwanda, who can better handle volumes of tourists. In the tea industry, adoption is a little lower but the Internet is used in similar ways – to coordinate the movement of tea from production to processing to selling, and this simplifies management for firms. So, connectivity has had benefits by improvements in efficiency, and this complements the fact that both sectors are looking to attract international investment and become better integrated into markets. In that sense, one can say that the growth in Internet connectivity is playing a significant role in strategies of private sector development.

Ed: The project partly focuses on value chains: ie where value is captured at different stages of a chain, leading (for example) from Rwandan tea bush to UK Tesco shelf. How have individual actors in the chain been affected? And has there been much in the way of (the often promised) disintermediation — ie are Rwandan tea farmers and tour operators now able to ‘plug directly’ into international markets?

Chris: Value chains allow us to pay more attention to who are the winners (and losers) of the processes described above, and particularly to see if this benefits Rwandan firms who are linked into global markets. One of the potential benefits originally discussed around new connectivity was that with the growth of online channels and platforms — and through social media — that firms as they became connected would have a more direct link to large markets and be able to disintermediate and improve the benefits they received. Generally, we can say that such disintermediation has not happened, for different reasons. In the tourism sector, many tourists are still reluctant to go directly to Rwandan tourist firms, for reasons related to trust (particularly around payment for holidays). In the tea sector, the value chains are very well established, and with just a few retailers in the end-markets, direct interaction with markets has simply not materialised. So, the hope of connectivity driving disintermediation in value chains has been limited by the market structure of both these sectors.

Ed: Is there any sense that the Internet is helping to ‘lock’ Rwanda into global markets and institutions: for example international standards organisations? And will greater transparency mean Rwanda is better able to compete in global markets, or will it just allow international actors to more efficiently exploit Rwanda’s resources — ie for the value in the chain to accrue to outsiders?

Chris: One of the core activities around the Internet that we found for both tea and tourism was firms using connectivity as a way to integrate themselves into logistic tracking, information systems, and quality and standards; whether this be automation in the tea sector or using global booking systems in the tourism sector. In one sense, this benefits Rwandan firms in that it’s crucial to improving efficiency in global markets, but it’s less clear that benefits of integration always accrue to those in Rwanda. It also moves away from the earlier ideas that connectivity would empower firms, unleashing a wave of innovation. To some of the firms we interviewed, it felt like this type of investment in the Internet was simply a way for others to better monitor, define and control every step they made, dictated by firms far away.

Ed. How do the project findings relate to (or comment on) the broader hopes of ICT4D developers? ie does ICT (magically) solve economic and market problems — and if so, who benefits?

Chris: For ICT developers looking to support development, there is often a tendency to look to build for actors who are struggling to find markets for their goods and services (such as apps linking buyers and producers, or market pricing information). But, the industries we looked at are quite different — actors (even farmers) are already linked via value chains to global markets, and so these types of application were less useful. In interviews, we found other informal uses of the Internet amongst lower-income actors in these sectors, which point the way towards new ICT applications: sectoral knowledge building, adapting systems to allow smallholders to better understand their costs, and systems to allow better links amongst cooperatives. More generally for those interested in ICT and development, this work highlights that changes in economies are not solely driven by connectivity, particularly in industries where rewards are already skewed towards larger global firms over those in developing countries. This calls for a context-dependent analysis of policy and structures, something that can be missed when more optimistic commentators discuss connectivity and the digital future.

Christopher Foster was talking to blog editor David Sutcliffe.

Individuals often have little knowledge about the actual risks, and single instances of breaches are exaggerated in the media. Key to successful adoption of Internet-based health records is, however, how much a patient places trust in the technology: trust that data will be properly secured from inadvertent leakage, and trust that it will not be accessed by unauthorised strangers.

Situated in this context, my own research has taken a closer look at the structural and institutional factors influencing patient trust in Internet-based health records. Utilising a survey and interviews, the research has looked specifically at Germany – a very suitable environment for this question given its wide range of actors in the health system, and often being referred to as a “hard-line privacy country”. Germany has struggled for years with the introduction of smart cards linked to centralised Electronic Health Records, not only changing its design features over several iterations, but also battling negative press coverage about data security.

The first element to this question of patient trust is the “who”: that is, does it make a difference whether the health record is maintained by either a medical or a non-medical entity, and whether the entity is public or private? I found that patients clearly expressed a higher trust in medical operators, evidence of a certain “halo effect” surrounding medical professionals and organisations driven by patient faith in their good intentions. This overrode the concern that medical operators might be less adept at securing the data than (for example) most non-medical IT firms. The distinction between public and private operators is much more blurry in patients’ perception. However, there was a sense among the interviewees that a stronger concern about misuse was related to a preference for public entities who would “not intentionally give data to others”, while data theft concerns resulted in a preference for private operators – as opposed to public institutions who might just “shrug their shoulders and finger-point at subordinate levels”.

Equally important to the question of “who” is managing the data may be the “how”: that is, is the patient’s ability to access and control their health-record content perceived as trust enhancing? While the general finding of this research is that having the opportunity to both access and control their records helps to build patient trust, an often overlooked (and discomforting) factor is that easy access for the patient may also mean easy access for the rest of the family. In the words of one interviewee: “For example, you have Alzheimer’s disease or dementia. You don’t want everyone around you to know. They will say ‘show us your health record online’, and then talk to doctors about you – just going over your head.” Nevertheless, for most people I surveyed, having access and control of records was perceived as trust enhancing.

At the same time, a striking survey finding is how greater access and control of records can be less trust-enhancing for those with lower Internet experience, confidence, and breadth of use: as one older interviewee put it – “I am sceptical because I am not good at these Internet things. My husband can help me, but somehow it is not really worth this effort.” The quote reveals one of the facets of digital divides, and additionally highlights the relevance of life-stage in the discussion. Older participants see the benefits of sharing data (if it means avoiding unnecessary repetition of routine examinations) and are less concerned about outsider access, while younger people are more apprehensive of the risk of medical data falling into the wrong hands. An older participant summarised this very effectively: “If I was 30 years younger and at the beginning of my professional career or my family life, it would be causing more concern for me than now”. Finally, this reinforces the importance of legal regulations and security audits ensuring a general level of protection – even if the patient chooses not to be (or cannot be) directly involved in the management of their data.

Interestingly, the research also uncovered what is known as the certainty trough: not only are those with low online affinity highly suspicious of Internet-based health records – the experts are as well! The more different activities a user engaged in, the higher the suspicion of Internet-based health records. This confirms the notion that with more knowledge and more intense engagement with the Internet, we tend to become more aware of the risks – and lose trust in the technology and what the protections might actually be worth.

Finally, it is clear that the “who” and the “how” are interrelated, as a low degree of trust goes hand in hand with a desire for control. For a generally less trustworthy operator, access to records is not sufficient to inspire patient trust. While access improves knowledge and may allow for legal steps to change what is stored online, few people make use of this possibility; only direct control of what is stored online helps to compensate for a general suspicion about the operator. It is noteworthy here that there is a discrepancy between how much importance people place on having control, and how much they actually use it, but in the end, trust is a subjective concept that doesn’t necessarily reflect actual privacy and security.

