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Ethics, Politics & Government

Five Pieces You Should Probably Read On: Fake News and Filter Bubbles

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by David Sutcliffe

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?

by David Sutcliffe

This is the second post in a series that will uncover great writing by faculty and students at the Oxford Internet Institute, things you should probably know, and things that deserve to be brought out for another viewing. This week: Fake News and Filter Bubbles! 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 polarised 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…

Politics & Government

Five Pieces You Should Probably Read On: The US Election

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by David Sutcliffe

Here are five pieces that consider the interaction of social media and democracy—the problems, but also potential ways forward.

by David Sutcliffe

Image from Gage Skidmore via Flickr Creative Commons

This is the first post in a series that will uncover great writing by faculty and students at the Oxford Internet Institute, things you should probably know, and things that deserve to be brought out for another viewing. This week: The US Election. This was probably the nastiest Presidential election in recent memory: awash with Twitter bots and scandal, polarisation and filter bubbles, accusations of interference by Russia and the Director of the FBI, and another shock result. We have written about electoral prediction elsewhere: instead, here are five pieces that consider the interaction of social media and democracy—the problems, but also potential ways forward. 1. James Williams: The Clickbait Candidate 10 October 2016 | 2700 words | 13 minutes “Trump is very straightforwardly an embodiment of the dynamics of clickbait: he is the logical product (though not endpoint) in the political domain of a media environment designed to invite, and indeed incentivise, relentless competition for our attention […] Like clickbait or outrage cascades, Donald Trump is merely the sort of informational packet our media environment is designed to select for.” James Williams says that now is probably the time to have that societal conversation about the design ethics of the attention economy—because in our current media environment, attention trumps everything. 2. Sam Woolley, Philip Howard: Bots Unite to Automate the Presidential Election [Wired] 15 May 2016 | 850 words | 4 minutes “Donald Trump understands minority communities. Just ask Pepe Luis Lopez, Francisco Palma, and Alberto Contreras […] each tweeted in support of Trump after his victory in the Nevada caucuses earlier this year. The problem is, Pepe, Francisco, and Alberto aren’t people. They’re bots.” It’s no surprise that automated spam accounts (or bots) are creeping into election politics, say Sam Woolley and Philip Howard. Demanding bot transparency would at least help clean up social media—which, for better or worse, is increasingly where presidents get elected. 3. Phil Howard:…

Image from Gage Skidmore via Flickr Creative Commons

Politics & Government

Of course social media is transforming politics. But it’s not to blame for Brexit and Trump

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by Helen Margetts

Mark Zuckerberg has responded with the strange claim that his company does not influence people’s decisions. So what role did social media play in the political events of 2016?

by Helen Margetts

After Brexit and the election of Donald Trump, 2016 will be remembered as the year of cataclysmic democratic events on both sides of the Atlantic. Social media has been implicated in the wave of populism that led to both these developments. Attention has focused on echo chambers, with many arguing that social media users exist in ideological filter bubbles, narrowly focused on their own preferences, prey to fake news and political bots, reinforcing polarisation and leading voters to turn away from the mainstream. Mark Zuckerberg has responded with the strange claim that his company (built on $5 billion of advertising revenue) does not influence people’s decisions. So what role did social media play in the political events of 2016? Political turbulence and the new populism There is no doubt that social media has brought change to politics. From the waves of protest and unrest in response to the 2008 financial crisis, to the Arab spring of 2011, there has been a generalised feeling that political mobilisation is on the rise, and that social media had something to do with it. Our book investigating the relationship between social media and collective action, Political Turbulence, focuses on how social media allows new, “tiny acts” of political participation (liking, tweeting, viewing, following, signing petitions and so on), which turn social movement theory around. Rather than identifying with issues, forming collective identity and then acting to support the interests of that identity—or voting for a political party that supports it—in a social media world, people act first, and think about it, or identify with others later, if at all. These tiny acts of participation can scale up to large-scale mobilisations, such as demonstrations, protests or campaigns for policy change. But they almost always don’t. The overwhelming majority (99.99%) of petitions to the UK or US governments fail to get the 100,000 signatures required for a parliamentary debate (UK) or an official response (US). The very few that…

