This workshop aims to build gender-friendly music recommendation systems bringing together different voices in the music industry. The participants will collaboratively explore the question: "What should a 'gender-friendly' music recommendation algorithm look like?" working in small thematic groups—focusing on areas like data analysis, visualization, and evaluation—to prototype innovative recommender systems. Emphasizing inclusivity and respect for gender diversity, the workshop will address key challenges already identified, including artist classification by self-identified gender, the treatment of historical artists, and the automation of gender-related data. No prior experience in developing recommender systems is required. Join us to contribute to a more equitable and diverse music industry!
More info about the previous edition (CAT): https://musicdataupc.org/ca/com-hauria-de-ser-un-algorisme-de-recomanacio-musical-gender-friendly/

Pre-registration not mandatory but welcomed: https://forms.gle/oM3mhZUH5LxCvbGj8