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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Ed: What persuasive technologies might we routinely meet online? And how are they designed to guide us towards certain decisions?

There’s a broad spectrum, from the very simple to the very complex. A simple example would be something like Amazon’s “one-click” purchase feature, which compresses the entire checkout process down to a split-second decision. This uses a persuasive technique known as “reduction” to minimise the perceived cost to a user of going through with a purchase, making it more likely that they’ll transact. At the more complex end of the spectrum, you have the whole set of systems and subsystems that is online advertising. As it becomes easier to measure people’s behaviour over time and across media, advertisers are increasingly able to customise messages to potential customers and guide them down the path toward a purchase.

It isn’t just commerce, though: mobile behavior-change apps have seen really vibrant growth in the past couple years. In particular, health and fitness: products like Nike+, Map My Run, and Fitbit let you monitor your exercise, share your performance with friends, use social motivation to help you define and reach your fitness goals, and so on. One interesting example I came across recently is called “Zombies, Run!” which motivates by fright, spawning virtual zombies to chase you down the street while you’re on your run.

As one final example, If you’ve ever tried to deactivate your Facebook account, you’ve probably seen a good example of social persuasive technology: the screen that comes up saying, “If you leave Facebook, these people will miss you” and then shows you pictures of your friends. Broadly speaking, most of the online services we think we’re using for “free” — that is, the ones we’re paying for with the currency of our attention — have some sort of persuasive design goal. And this can be particularly apparent when people are entering or exiting the system.

Ed: Advertising has been around for centuries, so we might assume that we have become clever about recognizing and negotiating it — what is it about these online persuasive technologies that poses new ethical questions or concerns?

The ethical questions themselves aren’t new, but the environment in which we’re asking them makes them much more urgent. There are several important trends here. For one, the Internet is becoming part of the background of human experience: devices are shrinking, proliferating, and becoming more persistent companions through life. In tandem with this, rapid advances in measurement and analytics are enabling us to more quickly optimise technologies to reach greater levels of persuasiveness. That persuasiveness is further augmented by applying knowledge of our non-rational psychological biases to technology design, which we are doing much more quickly than in the design of slower-moving systems such as law or ethics. Finally, 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”? When we call these types of technology “persuasive,” we’re implying that they shouldn’t cross the line into being coercive or manipulative. But it’s hard to say where that line is, especially when it comes to persuasion that plays on our non-rational biases and impulses. How persuasive is too persuasive? Again, this isn’t a new ethical question by any means, but it is more urgent than ever.

These technologies also remind us that the ethics of attention is just as important as the ethics of information. Many important conversations are taking place across society that deal with the tracking and measurement of user behaviour. But that information is valuable largely because it can be used to inform some sort of action, which is often persuasive in nature. But we don’t talk nearly as much about the ethics of the persuasive act as we do about the ethics of the data. If we did, we might decide, for instance, that some companies have a moral obligation to collect more of a certain type of user data because it’s the only way they could know if they were persuading a person to do something that was contrary to their well-being, values, or goals. Knowing a person better can be the basis not only for acting more wrongly toward them, but also more rightly.

As users, then, persuasive technologies require us to be more intentional about how we define and express our own goals. The more persuasion we encounter, the clearer we need to be about what it is we actually want. If you ask most people what their goals are, they’ll say things like “spending more time with family,” “being healthier,” “learning piano,” etc. But we don’t all accomplish the goals we have — we get distracted. The risk of persuasive technology is that we’ll have more temptations, more distractions. But its promise is that we can use it to motivate ourselves toward the things we find fulfilling. So I think what’s needed is more intentional and habitual reflection about what our own goals actually are. To me, the ultimate question in all this is how we can shape technology to support human goals, and not the other way around.

Ed: What if a persuasive design or technology is simply making it easier to do something we already want to do: isn’t this just ‘user centered design’? (ie a good thing?)

Yes, persuasive design can certainly help motivate a user toward their own goals. In these cases it generally resonates well with user-centered design. The tension really arises when the design leads users toward goals they don’t already have. User-centered design doesn’t really have a good way to address persuasive situations, where the goals of the user and the designer diverge.

To reconcile this tension, I think we’ll probably need to get much better at measuring people’s intentions and goals than we are now. Longer-term, we’ll probably need to rethink notions like “design” altogether. When it comes to online services, it’s already hard to talk about “products” and “users” as though they were distinct entities, and I think this will only get harder as we become increasingly enmeshed in an ongoing co-evolution.

Governments and corporations are increasingly interested in “data-driven” decision-making: isn’t that a good thing? Particularly if the technologies now exist to collect ‘big’ data about our online actions (if not intentions)?

I don’t think data ever really drives decisions. It can definitely provide an evidentiary basis, but any data is ultimately still defined and shaped by human goals and priorities. We too often forget that there’s no such thing as “pure” or “raw” data — that any measurement reflects, before anything else, evidence of attention.

