Lawless Surveillance


Paper by Barry Friedman: “Here in the United States, policing agencies are engaging in mass collection of personal data, building a vast architecture of surveillance. License plate readers collect our location information. Mobile forensics data terminals suck in the contents of cell phones during traffic stops. CCTV maps our movements. Cheap storage means most of this is kept for long periods of time—sometimes into perpetuity. Artificial intelligence makes searching and mining the data a snap. For most of us whose data is collected, stored, and mined, there is no suspicion whatsoever of wrongdoing.

This growing network of surveillance is almost entirely unregulated. It is, in short, lawless. The Fourth Amendment touches almost none of it, either because what is captured occurs in public, and so is supposedly “knowingly exposed,” or because of doctrine that shields information collected from third parties. It is unregulated by statutes because legislative bodies—when they even know about these surveillance systems—see little profit in taking on the police.

In the face of growing concern over such surveillance, this Article argues there is a constitutional solution sitting in plain view. In virtually every other instance in which personal information is collected by the government, courts require that a sound regulatory scheme be in place before information collection occurs. The rulings on the mandatory nature of regulation are remarkably similar, no matter under which clause of the Constitution collection is challenged.

This Article excavates this enormous body of precedent and applies it to the problem of government mass data collection. It argues that before the government can engage in such surveillance, there must be a regulatory scheme in place. And by changing the default rule from allowing police to collect absent legislative prohibition, to banning collection until there is legislative action, legislatures will be compelled to act (or there will be no surveillance). The Article defines what a minimally-acceptable regulatory scheme for mass data collection must include, and shows how it can be grounded in the Constitution…(More)”.

Citizens can effectively monitor the integrity of their elections: Evidence from Colombia


Paper by Natalia Garbiras-Díaz and Mateo Montenegro: “ICT-enabled monitoring tools effectively encourage citizens to oversee their elections and reduce fraud

Despite many efforts by governments and international organizations to guarantee free and fair elections, in many democracies, electoral integrity continues to be threatened. Irregularities including fraud, vote buying or voter intimidation reduce political accountability, which can distort the allocation of public goods and services (Hicken 2011, Khemani 2015). 

But why is it so hard to prevent and curb electoral irregularities? While traditional strategies such as the deployment of electoral observers and auditors have proven effective (Hyde 2010, Enikolopov et al. 2013, Leefers and Vicente 2019), these are difficult to scale up and involve large investments in the training, security and transportation of personnel to remote and developing areas.

In Garbiras-Díaz and Montenegro (2022), we designed and implemented a large-scale field experiment during the election period in Colombia to study an innovative and light-touch strategy that circumvents many of these costs. We examine whether citizens can effectively oversee elections through online platforms, and demonstrate that delegating monitoring to citizens can provide a cost-effective alternative to more traditional strategies. Moreover, with growing access to the internet in developing countries reducing the barriers to online monitoring, this strategy is scalable and can be particularly impactful. Our results show how citizens can be encouraged to monitor elections, and, more importantly, illustrate how this form of monitoring can prevent politicians from using electoral irregularities to undermine the integrity of elections…(More)”.

All Democracy Is Global


Article by  Larry Diamond: “The world is mired in a deep, diffuse, and protracted democratic recession. According to Freedom House, 2021 was the 16th consecutive year in which more countries declined in freedom than gained. Tunisia, the sole democracy to emerge from the Arab Spring protests that began in 2010, is morphing into a dictatorship. In countries as diverse as Bangladesh, Hungary, and Turkey, elections have long ceased to be democratic. Autocrats in Algeria, Belarus, Ethiopia, Sudan, Turkey, and Zimbabwe have clung to power despite mounting public demands for democratization. In Africa, seven democracies have slid back into autocracy since 2015, including Benin and Burkina Faso.

Democracy is looking shaky even in countries that hold free and fair elections. In emerging-market behemoths such as Brazil, India, and Mexico, democratic institutions and norms are under attack. Brazilian President Jair Bolsonaro has made threats of an autogolpe (self-coup) and a possible return to military rule if he does not win reelection in October. Indian Prime Minister Narendra Modi has steadily chipped away at press freedoms, minority rights, judicial independence, the integrity of the civil service, and the autonomy of civil society. Mexican President Andrés Manuel López Obrador has attempted to silence critics and remove democratic checks and balances.

Democratic prospects have risen and fallen in decades past, but they now confront a formidable new problem: democracy is at risk in the very country that has traditionally been its most ardent champion. Over the past dozen years, the United States has experienced one of the biggest declines in political rights and civil liberties of any country measured by the Freedom House annual survey. The Economist now ranks the United States as a “flawed democracy” behind Spain, Costa Rica, and Chile. U.S. President Donald Trump deserves much of the blame: he abused presidential power on a scale unprecedented in U.S. history and, after being voted out of office, propagated the “Big Lie” of election fraud and incited the violent rioters who stormed the U.S. Capitol on January 6, 2021. But American democracy was in peril before Trump assumed office, with rising polarization exposing acute flaws in American democratic institutions. The Electoral College, the representational structure of the Senate, the Senate filibuster, the brazen gerrymandering of House districts, and lifetime appointments to the Supreme Court have all made it possible for a political minority to exert prolonged outsize influence.

