Switch to: References

Add citations

You must login to add citations.
  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 (...)
    Download  
     
    Export citation  
     
    Bookmark   49 citations  
  • Concordance as evidence in the Watson for Oncology decision-support system.Aaro Tupasela & Ezio Di Nucci - 2020 - AI and Society 35 (4):811-818.
    Machine learning platforms have emerged as a new promissory technology that some argue will revolutionize work practices across a broad range of professions, including medical care. During the past few years, IBM has been testing its Watson for Oncology platform at several oncology departments around the world. Published reports, news stories, as well as our own empirical research show that in some cases, the levels of concordance over recommended treatment protocols between the platform and human oncologists have been quite low. (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • Alienation in a World of Data. Toward a Materialist Interpretation of Digital Information Technologies.Michael Steinmann - 2022 - Philosophy and Technology 35 (4):1-24.
    The essay proposes to use alienation as a heuristic and conceptual tool for the analysis of the impact of digital information and communication technologies (ICTs) on users. It follows a historical materialist understanding, according to which data can be considered as things produced in an industrial fashion. A representational interpretation, according to which data would merely reflect a given reality, is untenable. It will be argued instead to understand data as an additional layer which has a transformative impact on reality (...)
    Download  
     
    Export citation  
     
    Bookmark