Democracy is dead: long live democracy!

Curated on Posted on by Stefaan Verhulst

Helen Margetts in OpenDemocracy: “In the course of the World Forum for Democracy 2017, and in political commentary more generally, social media are blamed for almost everything that is wrong with democracy. They are held responsible for pollution of the democratic environment through fake news, junk science, computational propaganda and aggressive micro-targeting. In turn, these phenomena have been blamed for the rise of populism, political polarization, far-right extremism and radicalisation, waves of hate against women and minorities, post-truth, the end of representative democracy, fake democracy and ultimately, the death of democracy. It feels like the tirade of relatives of the deceased at the trial of the murderer. It is extraordinary how much of this litany is taken almost as given, the most gloomy prognoses as certain visions of the future.

Yet actually we know rather little about the relationship between social media and democracy. Because ten years of the internet and social media have challenged everything we thought we knew.  They have injected volatility and instability into political systems, bringing a continual cast of unpredictable events. They bring into question normative models of democracy – by which we might understand the macro-level shifts at work  – seeming to make possible the highest hopes and worst fears of republicanism and pluralism.

They have transformed the ecology of interest groups and mobilizations. They have challenged élites and ruling institutions, bringing regulatory decay and policy sclerosis. They create undercurrents of political life that burst to the surface in seemingly random ways, making fools of opinion polls and pollsters. And although the platforms themselves generate new sources of real-time transactional data that might be used to understand and shape this changed environment, most of this data is proprietary and inaccessible to researchers, meaning that the revolution in big data and data science has passed by democracy research.

What do we know? The value of tiny acts

Certainly digital media are entwined with every democratic institution and the daily lives of citizens. When deciding whether to vote, to support, to campaign, to demonstrate, to complain – digital media are with us at every step, shaping our information environment and extending our social networks by creating hundreds or thousands of ‘weak ties’, particularly for users of social media platforms such as Facebook or Instagram….(More)”.

Technopolitics in the Age of Big Data

Curated on Posted on by Stefaan Verhulst

Chapter by Stefania Milan and Miren Gutierrez in the book on Networks, Movements and Technopolitics in Latin America: ‘Big data’ offer novel opportunities for civic engagement and foster the emergence of data activism, a form of technopolitics from the ground–up that assumes people’s active engagement with data for empowerment. Proactive data activism, in particular, sees citizens taking advantage of the possibilities offered by data for advocacy and social change. This chapter combines social movement studies and media studies to analyze the emergence of proactive data activism in the Latin American continent. Analyzing the case of InfoAmazonia—a project blending citizen participation and data analysis to generate news about the endangered Amazon region—this chapter adds to our understanding of technopolitics as a way to reinterpret reality, empower people, facilitate collective action, and challenge the establish social norms embedded in our understanding of technology and social change. Furthermore, it contributes to the understanding of how data can restructure social reality, and in particular civil society action….(More) (Other chapters)”.

Participatory Grant Making: Has its Time Come?

Curated on Posted on by Stefaan Verhulst

Paper by Cynthia Gibson for the Ford Foundation: “…During the past decade, all sectors of society have faced heightened demand for greater accountability and transparency. People have become more distrustful of established institutions, they are demanding more information about issues and decisions afecting them and their families and communities, and they want more voice in decision-making processes. Technological innovation also has created new possibilities — and new pressures — for organizations and institutions to become more democratic by involving the public in their work.

Philanthropy is not immune from these trends. While for decades, philanthropy was seen as endowed foundations set up by the rich, recent years have seen a surge in crowdfunding, giving circles, donor-advised funds, and a panoply of digital giving platforms that allow anyone to be a philanthropist. Alongside these, traditions of giving from within communities that existed long before philanthropy became professionalized have become more prominent.

Philanthropy and other felds also are being reshaped by the attitudes and capacities of a new generation of young people who have grown up with the Internet and embrace its culture of transparency and bottom-up action. Additionally, there is a growing awareness that many public challenges are exceedingly complex and won’t respond to one-shot solutions from experts or institutions working on their own.

These and other trends refect a backlash against the “establishment” occurring in politics, higher education, the media, and other felds in which elite interests are perceived to have drowned out the concerns of ordinary people. Americans of all stripes and political persuasions have come to believe they have little say in guiding public decisions and improving the health and well-being of their communities..

This paper assesses the embrace of participatory approaches to date by philanthropy and other felds. In assessing philanthropy’s record, the paper fnds examples of individual foundations and networks of funders that are experimenting with participatory approaches. It also, however, fnds that there is a great deal of talk about participation in the feld but comparatively little commitment to integrating these practices into foundations’ strategies and activities, and especially their cultures, over the long term…(More)”.

