This session will explore the critical importance of metadata: the information hidden behind each song and how it impacts the visibility of artists within the digital music industry. With a special focus on how the absence of gender-related metadata reinforces biases in music recommendation algorithms, contributing to the invisibility of female and gender-diverse artists.

There will be an introductory session presented by Thais Ruiz de Alda, which will address possible solutions and explore how to influence the creation of new metadata standards to identify and correct these inequalities in digital distribution. This implies rethinking the industry's digital infrastructures to move towards a fairer and more inclusive ecosystem. Roser Batlle, researcher at the MTG, is one of the panelist, together with Cori Chinnici (BMAT) and Javier Lorbada (music pitcher)

Information:

Blind algorithms and biased metadata: de-automating equality in the music industry. Presented by UFI + APECAT

June 6th, 12:45

Auditori CCCB

Primavera Pro website

Activity in the frame of:

Cátedra UPF-BMAT en Inteligencia Artificial y Música (TSI-100929-2023-1). Project funded by Secretaría de Estado de Digitalización e Inteligencia Artificial, the European Union-Next Generation EU, and by BMAT Music Innovators, the Music Operating System