The results of this research provide valuable insights for the further development of Internet-based health records. In short: to gain patient trust, the operator should ideally be of a medical nature and should allow the patients to get involved in how their health records are maintained. Moreover, policy initiatives designed to increase the Internet and health literacy of the public are crucial in reaching all parts of the population, as is an underlying legal and regulatory framework within which any Internet-based health record should be embedded.

Read the full paper: Rauer, Ulrike (2012) Patient Trust in Internet-based Health Records: An Analysis Across Operator Types and Levels of Patient Involvement in Germany. Policy and Internet 4 (2).

Ed: You open your recent Policy and Internet article by noting that “the modern treasury of public institutions is where the wealth of public information is stored and processed” … what are the challenges of government use of cloud services?

Kristina: The public sector is a very large user of information technology but data handling policies, vendor accreditation and procurement often predate the era of cloud computing. Governments first have to put in place new internal policies to ensure the security and integrity of their information assets residing in the cloud. Through this process governments are discovering that their traditional notions of control are challenged because cloud services are virtual, dynamic, and operate across borders.

One central concern of those governments that are leading in the public sector’s migration to cloud computing is how to retain unconditional sovereignty over their data — after all, public sector information embodies the past, the present, and the future of a country. The ability to govern presupposes command and control over government information to the extent necessary to deliver public services, protect citizens’ personal data and to ensure the integrity of the state, among other considerations. One could even assert that in today’s interconnected world national sovereignty is conditional upon adequate data sovereignty.

Ed: A basic question: if a country’s health records (in the cloud) temporarily reside on / are processed on commercial servers in a different country: who is liable for the integrity and protection of that data, and under who’s legal scheme? ie can a country actually technically lose sovereignty over its data?

Kristina: There is always one line of responsibility flowing from the contract with the cloud service provider. However, when these health records cross borders they are effectively governed under a third country’s jurisdiction where disclosure authorities vis-à-vis the cloud service provider can likely be invoked. In some situations the geographical whereabouts of the public health records is not even that important because certain countries’ legislation has extra-territorial reach and it suffices that the cloud service provider is under an obligation to turn over data in its custody. In both situations countries’ exclusive sovereignty over public sector information would be contested. And service providers may find themselves in a Catch22 when they have to decide their legitimate course of action.

Ed: Is there a sense of how many government services are currently hosted “in the cloud”; and have there been any known problems so far about access and jurisdiction?

Kristina: The US has published some targets but otherwise we have no sense of the magnitude of government cloud computing. It is certainly an ever growing phenomenon in leading countries, for example both the US Federal Cloud Computing Strategy and the United Kingdom’s G-Cloud Framework leverage public sector cloud migration with a cloud-first strategy and they operate government application stores where public authorities can self-provision themselves with cloud-based IT services. Until now, the issues of access and jurisdiction have primarily been discussed in terms of risk (as I showed in my article) with governments adopting strategies to keep their public records within national territory, even if they are residing on a cloud service.

Ed: Is there anything about the cloud that is actually functionally novel; ie that calls for new regulation at national or international level, beyond existing data legislation?

Kristina: Cloud services are not meant to recognize national frontiers, but to thrive on economies of scale and scope globally. The legal risks arising from its transnationality won’t be solved by more legislation at the national level; even if this is a pragmatic solution, the resurrection of territoriality in cloud service contracts with the government conflicts with scalability. My article explores various avenues at the international level, for example extending diplomatic immunity, international agreements for cross-border data transfers, and reliance on mutual legal assistance treaties but in my opinion they do not satisfyingly restore a country’s quest for data sovereignty in the cloud context. In the EU a regional approach could be feasible and I am very much drawn by the idea of a European cloud environment where common information assurance principles prevail — also curtailing individual member states’ disclosure authorities.

Ed: As the economies of scale of cloud services kick in, do you think we will see increasing commercialisation of public record storing and processing (with a possible further erosion of national sovereignty)?

Kristina: Where governments have the capability they adopt a differentiated, risk-based approach corresponding to the information’s security classification: data in the public domain or that have low security markings are suitable for cloud services without further restrictions. Data that has medium security markings may still be processed on cloud services but are often confined to the national territory. Beyond this threshold, i.e. for sensitive and classified information, cloud services are not an option, judging from analysis of the emerging practice in the U.S., the UK, Canada and Australia. What we will increasingly see is IT-outsourcing that is labelled “cloud” despite not meeting the specifications of a true cloud service. Some governments are more inclined to introduce dedicated private “clouds” that are not fully scalable, in other words central data centres. For a vast number of countries, including developing ones, the options are further limited because there is no local cloud infrastructure and/or the public sector cannot afford to contract a dedicated government cloud. In this situation I could imagine an increasing reliance on transnational cloud services, with all the attendant pros and cons.

Ed: How do these sovereignty / jurisdiction / data protection questions relate to the revelations around the NSA’s PRISM surveillance programme?

Kristina: It only confirms that disclosure authorities are extensively used for intelligence gathering and that legal risks have to be taken as seriously as technical vulnerabilities. As a consequence of the Snowden revelations it is quite likely that the sensitivity of governments (as well as private sector organizations) to the impact of foreign jurisdictions will become even more pronounced. For example, there are reports estimating that the lack of trust in US-based cloud services is bound to affect the industry’s growth.

Ed: Could this usher in a whole new industry of ‘guaranteed’ national clouds..? ie how is the industry responding to these worries?

Kristina: This is already happening; in particular, European and Asian players are being very vocal in terms of marketing their regional or national cloud offerings as compatible with specific jurisdiction or national data protection frameworks.

Ed: And finally, who do you think is driving the debate about sovereignty and cloud services: government or industry?

Kristina: In the Western world it is government with its special security needs and buying power to which industry is responsive. As a nascent technology cloud services nonetheless thrive on business with governments because it opens new markets where previously in-house IT services dominated in the public sector.

Read the full paper: Kristina Irion (2013) Government Cloud Computing and National Data Sovereignty. Policy and Internet 4 (3/4) 40–71.

Kristina Irion was talking to blog editor David Sutcliffe.

Ed: How easy is it to request or scrape data from the “Chinese Web”? And how much of it is under some form of government control?

Han-Teng: Access to data from the Chinese Web, like other Web data, depends on the policies of platforms, the level of data openness, and the availability of data intermediary and tools. All these factors have direct impacts on the quality and usability of data. Since there are many forms of government control and intentions, increasingly not just the websites inside mainland China under Chinese jurisdiction, but also the Chinese “soft power” institutions and individuals telling the “Chinese story” or “Chinese dream” (as opposed to “American dreams”), it requires case-by-case research to determine the extent and level of government control and interventions. Based on my own research on Chinese user-generated encyclopaedias and Chinese-language twitter and Weibo, the research expectations seem to be that control and intervention by Beijing will be most likely on political and cultural topics, not likely on economic or entertainment ones.

