Law, AI, and Human Rights

Curated on Posted on by Stefaan Verhulst

Article by John Croker: “Technology has been at the heart of two injustices that courts have labelled significant miscarriages of justice. The first example will be familiar now to many people in the UK: colloquially known as the ‘post office’ or ‘horizon’ scandal. The second is from Australia, where the Commonwealth Government sought to utilise AI to identify overpayment in the welfare system through what is colloquially known as the ‘Robodebt System’. The first example resulted in the most widespread miscarriage of justice in the UK legal system’s history. The second example was labelled “a shameful chapter” in government administration in Australia and led to the government unlawfully asserting debts amounting to $1.763 billion against 433,000 Australians, and is now the subject of a Royal Commission seeking to identify how public policy failures could have been made on such a significant scale.

Both examples show that where technology and AI goes wrong, the scale of the injustice can result in unprecedented impacts across societies….(More)”.

Is Participatory Budgeting Coming to a Local Government Near You?

Curated on Posted on by Stefaan Verhulst

Article by Elizabeth Daigneau:”.. It’s far from a new idea, and you’ve probably been reading about it for years, but participatory budgeting has slowly been growing since it was first introduced in the U.S. in Chicago in 2009. Many anticipate it is about to see a boom as billions of federal dollars continue to pour into local communities…

But with the influx to local communities of billions in federal dollars through the American Rescue Plan Act (ARPA), the Infrastructure Investment and Jobs Act, and the Inflation Reduction Act, many experts think the time is ripe to adopt the tool.

“The stakes are high in restoring and rebuilding our nation’s crumbling civic, political and economic infrastructures,” wrote Hollie Russon Gilman and Lizbeth Lucero of New America’s Political Reform Program in a recent op-ed. “The long overdue improvements needed in America’s cities and countries call for remodeling how we govern and allocate federal funds across the country.”

ARPA dollars prompted the city of Cleveland to push for a participatory budgeting pilot. 

“Cleveland is a city that has one of the higher poverty rates for a city of their size in the United States. They have over 30 percent of their population living below the poverty line,” Kristania De Leon, co-executive director at the Participatory Budgeting Project, said on The Laura Flanders Show’s podcast last July. “So when they found out that they were getting American Rescue Plan Act funds allocated to their municipal government, they said, ‘Wait a minute, this is a huge influx of relatively flexible spending, where’s it going to go and who gets to have a say?’”

A community-led push culminated in a proposal by Cleveland Mayor Justin M. Bibb to the city council last year that $5 million in ARPA funds be allocated to pilot the first citywide participatory budgeting process in its history.

ARPA dollars also elicited Nashville’s city council to allocate $10 million this year to its participatory budgeting program, which is in its third year.

In general, there have been several high-profile participatory budgeting projects in the last year. 

Seattle’s project claims to be the biggest participatory budgeting process ever in the United States. The city council earmarked approximately $30 million in the 2021 budget to run a participatory budgeting process. The goal is to spend the money on initiatives that reduce police violence, reduce crime, and “creating true community safety through community-led safety programs and new investments.”

And in September, New York City Mayor Eric Adams announced the launch of the first-ever citywide participatory budgeting process. The program builds on a 2021 project that engaged residents of the 33 neighborhoods hardest hit by Covid-19 in a $1.3 million participatory budgeting process. The new program invites all New Yorkers, ages 11 and up, to decide how to spend $5 million of mayoral expense funding to address local community needs citywide…(More)”.

When Concerned People Produce Environmental Information: A Need to Re-Think Existing Legal Frameworks and Governance Models?

Curated on Posted on by Stefaan Verhulst

Paper by Anna Berti Suman, Mara Balestrini, Muki Haklay, and Sven Schade: “When faced with an environmental problem, locals are often among the first to act. Citizen science is increasingly one of the forms of participation in which people take action to help solve environmental problems that concern them. This implies, for example, using methods and instruments with scientific validity to collect and analyse data and evidence to understand the problem and its causes. Can the contribution of environmental data by citizens be articulated as a right? In this article, we explore these forms of productive engagement with a local matter of concern, focussing on their potential to challenge traditional allocations of responsibilities. Taking mostly the perspective of the European legal context, we identify an existing gap between the right to obtain environmental information, granted at present by the Aarhus Convention, and “a right to contribute information” and have that information considered by appointed institutions. We also explore what would be required to effectively practise this right in terms of legal and governance processes, capacities, and infrastructures, and we propose a flexible framework to implement it. Situated at the intersection of legal and governance studies, this article builds on existing literature on environmental citizen science, and on its interplay with law and governance. Our methodological approach combines literature review with legal analysis of the relevant conventions and national rules. We conclude by reflecting on the implications of our analysis, and on the benefits of this legal innovation, potentially fostering data altruism and an active citizenship, and shielding ordinary people against possible legal risks…(More)”.

