Published online by Cambridge University Press: 29 November 2018
This article explores how human curation and algorithmic recommendation are figured in cloud-based streaming platforms. In promoting their services as alternatives to illicit file-sharing, platforms such as Spotify, Deezer, and Apple Music have long touted the access they provide to a massive database of music. Yet the effectiveness of appeals to musical plenitude have been thrown into doubt, as high rates of user turnover threaten streaming's economic viability. Curation and recommendation have thus been posited as solutions to this problem, as means of producing and reproducing consumer desire. By attending to the fantasies woven around streaming and music recommendation more specifically, this article highlights the peculiar form of subjectivation at work in the way recommendation hails listeners. The normative listener constructed through such modes of hyper-personalized address is ideally one that is as dynamic and adaptive as the algorithmic systems that adjust to their fluctuating needs, dispositions, and desires.
Many thanks to Sumanth Gopinath, Ben Piekut, Marianne Wheeldon, and the anonymous reviewers of this journal for the useful commentary and suggestions they provided on earlier versions of this article. Thanks as well for the feedback I received at the University of Minnesota, the University of Chicago, and Yale University, where I was fortunate enough to share some of this research.