Could the open government movement shut the door on Freedom of Information

Curated on Posted on by Stefaan Verhulst

,  and  in The Conversation: “For democracy to work, citizens need to know what their government is doing. Then they can hold government officials and institutions accountable.

Over the last 50 years, Freedom of Information – or FOI – laws have been one of the most useful methods for citizens to learn what government is doing. These state and federal laws give people the power to request, and get, government documents. From everyday citizens to journalists, FOI laws have proven a powerful way to uncover the often-secret workings of government.

But a potential threat is emerging – from an unexpected place – to FOI laws.

We are scholars of government administration, ethics and transparency. And our research leads us to believe that while FOI laws have always faced many challenges, including resistance, evasion,  and poor implementation and enforcement, the last decade has brought a different kind of challenge in the form of a new approach to transparency….

The open government movement could help FOI implementation. Government information posted online, which is a core goal of open government advocates, can reduce the number of FOI requests. Open government initiatives can explicitly promote FOI by encouraging the passage of FOI laws, offering more training for officials who fill FOI requests, and developing technologies to make it easier to process and track FOI requests.

On the other hand, the relationship between open government and FOI may not always be positive in practice.

First, as with all kinds of public policy issues, resources – both money and political attention – are inherently scarce. Government officials now have to divide their attention between FOI and other open government initiatives. And funders now have to divide their financial resources between FOI and other open government initiatives.

Second, the open government reform movement as well as the FOI movement have long depended on nonprofit advocacy groups – from the National Freedom of Information Coalition and its state affiliates to the Sunlight Foundation – to obtain and disseminate government information. This means that the financial stability of those nonprofit groups is crucial. But their efforts, as they grow, may each only get a shrinking portion of the total amount of grant money available. Freedominfo.org, a website for gathering and comparing information on FOI laws around the world, had to suspend its operations in 2017 due to resources drying up.

We believe that priorities among government officials and good government advocates may also shift away from FOI. At a time when open data is “hot,” FOI programs could get squeezed as a result of this competition. Further, by allowing governments to claim credit for more politically convenient reforms such as online data portals, the open government agenda may create a false sense of transparency – there’s a lot more government information that isn’t available in those portals.

This criticism was leveled recently against Kenya, whose government launched a high-profile open data portal for publishing data on government performance and activities in 2011, yet delayed passage of an FOI law until 2016.

Similarly, in the United Kingdom, one government minister said in 2012,“I’d like to make Freedom of Information redundant, by pushing out so much data that people won’t have to ask for it.”…(More)”

Your Data Is Crucial to a Robotic Age. Shouldn’t You Be Paid for It?

Curated on Posted on by Stefaan Verhulst

Eduardo Porter at The New York Times: “The idea has been around for a bit. Jaron Lanier, the tech philosopher and virtual-reality pioneer who now works for Microsoft Research, proposed it in his 2013 book, “Who Owns the Future?,” as a needed corrective to an online economy mostly financed by advertisers’ covert manipulation of users’ consumer choices.

It is being picked up in “Radical Markets,” a book due out shortly from Eric A. Posner of the University of Chicago Law School and E. Glen Weyl, principal researcher at Microsoft. And it is playing into European efforts to collect tax revenue from American internet giants.

In a report obtained last month by Politico, the European Commission proposes to impose a tax on the revenue of digital companies based on their users’ location, on the grounds that “a significant part of the value of a business is created where the users are based and data is collected and processed.”

Users’ data is a valuable commodity. Facebook offers advertisers precisely targeted audiences based on user profiles. YouTube, too, uses users’ preferences to tailor its feed. Still, this pales in comparison with how valuable data is about to become, as the footprint of artificial intelligence extends across the economy.

Data is the crucial ingredient of the A.I. revolution. Training systems to perform even relatively straightforward tasks like voice translation, voice transcription or image recognition requires vast amounts of data — like tagged photos, to identify their content, or recordings with transcriptions.

“Among leading A.I. teams, many can likely replicate others’ software in, at most, one to two years,” notes the technologist Andrew Ng. “But it is exceedingly difficult to get access to someone else’s data. Thus data, rather than software, is the defensible barrier for many businesses.”

We may think we get a fair deal, offering our data as the price of sharing puppy pictures. By other metrics, we are being victimized: In the largest technology companies, the share of income going to labor is only about 5 to 15 percent, Mr. Posner and Mr. Weyl write. That’s way below Walmart’s 80 percent. Consumer data amounts to work they get free….

The big question, of course, is how we get there from here. My guess is that it would be naïve to expect Google and Facebook to start paying for user data of their own accord, even if that improved the quality of the information. Could policymakers step in, somewhat the way the European Commission did, demanding that technology companies compute the value of consumer data?…(More)”.

