Fair Equality of Chances for Prediction-based Decisions

Abstract

This article presents a fairness principle for evaluating decision-making based on predictions: a decision rule is unfair when the individuals directly impacted by the decisions who are equal with respect to the features that justify inequalities in outcomes do not have the same statistical prospects of being benefited or harmed by them, irrespective of their socially salient morally arbitrary traits. The principle can be used to evaluate prediction-based decision-making from the point of view of a wide range of antecedently specified substantive views about justice in outcome distributions.

Keywords: Fairness, bias, statistical decision-making, statistical discrimination