A study finds gender bias in music recommendation algorithms

Although the problem of gender discrimination is already found in the music industry, music recommendation algorithms would be increasing the gender gap. Andrés Ferraro and Xavier Serra, researchers of the Music Technology research group (MTG) of the UPF Department of Information and Communication Technologies (DTIC), with Christine Bauer, of the University of Utrecht (Netherlands), have recently published a paper on gender balance in music recommendation systems in which they ask themselves how the system should work to avoid gender bias.

from News on Artificial Intelligence and Machine Learning https://ift.tt/3gxwUXw

SHARE SHARE SHARE