Statistical Tests for Replacing Human Decision Makers with Algorithms

• 成果类型: Article; Early Access
• 署名作者: Feng, Kai; Hong, Han; Tang, Ke; Wang, Jingyuan
• 署名单位: Tsinghua University; Stanford University; Beihang University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2023.01845
• 发表日期: 2025
• 关键词: Artificial intelligence; Machine Learning; decision making; ROC curve

摘要

This paper proposes a statistical framework of using artificial intelligence to improve human decision making. The performance of each human decision maker is benchmarked against that of machine predictions. We replace the diagnoses made by a subset of the decision makers with the recommendation from the machine learning algorithm. We apply both a heuristic frequentist approach and a Bayesian posterior loss function approach to abnormal birth detection using a nationwide data set of doctor diagnoses from prepregnancy checkups of reproductive-age couples and pregnancy outcomes. We find that our algorithm on a test data set results in a higher overall true positive rate and a lower false positive rate than the diagnoses made by doctors only.