Critical decisions like loan approvals, medical interventions, and college admissions are guided by predictions made in the presence of uncertainty. In this paper, we prove that uncertainty has a disparate impact. While it imparts errors across all demographic groups, 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 show that additional data acquisition can eliminate the disparity and broaden access to opportunity. The strategy, which we call Affirmative Information, could stand as an alternative to Affirmative Action.

翻译：关键决策，如贷款审批、医疗干预和大学录取，均基于存在不确定性的预测结果。本文证明，不确定性具有差异化影响：尽管它会在所有人口统计群体中产生错误，但错误类型呈现系统性差异——平均结果较高的群体通常被分配更高的假阳性率，而平均结果较低的群体则被分配更高的假阴性率。我们表明，额外数据采集能够消除这种差异并扩大机会获取渠道。这种被称为“平权信息”的策略，可作为平权行动的替代方案。