This observation is linked to how various forms of government control and interventions are executed, which often requires massive data and human operations to filter, categorise and produce content that are often based on keywords. It is particularly true for Chinese websites in mainland China (behind the Great Firewall, excluding Hong Kong and Macao), where private website companies execute these day-to-day operations under the directives and memos of various Chinese party and government agencies.

Of course there is some extra layer of challenges if researchers try to request content and traffic data from the major Chinese websites for research, especially regarding censorship. Nonetheless, since most Web content data is open, researchers such as Professor Fu in Hong Kong University manage to scrape data sample from Weibo, helping researchers like me to access the data more easily. These openly collected data can then be used to measure potential government control, as has been done for previous research on search engines (Jiang and Akhtar 2011; Zhu et al. 2011) and social media (Bamman et al. 2012; Fu et al. 2013; Fu and Chau 2013; King et al. 2012; Zhu et al. 2012).

It follows that the availability of data intermediary and tools will become important for both academic and corporate research. Many new “public opinion monitoring” companies compete to provide better tools and datasets as data intermediaries, including the Online Public Opinion Monitoring and Measuring Unit (人民网舆情监测室) of the People’s Net (a Party press organ) with annual revenue near 200 million RMB. Hence, in addition to the on-going considerations on big data and Web data research, we need to factor in how these private and public Web data intermediaries shape the Chinese Web data environment (Liao et al. 2013).

Given the fact that the government’s control of information on the Chinese Web involves not only the marginalization (as opposed to the traditional censorship) of “unwanted” messages and information, but also the prioritisation of propaganda or pro-government messages (including those made by paid commentators and “robots”), I would add that the new challenges for researchers include the detection of paid (and sometimes robot-generated) comments. Although these challenges are not exactly the same as data access, researchers need to consider them for data collection.

Ed: How much of the content and traffic is identifiable or geolocatable by region (eg mainland vs Hong Kong, Taiwan, abroad)?

Han-Teng: Identifying geographic information from Chinese Web data, like other Web data, can be largely done by geo-IP (a straightforward IP to geographic location mapping service), domain names (.cn for China; .hk for Hong Kong; .tw for Taiwan), and language preferences (simplified Chinese used by mainland Chinese users; traditional Chinese used by Hong Kong and Taiwan). Again, like the question of data access, the availability and quality of such geographic and linguistic information depends on the policies, openness, and the availability of data intermediary and tools.

Nonetheless, there exist research efforts on using geographic and/or linguistic information of Chinese Web data to assess the level and extent of convergence and separation of Chinese information and users around the world (Etling et al. 2009; Liao 2008; Taneja and Wu 2013). Etling and colleagues (2009) concluded their mapping of Chinese blogsphere research with the interpretation of five “attentive spaces” roughly corresponding to five clusters or zones in the network map: on one side, two clusters of “Pro-state” and “Business” bloggers, and on the other, two clusters of “Overseas” bloggers (including Hong Kong and Taiwan) and “Culture”. Situated between the three clusters of “Pro-state”, “Overseas” and “Culture” (and thus at the centre of the network map) is the remaining cluster they call the “critical discourse” cluster, which is at the intersection of the two sides (albeit more on the “blocked” side of the Great Firewall).

I myself found distinct geographic focus and linguistic preferences between the online citations in Baidu Baike and Chinese Wikipedia (Liao 2008). Other research based on a sample of traffic data shows the existence of a “Chinese” cluster as an instance of a “culturally defined market”, regardless of their geographic and linguistic differences (Taneja and Wu 2013). Although I found their argument that the Great Firewall has very limited impacts on such a single “Chinese” cluster, they demonstrate the possibility of extracting geographic and linguistic information on Chinese Web data for better understanding the dynamics of Chinese online interactions; which are by no means limited within China or behind the Great Firewall.

Ed: In terms of online monitoring of public opinion, is it possible to identify robots / “50 cent party” — that is, what proportion of the “opinion” actually has a government source?

Han-Teng: There exist research efforts in identifying robot comments by analysing the patterns and content of comments, and their profile relationship with other accounts. It is more difficult to prove the direct footprint of government sources. Nonetheless, if researchers take another approach such as narrative analysis for well-defined propaganda research (such as the pro- and anti-Falun opinions), it might be easier to categorise and visualise the dynamics and then trace back to the origins of dominant keywords and narratives to identify the sources of loud messages. I personally think such research and analytical efforts require deep knowledge on both technical and cultural-political understanding of Chinese Web data, preferably with an integrated mixed method research design that incorporates both the quantitative and qualitative methods required for the data question at hand.

Ed: In terms of censorship, ISPs operate within explicit governmental guidelines; do the public (who contribute content) also have explicit rules about what topics and content are ‘acceptable’, or do they have to work it out by seeing what gets deleted?

Han-Teng: As a general rule, online censorship works better when individual contributors are isolated. Most of the time, contributors experience technical difficulties when using Beijing’s unwanted keywords or undesired websites, triggering self-censorship behaviours to avoid such difficulties. I personally believe such tacit learning serves as the most relevant psychological and behaviour mechanism (rather than explicit rules). In a sense, the power of censorship and political discipline is the fact that the real rules of engagement are never explicit to users, thereby giving more power to technocrats to exercise power in a more arbitrary fashion. I would describe the general situation as follows. Directives are given to both ISPs and ICPs about certain “hot terms”, some dynamic and some constant. Users “learn” them through encountering various forms of “technical difficulties”. Thus, while ISPs and ICPs may not enforce the same directives in the same fashion (some overshoot while others undershoot), the general tacit knowledge about the “red line” is thus delivered.

Nevertheless, there are some efforts where users do share their experiences with one another, so that they have a social understanding of what information and which category of users is being disciplined. There are also constant efforts outside mainland China, especially institutions in Hong Kong and Berkeley to monitor what is being deleted. However, given the fact that data is abundant for Chinese users, I have become more worried about the phenomenon of “marginalization of information and/or narratives”. It should be noted that censorship or deletion is just one of the tools of propaganda technocrats and that the Chinese Communist Party has had its share of historical lessons (and also victories) against its past opponents, such as the Chinese Nationalist Party and the United States during the Chinese Civil War and the Cold War. I strongly believe that as researchers we need better concepts and tools to assess the dynamics of information marginalization and prioritisation, treating censorship and data deletion as one mechanism of information marginalization in the age of data abundance and limited attention.

Ed: Has anyone tried to produce a map of censorship: ie mapping absence of discussion? For a researcher wanting to do this, how would they get hold of the deleted content?

