Fair prediction with disparate impact: A study of bias in recidivism prediction instruments

TL;DR

This paper examines how fairness criteria in recidivism prediction tools can unintentionally cause disparate impacts, especially when recidivism rates vary across groups, raising concerns about bias and discrimination.

Contribution

It introduces a fairness criterion from educational testing to assess bias in recidivism instruments and shows its potential to cause disparate impact under certain conditions.

Findings

Fairness criteria can lead to bias when recidivism rates differ across groups

Disparate impact may occur even when fairness criteria are applied

The study highlights the complexity of achieving fair risk assessments

Abstract

Recidivism prediction instruments provide decision makers with an assessment of the likelihood that a criminal defendant will reoffend at a future point in time. While such instruments are gaining increasing popularity across the country, their use is attracting tremendous controversy. Much of the controversy concerns potential discriminatory bias in the risk assessments that are produced. This paper discusses a fairness criterion originating in the field of educational and psychological testing that has recently been applied to assess the fairness of recidivism prediction instruments. We demonstrate how adherence to the criterion may lead to considerable disparate impact when recidivism prevalence differs across groups.