Switch to: References

Add citations

You must login to add citations.
  1. The Epistemology of Non-distributive Profiles.Patrick Allo - 2020 - Philosophy and Technology 33 (3):379-409.
    The distinction between distributive and non-distributive profiles figures prominently in current evaluations of the ethical and epistemological risks that are associated with automated profiling practices. The diagnosis that non-distributive profiles may coincidentally situate an individual in the wrong category is often perceived as the central shortcoming of such profiles. According to this diagnosis, most risks can be retraced to the use of non-universal generalisations and various other statistical associations. This article develops a top-down analysis of non-distributive profiles in which this (...)
    No categories
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  • A roadmap for research on identity in the information society.Ruth Halperin & James Backhouse - 2008 - Identity in the Information Society 1 (1):71-87.
    As research into identity in the information society gets into its stride, with contributions from many scholarly disciplines such as technology, social sciences, the humanities and the law, a moment of intellectual stocktaking seems appropriate. This article seeks to provide a roadmap of research currently undertaken in the field of identity and identity management showing how the area is developing and how disparate contributions relate to each other. Five different perspectives are proposed through which work in the identity field can (...)
    Direct download (7 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  • Managing Algorithmic Accountability: Balancing Reputational Concerns, Engagement Strategies, and the Potential of Rational Discourse.Alexander Buhmann, Johannes Paßmann & Christian Fieseler - 2020 - Journal of Business Ethics 163 (2):265-280.
    While organizations today make extensive use of complex algorithms, the notion of algorithmic accountability remains an elusive ideal due to the opacity and fluidity of algorithms. In this article, we develop a framework for managing algorithmic accountability that highlights three interrelated dimensions: reputational concerns, engagement strategies, and discourse principles. The framework clarifies that accountability processes for algorithms are driven by reputational concerns about the epistemic setup, opacity, and outcomes of algorithms; that the way in which organizations practically engage with emergent (...)
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   24 citations