Economics, Governance & Security

Could data pay for global development? Introducing data financing for global good

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by admin

Are there ways in which the data economy could directly finance global causes such as climate change prevention, poverty alleviation and infrastructure?

by admin

“If data is the new oil, then why aren’t we taxing it like we tax oil?” That was the essence of the provocative brief that set in motion our recent 6-month research project funded by the Rockefeller Foundation. The results are detailed in the new report: Data Financing for Global Good: A Feasibility Study. 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…

Ethics, Governance & Security

Should there be a better accounting of the algorithms that choose our news for us?

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by David Sutcliffe

The algorithms technology rely upon create a new type of curated media that can undermine the fairness and quality of political discourse.

by David Sutcliffe

The Facebook Wall, by René C. Nielsen (Flickr).

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—and content personalisation systems (think search engines, social media feeds and targeted advertising), and the algorithms they rely upon, create a new type of curated media that can undermine the fairness and quality of political discourse. A new article by Brent Mittlestadt explores the challenges of enforcing a political right to transparency in content personalisation systems. Firstly, he explains the value of transparency to political discourse and suggests how content personalisation systems undermine open exchange of ideas and evidence among participants: at a minimum, personalisation systems can undermine political discourse by curbing the diversity of ideas that participants encounter. Second, he explores work on the detection of discrimination in algorithmic decision making, including techniques of algorithmic auditing that service providers can employ to detect political bias. Third, he identifies several factors that inhibit auditing and thus indicate reasonable limitations on the ethical duties incurred by service providers—content personalisation systems can function opaquely and be resistant to auditing because of poor accessibility and interpretability of decision-making frameworks. Finally, Brent concludes with reflections on the need for regulation of content personalisation systems. He notes that no matter how auditing is pursued, standards to detect evidence of political bias in personalised content are urgently required. Methods are needed to routinely and consistently assign political value labels to content delivered by personalisation systems. This is perhaps the most pressing area for future work—to develop practical methods for algorithmic auditing. The right to transparency in political discourse may seem unusual and farfetched. However, standards already set by the U.S. Federal Communication Commission’s fairness doctrine—no longer in force—and the British Broadcasting Corporation’s fairness principle both demonstrate the importance of the idealised version of political discourse described here. Both precedents…

The Facebook Wall, by René C. Nielsen (Flickr).

Politics & Government

Can we predict electoral outcomes from Wikipedia traffic?

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by taha yasseri

Data show that the relative change in page views to the general Wikipedia page on the election can offer an estimate of the relative change in election turnout.

by taha yasseri

2016 presidential candidate Donald Trump in a residential backyard near Jordan Creek Parkway and Cody Drive in West Des Moines, Iowa, with lights and security cameras. Image by Tony Webster (Flickr).

As digital technologies become increasingly integrated into the fabric of social life their ability to generate large amounts of information about the opinions and activities of the population increases. The opportunities in this area are enormous: predictions based on socially generated data are much cheaper than conventional opinion polling, offer the potential to avoid classic biases inherent in asking people to report their opinions and behaviour, and can deliver results much quicker and be updated more rapidly. In their article published in EPJ Data Science, Taha Yasseri and Jonathan Bright develop a theoretically informed prediction of election results from socially generated data combined with an understanding of the social processes through which the data are generated. They can thereby explore the predictive power of socially generated data while enhancing theory about the relationship between socially generated data and real world outcomes. Their particular focus is on the readership statistics of politically relevant Wikipedia articles (such as those of individual political parties) in the time period just before an election. By applying these methods to a variety of different European countries in the context of the 2009 and 2014 European Parliament elections they firstly show that the relative change in number of page views to the general Wikipedia page on the election can offer a reasonable estimate of the relative change in election turnout at the country level. This supports the idea that increases in online information seeking at election time are driven by voters who are considering voting. Second, they show that a theoretically informed model based on previous national results, Wikipedia page views, news media mentions, and basic information about the political party in question can offer a good prediction of the overall vote share of the party in question. Third, they present a model for predicting change in vote share (i.e., voters swinging towards and away from a party), showing that Wikipedia page-view data provide an important increase…

2016 presidential candidate Donald Trump in a residential backyard near Jordan Creek Parkway and Cody Drive in West Des Moines, Iowa, with lights and security cameras. Image by Tony Webster (Flickr).

