Computing Taste: Care and Control in Algorithmic Music Recommendation

Meeting ID: 937 9210 4939

Passcode: 800615

The people who make music recommender systems have lofty goals: they want to broaden listeners' horizons and help obscure musicians find audiences, taking advantage of the enormous catalogs of music streaming services. But for their critics, recommender systems seem to embody all the potential harms of algorithms: they flatten culture into numbers, they normalize ever-broadening data collection, and they profile their users for commercial ends. This talk presents the results of several years of ethnographic fieldwork with makers of music recommendation in the US, describing how they navigate the tensions between care and control in the construction of algorithmic systems.

Nick Seaver is an assistant professor of Anthropology at Tufts University, where he also directs the program in Science, Technology & Society. His first book, _Computing Taste: Algorithms and the Makers of Music Recommendation_, will be published by the University of Chicago Press in December 2022.