  Existing research on music recommendation systems primarily focuses on
recommending similar music, thereby often neglecting diverse and distinctive
musical recordings. Musical outliers can provide valuable insights due to the
inherent diversity of music itself. In this paper, we explore music outliers,
investigating their potential usefulness for music discovery and recommendation
systems. We argue that not all outliers should be treated as noise, as they can
offer interesting perspectives and contribute to a richer understanding of an
artist's work. We introduce the concept of 'Genuine' music outliers and provide
a definition for them. These genuine outliers can reveal unique aspects of an
artist's repertoire and hold the potential to enhance music discovery by
exposing listeners to novel and diverse musical experiences.