Data-Driven Regulation and Governance in Smart Cities

Curated on Posted on by Stefaan Verhulst

Chapter by Sofia Ranchordas and Abram Klop in Berlee, V. Mak, E. Tjong Tjin Tai (Eds), Research Handbook on Data Science and Law (Edward Elgar, 2018): “This paper discusses the concept of data-driven regulation and governance in the context of smart cities by describing how these urban centres harness these technologies to collect and process information about citizens, traffic, urban planning or waste production. It describes how several smart cities throughout the world currently employ data science, big data, AI, Internet of Things (‘IoT’), and predictive analytics to improve the efficiency of their services and decision-making.

Furthermore, this paper analyses the legal challenges of employing these technologies to influence or determine the content of local regulation and governance. It explores in particular three specific challenges: the disconnect between traditional administrative law frameworks and data-driven regulation and governance, the effects of the privatization of public services and citizen needs due to the growing outsourcing of smart cities technologies to private companies; and the limited transparency and accountability that characterizes data-driven administrative processes. This paper draws on a review of interdisciplinary literature on smart cities and offers illustrations of data-driven regulation and governance practices from different jurisdictions….(More)”.

No One Owns Data

Curated on Posted on by Stefaan Verhulst

Paper by Lothar Determann: “Businesses, policy makers, and scholars are calling for property rights in data. They currently focus particularly on the vast amounts of data generated by connected cars, industrial machines, artificial intelligence, toys and other devices on the Internet of Things (IoT). This data is personal to numerous parties who are associated with a connected device, for example, the driver of a connected car, its owner and passengers, as well as other traffic participants. Manufacturers, dealers, independent providers of auto parts and services, insurance companies, law enforcement agencies and many others are also interested in this data. Various parties are actively staking their claims to data on the Internet of Things, as they are mining data, the fuel of the digital economy.

Stakeholders in digital markets often frame claims, negotiations and controversies regarding data access as one of ownership. Businesses regularly assert and demand that they own data. Individual data subjects also assume that they own data about themselves. Policy makers and scholars focus on how to redistribute ownership rights to data. Yet, upon closer review, it is very questionable whether data is—or should be—subject to any property rights. This article unambiguously answers the question in the negative, both with respect to existing law and future lawmaking, in the United States as in the European Union, jurisdictions with notably divergent attitudes to privacy, property and individual freedoms….

The article begins with a brief review of the current landscape of the Internet of Things notes explosive growth of data pools generated by connected devices, artificial intelligence, big data analytics tools and other information technologies. Part 1 lays the foundation for examining concrete current legal and policy challenges in the remainder of the article. Part 2 supplies conceptual differentiation and definitions with respect to “data” and “information” as the subject of rights and interests. Distinctions and definitional clarity serve as the basis for examining the purposes and reach of existing property laws in Part 3, including real property, personal property and intellectual property laws. Part 4 analyzes the effect of data-related laws that do not grant property rights. Part 5 examines how the interests of the various stakeholders are protected or impaired by the current framework of data-related laws to identify potential gaps that could warrant additional property rights. Part 6 examines policy considerations for and against property rights in data. Part 7 concludes that no one owns data and no one should own data….(More)”.

Do Academic Journals Favor Researchers from Their Own Institutions?

Curated on Posted on by Stefaan Verhulst

Yaniv Reingewertz and Carmela Lutmar at Harvard Business Review: “Are academic journals impartial? While many would suggest that academic journals work for the advancement of knowledge and science, we show this is not always the case. In a recent study, we find that two international relations (IR) journals favor articles written by authors who share the journal’s institutional affiliation. We term this phenomenon “academic in-group bias.”

In-group bias is a well-known phenomenon that is widely documented in the psychological literature. People tend to favor their group, whether it is their close family, their hometown, their ethnic group, or any other group affiliation. Before our study, the evidence regarding academic in-group bias was scarce, with only one studyfinding academic in-group bias in law journals. Studies from economics found mixedresults. Our paper provides evidence of academic in-group bias in IR journals, showing that this phenomenon is not specific to law. We also provide tentative evidence which could potentially resolve the conflict in economics, suggesting that these journals might also exhibit in-group bias. In short, we show that academic in-group bias is general in nature, even if not necessarily large in scope….(More)”.

Online Political Microtargeting: Promises and Threats for Democracy

Curated on Posted on by Stefaan Verhulst

Frederik Zuiderveen Borgesius et al in Utrecht Law Review: “Online political microtargeting involves monitoring people’s online behaviour, and using the collected data, sometimes enriched with other data, to show people-targeted political advertisements. Online political microtargeting is widely used in the US; Europe may not be far behind.

