Book by Yves Sintomer: “Electoral democracies are struggling. Sintomer, in this instructive book, argues for democratic innovations. One such innovation is using random selection to create citizen bodies with advisory or decisional political power. ‘Sortition’ has a long political history. Coupled with elections, it has represented an important yet often neglected dimension of Republican and democratic government, and has been reintroduced in the Global North, China and Mexico. The Government of Chance explores why sortation is returning, how it is coupled with deliberation, and why randomly selected ‘minipublics’ and citizens’ assemblies are flourishing. Relying on a growing international and interdisciplinary literature, Sintomer provides the first systematic and theoretical reconstruction of the government of chance from Athens to the present. At what conditions can it be rational? What lessons can be drawn from history? The Government of Chance therefore clarifies the democratic imaginaries at stake: deliberative, antipolitical, and radical, making a plaidoyer for the latter….(More)”.
How Democracy Can Win
Essay by Samantha Power: “…At the core of democratic theory and practice is respect for the dignity of the individual. But among the biggest errors many democracies have made since the Cold War is to view individual dignity primarily through the prism of political freedom without being sufficiently attentive to the indignity of corruption, inequality, and a lack of economic opportunity.
This was not a universal blind spot: a number of political figures, advocates, and individuals working at the grassroots level to advance democratic progress presciently argued that economic inequality could fuel the rise of populist leaders and autocratic governments that pledged to improve living standards even as they eroded freedoms. But too often, the activists, lawyers, and other members of civil society who worked to strengthen democratic institutions and protect civil liberties looked to labor movements, economists, and policymakers to address economic dislocation, wealth inequality, and declining wages rather than building coalitions to tackle these intersecting problems.
Democracy suffered as a result. Over the past two decades,as economic inequality rose, polls showed that people in rich and poor countries alike began to lose faith in democracy and worry that young people would end up worse off than they were, giving populists and ethnonationalists an opening to exploit grievances and gain a political foothold on every continent.
Moving forward, we must look at all economic programming that respects democratic norms as a form of democracy assistance. When we help democratic leaders provide vaccines to their people, bring down inflation or high food prices, send children to school, or reopen markets after a natural disaster, we are demonstrating—in a way that a free press or vibrant civil society cannot always do—that democracy delivers. And we are making it less likely that autocratic forces will take advantage of people’s economic hardship.
Nowhere is that task more important today than in societies that have managed to elect democratic reformers or throw off autocratic or antidemocratic rule through peaceful mass protests or successful political movements. These democratic bright spots are incredibly fragile. Unless reformers solidify their democratic and economic gains quickly, populations understandably grow impatient, especially if they feel that the risks they took to upend the old order have not yielded tangible dividends in their own lives. Such discontent allows opponents of democratic rule—often aided by external autocratic regimes—to wrest back control, reversing reforms and snuffing out dreams of rights-regarding self-government…(More)”.
Reclaiming Participatory Governance
Book edited by Adrian Bua and Sonia Bussu: “…offers empirical and theoretical perspectives on how the relationship between social movements and state institutions is emerging and developing through new modes of participatory governance.
One of the most interesting political developments of the past decade has been the adoption by social movements of strategies seeking to change political institutions through participatory governance. These strategies have flourished in a variety of contexts, from anti-austerity and pro-social justice protests in Spain, to movements demanding climate transition and race equality in the UK and the USA, to constitutional reforms in Belgium and Iceland. The chief ambition and challenge of these new forms of participatory governance is to institutionalise the prefigurative politics and social justice values that inspired them in the first place, by mobilising the bureaucracy to respond to their claims for reforms and rights. The authors of this volume assess how participatory governance is being transformed and explore the impact of such changes, providing timely critical reflections on: the constraints imposed by cultural, economic and political power relations on these new empowered participatory spaces; the potential of this new “wave” of participatory democracy to reimagine the relationship between citizens and traditional institutions towards more radical democratic renewal; where and how these new democratisation efforts sit within the representative state; and how tensions between the different demands of lay citizens, organised civil society and public officials are being managed….(More)”.
Your Data Is Diminishing Your Freedom
Interview by David Marchese: “It’s no secret — even if it hasn’t yet been clearly or widely articulated — that our lives and our data are increasingly intertwined, almost indistinguishable. To be able to function in modern society is to submit to demands for ID numbers, for financial information, for filling out digital fields and drop-down boxes with our demographic details. Such submission, in all senses of the word, can push our lives in very particular and often troubling directions. It’s only recently, though, that I’ve seen someone try to work through the deeper implications of what happens when our data — and the formats it’s required to fit — become an inextricable part of our existence, like a new limb or organ to which we must adapt. ‘‘I don’t want to claim we are only data and nothing but data,’’ says Colin Koopman, chairman of the philosophy department at the University of Oregon and the author of ‘‘How We Became Our Data.’’ ‘‘My claim is you are your data, too.’’ Which at the very least means we should be thinking about this transformation beyond the most obvious data-security concerns. ‘‘We’re strikingly lackadaisical,’’ says Koopman, who is working on a follow-up book, tentatively titled ‘‘Data Equals,’’ ‘‘about how much attention we give to: What are these data showing? What assumptions are built into configuring data in a given way? What inequalities are baked into these data systems? We need to be doing more work on this.’’
