setting, humans cannot verify the algorithm's quality. We, therefore, argue that algorithms exhibit traits of a credence good … intervention, we explain the way the algorithm functions. We find that while explanation helps participants recognize bias in the … algorithm, it remarkably decreases human decision-making performance. In the second treatment, we reveal the task's correct …

of participants (over 60%) prefer the algorithm as a decision maker over a human—but this is not driven by concerns over … decisions algorithmic decision-makers might be preferred, but actual performance of the algorithm plays an important role in how …

Are people algorithm averse, as some previous literature indicates? If so, can the retention of human oversight … made. In line with automation bias, participants adjust the recommendations that stem from an algorithm by less than those …