题目：Experimental Evaluation of Algorithm-Assisted Human Decision Making

主讲人：马萨诸塞大学阿默斯特分校 蒋智超助理教授

主持人：统计学院 刘耀午教授

时间：2022年3月8日（周二）上午10:00-11:00

地点：腾讯会议，165 906 906

报告摘要：

Despite an increasing reliance on fully-automated algorithmic decision-making in our day-to-day lives, human beings still make highly consequential decisions. As frequently seen in business, healthcare, and public policy, recommendations produced by algorithms are provided to human decision-makers to guide their decisions. While there exists a fast-growing literature evaluating the bias and fairness of such algorithmic recommendations, an overlooked question is whether they help humans make better decisions. Using the concept of principal stratification, we develop a statistical methodology for experimentally evaluating the causal impacts of algorithmic recommendations on human decisions. We propose the evaluation quantities of interest, identification assumptions, and estimation strategies. We also develop sensitivity analyses to assess the robustness of empirical findings to the potential violation of a key identification assumption. We apply the proposed methodology to preliminary data from the first-ever randomized controlled trial that evaluates the pretrial Public Safety Assessment (PSA) in the criminal justice system.

主讲人简介：

Zhichao Jiang is an assistant professor in the Department of Biostatistics and Epidemiology at University of Massachusetts Amherst. Zhichao obtained his PhD degree in the Department of Statistics at Peking University and then worked as a postdoctoral researcher at Princeton University and Harvard University. His main interests are causal inference methodologies and contaminated data problems with applications in biomedical sciences and social sciences.