Fake news, post-truth, “alternative facts”, filter bubbles — this is the news and media environment we apparently now inhabit, and that has formed the fabric and backdrop of Brexit (“£350 million a week”) and Trump (“This was the largest audience to ever witness an inauguration — period”). Do social media divide us, hide us from each other? Are you particularly aware of what content is personalised for you, what it is you’re not seeing? How much can we do with machine-automated or crowd-sourced verification of facts? And are things really any worse now than when Bacon complained in 1620 about the false notions that “are now in possession of the human understanding, and have taken deep root therein”?

1. Bernie Hogan: How Facebook divides us [Times Literary Supplement]

27 October 2016 / 1000 words / 5 minutes

“Filter bubbles can create an increasingly fractured population, such as the one developing in America. For the many people shocked by the result of the British EU referendum, we can also partially blame filter bubbles: Facebook literally filters our friends’ views that are least palatable to us, yielding a doctored account of their personalities.”

Bernie Hogan says it’s time Facebook considered ways to use the information it has about us to bring us together across political, ideological and cultural lines, rather than hide us from each other or push us into polarized and hostile camps. He says it’s not only possible for Facebook to help mitigate the issues of filter bubbles and context collapse; it’s imperative, and it’s surprisingly simple.

2. Luciano Floridi: Fake news and a 400-year-old problem: we need to resolve the ‘post-truth’ crisis [the Guardian]

29 November 2016 / 1000 words / 5 minutes

“The internet age made big promises to us: a new period of hope and opportunity, connection and empathy, expression and democracy. Yet the digital medium has aged badly because we allowed it to grow chaotically and carelessly, lowering our guard against the deterioration and pollution of our infosphere. […] some of the costs of misinformation may be hard to reverse, especially when confidence and trust are undermined. The tech industry can and must do better to ensure the internet meets its potential to support individuals’ wellbeing and social good.”

The Internet echo chamber satiates our appetite for pleasant lies and reassuring falsehoods, and has become the defining challenge of the 21st century, says Luciano Floridi. So far, the strategy for technology companies has been to deal with the ethical impact of their products retrospectively, but this is not good enough, he says. We need to shape and guide the future of the digital, and stop making it up as we go along. It is time to work on an innovative blueprint for a better kind of infosphere.

3. Philip Howard: Facebook and Twitter’s real sin goes beyond spreading fake news

3 January 2017 / 1000 words / 5 minutes

“With the data at their disposal and the platforms they maintain, social media companies could raise standards for civility by refusing to accept ad revenue for placing fake news. They could let others audit and understand the algorithms that determine who sees what on a platform. Just as important, they could be the platforms for doing better opinion, exit and deliberative polling.”

Only Facebook and Twitter know how pervasive fabricated news stories and misinformation campaigns have become during referendums and elections, says Philip Howard — and allowing fake news and computational propaganda to target specific voters is an act against democratic values. But in a time of weakening polling systems, withholding data about public opinion is actually their major crime against democracy, he says.

4. Brent Mittelstadt: Should there be a better accounting of the algorithms that choose our news for us?

7 December 2016 / 1800 words / 8 minutes

“Transparency is often treated as the solution, but merely opening up algorithms to public and individual scrutiny will not in itself solve the problem. Information about the functionality and effects of personalisation must be meaningful to users if anything is going to be accomplished. At a minimum, users of personalisation systems should be given more information about their blind spots, about the types of information they are not seeing, or where they lie on the map of values or criteria used by the system to tailor content to users.”

A central ideal of democracy is that political discourse should allow a fair and critical exchange of ideas and values. But political discourse is unavoidably mediated by the mechanisms and technologies we use to communicate and receive information, says Brent Mittelstadt. And content personalization systems and the algorithms they rely upon create a new type of curated media that can undermine the fairness and quality of political discourse.

5. Heather Ford: Verification of crowd-sourced information: is this ‘crowd wisdom’ or machine wisdom?

19 November 2013 / 1400 words / 6 minutes

“A key question being asked in the design of future verification mechanisms is the extent to which verification work should be done by humans or non-humans (machines). Here, verification is not a binary categorisation, but rather there is a spectrum between human and non-human verification work, and indeed, projects like Ushahidi, Wikipedia and Galaxy Zoo have all developed different verification mechanisms.”

‘Human’ verification, a process of checking whether a particular report meets a group’s truth standards, is an acutely social process, says Heather Ford. If code is law and if other aspects in addition to code determine how we can act in the world, it is important that we understand the context in which code is deployed. Verification is a practice that determines how we can trust information coming from a variety of sources — only by illuminating such practices and the variety of impacts that code can have in different environments can we begin to understand how code regulates our actions in crowdsourcing environments.

.. and just to prove we’re capable of understanding and acknowledging and assimilating multiple viewpoints on complex things, here’s Helen Margetts, with a different slant on filter bubbles: “Even if political echo chambers were as efficient as some seem to think, there is little evidence that this is what actually shapes election results. After all, by definition echo chambers preach to the converted. It is the undecided people who (for example) the Leave and Trump campaigns needed to reach. And from the research, it looks like they managed to do just that.”

The Authors

Bernie Hogan is a Research Fellow at the OII; his research interests lie at the intersection of social networks and media convergence.

Luciano Floridi is the OII’s Professor of Philosophy and Ethics of Information. His  research areas are the philosophy of Information, information and computer ethics, and the philosophy of technology.

Philip Howard is the OII’s Professor of Internet Studies. He investigates the impact of digital media on political life around the world.

Brent Mittelstadt is an OII Postdoc His research interests include the ethics of information handled by medical ICT, theoretical developments in discourse and virtue ethics, and epistemology of information.

