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How Apple Music’s Algorithmically Personalized Playlists Work

Reggie Ugwu, in a BuzzFeed feature story on the second act of Apple Music, got some details on the new ‘My Favorites Mix’ and ‘My New Music Mix’ playlists introduced with iOS 10:

Revealing how the mixes operate for the first time to BuzzFeed News, Apple claimed a potential advantage over similar algorithmically personalized playlists, including Spotify’s Discover Weekly and Pandora’s Thumbprint Radio: deep historical knowledge of individual users’ tastes and habits, based on years of data carried over from iTunes.

If you gave high ratings to a song or album in your old iTunes library, or just played it a lot more than others, you’ll find that behavior reflected in your My Favorites Mix. Meanwhile, the My New Music Mix algorithm serves recently released songs — as well as songs that Apple Music knows you haven’t played before — that the service’s music experts have flagged as similar to others in your taste profile. Apple Music executives suggested even more personalized playlists will follow in the series; but only after prototypes have been vetted, with all possible outcomes — intentional and otherwise — given careful consideration.

This explains why the ‘My Favorites Mix’ playlists have (anecdotally) been spot-on for people I talked to. As I previously noted, back-catalogue songs from artists you’re not familiar with (essentially, Discover Weekly) would be a good addition to Apple Music’s mixes.