Han-Teng: Mapping censorship has been done through experiment (MacKinnon 2008; Zhu et al. 2011) and by contrasting datasets (Fu et al. 2013; Liao 2013; Zhu et al. 2012). Here the availability of data intermediaries such as the WeiboScope in Hong Kong University, and unblocked alternative such as Chinese Wikipedia, serve as direct and indirect points of comparison to see what is being or most likely to be deleted. As I am more interested in mapping information marginalization (as opposed to prioritisation), I would say that we need more analytical and visualisation tools to map out the different levels and extent of information censorship and marginalization. The research challenges then shift to the questions of how and why certain content has been deleted inside mainland China, and thus kept or leaked outside China. As we begin to realise that the censorship regime can still achieve its desired political effects by voicing down the undesired messages and voicing up the desired ones, researchers do not necessarily have to get hold of the deleted content from the websites inside mainland China. They can simply reuse plenty of Chinese Web data available outside the censorship and filtering regime to undertake experiments or comparative study.

Ed: What other questions are people trying to explore or answer with data from the “Chinese Web”? And what are the difficulties? For instance, are there enough tools available for academics wanting to process Chinese text?

Han-Teng: As Chinese societies (including mainland China, Hong Kong, Taiwan and other overseas diaspora communities) go digital and networked, it’s only a matter of time before Chinese Web data becomes the equivalent of English Web data. However, there are challenges in processing Chinese language texts, although several of the major challenges become manageable as digital and network tools go multilingual. In fact, Chinese-language users and technologies have been the major goal and actors for a multi-lingual Internet (Liao 2009a,b). While there is technical progress in basic tools, we as Chinese Internet researchers still lack data and tool intermediaries that are designed to process Chinese texts smoothly. For instance, many analytical software and tools depend on or require the use of space characters as word boundaries, a condition that does not apply to Chinese texts.

In addition, since there exist some technical and interpretative challenges in analysing Chinese text datasets with mixed scripts (e.g. simplified and traditional Chinese) or with other foreign languages. Mandarin Chinese language is not the only language inside China; there are indications that the Cantonese and Shanghainese languages have a significant presence. Minority languages such as Tibetan, Mongolian, Uyghur, etc. are also still used by official Chinese websites to demonstrate the cultural inclusiveness of the Chinese authorities. Chinese official and semi-official diplomatic organs have also tried to tell “Chinese stories” in various of the world’s major languages, sometimes in direct competition with its political opponents such as Falun Gong.

These areas of the “Chinese Web” data remain unexplored territory for systematic research, which will require more tools and methods that are similar to the toolkits of multi-lingual Internet researchers. Hence I would say the basic data and tool challenges are not particular to the “Chinese Web”, but are rather a general challenge to the “Web” that is becoming increasingly multilingual by the day. We Chinese Internet researchers do need more collaboration when it comes to sharing data and tools, and I am hopeful that we will have more trustworthy and independent data intermediaries, such as Weiboscope and others, for a better future of the Chinese Web data ecology.

References

Bamman, D., O’Connor, B., & Smith, N. (2012). Censorship and deletion practices in Chinese social media. First Monday, 17(3-5).

Etling, B., Kelly, J., & Faris, R. (2009). Mapping Chinese Blogosphere. In 7th Annual Chinese Internet Research Conference (CIRC 2009). Annenberg School for Communication, University of Pennsylvania, Philadelphia, US.

Fu, K., Chan, C., & Chau, M. (2013). Assessing Censorship on Microblogs in China: Discriminatory Keyword Analysis and Impact Evaluation of the “Real Name Registration” Policy. IEEE Internet Computing, 17(3), 42–50.

Fu, K., & Chau, M. (2013). Reality Check for the Chinese Microblog Space: a random sampling approach. PLOS ONE, 8(3), e58356.

Jiang, M., & Akhtar, A. (2011). Peer into the Black Box of Chinese Search Engines: A Comparative Study of Baidu, Google, and Goso. Presented at the The 9th Chinese Internet Research Conference (CIRC 2011), Washington, D.C.: Institute for the Study of Diplomacy. Georgetown University.

King, G., Pan, J., & Roberts, M. (2012). How censorship in China allows government criticism but silences collective expression. In APSA 2012 Annual Meeting Paper.

Liao, H.-T. (2008). A webometric comparison of Chinese Wikipedia and Baidu Baike and its implications for understanding the Chinese-speaking Internet. In 9th annual Internet Research Conference: Rethinking Community, Rethinking Place. Copenhagen.

Liao, H.-T. (2009a). Are Chinese characters not modern enough? An essay on their role online. GLIMPSE: the art + science of seeing, 2(1), 16–24.

Liao, H.-T. (2009b). Conflict and Consensus in the Chinese version of Wikipedia. IEEE Technology and Society Magazine, 28(2), 49–56. doi:10.1109/MTS.2009.932799

Liao, H.-T. (2013, August 5). How do Baidu Baike and Chinese Wikipedia filter contribution? A case study of network gatekeeping. To be presented at the Wikisym 2013: The Joint International Symposium on Open Collaboration, Hong Kong.

Liao, H.-T., Fu, K., Jiang, M., & Wang, N. (2013, June 15). Chinese Web Data: Definition, Uses, and Scholarship. (Accepted). To be presented at the 11th Annual Chinese Internet Research Conference (CIRC 2013), Oxford, UK.

MacKinnon, R. (2008). Flatter world and thicker walls? Blogs, censorship and civic discourse in China. Public Choice, 134(1), 31–46. doi:10.1007/s11127-007-9199-0

Taneja, H., & Wu, A. X. (2013). How Does the Great Firewall of China Affect Online User Behavior? Isolated “Internets” as Culturally Defined Markets on the WWW. Presented at the 11th Annual Chinese Internet Research Conference (CIRC 2013), Oxford, UK.

Zhu, T., Bronk, C., & Wallach, D. S. (2011). An Analysis of Chinese Search Engine Filtering. arXiv:1107.3794.

Zhu, T., Phipps, D., Pridgen, A., Crandall, J. R., & Wallach, D. S. (2012). Tracking and Quantifying Censorship on a Chinese Microblogging Site. arXiv:1211.6166.

Han-Teng was talking to blog editor David Sutcliffe.

Han-Teng Liao is an OII DPhil student whose research aims to reconsider the role of keywords (as in understanding “keyword advertising” using knowledge from sociolinguistics and information science) and hyperlinks (webometrics) in shaping the sense of “fellow users” in digital networked environments. Specifically, his DPhil project is a comparative study of two major user-contributed Chinese encyclopedias, Chinese Wikipedia and Baidu Baike.

Blogs are becoming increasingly important for agenda setting and formation of collective public opinion on a wide range of issues. In countries like Russia where the Internet is not technically filtered, but where the traditional media is tightly controlled by the state, they may be particularly important. The Russian language blogosphere counts about 85 million blogs – an amount far beyond the capacities of any government to control – and the Russian search engine Yandex, with its blog rating service, serves as an important reference point for Russia’s educated public in its search of authoritative and independent sources of information. The blogosphere is thereby able to function as a mass medium of “public opinion” and also to exercise influence.

