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P&I Special Issue 2023 Call for Paper – Datafication. Platformisation. Metaverse. Global Internet Policy or a Fractured Communication Future?

Datafication. Platformisation. Metaverse. Global Internet Policy or a Fractured Communication Future?

Special Issue Call for Papers, Volume 15, Issue 4

Datafication. Platformization. Metaverse. What is the state of global internet policy? Within our current online and hyper-connected lives, is it possible to have such a thing as global internet policy? Building off the 2022 Policy & Internet Conference, this special issue addresses the complex and multiple perspectives of internet policy from around the globe.

As we evolve through the Anthropocene and attempt to navigate the significant challenges humanity currently faces, we are consistently reminded of the most pressing critical issues of our epoch. Economic systems are the point of breaking, industrial action mobilised by unions is at an all-time high, inflation is rising, workers’ pay continues to fall, and the stability of our political systems has come into question. Our health systems are under unfathomable stress, refugee numbers are increasing through displacement, and the war in Ukraine continues, all of which adds to the growing global societal, economic and political pressures. And yet, concurrently, our connectivity through digital media and its surrounding environments is at an all-time high, arguably from the rise of technology players providing suites of social media platforms and its supporting infrastructures that enable a seamless and convenient, always-on lifestyle. The same app that enables us to chat with our friends and family can also book our rideshares, order our food, pay for our purchases and tempt us to become internet celebrities. What was once framed as user generated content activity has now become a normalised cultural pastime, as TikTok influencers feed the demotic turn that sees ordinary folk become internet superstars in rather small timeframes.

At the same time, policymakers are reforming legislation to address the incomprehensible imbalance of power that is generated by technology giants. One of the immediate issues concerning users is their online privacy. In many instances, governments continue to struggle with bringing large-scale social media platforms to account, and seeking mutually beneficial outcomes. TikTok especially has raised concerns with user privacy as many cybersecurity agencies who advise governments have no clear answers on how to maintain its use while not knowing what will happen to user data. Alongside user data issues, in some countries the relationship between technology providers and governments is blurred, where regulation is becoming a weaponized approach to citizen control. To counter these sorts of power imbalances, advocacy groups are consistently calling for safe, inclusive, affordable and reliable internet connectivity, as the digital divide continues to increase. The urgency for healthy online civic spaces has been highlighted as a key focus for advocacy groups, while ensuring the safety of its users has also been highlighted.

This special issue asks for responses to these contemporary issues and seeks to understand if a global internet policy is possible. How might we incorporate co-design, open dialogues, increased governance, interoperability and user-centred discussions into policy discussions? What are the immediate issues for policymakers?

We welcome research that addresses the following areas of interest (but not limited to):

Takedowns, shadowbanning, throttling
Non-western approaches towards internet policy
Internet governance and infrastructures
Content moderation
Regulatory responses that address the growing digital divide
Communication and technology for positive economic development
Building strong communication systems during times of high societal pressure
Social media and labour concerns
Emerging digital communication for marginalised groups and individuals
Digital communication that bridges regional legislation
Communication and technology through comparative media systems
Regulation for diversity across media systems
Media automation for the next 10 years and beyond
Young people and social media
Innovative empirical examples of positive digital communication and/or technology development

Please send through your title and 150-200 word abstract to Jonathon Hutchinson [jonathon.hutchinson@sydney.edu.au] and Milly Stilinovic [milica.stilinovic@sydney.edu.au] with the subject line: Policy & Internet Special Issue by October 31 2022.

Timeline

October 31 – Abstracts due

November 18 – Notification of Accepted Papers

January 31 (2023) – Full Papers Due

March 31 (2023) – Final Revisions Due

Photo by Risto Kokkonen on Unsplash

Censorship or rumour management? How Weibo constructs “truth” around crisis events

As social media become increasingly important as a source of news and information for citizens, there is a growing concern over the impacts of social media platforms on information quality — as evidenced by the furore over the impact of “fake news”. Driven in part by the apparently substantial impact of social media on the outcomes of Brexit and the US Presidential election, various attempts have been made to hold social media platforms to account for presiding over misinformation, with recent efforts to improve fact-checking.

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

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

We caught up with the authors to discuss their findings:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

How policy makers can extract meaningful public opinion data from social media to inform their actions

The role of social media in fostering the transparency of governments and strengthening the interaction between citizens and public administrations has been widely studied. Scholars have highlighted how online citizen-government and citizen-citizen interactions favour debates on social and political matters, and positively affect citizens’ interest in political processes, like elections, policy agenda setting, and policy implementation.

