Fairness

The Conversation article on our CHIIR 2021 paper

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Music recommendation algorithms are unfair to female artists, but we can change that.

Article written by: Christine Bauer, Utrecht University and Andrés Ferraro, Universitat Pompeu Fabra

30 March 2021 4 min read News
The Conversation article on our CHIIR 2021 paper
CHIIR 2021 presentation: Break the Loop: Gender Imbalance in Music Recommenders

Andrés Ferraro will present our joint paper at CHIIR 2021. In the paper with the title Break the Loop: Gender Imbalance in Music Recommenders, we investigate the imbalance in music recommendations with respect to the artists gender. We propose a simple re-ranking approach to mitigate the problem and show in a simulation of feedback loops how the gender (im-)balances evolves over time.

14 March 2021 1 min read News
Recording of panel on gender bias and discrimination in AI on YouTube

The recording of the panel on gender bias and discrimination in AI (in German) at the VUT Indie Days 2020 (as part of c/o pop xoxo) last week is now also available on YouTube.

26 October 2020 1 min read News
Panelist at VUT Indie Days, co-located with c/o pop xoxo

I am happy to announce that I will be part of this year’s online edition of VUT Indie Days 2020, co-located with c/o pop xoxo. I will join the panel on Gender biases and discrimination in AI.

26 September 2020 1 min read News
SpART: Spotlight on Artists in Recommender Systems
The purpose of this project is to understand how current systems used to recommend music affect artists and to propose alternative solutions that could benefit the artists. The goal is to identify potential problems that affect artists, and to draw on the artists’ perspective about how future recommender systems could work.
SpART: Spotlight on Artists in Recommender Systems