Stefaan Verhulst
Paper by Nardine Alnemr: “Challenges in attaining deliberative democratic ideals – such as inclusion, authenticity and consequentiality – in wider political systems have driven the development of artificially-designed citizen deliberation. These designed deliberations, however, are expert-driven. Whereas they may achieve ‘deliberativeness’, their design and implementation are undemocratic and limit deliberative democracy’s emancipatory goals. This is relevant in respect to the role of facilitation. In online deliberation, algorithms and artificial actors replace the central role of human facilitators. The detachment of such designed settings from wider contexts is particularly troubling from a democratic perspective. Digital technologies in online deliberation are not developed in a manner consistent with democratic ideals and are not being amenable to scrutiny by citizens. I discuss the theoretical and the practical blind spots of algorithmic facilitation. Based on these, I present recommendations to democratise the design and implementation of online deliberation with a focus on chatbots as facilitators….(More)”.
Book by Volker Boehme-Neßler: “This book argues that in the digital era, a reinvention of democracy is urgently necessary. It discusses the mounting evidence showing that digitalisation is pushing classical parliamentary democracy to its limits, offering examples such as how living in a filter bubble and debating with political bots is profoundly changing democratic communication, making it more emotional, hysterical even, and less rational. It also explores how classical democracy involves long, slow thinking and decision processes, which don’t fit to the ever-increasing speed of the digital world, and examines the technical developments some fear will lead to governance by algorithms.In the digitalised world, democracy no longer functions as it has in the past. This does not mean waving goodbye to democracy – instead we need to reinvent it. How this could work is the central theme of this book….(More)”.
The University of Warwick: “Researchers from the University of Warwick, Imperial College London, EPFL (Lausanne) and Sciteb Ltd have found a mathematical means of helping regulators and business manage and police Artificial Intelligence systems’ biases towards making unethical, and potentially very costly and damaging commercial choices—an ethical eye on AI.
Artificial intelligence (AI) is increasingly deployed in commercial situations. Consider for example using AI to set prices of insurance products to be sold to a particular customer. There are legitimate reasons for setting different prices for different people, but it may also be profitable to ‘game’ their psychology or willingness to shop around.
The AI has a vast number of potential strategies to choose from, but some are unethical and will incur not just moral cost but a significant potential economic penalty as stakeholders will apply some penalty if they find that such a strategy has been used—regulators may levy significant fines of billions of Dollars, Pounds or Euros and customers may boycott you—or both.
So in an environment in which decisions are increasingly made without human intervention, there is therefore a very strong incentive to know under what circumstances AI systems might adopt an unethical strategy and reduce that risk or eliminate entirely if possible.
Mathematicians and statisticians from University of Warwick, Imperial, EPFL and Sciteb Ltd have come together to help business and regulators creating a new “Unethical Optimization Principle” and provide a simple formula to estimate its impact. They have laid out the full details in a paper bearing the name “An unethical optimization principle“, published in Royal Society Open Science on Wednesday 1st July 2020….(More)”.
In Custodia Legis Library of Congress: “It appears that COVID-19 will not go away any time soon. As there is currently no known cure or vaccine against it, countries have to find other ways to prevent and mitigate the spread of this infectious disease. Many countries have turned to electronic measures to provide general information and advice on COVID-19, allow people to check symptoms, trace contacts and alert people who have been in proximity to an infected person, identify “hot spots,” and track compliance with confinement measures and stay-at-home orders.
The Global Legal Research Directorate (GLRD) of the Law Library of Congress recently completed research on the kind of electronic measures countries around the globe are employing to fight the spread of COVID-19 and their potential privacy and data protection implications. We are excited to share with you the report that resulted from this research, Regulating Electronic Means to Fight the Spread of COVID-19. The report covers 23 selected jurisdictions, namely Argentina, Australia, Brazil, China, England, France, Iceland, India, Iran, Israel, Italy, Japan, Mexico, Norway, Portugal, the Russian Federation, South Africa, South Korea, Spain, Taiwan, Turkey, the United Arab Emirates, and the European Union (EU).
The surveys found that dedicated coronavirus apps that are downloaded to an individual’s mobile phone (particularly contact tracing apps), the use of anonymized mobility data, and creating electronic databases were the most common electronic measures. Whereas the EU recommends the use of voluntary apps because of the “high degree of intrusiveness” of mandatory apps, some countries take a different approach and require installing an app for people who enter the country from abroad, people who return to work, or people who are ordered to quarantine.
However, these electronic measures also raise privacy and data protection concerns, in particular as they relate to sensitive health data. The surveys discuss the different approaches countries have taken to ensure compliance with privacy and data protection regulations, such as conducting rights impact assessments before the measures were deployed or having data protection agencies conduct an assessment after deployment.
The map below shows which jurisdictions have adopted COVID-19 contact tracing apps and the technologies they use.
Map shows COVID-19 contact tracing apps in selected jurisdictions. Created by Susan Taylor, Law Library of Congress, based on surveys in “Regulating Electronic Means to Fight the Spread of COVID-19” (Law Library of Congress, June 2020). This map does not cover other COVID-19 apps that use GPS/geolocation….(More)”.