How Design is Governance

Curated on Posted on by Stefaan Verhulst

Essay by Amber Case: “At a fundamental level, all design is governance. We encounter inconveniences like this coffee shop every day, both offline and in the apps we use. But it’s not enough to say it’s the result of bad design. It’s also a result of governance decisions made on behalf of the customers during the design process.

Michel Foucault talked about governance as structuring the field of action for others. Governance is the processes, systems, and principles through which a group, organization, or society is managed and controlled.

Design not only shapes how a product or service will be used, but also restricts or frustrates people’s existing or emergent choices, even when they’re not a user themselves. My neighbor at the cafe, who now has a Mac power cord snaked under her feet, can attest to that.

In a coffee shop, we’re lucky that we can move chairs around or talk with other customers. But when it comes to apps, most people cannot move buttons on interfaces. We’re stuck.

When we create designs, we’re basically defining what is possible or at least highly encouraged within the context of our products. We’re also defining what is discouraged.

To illustrate, let’s revisit this same cafe from a governance perspective…(More)”.

Could a Global “Wicked Problems Agency” Incentivize Data Sharing?

Curated on Posted on by Stefaan Verhulst

Paper by Susan Ariel Aaronson: “Global data sharing could help solve “wicked” problems (problems such as climate change, terrorism and global poverty that no one knows how to solve without creating further problems). There is no one or best way to address wicked problems because they have many different causes and manifest in different contexts. By mixing vast troves of data, policy makers and researchers may find new insights and strategies to address these complex problems. National and international government agencies and large corporations generally control the use of such data, and the world has made little progress in encouraging cross-sectoral and international data sharing. This paper proposes a new international cloud-based organization, the “Wicked Problems Agency,” to catalyze both data sharing and data analysis in the interest of mitigating wicked problems. This organization would work to prod societal entities — firms, individuals, civil society groups and governments — to share and analyze various types of data. The Wicked Problems Agency could provide a practical example of how data sharing can yield both economic and public good benefits…(More)”.

The Data Delusion

Curated on Posted on by Stefaan Verhulst

Jill Lepore at The New Yorker: “…The move from a culture of numbers to a culture of data began during the Second World War, when statistics became more mathematical, largely for the sake of becoming more predictive, which was necessary for wartime applications involving everything from calculating missile trajectories to cracking codes. “This was not data in search of latent truths about humanity or nature,” Wiggins and Jones write. “This was not data from small experiments, recorded in small notebooks. This was data motivated by a pressing need—to supply answers in short order that could spur action and save lives.” That work continued during the Cold War, as an instrument of the national-security state. Mathematical modelling, increased data-storage capacity, and computer simulation all contributed to the pattern detection and prediction in classified intelligence work, military research, social science, and, increasingly, commerce.

Despite the benefit that these tools provided, especially to researchers in the physical and natural sciences—in the study of stars, say, or molecules—scholars in other fields lamented the distorting effect on their disciplines. In 1954, Claude Lévi-Strauss argued that social scientists need “to break away from the hopelessness of the ‘great numbers’—the raft to which the social sciences, lost in an ocean of figures, have been helplessly clinging.” By then, national funding agencies had shifted their priorities. The Ford Foundation announced that although it was interested in the human mind, it was no longer keen on non-predictive research in fields like philosophy and political theory, deriding such disciplines as “polemical, speculative, and pre-scientific.” The best research would be, like physics, based on “experiment, the accumulation of data, the framing of general theories, attempts to verify the theories, and prediction.” Economics and political science became predictive sciences; other ways of knowing in those fields atrophied.

The digitization of human knowledge proceeded apace, with libraries turning books first into microfiche and microfilm and then—through optical character recognition, whose origins date to the nineteen-thirties—into bits and bytes. The field of artificial intelligence, founded in the nineteen-fifties, at first attempted to sift through evidence in order to identify the rules by which humans reason. This approach hit a wall, in a moment known as “the knowledge acquisition bottleneck.” The breakthrough came with advances in processing power and the idea of using the vast stores of data that had for decades been compounding in the worlds of both government and industry to teach machines to teach themselves by detecting patterns: machines, learning…(More)”.

China’s fake science industry: how ‘paper mills’ threaten progress

Curated on Posted on by Stefaan Verhulst

Article by Eleanor Olcott, Clive Cookson and Alan Smith at the Financial Times: “…Over the past two decades, Chinese researchers have become some of the world’s most prolific publishers of scientific papers. The Institute for Scientific Information, a US-based research analysis organisation, calculated that China produced 3.7mn papers in 2021 — 23 per cent of global output — and just behind the 4.4mn total from the US.

At the same time, China has been climbing the ranks of the number of times a paper is cited by other authors, a metric used to judge output quality. Last year, China surpassed the US for the first time in the number of most cited papers, according to Japan’s National Institute of Science and Technology Policy, although that figure was flattered by multiple references to Chinese research that first sequenced the Covid-19 virus genome.