This paper maps microtargeting’s promises and threats to democracy. For example, microtargeting promises to optimise the match between the electorate’s concerns and political campaigns, and to boost campaign engagement and political participation. But online microtargeting could also threaten democracy. For instance, a political party could, misleadingly, present itself as a different one-issue party to different individuals. And data collection for microtargeting raises privacy concerns. We sketch possibilities for policymakers if they seek to regulate online political microtargeting. We discuss which measures would be possible, while complying with the right to freedom of expression under the European Convention on Human Rights….(More)”.

Data journalism and the ethics of publishing Twitter data

Curated on Posted on by Stefaan Verhulst

Matthew L. Williams at Data Driven Journalism: “Collecting and publishing data collected from social media sites such as Twitter are everyday practices for the data journalist. Recent findings from Cardiff University’s Social Data Science Lab question the practice of publishing Twitter content without seeking some form of informed consent from users beforehand. Researchers found that tweets collected around certain topics, such as those related to terrorism, political votes, changes in the law and health problems, create datasets that might contain sensitive content, such as extreme political opinion, grossly offensive comments, overly personal revelations and threats to life (both to oneself and to others). Handling these data in the process of analysis (such as classifying content as hateful and potentially illegal) and reporting has brought the ethics of using social media in social research and journalism into sharp focus.

Ethics is an issue that is becoming increasingly salient in research and journalism using social media data. The digital revolution has outpaced parallel developments in research governance and agreed good practice. Codes of ethical conduct that were written in the mid twentieth century are being relied upon to guide the collection, analysis and representation of digital data in the twenty-first century. Social media is particularly ethically challenging because of the open availability of the data (particularly from Twitter). Many platforms’ terms of service specifically state users’ data that are public will be made available to third parties, and by accepting these terms users legally consent to this. However, researchers and data journalists must interpret and engage with these commercially motivated terms of service through a more reflexive lens, which implies a context sensitive approach, rather than focusing on the legally permissible uses of these data.

Social media researchers and data journalists have experimented with data from a range of sources, including Facebook, YouTube, Flickr, Tumblr and Twitter to name a few. Twitter is by far the most studied of all these networks. This is because Twitter differs from other networks, such as Facebook, that are organised around groups of ‘friends’, in that it is more ‘open’ and the data (in part) are freely available to researchers. This makes Twitter a more public digital space that promotes the free exchange of opinions and ideas. Twitter has become the primary space for online citizens to publicly express their reaction to events of national significance, and also the primary source of data for social science research into digital publics.

The Twitter streaming API provides three levels of data access: the free random 1% that provides ~5M tweets daily and the random 10% and 100% (chargeable or free to academic researchers upon request). Datasets on social interactions of this scale, speed and ease of access have been hitherto unrealisable in the social sciences and journalism, and have led to a flood of journal articles and news pieces, many of which include tweets with full text content and author identity without informed consent. This is presumably because of Twitter’s ‘open’ nature, which leads to the assumption that ‘these are public data’ and using it does not require the rigor and scrutiny of an ethical oversight. Even when these data are scrutinised, journalists don’t need to be convinced by the ‘public data’ argument, due to the lack of a framework to evaluate the potential harms to users. The Social Data Science Lab takes a more ethically reflexive approach to the use of social media data in social research, and carefully considers users’ perceptions, online context and the role of algorithms in estimating potentially sensitive user characteristics.

A recent Lab survey conducted into users’ perceptions of the use of their social media posts found the following:

  • 94% were aware that social media companies had Terms of Service
  • 65% had read the Terms of Service in whole or in part
  • 76% knew that when accepting Terms of Service they were giving permission for some of their information to be accessed by third parties
  • 80% agreed that if their social media information is used in a publication they would expect to be asked for consent
  • 90% agreed that if their tweets were used without their consent they should be anonymized…(More)”.

Just and Unjust Leaks: When to Spill Secrets

Curated on Posted on by Stefaan Verhulst

Michael Walzer at Foreign Affairs: “All governments, all political parties, and all politicians keep secrets and tell lies. Some lie more than others, and those differences are important, but the practice is general. And some lies and secrets may be justified, whereas others may not. Citizens, therefore, need to know the difference between just and unjust secrets and between just and unjust deception before they can decide when it may be justifiable for someone to reveal the secrets or expose the lies—when leaking confidential information, releasing classified documents, or blowing the whistle on misconduct may be in the public interest or, better, in the interest of democratic government.

Revealing official secrets and lies involves a form of moral risk-taking: whistleblowers may act out of a sense of duty or conscience, but the morality of their actions can be judged only by their fellow citizens, and only after the fact. This is often a difficult judgment to make—and has probably become more difficult in the Trump era.

