(De)Composing the Algorithm: Explaining Music Recommender Systems to Artists for Understanding, Transparency, and Empowerment

Abstract

Music recommender systems (MRS) play a central role in shaping how audiences discover music. While there is growing interest in explainable and user-centered recommendations, the perspective of artists — as creators affected by these systems — remains underexplored. This study focuses on artists’ information needs, their understanding of the mechanisms behind MRS, and whether providing information about how MRS work can influence the artists’ perception of transparency as well as their engagement. To address these questions, we conducted a mixed-method study, which included semi-structured interviews, co-design sessions, and a questionnaire with artists. The findings suggest that while many artists have a general understanding of music recommendations from a listener’s perspective, they often struggle to apply that knowledge as creators. Explanations were found to support understanding and encourage reflection on the systems’ influence on their visibility and reach. Based on these insights, a prototype was developed and evaluated with a subset of the participants. Our results highlight the importance of artists understanding MRS. Additionally, the results indicate that participatory design may serve as a source of empowerment for artists.