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

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

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

We caught up with the authors to discuss their findings:

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

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

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

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

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

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

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

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

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

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

Social media and the battle for perceptions of the U.S.–Mexico border

The US-Mexican border region is home to approximately 12 million people, and is the most-crossed international border in the world. Unlike the current physical border, the image people hold of “the border” is not firmly established, and can be modified. One way is via narratives (or stories), which are a powerful tool for gaining support for public policies. Politicians’ narratives about the border have historically been perpetuated by the traditional media, particularly when this allows them to publish sensational and attention grabbing news stories.

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

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

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

We caught up with the authors to discuss their findings:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

We aren’t “rational actors” when it come to privacy — and we need protecting

We are increasingly exposed to new practices of data collection. Image by ijclark (Flickr CC BY 2.0).

As digital technologies and platforms are increasingly incorporated into our lives, we are exposed to new practices of data creation and collection — and there is evidence that American citizens are deeply concerned about the consequences of these practices. But despite these concerns, the public has not abandoned technologies that produce data and collect personal information. In fact, the popularity of technologies and services that reveal insights about our health, fitness, medical conditions, and family histories in exchange for extensive monitoring and tracking paints a picture of a public that is voluntarily offering itself up to increasingly invasive forms of surveillance.

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

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

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

We caught up with Nora to discuss her findings:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 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

Five Pieces You Should Probably Read On: The US Election

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 incentivize, relentless competition for our attention […] Like clickbait or outrage cascades, Donald Trump is merely the sort of informational packet our media environment is designed to select for.”

James Williams says that now is probably the time to have that societal conversation about the design ethics of the attention economy — because in our current media environment, attention trumps everything.

2. Sam Woolley, Philip Howard: Bots Unite to Automate the Presidential Election [Wired]

15 May 2016 / 850 words / 4 minutes

“Donald Trump understands minority communities. Just ask Pepe Luis Lopez, Francisco Palma, and Alberto Contreras […] each tweeted in support of Trump after his victory in the Nevada caucuses earlier this year. The problem is, Pepe, Francisco, and Alberto aren’t people. They’re bots.”

It’s no surprise that automated spam accounts (or bots) are creeping into election politics, say Sam Woolley and Philip Howard. Demanding bot transparency would at least help clean up social media — which, for better or worse, is increasingly where presidents get elected.

3. Phil Howard: Is Social Media Killing Democracy?

15 November 2016 / 1100 words / 5 minutes

“This is the big year for computational propaganda — using immense data sets to manipulate public opinion over social media. Both the Brexit referendum and US election have revealed the limits of modern democracy, and social media platforms are currently setting those limits […] these technologies permit too much fake news, encourage our herding instincts, and aren’t expected to provide public goods.”

Phil Howard discusses ways to address fake news, audit social algorithms, and deal with social media’s “moral pass” — social media is damaging democracy, he says, but can also be used to save it.

4. Helen Margetts: Don’t Shoot the Messenger! What part did social media play in 2016 US election?

15 November 2016 / 600 words / 3 minutes

“Rather than seeing social media solely as the means by which Trump ensnared his presidential goal, we should appreciate how they can provide a wealth of valuable data to understand the anger and despair that the polls missed, and to analyse political behaviour and opinion in the times ahead.”

New social information and visibility brings change to social behaviour, says Helen Margetts — ushering in political turbulence and unpredictability. Social media made visible what could have remain a country’s dark secret (hatred of women, rampant racism, etc.), but it will also underpin any radical counter-movement that emerges in the future.

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

9 January 2017 / 1700 words / 8 minutes

“Even if political echo chambers were as efficient as some seem to think, there is little evidence that this is what actually shapes election results. After all, by definition echo chambers preach to the converted. It is the undecided people who (for example) the Leave and Trump campaigns needed to reach. And from the research, it looks like they managed to do just that.”

Politics is a lot messier in the social media era than it used to be, says Helen Margetts, but rather than blaming social media for undermining democracy, we should be thinking about how we can improve the (inevitably major) part that it plays.

The Authors

James Williams is an OII doctoral candidate, studying the ethics of attention and persuasion in technology design.

Sam Woolley is a Research Assistant on the OII’s Computational Propaganda project; he is interested in political bots, and the intersection of political communication and automation.

