Missing Numbers

Curated on Posted on by Stefaan Verhulst

Introduction by Anna Powell-Smith of a new “blog on the data the government should collect, but doesn’t”: “…Over time, I started to notice a pattern. Across lots of different policy areas, it was impossible for governments to make good decisions because of a basic lack of data. There was always critical data that the state either didn’t collect at all, or collected so badly that it made change impossible.

Eventually, I decided that the power to not collect data is one of the most important and little-understood sources of power that governments have. This is why I’m writing Missing Numbers: to encourage others to ask “is this lack of data a deliberate ploy to get away with something”?

By refusing to amass knowledge in the first place, decision-makers exert power over over the rest of us. It’s time that this power was revealed, so we can have better conversations about what we need to know to run this country successfully.

A typical example

The government records and publishes data on how often each NHS hospital receives formal complaints. This is very helpful, because it means patients and the people who care for them can spot hospitals whose performance is worrying.

But the government simply doesn’t record data, even internally, on how often formal complaints are made about each Jobcentre. (That FOI response is from 2015, but I’ve confirmed it’s still true in 2019.) So it is impossible for it to know if some Jobcentres are being seriously mismanaged….(More)”.

Habeas Data: Privacy vs. The Rise of Surveillance Tech

Curated on Posted on by Stefaan Verhulst

Book by Cyrus Farivar: “Habeas Data shows how the explosive growth of surveillance technology has outpaced our understanding of the ethics, mores, and laws of privacy.

Award-winning tech reporter Cyrus Farivar makes the case by taking ten historic court decisions that defined our privacy rights and matching them against the capabilities of modern technology. It’s an approach that combines the charge of a legal thriller with the shock of the daily headlines.

Chapters include: the 1960s prosecution of a bookie that established the “reasonable expectation of privacy” in nonpublic places beyond your home (but how does that ruling apply now, when police can chart your every move and hear your every conversation within your own home — without even having to enter it?); the 1970s case where the police monitored a lewd caller — the decision of which is now the linchpin of the NSA’s controversial metadata tracking program revealed by Edward Snowden; and a 2010 low-level burglary trial that revealed police had tracked a defendant’s past 12,898 locations before arrest — an invasion of privacy grossly out of proportion to the alleged crime, which showed how authorities are all too willing to take advantage of the ludicrous gap between the slow pace of legal reform and the rapid transformation of technology.

A dazzling exposé that journeys from Oakland, California to the halls of the Supreme Court to the back of a squad car, Habeas Data combines deft reportage, deep research, and original interviews to offer an X-ray diagnostic of our current surveillance state….(More)”.

Belgium’s democratic experiment

Curated on Posted on by Stefaan Verhulst

David van Reybrouck in Politico: “Those looking for a solution to the wave of anger and distrust sweeping Western democracies should have a look at an experiment in European democracy taking place in a small region in eastern Belgium.

Starting in September, the parliament representing the German-speaking region of Belgium will hand some of its powers to a citizens’ assembly drafted by lot. It’ll be the first time a political institution creates a permanent structure to involve citizens in political decision making.

It’s a move Belgian media has rightly hailed as “historic.” I was in parliament the night MPs from all six parties moved past ideological differences to endorse the bill. It was a courageous move, a sign to other politicians — who tend to see their voters as a threat rather than a resource — that citizens should be trusted, not feared, or “spun.”

Nowhere else in the world will everyday citizens be so consistently involved in shaping the future of their community. In times of massive, widespread distrust of party politics, German-speaking Belgians will be empowered to put the issues they care about on the agenda, to discuss potential solutions, and to monitor the follow-up of their recommendations as they pass through parliament and government. Politicians, in turn, will be able to tap independent citizens’ panels to deliberate over thorny political issues.

This experiment is happening on a small scale: Belgium’s German-speaking community, the country’s third linguistic region, is the smallest federal entity in Europe. But its powers are comparable with those of Scotland or the German province of North Rhine-Westphalia, and the lessons of its experiment with a “people’s senate” will have implications for democrats across Europe….(More)”.