Paper by Tina Eliassi-Rad et al: “Political scientists have conventionally assumed that achieving democracy is a one-way ratchet. Only very recently has the question of “democratic backsliding” attracted any research attention. We argue that democratic instability is best understood with tools from complexity science. The explanatory power of complexity science arises from several features of complex systems. Their relevance in the context of democracy is discussed. Several policy recommendations are offered to help (re)stabilize current systems of representative democracy…(More)”.
About: “With initial support from the Bill & Melinda Gates Foundation, we are designing and developing a new purpose-built, multi-disciplinary, cross-institutional data platform to enable the reliable identification, measurement, and tracking of cultural narratives over long time scales across multiple cultural domains and media types, like online news, broadcast television, talk radio, and social media. Designed to provide better understanding of the cultural environment for key social issues, and more effective measurement of efforts to alter these environments, the goal is to help narrative change makers reach smarter strategic decisions and better understand their work’s impact.
We’re starting by looking at narratives around poverty and economic mobility in the U.S. . .(More)
Book edited by Sabina Leonelli and Niccolò Tempini: “This groundbreaking, open access volume analyses and compares data practices across several fields through the analysis of specific cases of data journeys. It brings together leading scholars in the philosophy, history and social studies of science to achieve two goals: tracking the travel of data across different spaces, times and domains of research practice; and documenting how such journeys affect the use of data as evidence and the knowledge being produced.
The volume captures the opportunities, challenges and concerns involved in making data move from the sites in which they are originally produced to sites where they can be integrated with other data, analysed and re-used for a variety of purposes. The in-depth study of data journeys provides the necessary ground to examine disciplinary, geographical and historical differences and similarities in data management, processing and interpretation, thus identifying the key conditions of possibility for the widespread data sharing associated with Big and Open Data.
The chapters are ordered in sections that broadly correspond to different stages of the journeys of data, from their generation to the legitimisation of their use for specific purposes. Additionally, the preface to the volume provides a variety of alternative “roadmaps” aimed to serve the different interests and entry points of readers; and the introduction provides a substantive overview of what data journeys can teach about the methods and epistemology of research….(More)”.
Paper by Cass Sunstein: “Do people from benefit from food labels? When? By how much? Public officials face persistent challenges in answering these questions. In various nations, they use four different approaches: they refuse to do so on the ground that quantification is not feasible; they engage in breakeven analysis; they project end-states, such as economic savings or health outcomes; and they estimate willingness-to-pay for the relevant information. Each of these approaches runs into strong objections. In principle, the willingness-to-pay question has important advantages. But for those who has that question, there is a serious problem. In practice, people often lack enough information to give a sensible answer to the question how much they would be willing to pay for (more) information. People might also suffer from behavioral biases (including present bias and optimistic bias). And when preferences are labile or endogenous, even an informed and unbiased answer to the willingness to pay question may fail to capture the welfare consequences, because people may develop new tastes and values as a result of information….(More)”.
Paper by Federica Lucivero et al : “Data-driven digital technologies are often presented in policy agendas as contributing to the goal of sustainable development by providing information to reduce energy consumption and offering a green alternative to industries and behaviour with a higher environmental footprint. However, it is widely acknowledged in the context of environmental research that Information and Communication Technologies (ICT) in general, and data centres and cloud computing in particular, have a heavy footprint featuring a high consumption of non-renewable energy, waste production and carbon dioxide emissions. In spite of this, environmental issues have so far figured only sparsely in both policy initiatives supporting data-driven digital initiatives, as well as in recent ethics and governance scholarly literature discussing the data-driven revolution. We convened an interdisciplinary workshop to map out the current conceptual landscape on the environmental impacts of data-driven technologies, and to explore how ethical thinking can contribute to it. In this commentary, we discuss the main themes that emerged and our call for action….(More)”.
Paper by Rainer Diaz-Bone et al: “The phenomenon of big data does not only deeply affect current societies but also poses crucial challenges to social research. This article argues for moving towards a sociology of social research in order to characterize the new qualities of big data and its deficiencies. We draw on the neopragmatist approach of economics of convention (EC) as a conceptual basis for such a sociological perspective.
This framework suggests investigating processes of quantification in their interplay with orders of justifications and logics of evaluation. Methodological issues such as the question of the “quality of big data” must accordingly be discussed in their deep entanglement with epistemic values, institutional forms, and historical contexts and as necessarily implying political issues such as who controls and has access to data infrastructures. On this conceptual basis, the article uses the example of health to discuss the challenges of big data analysis for social research.
Phenomena such as the rise of new and massive privately owned data infrastructures, the economic valuation of huge amounts of connected data, or the movement of “quantified self” are presented as indications of a profound transformation compared to established forms of doing social research. Methodological and epistemological, but also institutional and political, strategies are presented to face the risk of being “outperformed” and “replaced” by big data analysis as they are already done in big US American and Chinese Internet enterprises. In conclusion, we argue that the sketched developments have important implications both for research practices and methods teaching in the era of big data…(More)”.