That being said, data-based decisions are certainly preferable to arbitrary ones, provided that you’re giving attention to the right things. But data can’t tell you what those right things are. It can’t tell you what to care about. This point seems to be getting lost in a lot of the fervour about “big data,” which as far as I can tell is a way of marketing analytics and relational databases to people who are not familiar with them.

The psychology of that term, “big data,” is actually really interesting. On one hand, there’s a playful simplicity to the word “big” that suggests a kind of childlike awe where words fail. “How big is the universe? It’s really, really big.” It’s the unknown unknowns at scale, the sublime. On the other hand, there’s a physicality to the phrase that suggests an impulse to corral all our data into one place: to contain it, mould it, master it. Really, the term isn’t about data abundance at all – it reflects our grappling with a scarcity of attention.

The philosopher Luciano Floridi likens the “big data” question to being at a buffet where you can eat anything, but not everything. The challenge comes in the choosing. So how do you choose? Whether you’re a government, a corporation, or an individual, it’s your ultimate aims and values — your ethical priorities — that should ultimately guide your choosiness. In other words, the trick is to make sure you’re measuring what you value, rather than just valuing what you already measure.

James Williams is a doctoral student at the Oxford Internet Institute. 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.

James Williams was talking to blog editor Thain Simon.

As an introduction, it might be helpful to reflect on the French colonial concepts of l’Afrique utile and l’Afrique inutile (concepts most recently re-invoked by William Reno in 1999 and James Ferguson in 2005). L’Afrique utile, or usable Africa represented parts of Africa over which private actors felt they could exercise a degree of governance and control, and therefore extract profit. L’Afrique inutile, on the other hand, was the no-go area: places deemed too risky, too opaque and too wild for commercial profit. Until recently, it was difficult to convince multinationals to view Africa as usable and profitable because much economic activity took place in the unaccounted informal economy. With the exception of a few oil, gas and mineral installations and some export commodities like cocoa, cotton, tobacco, rubber, coffee, and tea, multinationals stayed out of the continent. Likewise, within the accounts of national public policy-making institutions, it was only the very narrow formal and recordable parts of the economy that were recorded. In a similar way that economists have traditionally excluded unpaid domestic labour from national accounts, most African states only scratched the surface of their populations’ true economic lives.

The mobile phone has undoubtedly changed the way private companies and public bodies view African economies. Firstly, the mobile phone has demonstrated that Africans can be voracious consumers at the bottom of the pyramid (paving the way for the distribution of other low-cost items such as soap, sanitary pads, soft drinks, etc.). While the colonial scramble for Africa focused on what lay in Africa’s lands and landscapes, the new scramble is focused on its people and markets (and workers; as the growing interest in business process outsourcing demonstrates).

Secondly, mobile phones (and other kinds of information and communication technologies) have created new channels of information about Africans and African markets, particularly in the informal sector. In an era where so much of the apparatus for measuring Africa’s economies has been weakened, this kind of data reaps enormous potential. One might say that the mobile phone and the internet have made former parts of l’Afrique inutile into l’Afrique utile — open for business, profit, analysis, and perhaps, control.

The ‘scramble for Africa’s data‘ is taking place within a particular historical trajectory of knowledge production. Africa has always been a laboratory for Western scientists and researchers, with local knowledge production often influenced by foreign powers and foreign ideas (think back to the early reliance on primary products for export, to which the entire colonial system of economic measurement and development planning was geared). Within the contemporary context of ever-expanding higher education and dwindling finances for local research, African academics and researchers have been forced to take on more and more consultancies and private contracts.

This ‘extraversion’ of African institutions of higher education has contributed to a re-orientation of the apparatus for academic research towards questions posed from outside. Within state bodies, similar processes are underway. Weakened by corruption, Structural Adjustment Policies (SAP), and pervasive informal economic activity, management of the economy has migrated from state institutions into the better paid offices of NGOs, consultancies and private companies. State capacity to measure and model is presently very weak, and African governments are therefore being encouraged to ‘open’ up their own records to non-state researchers. It is into this research context that big data emerges as a new source of ‘legibility’.

ICTs offer obvious benefits to economic researchers. They have often been heralded as offering potentially more democratic and participatory kinds of ‘legibility’. Their potential partly lies in the way that ICTs activate ‘social networks’ into infrastructures through which external actors can deliver and extract information. This ‘sociability’ makes them particularly suitable for studying informal economic networks. ICTs also offer the potential to modernise existing streams of data collection and broaden intra-institutional coordination, leading to better collaboration and more targeted public policy. In our project on the economic impacts of fibre optic broadband in East Africa, we have seen how institutions such as the Kenya Tea Board and the Rwandan Health Ministry are better integrating their information systems in order to gain a better national picture, and thereby contribute to industrial upgrading in the case of tea or better public services in the case of health. Nevertheless, big data is not accessible to all, and researchers must often prove commercial or strategic value in order to gain access.

