Management Science · 2026 · Andrew Caplin、David Deming、Shangwen Li、Daniel Martin、Philip Marx、Ben Weidmann
中文摘要
我们通过一项受控实验表明，能力与信念校准共同决定了与人工智能（AI）协作的收益。对于基线能力较低的人，AI 对绩效的提升更大。然而，在能力不变的情况下，AI 辅助对校准良好的人更有价值，即他们对自己能力持有准确的信念。知道自己能力较低的人从与 AI 协作中获益最多。在一项反事实分析中，我们表明，消除校准偏差将使 AI 缩小绩效不平等的幅度几乎达到其现有作用的两倍。本文由行为经济学与决策分析领域编辑 Marie Claire Villeval 接收。资助：本工作受阿尔弗雷德·P·斯隆基金会（工作中的认知经济学）资助。补充材料：在线附录与数据文件见 https://doi.org/10.1287/mnsc.2024.08994 。
Abstract
We use a controlled experiment to show that ability and belief calibration jointly determine the benefits of working with artificial intelligence (AI). AI improves performance more for people with low baseline ability. However, holding ability constant, AI assistance is more valuable for people who are calibrated, meaning they have accurate beliefs about their own ability. People who know they have low ability gain the most from working with AI. In a counterfactual analysis, we show that eliminating miscalibration would cause AI to reduce performance inequality nearly twice as much as it already does. This paper was accepted by Marie Claire Villeval, behavioral economics and decision analysis. Funding: This work was supported by the Alfred P. Sloan Foundation (Cognitive Economics at Work). Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.08994 .