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

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

#5OIIPieces

Five Pieces You Should Probably Read On: The US Election

1. James Williams: The Clickbait Candidate

10 October 2016 / 2700 words / 13 minutes

2. Sam Woolley, Philip Howard: Bots Unite to Automate the Presidential Election [Wired]

15 May 2016 / 850 words / 4 minutes

3. Phil Howard: Is Social Media Killing Democracy?

15 November 2016 / 1100 words / 5 minutes

4. Helen Margetts: Don’t Shoot the Messenger! What part did social media play in 2016 US election?

15 November 2016 / 600 words / 3 minutes

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

9 January 2017 / 1700 words / 8 minutes

The Authors

James Williams is an OII doctoral candidate, studying the ethics of attention and persuasion in technology design.

Sam Woolley is a Research Assistant on the OII’s Computational Propaganda project; he is interested in political bots, and the intersection of political communication and automation.

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

#5OIIPieces

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

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 polarization and leading voters to turn away from the mainstream. Mark Zuckerberg has responded with the strange claim that his company (built on $5 billion of advertising revenue) does not influence people’s decisions.

So what role did social media play in the political events of 2016?

Political turbulence and the new populism

There is no doubt that social media has brought change to politics. From the waves of protest and unrest in response to the 2008 financial crisis, to the Arab spring of 2011, there has been a generalized feeling that political mobilization is on the rise, and that social media had something to do with it.

Our book investigating the relationship between social media and collective action, Political Turbulence, focuses on how social media allows new, “tiny acts” of political participation (liking, tweeting, viewing, following, signing petitions and so on), which turn social movement theory around. Rather than identifying with issues, forming collective identity and then acting to support the interests of that identity – or voting for a political party that supports it – in a social media world, people act first, and think about it, or identify with others later, if at all.

These tiny acts of participation can scale up to large-scale mobilizations, such as demonstrations, protests or campaigns for policy change. But they almost always don’t. The overwhelming majority (99.99%) of petitions to the UK or US governments fail to get the 100,000 signatures required for a parliamentary debate (UK) or an official response (US).

The very few that succeed do so very quickly on a massive scale (petitions challenging the Brexit and Trump votes immediately shot above 4 million signatures, to become the largest petitions in history), but without the normal organizational or institutional trappings of a social or political movement, such as leaders or political parties – the reason why so many of the Arab Spring revolutions proved disappointing.

This explosive rise, non-normal distribution and lack of organization that characterizes contemporary politics can explain why many political developments of our time seem to come from nowhere. It can help to understand the shock waves of support that brought us the Italian Five Star Movement, Podemos in Spain, Jeremy Corbyn, Bernie Sanders, and most recently Brexit and Trump – all of which have campaigned against the “establishment” and challenged traditional political institutions to breaking point.

Each successive mobilization has made people believe that challengers from outside the mainstream are viable – and that is in part what has brought us unlikely results on both sides of the Atlantic. But it doesn’t explain everything.

We’ve had waves of populism before – long before social media (indeed many have made parallels between the politics of 2016 and that of the 1930s). While claims that social media feeds are the biggest threat to democracy, leading to the “disintegration of the general will” and “polarization that drives populism” abound, hard evidence is more difficult to find.

The myth of the echo chamber

The mechanism that is most often offered for this state of events is the existence of echo chambers or filter bubbles. The argument goes that first social media platforms feed people the news that is closest to their own ideological standpoint (estimated from their previous patterns of consumption) and second, that people create their own personalized information environments through their online behaviour, selecting friends and news sources that back up their world view.

Once in these ideological bubbles, people are prey to fake news and political bots that further reinforce their views. So, some argue, social media reinforces people’s current views and acts as a polarizing force on politics, meaning that “random exposure to content is gone from our diets of news and information”.

Really? Is exposure less random than before? Surely the most perfect echo chamber would be the one occupied by someone who only read the Daily Mail in the 1930s – with little possibility of other news – or someone who just watches Fox News? Can our new habitat on social media really be as closed off as these environments, when our digital networks are so very much larger and more heterogeneous than anything we’ve had before?

Research suggests not. A recent large-scale survey (of 50,000 news consumers in 26 countries) shows how those who do not use social media on average come across news from significantly fewer different online sources than those who do. Social media users, it found, receive an additional “boost” in the number of news sources they use each week, even if they are not actually trying to consume more news. These findings are reinforced by an analysis of Facebook data, where 8.8 billion posts, likes and comments were posted through the US election.