Manipulating Social Media to Undermine Democracy

Curated on Posted on by Stefaan Verhulst

Freedom of the Net 2017 Report by the Freedom House: “Governments around the world have dramatically increased their efforts to manipulate information on social media over the past year. The Chinese and Russianregimes pioneered the use of surreptitious methods to distort online discussions and suppress dissent more than a decade ago, but the practice has since gone global. Such state-led interventions present a major threat to the notion of the internet as a liberating technology.

Online content manipulation contributed to a seventh consecutive year of overall decline in internet freedom, along with a rise in disruptions to mobile internet service and increases in physical and technical attacks on human rights defenders and independent media.

Nearly half of the 65 countries assessed in Freedom on the Net 2017 experienced declines during the coverage period, while just 13 made gains, most of them minor. Less than one-quarter of users reside in countries where the internet is designated Free, meaning there are no major obstacles to access, onerous restrictions on content, or serious violations of user rights in the form of unchecked surveillance or unjust repercussions for legitimate speech.

The use of “fake news,” automated “bot” accounts, and other manipulation methods gained particular attention in the United States. While the country’s online environment remained generally free, it was troubled by a proliferation of fabricated news articles, divisive partisan vitriol, and aggressive harassment of many journalists, both during and after the presidential election campaign.

Russia’s online efforts to influence the American election have been well documented, but the United States was hardly alone in this respect. Manipulation and disinformation tactics played an important role in elections in at least 17 other countries over the past year, damaging citizens’ ability to choose their leaders based on factual news and authentic debate. Although some governments sought to support their interests and expand their influence abroad—as with Russia’s disinformation campaigns in the United States and Europe—in most cases they used these methods inside their own borders to maintain their hold on power.

Venezuela, the Philippines, and Turkey were among 30 countries where governments were found to employ armies of “opinion shapers” to spread government views, drive particular agendas, and counter government critics on social media. The number of governments attempting to control online discussions in this manner has risen each year since Freedom House began systematically tracking the phenomenon in 2009. But over the last few years, the practice has become significantly more widespread and technically sophisticated, with bots, propaganda producers, and fake news outlets exploiting social media and search algorithms to ensure high visibility and seamless integration with trusted content.

Unlike more direct methods of censorship, such as website blocking or arrests for internet activity, online content manipulation is difficult to detect. It is also more difficult to combat, given its dispersed nature and the sheer number of people and bots employed for this purpose… (More)”.

Democracy Needs a Reboot for the Age of Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

Katharine Dempsey at The Nation: “…A healthy modern democracy requires ordinary citizens to participate in public discussions about rapidly advancing technologies. We desperately need new policies, regulations, and safety nets for those displaced by machines. With computing power accelerating exponentially, the scale of AI’s significance is still not being fully internalized. The 2017 McKinsey Global Initiative report “A Future that Works” predicts that AI and advanced robotics could automate roughly half of all work globally by 2055, but, McKinsey notes, “this could happen up to 20 years earlier or later depending on the various factors, in addition to other wider economic conditions.”

Granted, the media are producing more articles focused on artificial intelligence, but too often these pieces veer into hysterics. Wired magazine labeled this year’s coverage “The Great Tech Panic of 2017.” We need less fear-mongering and more rational conversation. Dystopian narratives, while entertaining, can also be disorienting. Skynet from the Terminatormovies is not imminent. But that doesn’t mean there aren’t hazards ahead….

Increasingly, to thoughtfully discuss ethics, politics, or business, the general population needs to pay attention to AI. In 1989, Ursula Franklin, the distinguished German-Canadian experimental physicist, delivered a series of lectures titled “The Real World of Technology.” Franklin opened her lectures with an important observation: “The viability of technology, like democracy, depends in the end on the practice of justice and on the enforcements of limits to power.”

For Franklin, technology is not a neutral set of tools; it can’t be divorced from society or values. Franklin further warned that “prescriptive technologies”—ones that isolate tasks, such as factory-style work—find their way into our social infrastructures and create modes of compliance and orthodoxy. These technologies facilitate top-down control….(More)”.

Blocked: Why Some Companies Restrict Data Access to Reduce Competition and How Open APIs Can Help

Curated on Posted on by Stefaan Verhulst

Daniel Castro and Michael Steinberg at the Center for Data Innovation: “Over the past few years, some scholars, advocates, and policymakers have argued that businesses which possess large quantities of data, such as social media companies, present inherent competition concerns. These concerns are misplaced for a number of reasons, one being that competitors can often obtain similar data from other sources. But in some industries and markets, a small number of firms have exclusive access to particular datasets, and they exploit their market power to limit access to that data through both technical and administrative means without any legitimate business justification. This type of anti-competitive behavior limits innovation and hurts consumers, and when these problematic practices occur, policymakers should intervene….