Can you explain more what it means to say that we have become our data? Because a natural reaction to that might be, well, no, I’m my mind, I’m my body, I’m not numbers in a database — even if I understand that those numbers in that database have real bearing on my life. The claim that we are data can also be taken as a claim that we live our lives through our data in addition to living our lives through our bodies, through our minds, through whatever else. I like to take a historical perspective on this. If you wind the clock back a couple hundred years or go to certain communities, the pushback wouldn’t be, ‘‘I’m my body,’’ the pushback would be, ‘‘I’m my soul.’’ We have these evolving perceptions of our self. I don’t want to deny anybody that, yeah, you are your soul. My claim is that your data has become something that is increasingly inescapable and certainly inescapable in the sense of being obligatory for your average person living out their life. There’s so much of our lives that are woven through or made possible by various data points that we accumulate around ourselves — and that’s interesting and concerning. It now becomes possible to say: ‘‘These data points are essential to who I am. I need to tend to them, and I feel overwhelmed by them. I feel like it’s being manipulated beyond my control.’’ A lot of people have that relationship to their credit score, for example. It’s both very important to them and very mysterious…(More)”.
The Law of AI for Good
Paper by Orly Lobel: “Legal policy and scholarship are increasingly focused on regulating technology to safeguard against risks and harms, neglecting the ways in which the law should direct the use of new technology, and in particular artificial intelligence (AI), for positive purposes. This article pivots the debates about automation, finding that the focus on AI wrongs is descriptively inaccurate, undermining a balanced analysis of the benefits, potential, and risks involved in digital technology. Further, the focus on AI wrongs is normatively and prescriptively flawed, narrowing and distorting the law reforms currently dominating tech policy debates. The law-of-AI-wrongs focuses on reactive and defensive solutions to potential problems while obscuring the need to proactively direct and govern increasingly automated and datafied markets and societies. Analyzing a new Federal Trade Commission (FTC) report, the Biden administration’s 2022 AI Bill of Rights and American and European legislative reform efforts, including the Algorithmic Accountability Act of 2022, the Data Privacy and Protection Act of 2022, the European General Data Protection Regulation (GDPR) and the new draft EU AI Act, the article finds that governments are developing regulatory strategies that almost exclusively address the risks of AI while paying short shrift to its benefits. The policy focus on risks of digital technology is pervaded by logical fallacies and faulty assumptions, failing to evaluate AI in comparison to human decision-making and the status quo. The article presents a shift from the prevailing absolutist approach to one of comparative cost-benefit. The role of public policy should be to oversee digital advancements, verify capabilities, and scale and build public trust in the most promising technologies.
A more balanced regulatory approach to AI also illuminates tensions between current AI policies. Because AI requires better, more representative data, the right to privacy can conflict with the right to fair, unbiased, and accurate algorithmic decision-making. This article argues that the dominant policy frameworks regulating AI risks—emphasizing the right to human decision-making (human-in-the-loop) and the right to privacy (data minimization)—must be complemented with new corollary rights and duties: a right to automated decision-making (human-out-of-the-loop) and a right to complete and connected datasets (data maximization). Moreover, a shift to proactive governance of AI reveals the necessity for behavioral research on how to establish not only trustworthy AI, but also human rationality and trust in AI. Ironically, many of the legal protections currently proposed conflict with existing behavioral insights on human-machine trust. The article presents a blueprint for policymakers to engage in the deliberate study of how irrational aversion to automation can be mitigated through education, private-public governance, and smart policy design…(More)”
Contextualizing Datafication in Peru: Insights from a Citizen Data Literacy Project
Paper by Katherine Reilly and Marieliv Flores: The pilot data literacy project Son Mis Datos showed volunteers how to leverage Peru’s national data protection law to request access to personal data held by Peruvian companies, and then it showed them how to audit corporate data use based on the results. While this intervention had a positive impact on data literacy, by basing it on a universalist conception of datafication, our work inadvertently reproduced the dominant data paradigm we hoped to challenge. This paper offers a retrospective analysis of Son Mis Datos, and explores the gap between van Dijck’s widely cited theory of datafication, and the reality of our participants’ experiences with datafication and digital transformation on the ground in Peru. On this basis, we suggest an alternative definition of datafication more appropriate to critical scholarship as the transformation of social relations around the uptake of personal data in the coordination of transactions, and propose an alternative approach to data literacy interventions that begins with the experiences of data subjects…(More)”.
Digital (In)justice in the Smart City
Book edited by Debra Mackinnon, Ryan Burns and Victoria Fast: “In the contemporary moment, smart cities have become the dominant paradigm for urban planning and administration, which involves weaving the urban fabric with digital technologies. Recently, however, the promises of smart cities have been gradually supplanted by recognition of their inherent inequalities, and scholars are increasingly working to envision alternative smart cities.
