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Equalized odds is a requirement of algorithmic fairness.

Statistical criteria of fairness are formal measures of how an algorithm performs that aim to help us determine whether an algorithm would be fair to use in decision-making. In this paper, I introduce a new version of the criterion known as “Equalized Odds,” argue that it is a requirement of procedu...

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Publicado en:Synthese Vol. 201; no. 3; pp. 1 - 26
Autor principal: Grant, David Gray
Formato: Artículo
Publicado: Springer Nature Mar2023
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Equalized odds is a requirement of algorithmic fairness.
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        au: Grant, David Gray
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          Department of Philosophy, University of Florida, Gainesville, FL, USA
          Jain Family Institute, New York, NY, USA
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        Algorithmic fairness
        COMPAS
        Fairness in machine learning
        Statistical criteria of fairness
        Technology ethics
      ab: Statistical criteria of fairness are formal measures of how an algorithm performs that aim to help us determine whether an algorithm would be fair to use in decision-making. In this paper, I introduce a new version of the criterion known as “Equalized Odds,” argue that it is a requirement of procedural fairness, and show that it is immune to a number of objections to the standard version.
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    language: English
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