To promote competition, innovation, and consumer benefits in these three industries, policymakers should take the following steps:

  • In real estate, anti-trust regulators at the Department of Justice (DOJ) and the Federal Trade Commission (FTC) should investigate whether MLS actions to block data from online listing companies are collusive and exclusionary, and state policymakers should require brokers to provide open access to their real estate listings;
  • In the financial services, the Consumer Finance Protection Bureau (CFPB) should establish guidance for financial institutions to allow third parties to access customer data, securely and with the customer’s permission, through open APIs;
  • In the air travel industry, the Department of Transportation (DOT) should establish rules requiring airlines to make all ticket pricing information publicly available in a standardized format and prohibit unfair marketing practices that limit distribution of this information to certain companies….(More)”.

The Illusion of Freedom in the Digital Age

Curated on Posted on by Stefaan Verhulst

Mark Leonard at Project Syndicate: “Over the last few weeks, media around the world have been saturated with stories about how technology is destroying politics. In autocracies like China, the fear is of ultra-empowered Big Brother states, like that in George Orwell’s 1984. In democracies like the United States, the concern is that tech companies will continue to exacerbate political and social polarization by facilitating the spread of disinformation and creating ideological “filter bubbles,” leading to something resembling Aldous Huxley’s Brave New World….

Big tech companies, worth more than some countries’ GDP, seek to maximize profits, not social welfare. Yet, at a time when attention is supplanting money as the most valuable commodity, the impact of their decisions is far-reaching. James Williams, a Google engineer turned academic, argues that the digital age has unleashed fierce competition for our attention, and few have benefited more than Trump, who is for the Internet what Ronald Reagan was for television….

In the digital age, the biggest danger is not that technology will put free and autocratic societies increasingly at odds with one another. It is that the worst fears of both Orwell and Huxley will become manifest in both types of system, creating a different kind of dystopia. With many of their deepest desires being met, citizens will have the illusion of freedom and empowerment. In reality, their lives, the information they consume, and the choices they make will be determined by algorithms and platforms controlled by unaccountable corporate or government elites….(More)”.

Better Data for Better Policy: Accessing New Data Sources for Statistics Through Data Collaboratives

Curated on Posted on by Stefaan Verhulst

Medium Blog by Stefaan Verhulst: “We live in an increasingly quantified world, one where data is driving key business decisions. Data is claimed to be the new competitive advantage. Yet, paradoxically, even as our reliance on data increases and the call for agile, data-driven policy making becomes more pronounced, many Statistical Offices are confronted with shrinking budgets and an increased demand to adjust their practices to a data age. If Statistical Offices fail to find new ways to deliver “evidence of tomorrow”, by leveraging new data sources, this could mean that public policy may be formed without access to the full range of available and relevant intelligence — as most business leaders have. At worst, a thinning evidence base and lack of rigorous data foundation could lead to errors and more “fake news,” with possibly harmful public policy implications.

While my talk was focused on the key ways data can inform and ultimately transform the full policy cycle (see full presentation here), a key premise I examined was the need to access, utilize and find insight in the vast reams of data and data expertise that exist in private hands through the creation of new kinds of public and private partnerships or “data collaboratives” to establish more agile and data-driven policy making.

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Applied to statistics, such approaches have already shown promise in a number of settings and countries. Eurostat itself has, for instance, experimented together with Statistics Belgium, with leveraging call detail records provided by Proximus to document population density. Statistics Netherlands (CBS) recently launched a Center for Big Data Statistics (CBDS)in partnership with companies like Dell-EMC and Microsoft. Other National Statistics Offices (NSOs) are considering using scanner data for monitoring consumer prices (Austria); leveraging smart meter data (Canada); or using telecom data for complementing transportation statistics (Belgium). We are now living undeniably in an era of data. Much of this data is held by private corporations. The key task is thus to find a way of utilizing this data for the greater public good.

Value Proposition — and Challenges

There are several reasons to believe that public policy making and official statistics could indeed benefit from access to privately collected and held data. Among the value propositions:

  • Using private data can increase the scope and breadth and thus insights offered by available evidence for policymakers;
  • Using private data can increase the quality and credibility of existing data sets (for instance, by complementing or validating them);
  • Private data can increase the timeliness and thus relevance of often-outdated information held by statistical agencies (social media streams, for example, can provide real-time insights into public behavior); and
  • Private data can lower costs and increase other efficiencies (for example, through more sophisticated analytical methods) for statistical organizations….(More)”.