One topic that was particularly salient over the period we studied concerned the Russian Parliamentary elections of December 2011. Widely reported as fraudulent, they provoked immediate and mass street protest action by tens of thousands of people in Moscow and cities and towns across Russia, as well as corresponding activity in the blogosphere. Protesters made effective use of the Internet to organize a movement that demanded cancellation of the parliamentary election results, and the holding of new and fair elections. These protests continued until the following summer, gaining widespread national and international attention.

Most of the political and social discussion blogged in Russia is hosted on the blog platform LiveJournal. Some of these bloggers can claim a certain amount of influence; the top thirty bloggers have over 20,000 “friends” each, representing a good circulation for the average Russian newspaper. Part of the blogosphere may thereby resemble the traditional media; the deeper into the long tail of average bloggers, however, the more it functions as more as pure public opinion. This “top list” effect may be particularly important in societies (like Russia’s) where popularity lists exert a visible influence on bloggers’ competitive behavior and on public perceptions of their significance. Given the influence of these top bloggers, it may be claimed that, like the traditional media, they act as filters of issues to be thought about, and as definers of their relative importance and salience.

Gauging public opinion is of obvious interest to governments and politicians, and opinion polls are widely used to do this, but they have been consistently criticized for the imposition of agendas on respondents by pollsters, producing artefacts. Indeed, the public opinion literature has tended to regard opinion as something to be “extracted” by pollsters, which inevitably pre-structures the output. This literature doesn’t consider that public opinion might also exist in the form of natural language texts, such as blog posts, that have not been pre-structured by external observers.

There are two basic ways to detect topics in natural language texts: the first is manual coding of texts (ie by traditional content analysis), and the other involves rapidly developing techniques of automatic topic modeling or text clustering. The media studies literature has relied heavily on traditional content analysis; however, these studies are inevitably limited by the volume of data a person can physically process, given there may be hundreds of issues and opinions to track — LiveJournal’s 2.8 million blog accounts, for example, generate 90,000 posts daily.

For large text collections, therefore, only the second approach is feasible. In our article we explored how methods for topic modeling developed in computer science may be applied to social science questions – such as how to efficiently track public opinion on particular (and evolving) issues across entire populations. Specifically, we demonstrate how automated topic modeling can identify public agendas, their composition, structure, the relative salience of different topics, and their evolution over time without prior knowledge of the issues being discussed and written about. This automated “discovery” of issues in texts involves division of texts into topically — or more precisely, lexically — similar groups that can later be interpreted and labeled by researchers. Although this approach has limitations in tackling subtle meanings and links, experiments where automated results have been checked against human coding show over 90 percent accuracy.

The computer science literature is flooded with methodological papers on automatic analysis of big textual data. While these methods can’t entirely replace manual work with texts, they can help reduce it to the most meaningful and representative areas of the textual space they help to map, and are the only means to monitor agendas and attitudes across multiple sources, over long periods and at scale. They can also help solve problems of insufficient and biased sampling, when entire populations become available for analysis. Due to their recentness, as well as their mathematical and computational complexity, these approaches are rarely applied by social scientists, and to our knowledge, topic modeling has not previously been applied for the extraction of agendas from blogs in any social science research.

The natural extension of automated topic or issue extraction involves sentiment mining and analysis; as Gonzalez-Bailon, Kaltenbrunner, and Banches (2012) have pointed out, public opinion doesn’t just involve specific issues, but also encompasses the state of public emotion about these issues, including attitudes and preferences. This involves extracting opinions on the issues/agendas that are thought to be present in the texts, usually by dividing sentences into positive and negative. These techniques are based on human-coded dictionaries of emotive words, on algorithmic construction of sentiment dictionaries, or on machine learning techniques.

Both topic modeling and sentiment analysis techniques are required to effectively monitor self-generated public opinion. When methods for tracking attitudes complement methods to build topic structures, a rich and powerful map of self-generated public opinion can be drawn. Of course this mapping can’t completely replace opinion polls; rather, it’s a new way of learning what people are thinking and talking about; a method that makes the vast amounts of user-generated content about society – such as the 65 million blogs that make up the Russian blogosphere — available for social and policy analysis.

Naturally, this approach to public opinion and attitudes is not free of limitations. First, the dataset is only representative of the self-selected population of those who have authored the texts, not of the whole population. Second, like regular polled public opinion, online public opinion only covers those attitudes that bloggers are willing to share in public. Furthermore, there is still a long way to go before the relevant instruments become mature, and this will demand the efforts of the whole research community: computer scientists and social scientists alike.

Read the full paper: Olessia Koltsova and Sergei Koltcov (2013) Mapping the public agenda with topic modeling: The case of the Russian livejournal. Policy and Internet 5 (2) 207–227.

Also read on this blog: Can text mining help handle the data deluge in public policy analysis? by Aude Bicquelet.

References

González-Bailón, S., A. Kaltenbrunner, and R.E. Banches. 2012. “Emotions, Public Opinion and U.S. Presidential Approval Rates: A 5 Year Analysis of Online Political Discussions,” Human Communication Research 38 (2): 121–43.

What follows are those impressions that relate to public policy and the internet, and reflect only my own experience there. Outside the official programme there are whole hierarchies of breakfasts, lunches, dinners and other events, most of which a newcomer to Davos finds it difficult to discover and some of which require one to be at least a president of a small to medium-sized state — or Matt Damon.

There was much talk of hyperconnectivity, spirals of innovation, S-curves and exponential growth of technological diffusion, digitalization and disruption. As you might expect, the pace of these was emphasized most by those participants from the technology industry. The future of work in the face of leaps forward in robotics was a key theme, drawing on the new book by Eric Brynjolfsson and Andrew McAfee, The Second Machine Age: Work, Progress and Prosperity in a Time of Brilliant Technologies, which is just out in the US. There were several sessions on digital health and the eventual fruition of decades of pilots in telehealth (a banned term now, apparently), as applications based on mobile technologies start to be used more widely. Indeed, all delegates were presented with a ‘Jawbone’ bracelet which tracks the wearer’s exercise and sleep patterns (7,801 steps so far today). And of course there was much talk about the possibilities afforded by big data, if not quite as much as I expected.

The University of Oxford was represented in an ‘Ideas Lab’, convened by the Oxford Martin School on Data, Machines and the Human Factor. This format involves each presenter talking for five minutes in front of their 15 selected images rolling at 20 seconds each, with no control over the timing (described by the designer of the format before the session as ‘waterboarding for academics’, due to the conciseness and brevity required — and I can vouch for that). It was striking how much synergy there was in the presentations by the health engineer Lionel Tarassenko (talking about developments in digital healthcare in the home), the astrophysicist Chris Lintott (on crowdsourcing of science) and myself talking about collective action and mobilization in the social media age. We were all talking about the new possibilities that the internet and social media afford for citizens to contribute to healthcare, scientific knowledge and political change. Indeed, I was surprised that the topics of collective action and civic engagement, probably not traditional concerns of Davos, attracted widespread interest, including a session on ‘The New Citizen’ with the founders of Avaaz.

