2024/01/30 by David Almog, Almog, David, Romain Gauriot +6 · 1 voice
Computer Science · Economics, Econometrics and Finance · Social Sciences · #Artificial Intelligence in Law #Computers and Society (cs.CY) #FOS: Computer and information sciences #FOS: Economics and business #General Economics (econ.GN) #Insurance and Financial Risk Management #Law, Economics, and Judicial Systems #Machine Learning (cs.LG) #cs.CY #cs.LG #econ.GN
paper · pdf · doi:10.48550/arxiv.2401.16754
openalex publication_date 2024/01/30 · arxiv published 2024/01/30 · arxiv updated 2025/02/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Powered by the increasing predictive capabilities of machine learning algorithms, artificial intelligence (AI) systems have the potential to overrule human mistakes in many settings. We provide the first field evidence that the use of AI oversight can impact human decision-making. We investigate one of the highest visibility settings where AI oversight has occurred: Hawk-Eye review of umpires in top tennis tournaments. We find that umpires lowered their overall mistake rate after the introduction of Hawk-Eye review, but also that umpires increased the rate at which they called balls in, producing a shift from making Type II errors (calling a ball out when in) to Type I errors (calling a ball in when out). We structurally estimate the psychological costs of being overruled by AI using a model of attention-constrained umpires, and our results suggest that because of these costs, umpires cared 37% more about Type II errors under AI oversight.