Use of ‘big data’ is still a growing field, born within the discipline of computer science. My initial interviews with big data researchers working on Africa indicate they are still figuring out what kinds of questions can be answered with big data and how they might justify themselves and their methodologies to mainstream economics. Big data’s potential for hypothesis-building is somewhat at odds with the tradition of hypothesis-testing in economics. Big data researchers start with the question, ‘Where can this data lead me?’ There is also the question of how restricted access might frame research design. To date, the researchers that have been most successful in gaining access to African big data have worked with private companies, banks and financial institutions. It is therefore the incorporation and integration of poor people into private sector understandings that big data currently seems to offer.

This vision of development fits into a broader trend. Just as Hernando de Soto has argued that development is hampered by the exclusion of poor people from formalised property rights, proponents of microcredit have likewise argued it is the poor’s exclusion from financial institutions that limit their ability to develop self-sustaining enterprises. Researchers are therefore encouraged to use big data to model poor peoples’ actions and credit worthiness to incorporate them into financial systems, thereby transforming them from invisible selves into visible selves.

Critics of microfinance have cautioned that incorporating poor people into globalised structures of finance makes them more vulnerable to state interference in the form of taxes and to debt and international financial crises. It is also unclear what the drift into the private sector might do to wider understandings of poverty. While national measures situate citizens as members of national or collective groups, mobile financial innovations often focus on the individual’s financial records and credit worthiness. It remains to be seen whether this change of focus might move us away from more social definitions for poverty towards more individual or private explanations.

Likewise the flow of digital information across geographical space has the potential to change the nature of collaboration. As Mahmoud Mamdani has cautioned, “The global market tends to relegate Africa to providing raw material (“data”) to outside academics who process it and then re-export their theories back to Africa. Research proposals are increasingly descriptive accounts of data collection and the methods used to collate data, collaboration is reduced to assistance, and there is a general impoverishment of theory and debate”. This problem could potentially be exacerbated by open data initiatives that seek to get more people using publicly collected data. As Morten Jerven writes in his recent book, Poor Numbers, interactions between African data producers and users are currently limited, with users often unable to effectively assess the source and methods used to collect the original data. Nevertheless, such numbers are often taken at face value, with dubious policy recommendations formed as a result. While multiple sources of data (from the public and private sector) can help increase the precision of research and lead to better conclusions, we do not understand how big data (and open data) will impact the overall research environment in Africa.

My next project will examine these issues in relation to economic studies of unemployment in Egypt and financial inclusion in Uganda. The key objectives will be to improve our understanding of how data is being collected, how data is being communicated across groups and within systems, how new models of the economy are being formed, and what these changes are doing to political and economic relationships on the ground. Specifically, the project poses six interrelated questions: Where is economic intelligence and expertise currently located? What is being measured by whom, and how, and why? How do different tools of measurement change the way researchers understand economic truth and construct their models? How does more ‘legibility’ over African economies change power relations? What resistance or critical thinking exists within these new configurations of expertise? How can we combine approaches to assemble a fuller picture of economic understanding? The project will emphasise how economics, as a discipline, does not merely measure external reality, but helps to shape and influence that reality.

How we measure economies matters, particularly in the context of ever increasing evidence-based policy-making and with increasing interest from the private sector in Africa. Measurement often changes and shapes our realities of the external world. As Timothy Mitchell writes: “the practices that form the economy operate, in part, to establish equivalences, contain circulations, identify social actors or agents, make quantities and performances measurable, and designate relations of control and command”. In other words, researchers cannot make sense of an economy without first establishing a research infrastructure through which subjects are measured and incorporated. The particular shape, tools and technologies of that research infrastructure help frame and construct economic models and truth.

Such frames also have political implications, as control over information often strengthens one group over others. Indeed, as James C. Scott’s work Seeing Like a State has shown, the struggle to establish legibility over societies is inherently political. Elites have always attempted to standardise and regularise more marginal groups in an effort to draw them into dominant political and economic orders. However, legibility does not have be ‘top-down’. Weaker groups suffer most from illegible societies, and can benefit from more legibility. As information and trust become more deeply embedded within stronger ties and within transnational networks of skill and expertise, marginalised ‘out groups’ are particularly disadvantaged.

While James C. Scott’s work highlighted the dangers of a high modernist ‘legibility’, the very absence of legibility can also disempower marginal groups. It is the kind of legibility at stake that is important. While big data offers enormous potential for economists to better understand what is going on in Africa’s informal economies, economic sociologists, anthropologists and historians must remind them how our tools and measurements influence systems of knowledge production and change our understandings and beliefs about the external world. Africa might be becoming ‘more usable’ and ‘more legible,’ but we need to ask, for whom, by whom, and for what purpose?

Dr Laura Mann is a Postdoctoral Researcher at the Oxford Internet Institute, University of Oxford. Her research focuses on the political economy of markets and value chains in Africa. Her current research examines the effects of broadband internet on the tea, tourism and outsourcing value chains of Kenya and Rwanda. From January 2014 she will be based at the African Studies Centre at Leiden University. Read Laura’s blog.