Economics, Governance & Security

The blockchain paradox: Why distributed ledger technologies may do little to transform the economy

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by admin

Applying elementary institutional economics to examine what blockchain technologies really do in terms of economic organisation, and what problems this gives rise to.

by admin

Bitcoin’s underlying technology, the blockchain, is widely expected to find applications far beyond digital payments. It is celebrated as a “paradigm shift in the very idea of economic organisation”. But the OII’s Professor Vili Lehdonvirta contends that such revolutionary potentials may be undermined by a fundamental paradox that has to do with the governance of the technology. 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 “revolutionise 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 organisation, 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. 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…

Politics & Government

Is Social Media Killing Democracy?

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by Phil Howard

Both the Brexit referendum and US election have revealed the limits of modern democracy, and social media platforms are currently setting those limits.

by Phil Howard

Donald Trump in Reno, Nevada, by Darron Birgenheier (Flickr).

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 organisations, 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 organisations 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 organisations to trust, we prefer to strengthen our ties to the people and organisations we already know and like. When offered a choice of news stories, we prefer to read about the issues we already care about,…

Donald Trump in Reno, Nevada, by Darron Birgenheier (Flickr).

Politics & Government

Don’t Shoot the Messenger! What part did social media play in 2016 US e­lection?

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by Helen Margetts

We should appreciate how social media can provide a wealth of valuable data to understand the anger and despair that the polls missed, and to analyse political behaviour and opinion in the times ahead.

by Helen Margetts

Young activists gather at Lafayette Park in protest at the presidential campaign of presumptive Republican nominee Donald J. Trump. By Stephen Melkisethian (Flickr).

Commentators have been quick to ‘blame social media’ for ‘ruining’ the 2016 election in putting Mr Donald Trump in the White House. Just as was the case in the campaign for Brexit, people argue that social media has driven us to a ‘post-truth’ world of polarisation and echo chambers. Is this really the case? At first glance, the ingredients of the Trump victory — as for Brexit — seem remarkably traditional. The Trump campaign spent more on physical souvenirs than on field data, more on Make America Great Again hats (made in China) than on polling. The Daily Mail characterisation of judges as Enemies of the People after their ruling that the triggering of Article 50 must be discussed in parliament seemed reminiscent of the 1930s. Likewise, US crowds chanting ‘Lock her up’, like lynch mobs, seemed like ghastly reminders of a pre-democratic era. Clearly social media were a big part of the 2016 election, used heavily by the candidates themselves, and generating 8.8 billion posts, likes and commentson Facebook alone. Social media also make visible what in an earlier era could remain a country’s dark secret — hatred of women (through death and rape threats and trolling of female politicians in both the UK and US), and rampant racism. This visibility, society’s new self-awareness, brings change to political behaviour. Social media provide social information about what other people are doing: viewing, following, liking, sharing, tweeting, joining, supporting and so on. This social information is the driver behind the political turbulence that characterises politics today. Those rustbelt Democrats feeling abandoned by the system saw on social media that they were not alone — that other people felt the same way, and that Trump was viable as a candidate. For a woman drawn towards the Trump agenda but feeling tentative, the hashtag #WomenForTrump could reassure her that there were like-minded people she could identify with. Decades of social science research shows information about the behaviour of others influences how groups behave and now it is driving the unpredictability of politics,…

Young activists gather at Lafayette Park in protest at the presidential campaign of presumptive Republican nominee Donald J. Trump. By Stephen Melkisethian (Flickr).

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