Confidence Displays and Training in Recommender Systems

Recommender systems help users sort through vast quantities of information. Sometimes, however, users do not know if they can trust the recommendations they receive. Adding a confidence metric has the potential to improve user satisfaction and alter user behavior in a recommender system. We performed an experiment to measure the effects of a confidence display as a component of an existing collaborative filteringbased recommender system. Minimal training improved use of the confidence display compared to no training. Novice users were less likely to notice, understand, and use the confidence display than experienced users of the system. Providing training about a confidence display to experienced users greatly reduced user satisfaction in the recommender system. These results raise interesting issues and demonstrate subtle effects about how and when to train users when adding features to a system.