Can a country in the throes of its own democratic decay do anything to arrest the broader global decline? For many, the answer is no…(More)”.

The case for lotteries as a tiebreaker of quality in research funding


Editorial at Nature: “Earlier this month, the British Academy, the United Kingdom’s national academy for humanities and social sciences, introduced an innovative process for awarding small research grants. The academy will use the equivalent of a lottery to decide between funding applications that its grant-review panels consider to be equal on other criteria, such as the quality of research methodology and study design.

Using randomization to decide between grant applications is relatively new, and the British Academy is in a small group of funders to trial it, led by the Volkswagen Foundation in Germany, the Austrian Science Fund and the Health Research Council of New Zealand. The Swiss National Science Foundation (SNSF) has arguably gone the furthest: it decided in late 2021 to use randomization in all tiebreaker cases across its entire grant portfolio of around 880 million Swiss francs (US$910 million).

Other funders should consider whether they should now follow in these footsteps. That’s because it is becoming clear that randomization is a fairer way to allocate grants when applications are too close to call, as a study from the Research on Research Institute in London shows (see go.nature.com/3s54tgw). Doing so would go some way to assuage concerns, especially in early-career researchers and those from historically marginalized communities, about the lack of fairness when grants are allocated using peer review.

The British Academy/Leverhulme small-grants scheme distributes around £1.5 million (US$1.7 million) each year in grants of up to £10,000 each. These are valuable despite their relatively small size, especially for researchers starting out. The academy’s grants can be used only for direct research expenses, but small grants are also typically used to fund conference travel or to purchase computer equipment or software. Funders also use them to spot promising research talent for future (or larger) schemes. For these reasons and more, small grants are competitive — the British Academy says it is able to fund only 20–30% of applications in each funding round…(More)”.

Artificial Intelligence Needs Both Pragmatists and Blue-Sky Visionaries


Essay by Ben Shneiderman: “Artificial intelligence thinkers seem to emerge from two communities. One is what I call blue-sky visionaries who speculate about the future possibilities of the technology, invoking utopian fantasies to generate excitement. Blue-sky ideas are compelling but are often clouded over by unrealistic visions and the ethical challenges of what can and should be built.

In contrast, what I call muddy-boots pragmatists are problem- and solution-focused. They want to reduce the harms that widely used AI-infused systems can create. They focus on fixing biased and flawed systems, such as in facial recognition systems that often mistakenly identify people as criminals or violate privacy. The pragmatists want to reduce deadly medical mistakes that AI can make, and steer self-driving cars to be safe-driving cars. Their goal is also to improve AI-based decisions about mortgage loans, college admissions, job hiring and parole granting.

As a computer science professor with a long history of designing innovative applications that have been widely implemented, I believe that the blue-sky visionaries would benefit by taking the thoughtful messages of the muddy-boots realists. Combining the work of both camps is more likely to produce the beneficial outcomes that will lead to successful next-generation technologies.

While the futuristic thinking of the blue-sky speculators sparks our awe and earns much of the funding, muddy-boots thinking reminds us that some AI applications threaten privacy, spread misinformation and are decidedly racistsexist and otherwise ethically dubious. Machines are undeniably part of our future, but will they serve all future humans equally? I think the caution and practicality of the muddy-boots camp will benefit humanity in the short and long run by ensuring diversity and equality in the development of the algorithms that increasingly run our day-to-day lives. If blue-sky thinkers integrate the concerns of muddy-boots realists into their designs, they can create future technologies that are more likely to advance human values, rights and dignity…(More)”.

Social capital: measurement and associations with economic mobility


Paper by Raj Chetty et al: “Social capital—the strength of an individual’s social network and community—has been identified as a potential determinant of outcomes ranging from education to health. However, efforts to understand what types of social capital matter for these outcomes have been hindered by a lack of social network data. Here, in the first of a pair of papers, we use data on 21 billion friendships from Facebook to study social capital. We measure and analyse three types of social capital by ZIP (postal) code in the United States: (1) connectedness between different types of people, such as those with low versus high socioeconomic status (SES); (2) social cohesion, such as the extent of cliques in friendship networks; and (3) civic engagement, such as rates of volunteering. These measures vary substantially across areas, but are not highly correlated with each other. We demonstrate the importance of distinguishing these forms of social capital by analysing their associations with economic mobility across areas. The share of high-SES friends among individuals with low SES—which we term economic connectedness—is among the strongest predictors of upward income mobility identified to date Other social capital measures are not strongly associated with economic mobility. If children with low-SES parents were to grow up in counties with economic connectedness comparable to that of the average child with high-SES parents, their incomes in adulthood would increase by 20% on average. Differences in economic connectedness can explain well-known relationships between upward income mobility and racial segregation, poverty rates, and inequality. To support further research and policy interventions, we publicly release privacy-protected statistics on social capital by ZIP code at https://www.socialcapital.org…(More)”.