Of course there was some discussion of the Snowden revelations of the data crawling activities of the US NSA and UK GCHQ, and the privacy implications. A dinner on ‘the Digital Me’ generated an interesting discussion on privacy in the age of social media, reflecting a growing and welcome (to me anyway) pragmatism with respect to issues often hotly contested. As one participant put it, in an age of imperfect, partial information, we become used to the idea that what we read on Facebook is often, through its relation to the past, irrelevant to the present time and not to be taken into consideration when (for example) considering whether to offer someone a job. The wonderful danah boyd gave some insight from her new book It’s Complicated: the social lives of networked teens, from which emerged a discussion of a ‘taxonomy of privacy’ and the importance of considering the use to which data is put, as opposed to just the possession or collection of the data – although this could be dangerous ground, in the light of the Snowden revelations.

There was more talk of the future than the past. I participated in one dinner discussion of the topic of ‘Rethinking Living’ in 50 years time, a timespan challenged by Google Chairman Eric Schmidt’s argument earlier in the day that five years was an ‘infinite’ amount of time in the current speed of technological innovation. The after dinner discussion was surprisingly fun, and at my table at least we found ourselves drawn back to the past, wondering if the rise of preventative health care and the new localism that connectivity affords might look like a return to the pre-industrial age. When it came to the summing up and drawing out the implications for government, I was struck how most elements of any trajectory of change exposed a growing disconnect between citizens, or business, on the one hand – and government on the other.

This was the one topic that for me was notably absent from WEF 2014; the nature of government in this rapidly changing world, in spite of the three pillars — politics, society, and business — of the theme of the conference noted above. At one lunch convened by McKinsey that was particularly ebullient regarding the ceaseless pace of technological change, I pointed out that government was only at the beginning of the S-curve, or perhaps that such a curve had no relevance for government. Another delegate asked how the assembled audience might help government to manage better here, and another pointed out that globally, we were investing less and less in government at a time when it needed more resources, including far higher remuneration for top officials. But the panellists were less enthusiastic to pick up on these points.

As I have discussed previously on this blog and elsewhere, we are in an era where governments struggle to innovate technologically or to incorporate social media into organizational processes, where digital services lag far behind those of business, where the big data revolution is passing government by (apart from open data, which is not the same thing as big data, see my Guardian blog post on this issue). Pockets of innovation like the UK Government Digital Service push for governmentwide change, but we are still seeing major policy initiatives such as Obama’s healthcare plans in the US or Universal Credit in the UK flounder on technological grounds. Yet there were remarkably few delegates at the WEF representing the executive arm of government, particularly for the UK. So on the relationship between government and citizens in an age of rapid technological change, it was citizens – rather than governments – and, of course, business (given the predominance of CEOs) that received the attention of this high-powered crowd.

At the end of the ‘Rethinking Living’ dinner, a participant from another table said to me that in contrast to the participants from the technology industry, he thought 50 years was a rather short time horizon. As a landscape architect, designing with trees that take 30 years to grow, he had no problem imagining how things would look on this timescale. It occurred to me that there could be an analogy here with government, which likewise could take this kind of timescale to catch up with the technological revolution. But by that time, technology will have moved on and it may be that governments cannot afford this relaxed pace catching up with their citizens and the business world. Perhaps this should be a key theme for future forums.

Helen Margetts is the Director of the OII, and Professor of Society and the Internet. She is a political scientist specialising in digital era governance and politics.

Taha: Yes we did … actually, we have shown that controversy measures based on “controversial” flags are not inclusive at all and although they might have high precision, they have very low recall. Instead, we constructed an automated algorithm to locate and quantify the editorial wars taking place on the Wikipedia platform. Our algorithm is based on reversions, i.e. when editors undo each other’s contributions. We focused specifically on mutual reverts between pairs of editors and we assigned a maturity score to each editor, based on the total volume of their previous contributions. While counting the mutual reverts, we used more weight for those ones committed by/on editors with higher maturity scores; as a revert between two experienced editors indicates a more serious problem. We always validated our method and compared it with other methods, using human judgement on a random selection of articles.

Ed: Was there any discrepancy between the content deemed controversial by your own quantitative measure, and what the editors themselves had flagged?

Taha: We were able to capture all the flagged content, but not all the articles found to be controversial by our method are flagged. And when you check the editorial history of those articles, you soon realise that they are indeed controversial but for some reason have not been flagged. It’s worth mentioning that the flagging process is not very well implemented in smaller language editions of Wikipedia. Even if the controversy is detected and flagged in English Wikipedia, it might not be in the smaller language editions. Our model is of course independent of the size and editorial conventions of different language editions.

Ed: Were there any differences in the way conflicts arose / were resolved in the different language versions?

Taha: We found the main differences to be the topics of controversial articles. Although some topics are globally debated, like religion and politics, there are many topics which are controversial only in a single language edition. This reflects the local preferences and importances assigned to topics by different editorial communities. And then the way editorial wars initiate and more importantly fade to consensus is also different in different language editions. In some languages moderators interfere very soon, while in others the war might go on for a long time without any moderation.

Ed: In general, what were the most controversial topics in each language? And overall?

Taha: Generally, religion, politics, and geographical places like countries and cities (sometimes even villages) are the topics of debates. But each language edition has also its own focus, for example football in Spanish and Portuguese, animations and TV series in Chinese and Japanese, sex and gender-related topics in Czech, and Science and Technology related topics in French Wikipedia are very often behind editing wars.

Ed: What other quantitative studies of this sort of conflict -ie over knowledge and points of view- are there?

Taha: My favourite work is one by researchers from Barcelona Media Lab. In their paper Jointly They Edit: Examining the Impact of Community Identification on Political Interaction in Wikipedia they provide quantitative evidence that editors interested in political topics identify themselves more significantly as Wikipedians than as political activists, even though they try hard to reflect their opinions and political orientations in the articles they contribute to. And I think that’s the key issue here. While there are lots of debates and editorial wars between editors, at the end what really counts for most of them is Wikipedia as a whole project, and the concept of shared knowledge. It might explain how Wikipedia really works despite all the diversity among its editors.

Ed: How would you like to extend this work?

Taha: Of course some of the controversial topics change over time. While Jesus might stay a controversial figure for a long time, I’m sure the article on President (W) Bush will soon reach a consensus and most likely disappear from the list of the most controversial articles. In the current study we examined the aggregated data from the inception of each Wikipedia-edition up to March 2010. One possible extension that we are working on now is to study the dynamics of these controversy-lists and the positions of topics in them.

Read the full paper: Yasseri, T., Spoerri, A., Graham, M. and Kertész, J. (2014) The most controversial topics in Wikipedia: A multilingual and geographical analysis. In: P.Fichman and N.Hara (eds) Global Wikipedia: International and cross-cultural issues in online collaboration. Scarecrow Press.

