Aversion to hiring algorithms: Transparency, gender profiling, and self-confidence

We run an online experiment to study the origins of algorithm aversion. Partici-pants are in the role of either workers or managers. Workers perform three real-effort tasks:task 1, task 2, and the job task, which is a combination of tasks 1 and 2. They choosewhether the hiring decision between themselves and another worker is made by a partici-pant in the role of a manager or by an algorithm. In a second set of experiments, managerschoose whether they want to delegate their hiring decisions to the algorithm. When thealgorithm does not use workers' gender to predict their job-task performance and workersknow this, they choose the algorithm more often than in the baseline treatment where gen-der is employed. Feedback to the managers about their performance in hiring the bestworkers increases their preference for the algorithm relative to the baseline without feed-back, because managers are, on average, overconfident. Finally, providing details on howthe algorithm works does not increase the preference for the algorithm for workers or formanagers.