Informed by these pressing challenges, Digital (In)Justice in the Smart City foregrounds discussions of how we should think of and work towards urban digital justice in the smart city. It provides a deep exploration of the sources of injustice that percolate throughout a range of sociotechnical assemblages, and it questions whether working towards more just, sustainable, liveable, and egalitarian cities requires that we look beyond the limitations of “smartness” altogether. The book grapples with how geographies impact smart city visions and roll-outs, on the one hand, and how (unjust) geographies are produced in smart pursuits, on the other. Ultimately, Digital (In)Justice in the Smart City envisions alternative cities – smart or merely digital – and outlines the sorts of roles that the commons, utopia, and the law might take on in our conceptions and realizations of better cities…(More)”.
Models and experts: urgent questions about how we inform decisions and public policy
Blog and book by Erica Thompson: “Mathematical models are here to stay. Whether they are determining supply chain vulnerabilities, demonstrating regulatory compliance, or informing policies for a zero-carbon future, quantitative models are at the heart of modern societies. And as computers become more powerful and more readily accessible, artificial intelligence and machine learning models are also being applied in many new areas.
Given that, we urgently need to understand how best to use and work with models to make good and responsible decisions. Statistician George Box was quite right to point out that “all models are wrong”. They are necessarily simplifications of the messy reality we want to get to grips with. But many quantitative methods for working with models basically assume that the model is right, or at least that it can accurately estimate the range of plausible outcomes.
If the model is not quite perfect, we can expect some of its outputs to be wrong (not just inaccurate). In that case, the information that is offered as decision support could be misleading. We have two options here. We could remain in what I call model land and just expect to have to say “what a shame, we made the wrong decision” occasionally. In some circumstances that might be a reasonable answer, but if we are making decisions about critical infrastructure or selling a product that might be unsafe to millions of people, then we have both a legal and ethical responsibility to do better, to get out of model land and understand how relevant our model results are for the real world.
So what’s the second option? You won’t be surprised to know that it isn’t easy. In my new book, I consider some of the implications of working with imperfect models and the kinds of strategies that we need to adopt to make best use of the information they contain. One theme that I explore is the need to understand the role of expert judgement in constructing, calibrating, evaluating, and using models, and the way that that expert judgement might be shaped by our social context.
Experts make models – and that’s a very good thing, because who would want to rely on a model created by a non-expert? But their expertise is often limited, and it comes from a particular background and set of experiences. Indeed, you can often find equally qualified experts who will disagree about the right assumptions to make when constructing a model and who give different advice about how to achieve the stated aims. Then the decision-maker – probably a non-expert – will be in the difficult position of trying to adjudicate between different models from different experts, weighing up their relative credibility…(More)”.
How Data Happened: A History from the Age of Reason to the Age of Algorithms
Book by Chris Wiggins and Matthew L Jones: “From facial recognition—capable of checking people into flights or identifying undocumented residents—to automated decision systems that inform who gets loans and who receives bail, each of us moves through a world determined by data-empowered algorithms. But these technologies didn’t just appear: they are part of a history that goes back centuries, from the census enshrined in the US Constitution to the birth of eugenics in Victorian Britain to the development of Google search.
Expanding on the popular course they created at Columbia University, Chris Wiggins and Matthew L. Jones illuminate the ways in which data has long been used as a tool and a weapon in arguing for what is true, as well as a means of rearranging or defending power. They explore how data was created and curated, as well as how new mathematical and computational techniques developed to contend with that data serve to shape people, ideas, society, military operations, and economies. Although technology and mathematics are at its heart, the story of data ultimately concerns an unstable game among states, corporations, and people. How were new technical and scientific capabilities developed; who supported, advanced, or funded these capabilities or transitions; and how did they change who could do what, from what, and to whom?
Wiggins and Jones focus on these questions as they trace data’s historical arc, and look to the future. By understanding the trajectory of data—where it has been and where it might yet go—Wiggins and Jones argue that we can understand how to bend it to ends that we collectively choose, with intentionality and purpose…(More)”.
Exploring data journalism practices in Africa: data politics, media ecosystems and newsroom infrastructures
Paper by Sarah Chiumbu and Allen Munoriyarwa: “Extant research on data journalism in Africa has focused on newsroom factors and the predilections of individual journalists as determinants of the uptake of data journalism on the continent. This article diverts from this literature by examining the slow uptake of data journalism in sub- Saharan Africa through the prisms of non-newsroom factors. Drawing on in-depth interviews with prominent investigative journalists sampled from several African countries, we argue that to understand the slow uptake of data journalism on the continent; there is a need to critique the role of data politics, which encompasses state, market and existing media ecosystems across the continent. Therefore, it is necessary to move beyond newsroom-centric factors that have dominated the contemporary understanding of data journalism practices. A broader, non-newsroom conceptualisation beyond individual journalistic predilections and newsroom resources provides productive clarity on data journalism’s slow uptake on the continent. These arguments are made through the conceptual prisms of materiality, performativity and reflexivity…(More)”.