Corpus ID: 88524010

Prediction-Based Decisions and Fairness: A Catalogue of Choices, Assumptions, and Definitions

@article{Mitchell2018PredictionBasedDA,
  title={Prediction-Based Decisions and Fairness: A Catalogue of Choices, Assumptions, and Definitions},
  author={Shira Mitchell and Eric Potash and Solon Barocas and Alexander D'Amour and Kristian Lum},
  journal={arXiv: Applications},
  year={2018}
}
  • Shira Mitchell, Eric Potash, +2 authors Kristian Lum
  • Published 2018
  • Mathematics
  • arXiv: Applications
  • A recent flurry of research activity has attempted to quantitatively define "fairness" for decisions based on statistical and machine learning (ML) predictions. The rapid growth of this new field has led to wildly inconsistent terminology and notation, presenting a serious challenge for cataloguing and comparing definitions. This paper attempts to bring much-needed order. First, we explicate the various choices and assumptions made---often implicitly---to justify the use of prediction-based… CONTINUE READING

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    Tracking and Improving Information in the Service of Fairness

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    CITES BACKGROUND & METHODS

    Decisions, Counterfactual Explanations and Strategic Behavior

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    Algorithmic and Economic Perspectives on Fairness

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    Measurement and Fairness

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    On formalizing fairness in prediction with machine learning

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    Counterfactual Fairness

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