Paradoxes in Fair Computer-Aided Decision Making

Andrew Morgan, R. Pass
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引用次数: 8

Abstract

Computer-aided decision making--where a human decision-maker is aided by a computational classifier in making a decision--is becoming increasingly prevalent. For instance, judges in at least nine states make use of algorithmic tools meant to determine "recidivism risk scores" for criminal defendants in sentencing, parole, or bail decisions. A subject of much recent debate is whether such algorithmic tools are "fair" in the sense that they do not discriminate against certain groups (e.g., races) of people. Our main result shows that for "non-trivial" computer-aided decision making, either the classifier must be discriminatory, or a rational decision-maker using the output of the classifier is forced to be discriminatory. We further provide a complete characterization of situations where fair computer-aided decision making is possible.
公平计算机辅助决策中的悖论
计算机辅助决策——人类决策者在计算机分类器的帮助下做出决策——正变得越来越普遍。例如,至少有9个州的法官使用算法工具来确定刑事被告在量刑、假释或保释决定中的“再犯风险评分”。最近争论的一个主题是,这些算法工具是否“公平”,即它们不歧视某些群体(如种族)。我们的主要结果表明,对于“非平凡的”计算机辅助决策,要么分类器必须具有歧视性,要么使用分类器输出的理性决策者被迫具有歧视性。我们进一步提供了一个完整的表征的情况下,公平的计算机辅助决策是可能的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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