  Our narrative literature review acknowledges that, although there is an
increasing interest in recommender system fairness in general, the music domain
has received relatively little attention in this regard. However, addressing
fairness of music recommender systems (MRSs) is highly important because the
performance of these systems considerably impacts both the users of music
streaming platforms and the artists providing music to those platforms. The
distinct needs that these stakeholder groups may have, and the different
aspects of fairness that therefore should be considered, make for a challenging
research field with ample opportunities for improvement. The review first
outlines current literature on MRS fairness from the perspective of each
stakeholder and the stakeholders combined, and then identifies promising
directions for future research.
  The two open questions arising from the review are as follows: (i) In the MRS
field, only limited data is publicly available to conduct fairness research;
most datasets either originate from the same source or are proprietary (and,
thus, not widely accessible). How can we address this limited data
availability? (ii) Overall, the review shows that the large majority of works
analyze the current situation of MRS fairness, whereas only few works propose
approaches to improve it. How can we move forward to a focus on improving
fairness aspects in these recommender systems?
  At FAccTRec '22, we emphasize the specifics of addressing RS fairness in the
music domain.
