IA, Recommendations & The Curation of Culture

Traditionally, music and cultural goods have been distributed through radio, television, and retail outlets. The application of artificial intelligence (AI) has allowed for new platforms to use recommendation systems to distribute content and curate media catalogues. There is a particular emphasis on using data to curate personal recommendations, with the goal of optimizing each user’s experience. However, this affects how audiences encounter media, which in turn has an effect on how it is produced and consumed. On October 4-5, 2019, CIFAR, in collaboration with the workshop leadership team, convened 22 experts from academia and industry to explore how algorithmically-powered recommendation systems for music platforms such as Spotify and Pandora are shaping the consumption, production and distribution of music and culture around the world.

LEADERSHIP TEAM • Ashton Anderson, University of Toronto • Fernando Diaz, Microsoft Research • Georgina Born, Oxford University • Jeremy Morris, University Wisconsin-Madison

IMPACTED STAKEHOLDERS • Music and recording artists • Technologists and computer scientists • Music producers and record companies • Ethnographers and culture researchers • Music curation companies and platforms • Consumers of music and cultural platforms