Predicting Decision-makers' Algorithm Use

Abstract

Decision makers typically integrate multiple pieces of information to make predictions and decisions. They also sometimes receive algorithmic advice, but often discount such advice. This usually results in less consistent and less accurate predictions than strictly using the advice. Therefore, we investigated if conscientiousness, decision-making styles, predictor validity beliefs, and cognitive ability are related to algorithm use, judgment consistency, and predictive validity. Participants with hiring experience (N = 308) predicted the performance of job applicants based on test scores and interview ratings, and they also received algorithmic advice. We found that more dutiful participants and participants with more accurate predictor validity beliefs used the algorithm more, and made more consistent and more accurate predictions. We did not find evidence that an intuitive decision-making style was related to these outcomes. Exploratory analyses showed that cognitive ability was related to algorithm use and judgment consistency, but not to predictive validity. Organizations may want to hire more conscientious and knowledgeable decision makers, and provide training on predictor validities.