A New Way of Voting That Makes Zealotry Expensive

Curated on Posted on by Stefaan Verhulst

Peter Coy at Bloomberg Business Week: “An intriguing new tool of democracy just had its first test in the real world of politics, and it passed with flying colors.

The tool is called quadratic voting, and it’s just as nerdy as it sounds. The concept is that each voter is given a certain number of tokens—say, 100—to spend as he or she sees fit on votes for a variety of candidates or issues. Casting one vote for one candidate or issue costs one token, but two votes cost four tokens, three votes cost nine tokens, and so on up to 10 votes costing all 100 of your tokens. In other words, if you really care about one candidate or issue, you can cast up to 10 votes for him, her, or it, but it’s going to cost you all your tokens.

Quadratic voting was invented not by political scientists but by economists and others, including Glen Weyl, an economist and principal researcher at Microsoft Corp. The purpose of quadratic voting is to determine “whether the intense preferences of the minority outweigh the weak preferences of the majority,” Weyl and Eric Posner, a University of Chicago Law School professor, wrote last year in an important book called Radical Markets: Uprooting Capitalism and Democracy for a Just Society. ….

This spring, quadratic voting was used in a successful experiment by the Democratic caucus of the Colorado House of Representatives. The lawmakers used it to decide on their legislative priorities for the coming two years among 107 possible bills. (Wiredmagazine wrote about it here.)…

In this year’s experiment, the 41 lawmakers in the Democratic caucus were given 100 tokens each to allocate among the 107 bills. No one chose to spend all 100 tokens on a single bill. Many of them spread their votes around widely but thinly because it was inexpensive to do so—one vote is just one token. The top vote-getter by a wide margin turned out to be a bill guaranteeing equal pay to women for equal work. “There was clear separation” of the favorites from the also-rans, Hansen says.

The computer interface and other logistics were provided by Democracy Earth, which describes itself as a borderless community and “a global commons of self-sovereign citizens.” The lawmakers had more immediate concerns—hammering out a party agenda. “Some members were more tech-savvy,” Hansen says. “Some started skeptical but came around. I was pleasantly surprised. There was this feeling of ownership—your voice being heard.”

I recently wrote about the democratic benefits of ranked-choice voting, in which voters rank all the candidates in a race and votes are reassigned from the lowest vote-getters to the higher finishers until someone winds up with a majority. But although ranked-choice voting is gaining in popularity, it traces its roots back to the 19th century. Quadratic voting is much more of a break from the past. “This is a new idea, which is rare in economic theory, so it should be saluted as such, especially since it is accompanied by outstanding execution,” George Mason University economist Tyler Cowen wrote in 2015. (He did express some cautions about it as well.)…(More)”.

The EU Wants to Build One of the World’s Largest Biometric Databases. What Could Possibly Go Wrong?

Curated on Posted on by Stefaan Verhulst

Grace Dobush at Fortune: “China and India have built the world’s largest biometric databases, but the European Union is about to join the club.

The Common Identity Repository (CIR) will consolidate biometric data on almost all visitors and migrants to the bloc, as well as some EU citizens—connecting existing criminal, asylum, and migration databases and integrating new ones. It has the potential to affect hundreds of millions of people.

The plan for the database, first proposed in 2016 and approved by the EU Parliament on April 16, was sold as a way to better track and monitor terrorists, criminals, and unauthorized immigrants.

The system will target the fingerprints and identity data for visitors and immigrants initially, and represents the first step towards building a truly EU-wide citizen database. At the same time, though, critics argue its mere existence will increase the potential for hacks, leaks, and law enforcement abuse of the information….

The European Parliament and the European Council have promised to address those concerns, through “proper safeguards” to protect personal privacy and to regulate officers’ access to data. In 2016, they passed a law regarding law enforcement’s access to personal data, alongside General Data Protection Regulation or GDPR.

But total security is a tall order. Germany is currently dealing with multipleinstances of police officers allegedly leaking personal information to far-right groups. Meanwhile, a Swedish hacker went to prison for hacking into Denmark’s public records system in 2012 and dumping online the personal data of hundreds of thousands of citizens and migrants….(More)”.


