The recommendation algorithm

Actually Interesting

My music streaming service works a whole lot better than it used to.

There's a reason for that, and it's the decisive tilt that Apple made a few months ago towards algorithmic playlists on Apple Music. Having branded itself on the virtues of human curation – it's only a year ago that Apple CEO Tim Cook lamented the dehumanising effect of Spotify's data-driven approach to curation – Apple seems to be acknowledging that maybe Spotify has it right.

New Music recommendations have improved markedly under this personal robot curation – like I'm getting what an algorithm thinks I'd like, rather than what someone thinks I should like. But the playlist that's really working for me is Favourites Mix, a rolling weekly selection of things that I have loved (and sometimes forgotten) at some point in the past decade or more. Apple knows what I have loved because for all that time I've been telling it, by uploading Genius data from iTunes to the mothership. Apple had a lot of data to push my buttons with – it just finally got around to using it. It's great.

It's an example of the power of the aspect of AI we see most in popular culture – the recommendation algorithm. Actually Interesting spoke to Juan Swartz of the Christchurch-based tech company 4th and Andy Low, general manager of DRM New Zealand the country's largest digital distributor of music, about the power of the algorithm.

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