Recent research published in Science shows that algorithms play less of a role in exposure to attitude-challenging content than individuals’ own choices and that “on average more than 20% of an individual’s Facebook friends who report an ideological affiliation are from the opposing party”, meaning that social media exposes individuals to at least some ideologically cross-cutting viewpoints: “24% of the hard content shared by liberals’ friends is cross-cutting, compared to 35% for conservatives” (the equivalent figures would be 40% and 45% if random).

In fact, companies have no incentive to create hermetically sealed (as I have heard one commentator claim) echo chambers. Most of social media content is not about politics (sorry guys) – most of that £5 billion advertising revenue does not come from political organizations. So any incentives that companies have to create echo chambers – for the purposes of targeted advertising, for example – are most likely to relate to lifestyle choices or entertainment preferences, rather than political attitudes.

And where filter bubbles do exist they are constantly shifting and sliding – easily punctured by a trending cross-issue item (anybody looking at #Election2016 shortly before polling day would have seen a rich mix of views, while having little doubt about Trump’s impending victory).

And of course, even if political echo chambers were as efficient as some seem to think, there is little evidence that this is what actually shapes election results. After all, by definition echo chambers preach to the converted. It is the undecided people who (for example) the Leave and Trump campaigns needed to reach.

And from the research, it looks like they managed to do just that. A barrage of evidence suggests that such advertising was effective in the 2015 UK general election (where the Conservatives spent 10 times as much as Labour on Facebook advertising), in the EU referendum (where the Leave campaign also focused on paid Facebook ads) and in the presidential election, where Facebook advertising has been credited for Trump’s victory, while the Clinton campaign focused on TV ads. And of course, advanced advertising techniques might actually focus on those undecided voters from their conversations. This is not the bottom-up political mobilization that fired off support for Podemos or Bernie Sanders. It is massive top-down advertising dollars.

Ironically however, these huge top-down political advertising campaigns have some of the same characteristics as the bottom-up movements discussed above, particularly sustainability. Former New York Governor Mario Cuomo’s dictum that candidates “campaign in poetry and govern in prose” may need an update. Barack Obama’s innovative campaigns of online social networks, micro-donations and matching support were miraculous, but the extent to which he developed digital government or data-driven policy-making in office was disappointing. Campaign digitally, govern in analogue might be the new mantra.

Chaotic pluralism

Politics is a lot messier in the social media era than it used to be – whether something takes off and succeeds in gaining critical mass is far more random than it appears to be from a casual glance, where we see only those that succeed.

In Political Turbulence, we wanted to identify the model of democracy that best encapsulates politics intertwined with social media. The dynamics we observed seem to be leading us to a model of “chaotic pluralism”, characterized by diversity and heterogeneity – similar to early pluralist models – but also by non-linearity and high interconnectivity, making liberal democracies far more disorganized, unstable and unpredictable than the architects of pluralist political thought ever envisaged.

Perhaps rather than blaming social media for undermining democracy, we should be thinking about how we can improve the (inevitably major) part that it plays.

Within chaotic pluralism, there is an urgent need for redesigning democratic institutions that can accommodate new forms of political engagement, and respond to the discontent, inequalities and feelings of exclusion – even anger and alienation – that are at the root of the new populism. We should be using social media to listen to (rather than merely talk at) the expression of these public sentiments, and not just at election time.

Many political institutions – for example, the British Labour Party, the US Republican Party, and the first-past-the-post electoral system shared by both countries – are in crisis, precisely because they have become so far removed from the concerns and needs of citizens. Redesign will need to include social media platforms themselves, which have rapidly become established as institutions of democracy and will be at the heart of any democratic revival.

As these platforms finally start to admit to being media companies (rather than tech companies), we will need to demand human intervention and transparency over algorithms that determine trending news; factchecking (where Google took the lead); algorithms that detect fake news; and possibly even “public interest” bots to counteract the rise of computational propaganda.

Meanwhile, the only thing we can really predict with certainty is that unpredictable things will happen and that social media will be part of our political future.

Discussing the echoes of the 1930s in today’s politics, the Wall Street Journal points out how Roosevelt managed to steer between the extremes of left and right because he knew that “public sentiments of anger and alienation aren’t to be belittled or dismissed, for their causes can be legitimate and their consequences powerful”. The path through populism and polarization may involve using the opportunity that social media presents to listen, understand and respond to these sentiments.

