As music services increasingly rely on algorithms and machine learning to deliver personalized recommendations to listeners, there is a growing need for machines to understand how to accurately classify music. For example, a listener can now simply ask their device to “play some Indie Rock”, and in doing so, they expect to hear Indie Rock music. But what are they really expecting here? What is “Indie Rock”? What isn’t “Indie Rock”? How can we expect machines to accurately understand musical genres when these labels are not always clear to us humans? In this talk, Evan Paul will discuss the challenges that both humans and machines face when attempting to classify music and how these challenges will shape the future of personalized music recommendations.

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