Taha was talking to blog editor David Sutcliffe.

Taha Yasseri is the Big Data Research Officer at the OII. Prior to coming to the OII, he spent two years as a Postdoctoral Researcher at the Budapest University of Technology and Economics, working on the socio-physical aspects of the community of Wikipedia editors, focusing on conflict and editorial wars, along with Big Data analysis to understand human dynamics, language complexity, and popularity spread. He has interests in analysis of Big Data to understand human dynamics, government-society interactions, mass collaboration, and opinion dynamics.

Taha: The socially generated transactional data that we call “big data” have been available only very recently; the amount of data we now produce about human activities in a year is comparable to the amount that used to be produced in decades (or centuries). And this is all due to recent advancements in ICTs. Despite the short period of availability of big data, the use of them in different sectors including academia and business has been significant. However, in many cases, the use of big data is limited to monitoring and post hoc analysis of different patterns. Predictive models have been rarely used in combination with big data. Nevertheless, there are very interesting examples of using big data to make predictions about disease outbreaks, financial moves in the markets, social interactions based on human mobility patterns, election results, etc.

Ed: What were the advantages of using Wikipedia as a data source for your study — as opposed to Twitter, blogs, Facebook or traditional media, etc.?

Taha: Our results have shown that the predictive power of Wikipedia page view and edit data outperforms similar box office-prediction models based on Twitter data. This can partially be explained by considering the different nature of Wikipedia compared to social media sites. Wikipedia is now the number one source of online information, and Wikipedia article page view statistics show how much Internet users have been interested in knowing about a specific movie. And the edit counts — even more importantly — indicate the level of interest of the editors in sharing their knowledge about the movies with others. Both indicators are much stronger than what you could measure on Twitter, which is mainly the reaction of the users after watching or reading about the movie. The cost of participation in Wikipedia’s editorial process makes the activity data more revealing about the potential popularity of the movies.

Another advantage is the sheer availability of Wikipedia data. Twitter streams, by comparison, are limited in both size and time. Gathering Facebook data is also problematic, whereas all the Wikipedia editorial activities and page views are recorded in full detail — and made publicly available.

Ed: Could you briefly describe your method and model?

Taha: We retrieved two sets of data from Wikipedia, the editorial activity and the page views relating to our set of 312 movies. The former indicates the popularity of the movie among the Wikipedia editors and the latter among Wikipedia readers. We then defined different measures based on these two data streams (eg number of edits, number of unique editors, etc.) In the next step we combined these data into a linear model that assumes the more popular the movie is, the larger the size of these parameters. However this model needs both training and calibration. We calibrated the model based on the IMBD data on the financial success of a set of ‘training’ movies. After calibration, we applied the model to a set of “test” movies and (luckily) saw that the model worked very well in predicting the financial success of the test movies.

Ed: What were the most significant variables in terms of predictive power; and did you use any content or sentiment analysis?

Taha: The nice thing about this method is that you don’t need to perform any content or sentiment analysis. We deal only with volumes of activities and their evolution over time. The parameter that correlated best with financial success (and which was therefore the best predictor) was the number of page views. I can easily imagine that these days if someone wants to go to watch a movie, they most likely turn to the Internet and make a quick search. Thanks to Google, Wikipedia is going to be among the top results and it’s very likely that the click will go to the Wikipedia article about the movie. I think that’s why the page views correlate to the box office takings so significantly.

Ed: Presumably people are picking up on signals, ie Wikipedia is acting like an aggregator and normaliser of disparate environmental signals — what do you think these signals might be, in terms of box office success? ie is it ultimately driven by the studio media machine?

Taha: This is a very difficult question to answer. There are numerous factors that make a movie (or a product in general) popular. Studio marketing strategies definitely play an important role, but the quality of the movie, the collective mood of the public, herding effects, and many other hidden variables are involved as well. I hope our research serves as a first step in studying popularity in a quantitative framework, letting us answer such questions. To fully understand a system the first thing you need is a tool to monitor and observe it very well quantitatively. In this research we have shown that (for example) Wikipedia is a nice window and useful tool to observe and measure popularity and its dynamics; hopefully leading to a deep understanding of the underlying mechanisms as well.

Ed: Is there similar work / approaches to what you have done in this study?

Taha: There have been other projects using socially generated data to make predictions on the popularity of movies or movement in financial markets, however to the best of my knowledge, it’s been the first time that Wikipedia data have been used to feed the models. We were positively surprised when we observed that these data have stronger predictive power than previously examined datasets.

Ed: If you have essentially shown that ‘interest on Wikipedia’ tracks ‘real-world interest’ (ie box office receipts), can this be applied to other things? eg attention to legislation, political scandal, environmental issues, humanitarian issues: ie Wikipedia as “public opinion monitor”?

Taha: I think so. Now I’m running two other projects using a similar approach; one to predict election outcomes and the other one to do opinion mining about the new policies implemented by governing bodies. In the case of elections, we have observed very strong correlations between changes in the information seeking rates of the general public and the number of ballots cast. And in the case of new policies, I think Wikipedia could be of great help in understanding the level of public interest in searching for accurate information about the policies, and how this interest is satisfied by the information provided online. And more interestingly, how this changes overtime as the new policy is fully implemented.

Ed: Do you think there are / will be practical applications of using social media platforms for prediction, or is the data too variable?

Taha: Although the availability and popularity of social media are recent phenomena, I’m sure that social media data are already being used by different bodies for predictions in various areas. We have seen very nice examples of using these data to predict disease outbreaks or the arrival of earthquake waves. The future of this field is very promising, considering both the advancements in the methodologies and also the increase in popularity and use of social media worldwide.

Ed: How practical would it be to generate real-time processing of this data — rather than analysing databases post hoc?

Taha: Data collection and analysis could be done instantly. However the challenge would be the calibration. Human societies and social systems — similarly to most complex systems — are non-stationary. That means any statistical property of the system is subject to abrupt and dramatic changes. That makes it a bit challenging to use a stationary model to describe a continuously changing system. However, one could use a class of adaptive models or Bayesian models which could modify themselves as the system evolves and more data are available. All these could be done in real time, and that’s the exciting part of the method.

Ed: As a physicist; what are you learning in a social science department? And what does physicist bring to social science and the study of human systems?

Taha: Looking at complicated phenomena in a simple way is the art of physics. As Einstein said, a physicist always tries to “make things as simple as possible, but not simpler”. And that works very well in describing natural phenomena, ranging from sub-atomic interactions all the way to cosmology. However, studying social systems with the tools of natural sciences can be very challenging, and sometimes too much simplification makes it very difficult to understand the real underlying mechanisms. Working with social scientists, I’m learning a lot about the importance of the individual attributes (and variations between) the elements of the systems under study, outliers, self-awarenesses, ethical issues related to data, agency and self-adaptation, and many other details that are mostly overlooked when a physicist studies a social system.