This piece draws on research from Political Turbulence: How Social Media Shape Collective Action (Princeton University Press, 2016), by Helen Margetts, Peter John, Scott Hale and Taha Yasseri.

It is cross-posted from the World Economic Forum, where it was first published on 22 December 2016.

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

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 personalization 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 personalization systems. Firstly, he explains the value of transparency to political discourse and suggests how content personalization systems undermine open exchange of ideas and evidence among participants: at a minimum, personalization systems can undermine political discourse by curbing the diversity of ideas that participants encounter. Second, he explores work on the detection of discrimination in algorithmic decision making, including techniques of algorithmic auditing that service providers can employ to detect political bias. Third, he identifies several factors that inhibit auditing and thus indicate reasonable limitations on the ethical duties incurred by service providers — content personalization systems can function opaquely and be resistant to auditing because of poor accessibility and interpretability of decision-making frameworks. Finally, Brent concludes with reflections on the need for regulation of content personalization systems.

He notes that no matter how auditing is pursued, standards to detect evidence of political bias in personalized content are urgently required. Methods are needed to routinely and consistently assign political value labels to content delivered by personalization systems. This is perhaps the most pressing area for future work—to develop practical methods for algorithmic auditing.

The right to transparency in political discourse may seem unusual and farfetched. However, standards already set by the U.S. Federal Communication Commission’s fairness doctrine — no longer in force — and the British Broadcasting Corporation’s fairness principle both demonstrate the importance of the idealized version of political discourse described here. Both precedents promote balance in public political discourse by setting standards for delivery of politically relevant content. Whether it is appropriate to hold service providers that use content personalization systems to a similar standard remains a crucial question.

Read the full article: Mittelstadt, B. (2016) Auditing for Transparency in Content Personalization Systems. International Journal of Communication 10(2016), 4991–5002.

We caught up with Brent to explore the broader implications of the study:

Ed: We basically accept that the tabloids will be filled with gross bias, populism and lies (in order to sell copy) — and editorial decisions are not generally transparent to us. In terms of their impact on the democratic process, what is the difference between the editorial boardroom and a personalising social media algorithm?

Brent: There are a number of differences. First, although not necessarily transparent to the public, one hopes that editorial boardrooms are at least transparent to those within the news organisations. Editors can discuss and debate the tone and factual accuracy of their stories, explain their reasoning to one another, reflect upon the impact of their decisions on their readers, and generally have a fair debate about the merits and weaknesses of particular content.

This is not the case for a personalising social media algorithm; those working with the algorithm inside a social media company are often unable to explain why the algorithm is functioning in a particular way, or determined a particular story or topic to be ‘trending’ or displayed to particular users, while others are not. It is also far more difficult to ‘fact check’ algorithmically curated news; a news item can be widely disseminated merely by many users posting or interacting with it, without any purposeful dissemination or fact checking by the platform provider.

Another big difference is the degree to which users can be aware of the bias of the stories they are reading. Whereas a reader of The Daily Mail or The Guardian will have some idea of the values of the paper, the same cannot be said of platforms offering algorithmically curated news and information. The platform can be neutral insofar as it disseminates news items and information reflecting a range of values and political viewpoints. A user will encounter items reflecting her particular values (or, more accurately, her history of interactions with the platform and the values inferred from them), but these values, and their impact on her exposure to alternative viewpoints, may not be apparent to the user.

Ed: And how is content “personalisation” different to content filtering (e.g. as we see with the Great Firewall of China) that people get very worked up about? Should we be more worried about personalisation?

Brent: Personalisation and filtering are essentially the same mechanism; information is tailored to a user or users according to some prevailing criteria. One difference is whether content is merely infeasible to access, or technically inaccessible. Content of all types will typically still be accessible in principle when personalisation is used, but the user will have to make an effort to access content that is not recommended or otherwise given special attention. Filtering systems, in contrast, will impose technical measures to make particular content inaccessible from a particular device or geographical area.

Another difference is the source of the criteria used to set the visibility of different types of content. In the case of personalisation, these criteria are typically based on the users (inferred) interests, values, past behaviours and explicit requests. Critically, these values are not necessarily apparent to the user. For filtering, criteria are typically externally determined by a third party, often a government. Some types of information are set off limits, according to the prevailing values of the third party. It is the imposition of external values, which limit the capacity of users to access content of their choosing, which often causes an outcry against filtering and censorship.

