Activity: Talk or presentation › Guest lecture › science to science / art to art
Description
Algorithms have seamlessly integrated into the music industry, with music recommendation systems facilitating navigation through vast catalogs of musical tracks. These systems suggest similar artists or recommend the next track for us to listen to. An ideal music recommendation system should recommend the "right music to the right person at the right moment." However, what happens when it falls short of being ideal? In this presentation, I delve into the perspective of artists, exploring their notions of fairness. Among others, I will present research findings on gender bias in music recommendations and provide strategies for mitigation.
Period
28 Nov 2023
Held at
Jheronimus Academy of Data Science (JADS), Netherlands
Degree of Recognition
Local
Fields of Science and Technology Classification 2012