User Perceptions and Responses to Minority Fairness in Music Recommendations and Item Labels

Abstract

Music recommender systems play a central role in how users explore and consume music, yet they are often associated with concerns related to bias and unequal representation. While existing research has largely focused on improving fairness at the algorithmic level, less is known about how users interpret fairness and whether such information affects their choices. This paper examines how users engage with fairness-related information presented alongside songs, and whether it influences their decision-making. To investigate this, we conducted an online mixed method user study with 28 participants, combining a ranking task with follow-up reflections. Participants were asked to rank songs based on their preferences while being shown labels indicating associations with categories such as gender, age, location, and orientation. The findings indicate that these labels had minimal influence on ranking behaviour. At the same time, participants showed low agreement in their rankings, reflecting the highly subjective nature of music preferences. Most participants reported relying on familiarity, personal taste, and emotional responses rather than the provided labels. These results suggest that providing fairness-related information alone is unlikely to change user behaviour. Instead, such information needs to be both meaningful and relevant to users in order to be considered during decision-making. This work highlights the importance of accounting for user perception and taste when designing fairness-oriented recommender systems.