Feb. 9, 2024, 5:44 a.m. | Claire Lazar Reich

cs.LG updates on arXiv.org arxiv.org

Critical decisions like hiring, college admissions, and loan approvals are guided by predictions made in the presence of uncertainty. While uncertainty imparts errors across all demographic groups, this paper shows that the types of errors vary systematically: Groups with higher average outcomes are typically assigned higher false positive rates, while those with lower average outcomes are assigned higher false negative rates. We characterize the conditions that give rise to this disparate impact and explain why the intuitive remedy to omit …

admissions college cs.lg decisions econ.th errors false hiring impact information paper positive predictions shows stat.ml types uncertainty

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