Supporting peace negotiations in the Yemen war through machine learning


Paper by Miguel Arana-Catania, Felix-Anselm van Lier and Rob Procter: “Today’s conflicts are becoming increasingly complex, fluid, and fragmented, often involving a host of national and international actors with multiple and often divergent interests. This development poses significant challenges for conflict mediation, as mediators struggle to make sense of conflict dynamics, such as the range of conflict parties and the evolution of their political positions, the distinction between relevant and less relevant actors in peace-making, or the identification of key conflict issues and their interdependence. International peace efforts appear ill-equipped to successfully address these challenges. While technology is already being experimented with and used in a range of conflict related fields, such as conflict predicting or information gathering, less attention has been given to how technology can contribute to conflict mediation. This case study contributes to emerging research on the use of state-of-the-art machine learning technologies and techniques in conflict mediation processes. Using dialogue transcripts from peace negotiations in Yemen, this study shows how machine-learning can effectively support mediating teams by providing them with tools for knowledge management, extraction and conflict analysis. Apart from illustrating the potential of machine learning tools in conflict mediation, the article also emphasizes the importance of interdisciplinary and participatory, cocreation methodology for the development of context-sensitive and targeted tools and to ensure meaningful and responsible implementation…(More)”.

Learning to Share: Lessons on Data-Sharing from Beyond Social Media


Paper by CDT: “What role has social media played in society? Did it influence the rise of Trumpism in the U.S. and the passage of Brexit in the UK? What about the way authoritarians exercise power in India or China? Has social media undermined teenage mental health? What about its role in building social and community capital, promoting economic development, and so on?

To answer these and other important policy-related questions, researchers such as academics, journalists, and others need access to data from social media companies. However, this data is generally not available to researchers outside of social media companies and, where it is available, it is often insufficient, meaning that we are left with incomplete answers.

Governments on both sides of the Atlantic have passed or proposed legislation to address the problem by requiring social media companies to provide certain data to vetted researchers (Vogus, 2022a). Researchers themselves have thought a lot about the problem, including the specific types of data that can further public interest research, how researchers should be vetted, and the mechanisms companies can use to provide data (Vogus, 2022b).

For their part, social media companies have sanctioned some methods to share data to certain types of researchers through APIs (e.g., for researchers with university affiliations) and with certain limitations (such as limits on how much and what types of data are available). In general, these efforts have been insufficient. In part, this is due to legitimate concerns such as the need to protect user privacy or to avoid revealing company trade secrets.  But, in some cases, the lack of sharing is due to other factors such as lack of resources or knowledge about how to share data effectively or resistance to independent scrutiny.

The problem is complex but not intractable. In this report, we look to other industries where companies share data with researchers through different mechanisms while also addressing concerns around privacy. In doing so, our analysis contributes to current public and corporate discussions about how to safely and effectively share social media data with researchers. We review experiences based on the governance of clinical trials, electricity smart meters, and environmental impact data…(More)”

What competencies do public sector officials need to enhance national digital transformations?


Report by the Broadband Commission for Sustainable Development: “The Broadband Commission Working Group on AI Capacity Building has leveraged a multi-stakeholder leadership model to assess the critical capacity needs for public sector digital transformation, including from a developing country perspective. From interviews with policymakers, global and regional expert consultations and evaluation of current international practices, the Working Group has developed three competency domains and nine recommendations. The output is a competency framework for civil servants, spelling out the Artificial Intelligence and Digital Transformation Competencies needed today…(More)”

New WHO policy requires sharing of all research data


Press release: “Science and public health can benefit tremendously from sharing and reuse of health data. Sharing data allows us to have the fullest possible understanding of health challenges, to develop new solutions, and to make decisions using the best available evidence.

The Research for Health department has helped spearhead the launch of a new policy from the Science Division which covers all research undertaken by or with support from WHO. The goal is to make sure that all research data is shared equitably, ethically and efficiently. Through this policy, WHO indicates its commitment to transparency in order to reach the goal of one billion more people enjoying better health and well-being.

The WHO policy is accompanied by practical guidance to enable researchers to develop and implement a data management and sharing plan, before the research has even started. The guide provides advice on the technical, ethical and legal considerations to ensure that data, even patient data, can be shared for secondary analysis without compromising personal privacy.  Data sharing is now a requirement for research funding awarded by WHO and TDR. 

“We have seen the problems caused by the lack of data sharing on COVID-19,” said Dr. Soumya Swaminathan, WHO Chief Scientist. “When data related to research activities are shared ethically, equitably and efficiently, there are major gains for science and public health.”

The policy to share data from all research funded or conducted by WHO, and practical guidance to do so, can be found here…(More)”.