The recommendation algorithm

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.

Learn more about your ad choices. Visit megaphone.fm/adchoices