The soaring output has sparked concern in western capitals. Chinese advances in high-profile fields such as quantum technology, genomics and space science, as well as Beijing’s surprise hypersonic missile test two years ago, have amplified the view that China is marching towards its goal of achieving global hegemony in science and technology.

That concern is a part of a wider breakdown of trust in some quarters between western institutions and Chinese ones, with some universities introducing background checks on Chinese academics amid fears of intellectual property theft.

But experts say that China’s impressive output masks systemic inefficiencies and an underbelly of low-quality and fraudulent research. Academics complain about the crushing pressure to publish to gain prized positions at research universities…(More)”.

The limits of expert judgment: Lessons from social science forecasting during the pandemic

Curated on Posted on by Stefaan Verhulst

Article by Cendri Hutcherson  Michael Varnum Imagine being a policymaker at the beginning of the COVID-19 pandemic. You have to decide which actions to recommend, how much risk to tolerate and what sacrifices to ask your citizens to bear.

Who would you turn to for an accurate prediction about how people would react? Many would recommend going to the experts — social scientists. But we are here to tell you this would be bad advice.

As psychological scientists with decades of combined experience studying decision-making, wisdom, expert judgment and societal change, we hoped social scientists’ predictions would be accurate and useful. But we also had our doubts.

Our discipline has been undergoing a crisis due to failed study replications and questionable research practices. If basic findings can’t be reproduced in controlled experiments, how confident can we be that our theories can explain complex real-world outcomes?

To find out how well social scientists could predict societal change, we ran the largest forecasting initiative in our field’s history using predictions about change in the first year of the COVID-19 pandemic as a test case….

Our findings, detailed in peer-reviewed papers in Nature Human Behaviour and in American Psychologist, paint a sobering picture. Despite the causal nature of most theories in the social sciences, and the fields’ emphasis on prediction in controlled settings, social scientists’ forecasts were generally not very good.

In both papers, we found that experts’ predictions were generally no more accurate than those made by samples of the general public. Further, their predictions were often worse than predictions generated by simple statistical models.

Our studies did still give us reasons to be optimistic. First, forecasts were more accurate when teams had specific expertise in the domain they were making predictions in. If someone was an expert in depression, for example, they were better at predicting societal trends in depression.

Second, when teams were made up of scientists from different fields working together, they tended to do better at forecasting. Finally, teams that used simpler models to generate their predictions and made use of past data generally outperformed those that didn’t.

These findings suggest that, despite the poor performance of the social scientists in our studies, there are steps scientists can take to improve their accuracy at this type of forecasting….(More)”.

What We Gain from More Behavioral Science in the Global South

Curated on Posted on by Stefaan Verhulst

Article by Pauline Kabitsis and Lydia Trupe: “In recent years, the field has been critiqued for applying behavioral science at the margins, settling for small but statistically significant effect sizes. Critics have argued that by focusing our efforts on nudging individuals to increase their 401(k) contributions or to reduce their so-called carbon footprint, we have ignored the systemic drivers of important challenges, such as fundamental flaws in the financial system and corporate responsibility for climate change. As Michael Hallsworth points out, however, the field may not be willfully ignoring these deeper challenges, but rather investing in areas of change that are likely easier to move, measure, and secure funding.

It’s been our experience working in the Global South that nudge-based solutions can provide short-term gains within current systems, but for lasting impact a focus beyond individual-level change is required. This is because the challenges in the Global South typically navigate fundamental problems, like enabling women’s reproductive choice, combatting intimate partner violence and improving food security among the world’s most vulnerable populations.

Our work at Common Thread focuses on improving behaviors related to health, like encouraging those persistently left behind to get vaccinated, and enabling Ukrainian refugees in Poland to access health and welfare services. We use a behavioral model that considers not just the individual biases that impact people’s behaviors, but the structural, social, interpersonal, and even historical context that triggers these biases and inhibits health seeking behaviors…(More)”.

Automating Public Services: Learning from Cancelled Systems

Curated on Posted on by Stefaan Verhulst

Report by Joanna Redden, Jessica Brand, Ina Sander and Harry Warne: “Pressure on public finances means that governments are trying to do more with less. Increasingly, policymakers are turning to technology to cut costs. But what if this technology doesn’t work as it should?

This report looks at the rise and fall of automated decision systems (ADS). If you’ve tried to get medical advice over the phone recently you’ve got some experience of an ADS – a computer system or algorithm designed to help or replace human decision making. These sorts of systems are being used by governments to consider when and how to act. The stakes are high. For example, they’re being used to try to detect crime and spot fraud, and to determine whether child protective services should act.

This study identifies 61 occasions across Australia, Canada, Europe, New Zealand and the United States when ADS projects were cancelled or paused. From this evidence, we’ve made recommendations designed to increase transparency and to protect communities and individuals…(More)”.