Computing Taste: Care & Control in Algorithmic Recommendation

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.

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