At the same time, I try to contribute the methodological approaches and quantitative skills that physicists have gained during two centuries of studying complex systems. I think statistical physics is an amazing example where statistical techniques can be used to describe the macro-scale collective behaviour of billions and billions of atoms with a single formula. I should admit here that humans are way more complicated than atoms — but the dialogue between natural scientists and social scientists could eventually lead to multi-scale models which could help us to gain a quantitative understanding of social systems, thereby facilitating accurate predictions of social phenomena.

Ed: What database would you like access to, if you could access anything?

Taha: I have day dreams about the database of search queries from all the Internet users worldwide at the individual level. These data are being collected continuously by search engines and technically could be accessed, but due to privacy policy issues it’s impossible to get a hold on; even if only for research purposes. This is another difference between social systems and natural systems. An atom never gets upset being watched through a microscope all the time, but working on social systems and human-related data requires a lot of care with respect to privacy and ethics.

Read the full paper: Mestyán, M., Yasseri, T., and Kertész, J. (2013) Early Prediction of Movie Box Office Success based on Wikipedia Activity Big Data. PLoS ONE 8 (8) e71226.

Taha Yasseri was talking to blog editor David Sutcliffe.

Taha Yasseri is the Big Data Research Officer at the OII. Prior to coming to the OII, he spent two years as a Postdoctoral Researcher at the Budapest University of Technology and Economics, working on the socio-physical aspects of the community of Wikipedia editors, focusing on conflict and editorial wars, along with Big Data analysis to understand human dynamics, language complexity, and popularity spread. He has interests in analysis of Big Data to understand human dynamics, government-society interactions, mass collaboration, and opinion dynamics.

In ‘Code and Other Laws of Cyberspace’, Lawrence Lessig (2006) writes that computer code (or what he calls ‘West Coast code’) can have the same regulatory effect as the laws and legal code developed in Washington D.C., so-called ‘East Coast code’. Computer code impacts on a person’s behaviour by virtue of its essentially restrictive architecture: on some websites you must enter a password before you gain access, in other places you can enter unidentified. The problem with computer code, Lessig argues, is that it is invisible, and that it makes it easy to regulate people’s behaviour directly and often without recourse.

For example, fair use provisions in US copyright law enable certain uses of copyrighted works, such as copying for research or teaching purposes. However the architecture of many online publishing systems heavily regulates what one can do with an e-book: how many times it can be transferred to another device, how many times it can be printed, whether it can be moved to a different format – activities that have been unregulated until now, or that are enabled by the law but effectively ‘closed off’ by code. In this case code works to reshape behaviour, upsetting the balance between the rights of copyright holders and the rights of the public to access works to support values like education and innovation.

Working as an ethnographic researcher for Ushahidi, the non-profit technology company that makes tools for people to crowdsource crisis information, has made me acutely aware of the many ways in which ‘code’ can become ‘law’. During my time at Ushahidi, I studied the practices that people were using to verify reports by people affected by a variety of events – from earthquakes to elections, from floods to bomb blasts. I then compared these processes with those followed by Wikipedians when editing articles about breaking news events. In order to understand how to best design architecture to enable particular behaviour, it becomes important to understand how such behaviour actually occurs in practice.

In addition to the impact of code on the behaviour of users, norms, the market and laws also play a role. By interviewing both the users and designers of crowdsourcing tools I soon realized that ‘human’ verification, a process of checking whether a particular report meets a group’s truth standards, is an acutely social process. It involves negotiation between different narratives of what happened and why; identifying the sources of information and assessing their reputation among groups who are considered important users of that information; and identifying gatekeeping and fact checking processes where the source is a group or institution, amongst other factors.

One disjuncture between verification ‘practice’ and the architecture of the verification code developed by Ushahidi for users was that verification categories were set as a default feature, whereas some users of the platform wanted the verification process to be invisible to external users. Items would show up as being ‘unverified’ unless they had been explicitly marked as ‘verified’, thus confusing users about whether the item was unverified because the team hadn’t yet verified it, or whether it was unverified because it had been found to be inaccurate. Some user groups wanted to be able to turn off such features when they could not take responsibility for data verification. In the case of the Christchurch Recovery Map in the aftermath of the 2011 New Zealand earthquake, the government officials with whom volunteers who set up the Ushahidi instance were working wanted to be able to turn off such features because they were concerned that they could not ensure that reports were indeed verified and having the category show up (as ‘unverified’ until ‘verified’) implied that they were engaged in some kind of verification process.

The existence of a default verification category impacted on the Christchurch Recovery Map group’s ability to gain support from multiple stakeholders, including the government, but this feature of the platform’s architecture did not have the same effect in other places and at other times. For other users like the original Ushahidi Kenya team who worked to collate instances of violence after the Kenyan elections in 2007/08, this detailed verification workflow was essential to counter the misinformation and rumour that dogged those events. As Ushahidi’s use cases have diversified – from reporting death and damage during natural disasters to political events including elections, civil war and revolutions, the architecture of Ushahidi’s code base has needed to expand. Ushahidi has recognised that code plays a defining role in the experience of verification practices, but also that code’s impact will not be the same at all times, and in all circumstances. This is why it invested in research about user diversity in a bid to understand the contexts in which code runs, and how these contexts result in a variety of different impacts.

A key question being asked in the design of future verification mechanisms is the extent to which verification work should be done by humans or non-humans (machines). Here, verification is not a binary categorisation, but rather there is a spectrum between human and non-human verification work, and indeed, projects like Ushahidi, Wikipedia and Galaxy Zoo have all developed different verification mechanisms. Wikipedia uses a set of policies and practices about how content should be added and reviewed, such as the use of ‘citation needed’ tags for information that sounds controversial and that should be backed up by a reliable source. Galaxy Zoo uses an algorithm to detect whether certain contributions are accurate by comparing them to the same work by other volunteers.

Ushahidi leaves it up to individual deployers of their tools and platform to make decisions about verification policies and practices, and is going to be designing new defaults to accommodate this variety of use. In parallel, Veri.ly, a project by ex-Ushahidi Patrick Meier with organisations Masdar and QCRI is responding to the large amounts of unverified and often contradictory information that appears on social media following natural disasters by enabling social media users to collectively evaluate the credibility of rapidly crowdsourced evidence. The project was inspired by MIT’s winning entry to DARPA’s ‘Red Balloon Challenge’ which was intended to highlight social networking’s potential to solve widely distributed, time-sensitive problems, in this case by correctly identifying the GPS coordinates of 10 balloons suspended at fixed, undisclosed locations across the US. The winning MIT team crowdsourced the problem by using a monetary incentive structure, promising $2,000 to the first person who submitted the correct coordinates for a single balloon, $1,000 to the person who invited that person to the challenge; $500 to the person who invited the inviter, and so on. The system quickly took root, spawning geographically broad, dense branches of connections. After eight hours and 52 minutes, the MIT team identified the correct coordinates for all 10 balloons.