Victor Richmond Jose's contribution to the Discussion of ‘Experimental evaluation of algorithm-assisted human decision-making: application to pretrial public safety assessment’ by Imai et al.
本文讨论了算法辅助人类决策的实验评估方法，并应用于美国刑事司法系统中审前公共安全评估的随机对照试验，发现提供算法建议对法官决策影响不大。
Despite an increasing reliance on fully-automated algorithmic decision-making in our day-to-day lives, humans still make consequential decisions.While the existing literature focuses on the bias and fairness of algorithmic recommendations, an overlooked question is whether they improve human decisions.We develop a general statistical methodology for experimentally evaluating the causal impacts of algorithmic recommendations on human decisions.We also examine whether algorithmic recommendations improve the fairness of human decisions and derive the optimal decision rules under various settings.We apply the proposed methodology to the first-ever randomized controlled trial that evaluates the pretrial Public Safety Assessment in the United States criminal justice system.Our analysis of the preliminary data shows that providing the PSA to the judge has little overall impact on the judge's decisions and subsequent arrestee behaviour.