Importantly, the two mechanisms do not necessarily differ in terms of the transparency of the limiting factors or rules to users. In some cases, such as the recently proposed ban in the UK of adult websites that do not provide meaningful age verification mechanisms, the criteria that determine whether sites are off limits will be publicly known at a general level. In other cases, and especially with personalisation, the user inside the ‘filter bubble’ will be unaware of the rules that determine whether content is (in)accessible. And it is not always the case that the platform provider intentionally keeps these rules secret. Rather, the personalisation algorithms and background analytics that determine the rules can be too complex, inaccessible or poorly understood even by the provider to give the user any meaningful insight.

Ed: Where are these algorithms developed: are they basically all proprietary? i.e. how would you gain oversight of massively valuable and commercially sensitive intellectual property?

Brent: Personalisation algorithms tend to be proprietary, and thus are not normally open to public scrutiny in any meaningful sense. In one sense this is understandable; personalisation algorithms are valuable intellectual property. At the same time the lack of transparency is a problem, as personalisation fundamentally affects how users encounter and digest information on any number of topics. As recently argued, it may be the case that personalisation of news impacts on political and democratic processes. Existing regulatory mechanisms have not been successful in opening up the ‘black box’ so to speak.

It can be argued, however, that legal requirements should be adopted to require these algorithms to be open to public scrutiny due to the fundamental way they shape our consumption of news and information. Oversight can take a number of forms. As I argue in the article, algorithmic auditing is one promising route, performed both internally by the companies themselves, and externally by a government agency or researchers. A good starting point would be for the companies developing and deploying these algorithms to extend their cooperation with researchers, thereby allowing a third party to examine the effects these systems are having on political discourse, and society more broadly.

Ed: By “algorithm audit” — do you mean examining the code and inferring what the outcome might be in terms of bias, or checking the outcome (presumably statistically) and inferring that the algorithm must be introducing bias somewhere? And is it even possible to meaningfully audit personalisation algorithms, when they might rely on vast amounts of unpredictable user feedback to train the system?

Brent: Algorithm auditing can mean both of these things, and more. Audit studies are a tool already in use, whereby human participants introduce different inputs into a system, and examine the effect on the system’s outputs. Similar methods have long been used to detect discriminatory hiring practices, for instance. Code audits are another possibility, but are generally prohibitive due to problems of access and complexity. Also, even if you can access and understand the code of an algorithm, that tells you little about how the algorithm performs in practice when given certain input data. Both the algorithm and input data would need to be audited.

Alternatively, auditing can assess just the outputs of the algorithm; recent work to design mechanisms to detect disparate impact and discrimination, particularly in the Fairness, Accountability and Transparency in Machine Learning (FAT-ML) community, is a great example of this type of auditing. Algorithms can also be designed to attempt to prevent or detect discrimination and other harms as they occur. These methods are as much about the operation of the algorithm, as they are about the nature of the training and input data, which may itself be biased. In short, auditing is very difficult, but there are promising avenues of research and development. Once we have reliable auditing methods, the next major challenge will be to tailor them to specific sectors; a one-size-meets-all approach to auditing is not on the cards.

Ed: Do you think this is a real problem for our democracy? And what is the solution if so?

Brent: It’s difficult to say, in part because access and data to study the effects of personalisation systems are hard to come by. It is one thing to prove that personalisation is occurring on a particular platform, or to show that users are systematically displayed content reflecting a narrow range of values or interests. It is quite another to prove that these effects are having an overall harmful effect on democracy. Digesting information is one of the most basic elements of social and political life, so any mechanism that fundamentally changes how information is encountered should be subject to serious and sustained scrutiny.

Assuming personalisation actually harms democracy or political discourse, mitigating its effects is quite a different issue. Transparency is often treated as the solution, but merely opening up algorithms to public and individual scrutiny will not in itself solve the problem. Information about the functionality and effects of personalisation must be meaningful to users if anything is going to be accomplished.

At a minimum, users of personalisation systems should be given more information about their blind spots, about the types of information they are not seeing, or where they lie on the map of values or criteria used by the system to tailor content to users. A promising step would be proactively giving the user some idea of what the system thinks it knows about them, or how they are being classified or profiled, without the user first needing to ask.

Brent Mittelstadt was talking to blog editor David Sutcliffe.