Digital inequalities in the age of artificial intelligence and big data

Curated on Posted on by Stefaan Verhulst

Paper by Christoph Lutz: “In this literature review, I summarize key concepts and findings from the rich academic literature on digital inequalities. I propose that digital inequalities research should look more into labor‐ and big data‐related questions such as inequalities in online labor markets and the negative effects of algorithmic decision‐making for vulnerable population groups.

The article engages with the sociological literature on digital inequalities and explains the general approach to digital inequalities, based on the distinction of first‐, second‐, and third‐level digital divides. First, inequalities in access to digital technologies are discussed. This discussion is extended to emerging technologies, including the Internet‐of‐things and artificial intelligence‐powered systems such as smart speakers. Second, inequalities in digital skills and technology use are reviewed and connected to the discourse on new forms of work such as the sharing economy or gig economy. Third and finally, the discourse on the outcomes, in the form of benefits or harms, from digital technology use is taken up.

Here, I propose to integrate the digital inequalities literature more strongly with critical algorithm studies and recent discussions about datafication, digital footprints, and information privacy….(More)”.

As Surveys Falter Big Data Polling Narrows Our Societal Understanding

Curated on Posted on by Stefaan Verhulst

Kalev Leetaru at Forbes: “One of the most talked-about stories in the world of polling and survey research in recent years has been the gradual death of survey response rates and the reliability of those insights….

The online world’s perceived anonymity has offered some degree of reprieve in which online polls and surveys have often bested traditional approaches in assessing views towards society’s most controversial issues. Yet, here as well increasing public understanding of phishing and online safety are ever more problematic.

The answer has been the rise of “big data” analysis of society’s digital exhaust to fill in the gaps….

Is it truly the same answer though?

Constructing and conducting a well-designed survey means being able to ask the public exactly the questions of interest. Most importantly, it entails being able to ensure representative demographics of respondents.

An online-only poll is unlikely to accurately capture the perspectives of the three quarters of the earth’s population that the digital revolution has left behind. Even within the US, social media platforms are extraordinarily skewed.

The far greater problem is that society’s data exhaust is rarely a perfect match for the questions of greatest interest to policymakers and public.

Cellphone mobility records can offer an exquisitely detailed look at how the people of a city go about their daily lives, but beneath all that blinding light are the invisible members of society not deemed valuable to advertisers and thus not counted. Even for the urban society members whose phones are their ever-present companions, mobility data only goes so far. It can tell us that occupants of a particular part of the city during the workday spend their evenings in a particular part of the city, allowing us to understand their work/life balance, but it offers few insights into their political leanings.

One of the greatest challenges of today’s “big data” surveying is that it requires us to narrow our gaze to only those questions which can be easily answered from the data at hand.

Much as AI’s crisis of bias comes from the field’s steadfast refusal to pay for quality data, settling for highly biased free data, so too has “big data” surveying limited itself largely to datasets it can freely and easily acquire.

The result is that with traditional survey research, we are free to ask the precise questions we are most interested in. With data exhaust research, we must imperfectly shoehorn our questions into the few available metrics. With sufficient creativity it is typically possible to find some way of proxying the given question, but the resulting proxies may be highly unstable, with little understanding of when and where they may fail.

Much like how the early rise of the cluster computing era caused “big data” researchers to limit the questions they asked of their data to just those they could fit into a set of tiny machines, so too has the era of data exhaust surveying forced us to greatly restrict our understanding of society.

Most dangerously, however, big data surveying implicitly means we are measuring only the portion of society our vast commercial surveillance state cares about.

In short, we are only able to measure those deemed of greatest interest to advertisers and thus the most monetizable.

Putting this all together, the decline of traditional survey research has led to the rise of “big data” analysis of society’s data exhaust. Instead of giving us an unprecedented new view into the heartbeat of daily life, this reliance on the unintended output of our digital lives has forced researchers to greatly narrow the questions they can explore and severely skews them to the most “monetizable” portions of society.

In the end, the shift of societal understanding from precision surveys to the big data revolution has led not to an incredible new understanding of what makes us tick, but rather a far smaller, less precise and less accurate view than ever before, just our need to understand ourselves has never been greater….(More)”.