LIES AND DAMNED LIES

A quick word about language: “leaker” and “whistleblower” are overlapping terms, but they aren’t synonyms. A leaker, in this context, anonymously reveals information that might embarrass officials or open up the government’s internal workings to unwanted public scrutiny. In Washington, good reporters cultivate sources inside every presidential administration and every Congress and hope for leaks. A whistleblower reveals what she believes to be immoral or illegal official conduct to her bureaucratic superiors or to the public. Certain sorts of whistle-blowing, relating chiefly to mismanagement and corruption, are protected by law; leakers are not protected, nor are whistleblowers who reveal state secrets…(More)”.

Free Speech in the Filter Age

Curated on Posted on by Stefaan Verhulst
Alexandra Borchardt at Project Syndicate: “In a democracy, the rights of the many cannot come at the expense of the rights of the few. In the age of algorithms, government must, more than ever, ensure the protection of vulnerable voices, even erring on victims’ side at times.

Germany’s Network Enforcement Act – according to which social-media platforms like Facebook and YouTube could be fined €50 million ($63 million) for every “obviously illegal” post within 24 hours of receiving a notification – has been controversial from the start. After it entered fully into effect in January, there was a tremendous outcry, with critics from all over the political map arguing that it was an enticement to censorship. Government was relinquishing its powers to private interests, they protested.

So, is this the beginning of the end of free speech in Germany?

Of course not. To be sure, Germany’s Netzwerkdurchsetzungsgesetz (or NetzDG) is the strictest regulation of its kind in a Europe that is growing increasingly annoyed with America’s powerful social-media companies. And critics do have some valid points about the law’s weaknesses. But the possibilities for free expression will remain abundant, even if some posts are deleted mistakenly.

The truth is that the law sends an important message: democracies won’t stay silent while their citizens are exposed to hateful and violent speech and images – content that, as we know, can spur real-life hate and violence. Refusing to protect the public, especially the most vulnerable, from dangerous content in the name of “free speech” actually serves the interests of those who are already privileged, beginning with the powerful companies that drive the dissemination of information.

Speech has always been filtered. In democratic societies, everyone has the right to express themselves within the boundaries of the law, but no one has ever been guaranteed an audience. To have an impact, citizens have always needed to appeal to – or bypass – the “gatekeepers” who decide which causes and ideas are relevant and worth amplifying, whether through the media, political institutions, or protest.

The same is true today, except that the gatekeepers are the algorithms that automatically filter and rank all contributions. Of course, algorithms can be programmed any way companies like, meaning that they may place a premium on qualities shared by professional journalists: credibility, intelligence, and coherence.

But today’s social-media platforms are far more likely to prioritize potential for advertising revenue above all else. So the noisiest are often rewarded with a megaphone, while less polarizing, less privileged voices are drowned out, even if they are providing the smart and nuanced perspectives that can truly enrich public discussions….(More)”.

An AI That Reads Privacy Policies So That You Don’t Have To

Curated on Posted on by Stefaan Verhulst

Andy Greenberg at Wired: “…Today, researchers at Switzerland’s Federal Institute of Technology at Lausanne (EPFL), the University of Wisconsin and the University of Michigan announced the release of Polisis—short for “privacy policy analysis”—a new website and browser extension that uses their machine-learning-trained app to automatically read and make sense of any online service’s privacy policy, so you don’t have to.

In about 30 seconds, Polisis can read a privacy policy it’s never seen before and extract a readable summary, displayed in a graphic flow chart, of what kind of data a service collects, where that data could be sent, and whether a user can opt out of that collection or sharing. Polisis’ creators have also built a chat interface they call Pribot that’s designed to answer questions about any privacy policy, intended as a sort of privacy-focused paralegal advisor. Together, the researchers hope those tools can unlock the secrets of how tech firms use your data that have long been hidden in plain sight….

Polisis isn’t actually the first attempt to use machine learning to pull human-readable information out of privacy policies. Both Carnegie Mellon University and Columbia have made their own attempts at similar projects in recent years, points out NYU Law Professor Florencia Marotta-Wurgler, who has focused her own research on user interactions with terms of service contracts online. (One of her own studies showed that only .07 percent of users actually click on a terms of service link before clicking “agree.”) The Usable Privacy Policy Project, a collaboration that includes both Columbia and CMU, released its own automated tool to annotate privacy policies just last month. But Marotta-Wurgler notes that Polisis’ visual and chat-bot interfaces haven’t been tried before, and says the latest project is also more detailed in how it defines different kinds of data. “The granularity is really nice,” Marotta-Wurgler says. “It’s a way of communicating this information that’s more interactive.”…(More)”.