Heather Ford completed her doctorate at the OII, where she studied how Wikipedia editors write history as it happens. She is now a University Academic Fellow in Digital Methods at the University of Leeds. Her forthcoming book “Fact Factories: Wikipedia’s Quest for the Sum of All Human Knowledge” will be published by MIT Press.

Helen Margetts is the OII’s Director, and Professor of Society and the Internet. She specialises in digital era government, politics and public policy, and data science and experimental methods. Her most recent book is Political Turbulence (Princeton).

Coming up! .. It’s the economy, stupid / Augmented reality and ambient fun / The platform economy / Power and development / Internet past and future / Government / Labour rights / The disconnected / Ethics / Staying critical

This is the big year for computational propaganda — using immense data sets to manipulate public opinion over social media. Both the Brexit referendum and US election have revealed the limits of modern democracy, and social media platforms are currently setting those limits.

Platforms like Twitter and Facebook now provide a structure for our political lives. We’ve always relied on many kinds of sources for our political news and information. Family, friends, news organizations, charismatic politicians certainly predate the internet. But whereas those are sources of information, social media now provides the structure for political conversation. And the problem is that these technologies permit too much fake news, encourage our herding instincts, and aren’t expected to provide public goods.

First, social algorithms allow fake news stories from untrustworthy sources to spread like wildfire over networks of family and friends. Many of us just assume that there is a modicum of truth-in-advertising. We expect this from advertisements for commercial goods and services, but not from politicians and political parties. Occasionally a political actor gets punished for betraying the public trust through their misinformation campaigns. But in the United States “political speech” is completely free from reasonable public oversight, and in most other countries the media organizations and public offices for watching politicians are legally constrained, poorly financed, or themselves untrustworthy. Research demonstrates that during the campaigns for Brexit and the U.S. presidency, large volumes of fake news stories, false factoids, and absurd claims were passed over social media networks, often by Twitter’s highly automated accounts and Facebook’s algorithms.

Second, social media algorithms provide very real structure to what political scientists often call “elective affinity” or “selective exposure”. When offered the choice of who to spend time with or which organizations to trust, we prefer to strengthen our ties to the people and organizations we already know and like. When offered a choice of news stories, we prefer to read about the issues we already care about, from pundits and news outlets we’ve enjoyed in the past. Random exposure to content is gone from our diets of news and information. The problem is not that we have constructed our own community silos — humans will always do that. The problem is that social media networks take away the random exposure to new, high-quality information.

This is not a technological problem. We are social beings and so we will naturally look for ways to socialize, and we will use technology to socialize each other. But technology could be part of the solution. A not-so-radical redesign might occasionally expose us to new sources of information, or warn us when our own social networks are getting too bounded.

The third problem is that technology companies, including Facebook and Twitter, have been given a “moral pass” on the obligations we hold journalists and civil society groups to.

In most democracies, the public policy and exit polling systems have been broken for a decade. Many social scientists now find that big data, especially network data, does a better job of revealing public preferences than traditional random digit dial systems. So Facebook actually got a moral pass twice this year. Their data on public opinion would have certainly informed the Brexit debate, and their data on voter preferences would certainly have informed public conversation during the US election.

Facebook has run several experiments now, published in scholarly journals, demonstrating that they have the ability to accurately anticipate and measure social trends. Whereas journalists and social scientists feel an obligation to openly analyze and discuss public preferences, we do not expect this of Facebook. The network effects that clearly were unmeasured by pollsters were almost certainly observable to Facebook. When it comes to news and information about politics, or public preferences on important social questions, Facebook has a moral obligation to share data and prevent computational propaganda. The Brexit referendum and US election have taught us that Twitter and Facebook are now media companies. Their engineering decisions are effectively editorial decisions, and we need to expect more openness about how their algorithms work. And we should expect them to deliberate about their editorial decisions.

There are some ways to fix these problems. Opaque software algorithms shape what people find in their news feeds. We’ve all noticed fake news stories (often called clickbait), and while these can be an entertaining part of using the internet, it is bad when they are used to manipulate public opinion. These algorithms work as “bots” on social media platforms like Twitter, where they were used in both the Brexit and US presidential campaign to aggressively advance the case for leaving Europe and the case for electing Trump. Similar algorithms work behind the scenes on Facebook, where they govern what content from your social networks actually gets your attention.

So the first way to strengthen democratic practices is for academics, journalists, policy makers and the interested public to audit social media algorithms. Was Hillary Clinton really replaced by an alien in the final weeks of the 2016 campaign? We all need to be able to see who wrote this story, whether or not it is true, and how it was spread. Most important, Facebook should not allow such stories to be presented as news, much less spread. If they take ad revenue for promoting political misinformation, they should face the same regulatory punishments that a broadcaster would face for doing such a public disservice.

The second problem is a social one that can be exacerbated by information technologies. This means it can also be mitigated by technologies. Introducing random news stories and ensuring exposure to high quality information would be a simple — and healthy — algorithmic adjustment to social media platforms. The third problem could be resolved with moral leadership from within social media firms, but a little public policy oversight from elections officials and media watchdogs would help. Did Facebook see that journalists and pollsters were wrong about public preferences? Facebook should have told us if so, and shared that data.

Social media platforms have provided a structure for spreading around fake news, we users tend to trust our friends and family, and we don’t hold media technology firms accountable for degrading our public conversations. The next big thing for technology evolution is the Internet of Things, which will generate massive amounts of data that will further harden these structures. Is social media damaging democracy? Yes, but we can also use social media to save democracy.