Facebook will open its data up to academics to see how it impacts elections

Curated on Posted on by Stefaan Verhulst

MIT Technology Review: “More than 60 researchers from 30 institutions will get access to Facebook user data to study its impact on elections and democracy, and how it’s used by advertisers and publishers.

A vast trove: Facebook will let academics see which websites its users linked to from January 2017 to February 2019. Notably, that means they won’t be able to look at the platform’s impact on the US presidential election in 2016, or on the Brexit referendum in the UK in the same year.

Despite this slightly glaring omission, it’s still hard to wrap your head around the scale of the data that will be shared, given that Facebook is used by 1.6 billion people every day. That’s more people than live in all of China, the most populous country on Earth. It will be one of the largest data sets on human behavior online to ever be released.

The process: Facebook didn’t pick the researchers. They were chosen by the Social Science Research Council, a US nonprofit. Facebook has been working on this project for over a year, as it tries to balance research interests against user privacy and confidentiality.

Privacy: In a blog post, Facebook said it will use a number of statistical techniques to make sure the data set can’t be used to identify individuals. Researchers will be able to access it only via a secure portal that uses a VPN and two-factor authentication, and there will be limits on the number of queries they can each run….(More)”.

Nagging misconceptions about nudge theory

Curated on Posted on by Stefaan Verhulst

Cass Sunstein at The Hill: “Nudges are private or public initiatives that steer people in particular directions but that also allow them to go their own way.

A reminder is a nudge; so is a warning. A GPS device nudges; a default rule, automatically enrolling people in some program, is a nudge.

To qualify as a nudge, an initiative must not impose significant economic incentives. A subsidy is not a nudge; a tax is not a nudge; a fine or a jail sentence is not a nudge. To count as such, a nudge must fully preserve freedom of choice.

In 2009, University of Chicago economist Richard Thaler and I co-wrote a book that drew on research in psychology and behavioral economics to help people and institutions, both public and private, improve their decision-making.

In the 10 years since “Nudge” was published, there has been an extraordinary outpouring of new thought and action, with particular reference to public policy.

Behavioral insight teams, or “nudge units” of various sorts, can be found in many nations, including Australia, Canada, Denmark, United Kingdom, the United States, the Netherlands, Germany, Singapore, Japan and Qatar.

Those teams are delivering. By making government more efficient, and by improving safety and health, they are helping to save a lot of money and a lot of lives. And in many countries, including the U.S., they don’t raise partisan hackles; both Democrats and Republicans have enthusiastically embraced them.   

Still, there are a lot of mistakes and misconceptions out there, and they are diverting attention and hence stalling progress. Here are the three big ones:

1. Nudges do not respect freedom. …

2. Nudges are based on excessive trust in government...

3. Nudges cannot achieve a whole lot.…(More)”.

Revisiting the causal effect of democracy on long-run development

Curated on Posted on by Stefaan Verhulst

Blog post by Markus Eberhardt: “In a recent paper, Acemoglu et al. (2019), henceforth “ANRR”, demonstrated a significant and large causal effect of democracy on long-run growth. By adopting a simple binary indicator for democracy, and accounting for the dynamics of development, these authors found that a shift to democracy leads to a 20% higher level of development in the long run.1

The findings are remarkable in three ways: 

  1. Previous research often emphasised that a simple binary measure for democracy was perhaps “too blunt a concept” (Persson and Tabellini 2006) to provide robust empirical evidence.
  2.  Positive effects of democracy on growth were typically only a “short-run boost” (Rodrik and Wacziarg 2005). 
  3. The empirical findings are robust across a host of empirical estimators with different assumptions about the data generating process, including one adopting a novel instrumentation strategy (regional waves of democratisation).

ANRR’s findings are important because, as they highlight in a column on Vox, there is “a belief that democracy is bad for economic growth is common in both academic political economy as well as the popular press.” For example, Posner (2010) wrote that “[d]ictatorship will often be optimal for very poor countries”. 

The simplicity of ANRR’s empirical setup, the large sample of countries, the long time horizon (1960 to 2010), and the robust positive – and remarkably stable – results across the many empirical methods they employ send a very powerful message against such doubts that democracy does cause growth.

I agree with their conclusion, but with qualifications. …(More)”.