Accountable Artificial Intelligence: Holding Algorithms to Account.

Artificial intelligence (AI) algorithms govern in subtle yet fundamental ways the way we live and are transforming our societies. The promise of efficient, low‐cost, or "neutral" solutions harnessing the potential of big data has led public bodies to adopt algorithmic systems in the provision of pub...

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Publicado en:Public Administration Review Vol. 81; no. 5; pp. 825 - 837
Formato: Artículo
Publicado: Wiley-Blackwell Sep2021
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Sep2021
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      pub: Wiley-Blackwell
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        atl: Accountable Artificial Intelligence: Holding Algorithms to Account.
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      su:
        Organizational accountability
        Artificial intelligence
        Discrimination (Sociology)
        Organizational transparency
        Algorithms
        Decision making in public administration
      sug:
        subj:
          Organizational accountability
          Artificial intelligence
          Discrimination (Sociology)
          Organizational transparency
          Other General Government Support
          Algorithms
          Decision making in public administration
      ab: Artificial intelligence (AI) algorithms govern in subtle yet fundamental ways the way we live and are transforming our societies. The promise of efficient, low‐cost, or "neutral" solutions harnessing the potential of big data has led public bodies to adopt algorithmic systems in the provision of public services. As AI algorithms have permeated high‐stakes aspects of our public existence—from hiring and education decisions to the governmental use of enforcement powers (policing) or liberty‐restricting decisions (bail and sentencing)—this necessarily raises important accountability questions: What accountability challenges do AI algorithmic systems bring with them, and how can we safeguard accountability in algorithmic decision‐making? Drawing on a decidedly public administration perspective, and given the current challenges that have thus far become manifest in the field, we critically reflect on and map out in a conceptually guided manner the implications of these systems, and the limitations they pose, for public accountability.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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