AI Oversight and Human Mistakes: Evidence from Centre Court
This provides the first field evidence on how AI oversight affects human errors in high-stakes settings, with implications for domains like sports officiating and beyond.
The study examined the impact of AI oversight on human decision-making in professional tennis, finding that umpires reduced overall mistake rates but shifted from Type II to Type I errors after Hawk-Eye review was introduced. It estimated that umpires cared 37% more about Type II errors due to psychological costs of being overruled.
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.