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  1. Algorithmic Accountability and Public Reason.Reuben Binns - 2018 - Philosophy and Technology 31 (4):543-556.
    The ever-increasing application of algorithms to decision-making in a range of social contexts has prompted demands for algorithmic accountability. Accountable decision-makers must provide their decision-subjects with justifications for their automated system’s outputs, but what kinds of broader principles should we expect such justifications to appeal to? Drawing from political philosophy, I present an account of algorithmic accountability in terms of the democratic ideal of ‘public reason’. I argue that situating demands for algorithmic accountability within this justificatory framework enables us to (...)
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  • Group privacy.Bart van der Sloot, Luciano Floridi & Linnet Taylor (eds.) - 2016 - Springer Verlag.
    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 (...)
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  • Logged out: Ownership, exclusion and public value in the digital data and information commons.Barbara Prainsack - 2019 - Big Data and Society 6 (1).
    In recent years, critical scholarship has drawn attention to increasing power differentials between corporations that use data and people whose data is used. A growing number of scholars see digital data and information commons as a way to counteract this asymmetry. In this paper I raise two concerns with this argument: First, because digital data and information can be in more than one place at once, governance models for physical common-pool resources cannot be easily transposed to digital commons. Second, not (...)
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  • Big Data: A Revolution That Will Transform How We Live, Work, and Think.V. Mayer-Schoenberger & K. Cukier - unknown
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  • Where are human subjects in Big Data research? The emerging ethics divide.Kate Crawford & Jacob Metcalf - 2016 - Big Data and Society 3 (1).
    There are growing discontinuities between the research practices of data science and established tools of research ethics regulation. Some of the core commitments of existing research ethics regulations, such as the distinction between research and practice, cannot be cleanly exported from biomedical research to data science research. Such discontinuities have led some data science practitioners and researchers to move toward rejecting ethics regulations outright. These shifts occur at the same time as a proposal for major revisions to the Common Rule—the (...)
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  • Critical Data Studies: A dialog on data and space.Jim Thatcher, Linnet Taylor & Craig M. Dalton - 2016 - Big Data and Society 3 (1).
    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.
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