Using folk theories of recommender systems to inform human-centered explainable AI (HCXAI)

Abstract

This study uses folk theories of the Spotify music recommender system to inform the principles of human-centered explainable AI (HCXAI). The results show that folk theories can reinforce, challenge, and augment these principles facilitating the development of more transparent and explainable recommender systems for the non-expert, lay public.