The goal of the book is to present the latest research on the new challenges of data technologies. It will offer an overview of the social, ethical and legal problems posed by group profiling, big data and predictive analysis and of the different approaches and methods that can be used to address them. In doing so, it will help the reader to gain a better grasp of the ethical and legal conundrums posed by group profiling. The volume first maps the (...) current and emerging uses of new data technologies and clarifies the promises and dangers of group profiling in real life situations. It then balances this with an analysis of how far the current legal paradigm grants group rights to privacy and data protection, and discusses possible routes to addressing these problems. Finally, an afterword gathers the conclusions reached by the different authors and discuss future perspectives on regulating new data technologies. (shrink)

The increasing availability of digital data reflecting economic and human development, and in particular the availability of data emitted as a by-product of people’s use of technological devices and services, has both political and practical implications for the way people are seen and treated by the state and by the private sector. Yet the data revolution is so far primarily a technical one: the power of data to sort, categorise and intervene has not yet been explicitly connected to a social (...) justice agenda by the agencies and authorities involved. Meanwhile, although data-driven discrimination is advancing at a similar pace to data processing technologies, awareness and mechanisms for combating it are not. This paper posits that just as an idea of justice is needed in order to establish the rule of law, an idea of data justice – fairness in the way people are made visible, represented and treated as a result of their production of digital data – is necessary to determine ethical paths through a datafying world. Bringing together the emerging scholarly perspectives on this topic, I propose three pillars as the basis of a notion of international data justice: visibility, engagement with technology and antidiscrimination. These pillars integrate positive with negative rights and freedoms, and by doing so challenge both the basis of current data protection regulations and the growing assumption that being visible through the data we emit is part of the contemporary social contract. (shrink)

The goal of the book is to present the latest research on the new challenges of data technologies. It will offer an overview of the social, ethical and legal problems posed by group profiling, big data and predictive analysis and of the different approaches and methods that can be used to address them. In doing so, it will help the reader to gain a better grasp of the ethical and legal conundrums posed by group profiling. The volume first maps the (...) current and emerging uses of new data technologies and clarifies the promises and dangers of group profiling in real life situations. It then balances this with an analysis of how far the current legal paradigm grants group rights to privacy and data protection, and discusses possible routes to addressing these problems. Finally, an afterword gathers the conclusions reached by the different authors and discuss future perspectives on regulating new data technologies. (shrink)

In light of recent technological innovations and discourses around data and algorithmic analytics, scholars of many stripes are attempting to develop critical agendas and responses to these developments. In this mutual interview, three scholars discuss the stakes, ideas, responsibilities, and possibilities of critical data studies. The resulting dialog seeks to explore what kinds of critical approaches to these topics, in theory and practice, could open and make available such approaches to a broader audience.

The Covid-19 pandemic broke on a world whose grip on epistemic trust was already in disarray. The first months of the pandemic saw many governments publicly performing reliance on epidemiological and modelling expertise in order to signal that data would be the basis for justifying whatever population-level measures of control were judged necessary. But comprehensive data has not become available, and instead scientists, policymakers and the public find themselves in a situation where policy inputs determine the data available and vice (...) versa. This essay asks how we can live with what Amoore has termed ‘post-Cartesian doubt’ in situations of existential risk, and what kind of approach to science and data can answer the moral and human demands of a situation such as the Covid-19 pandemic. I suggest that science and policy could be able to control the pandemic better by addressing the sources of uncertainty and missing data not as gaps in the information landscape, but as individuals who are likely to be members of less-visible and less powerful groups including low-wage workers, the elderly, migrants, prisoners and others. This would shift both data use and policy toward an ethics of care, an embodied approach which asks what people need and how they behave in relation to each other, rather than how to manage population-level behaviour. This approach, I argue, is more appropriate for pandemic response than a utilitarian calculation of how many people each country should expect to lose as a result of the disease. (shrink)

The scale and asymmetry of commercial technology firms’ power over people through data, combined with the increasing involvement of the private sector in public governance, means that increasingly, people do not have the ability to opt out of engaging with technology firms. At the same time, those firms are increasingly intervening on the population level in ways that have implications for social and political life. This creates the potential for power relations of domination, and demands that we decide what constitutes (...) the legitimacy to act on the public. Business ethics and private law are not designed to answer these questions, which are primarily political. If people have lost the right to disengage with commercial technologies, we may need to hold the companies that offer them to the same standards to which we hold the public sector. This paper first defines the problem and demonstrates that it is significant and widespread, and then argues for the development of an overarching normative framework for what constitutes non-domination with regard to digital technologies. Such a framework must involve a nuanced idea of political power and accountability that can respond not only to the legality of corporate behaviour, but to its legitimacy. (shrink)

Although the terminology of Big Data has so far gained little traction in economics, the availability of unprecedentedly rich datasets and the need for new approaches – both epistemological and computational – to deal with them is an emerging issue for the discipline. Using interviews conducted with a cross-section of economists, this paper examines perspectives on Big Data across the discipline, the new types of data being used by researchers on economic issues, and the range of responses to this opportunity (...) amongst economists. First, we outline the areas in which it is being used, including the prediction and ‘nowcasting’ of economic trends; mapping and predicting influence in the context of marketing; and acting as a cheaper or more accurate substitute for existing types of data such as censuses or labour market data. We then analyse the broader current and potential contributions of Big Data to economics, such as the ways in which econometric methodology is being used to shed light on questions beyond economics, how Big Data is improving or changing economic models, and the kinds of collaborations arising around Big Data between economists and other disciplines. (shrink)

In the expansion of health ecosystems, issues of responsibility and sustainability of the data science involved are central. The idea that these values should be central to the practice of data science is increasingly gaining traction, yet there is no agreement on what exactly makes data science responsible or sustainable because these concepts prove slippery when applied to a global field involving commercial, academic and governmental actors. This lack of clarity is causing problems in setting goals and boundaries for data (...) scientific practice, and risks fundamental disagreement on governance principles for this emerging field. We will argue in this commentary for a commons analytical framework as one approach to this problem, since it offers useful signposts for how to establish governance principles for shared resources. (shrink)