The Unexpected Power of Google-Doc Activism

Curated on Posted on by Stefaan Verhulst

 at The Cut: “Earlier this month, after major news outlets published detailed allegations of abuse and harassment by Harvey Weinstein, an anonymous woman created a public Google spreadsheet titled Shitty Media Men. It was a space for other anonymous women to name men in media who had exhibited bad behavior ranging from sleazy DMs to rape. There were just a few rules: “Please never name an accuser,” it said at the top. “Please never share this spreadsheet with a man.” The document was live for less than 48 hours, in which time it was shared with dozens of women — and almost certainly a few men.

The goal of the document was not public accountability, according to its creator. It was to privately warn other women, especially those who are not well connected in the industry, about which men in their profession to avoid. This is information women have always shared among themselves, at after-work drinks and in surreptitious chat messages, but the Google Doc sought to collect it in a way that transcended any one woman’s immediate social network. And because the goal was to occupy a kind of middle ground — not public, not quite private either — with little oversight, it made perfect sense that the information appeared as a Google Doc.

Especially in the year since the election, the shared Google Doc has become a familiar way station on the road to collective political action. Shared documents are ideal for collecting resources in one place quickly and easily, without gatekeepers, because they’re free and easy to use. They have been used to crowdsource tweets and hashtags for pushing back against Trump’s first State of the Union address, to spread information on local town-hall events with members of Congress, and to collect vital donation and evacuee info for people affected by the fires in Northern California. A shared Google Doc allows collaborators to work together across time zones and is easy to update as circumstances change.

But perhaps most notably, a Google Doc can be technically public while functionally quite private, allowing members of a like-minded community to reach beyond their immediate friends and collaborators while avoiding the abuse and trolling that comes with publishing on other platforms….(More)”.

Our laws don’t do enough to protect our health data

Curated on Posted on by Stefaan Verhulst

 at the Conversation: “A particularly sensitive type of big data is medical big data. Medical big data can consist of electronic health records, insurance claims, information entered by patients into websites such as PatientsLikeMeand more. Health information can even be gleaned from web searches, Facebook and your recent purchases.

Such data can be used for beneficial purposes by medical researchers, public health authorities, and healthcare administrators. For example, they can use it to study medical treatments, combat epidemics and reduce costs. But others who can obtain medical big data may have more selfish agendas.

I am a professor of law and bioethics who has researched big data extensively. Last year, I published a book entitled Electronic Health Records and Medical Big Data: Law and Policy.

I have become increasingly concerned about how medical big data might be used and who could use it. Our laws currently don’t do enough to prevent harm associated with big data.

What your data says about you

Personal health information could be of interest to many, including employers, financial institutions, marketers and educational institutions. Such entities may wish to exploit it for decision-making purposes.

For example, employers presumably prefer healthy employees who are productive, take few sick days and have low medical costs. However, there are laws that prohibit employers from discriminating against workers because of their health conditions. These laws are the Americans with Disabilities Act (ADA) and the Genetic Information Nondiscrimination Act. So, employers are not permitted to reject qualified applicants simply because they have diabetes, depression or a genetic abnormality.

However, the same is not true for most predictive information regarding possible future ailments. Nothing prevents employers from rejecting or firing healthy workers out of the concern that they will later develop an impairment or disability, unless that concern is based on genetic information.

What non-genetic data can provide evidence regarding future health problems? Smoking status, eating preferences, exercise habits, weight and exposure to toxins are all informative. Scientists believe that biomarkers in your blood and other health details can predict cognitive decline, depression and diabetes.

Even bicycle purchases, credit scores and voting in midterm elections can be indicators of your health status.

Gathering data

How might employers obtain predictive data? An easy source is social media, where many individuals publicly post very private information. Through social media, your employer might learn that you smoke, hate to exercise or have high cholesterol.

Another potential source is wellness programs. These programs seek to improve workers’ health through incentives to exercise, stop smoking, manage diabetes, obtain health screenings and so on. While many wellness programs are run by third party vendors that promise confidentiality, that is not always the case.

In addition, employers may be able to purchase information from data brokers that collect, compile and sell personal information. Data brokers mine sources such as social media, personal websites, U.S. Census records, state hospital records, retailers’ purchasing records, real property records, insurance claims and more. Two well-known data brokers are Spokeo and Acxiom.

Some of the data employers can obtain identify individuals by name. But even information that does not provide obvious identifying details can be valuable. Wellness program vendors, for example, might provide employers with summary data about their workforce but strip away particulars such as names and birthdates. Nevertheless, de-identified information can sometimes be re-identified by experts. Data miners can match information to data that is publicly available….(More)”.