Rise of the Robot Music IndustryPosted: December 3, 2016
AI is transforming music streaming, talent spotting, promotion and even composition.
Robotic is not an adjective that many musicians would want applied to their songs but the industry has been fast to embrace data analytics and artificial intelligence to help tailor its services to the increasingly fickle listener.
Algorithms are seeping into the music business to help with talent spotting, promotion and even composition in an industry that has been historically resistant to change and was one of the first to feel the effects of “disruption” through piracy and music sharing.
Streaming services have already ushered in an era of “hyper personalisation” for music lovers. Spotify’s Discover Weekly playlist, launched in July 2015, had racked up 40m listeners around the world and 5bn track streams by May this year, according to a report from the BPI prepared by Music Ally. These playlists monitor what a person is listening to, and cross-references that data with other users with similar tastes to recommend new songs and artists.
Apple Music has opted to use human curators such as Zane Lowe, the radio DJ, for its playlists, but Spotify has doubled down on its robotic recommenders with new services such as Release Radar and the Daily Mix to tempt its subscribers down different paths.
Yet discovery is only the equivalent of a debut album for streaming services, and can be a blunt tool. Users of Spotify Discover complain that it is hit and miss — often suggesting the same artists and songs repeatedly, and failing to adapt to the often random whims of the listener.
The industry is now hoping that the use of artificial intelligence will bring better analytics, and even predictive technology.
A listener’s location, mood and even the weather conditions are now being built into some recommendation engines. Google Play is, for example, working on such adaptive functions.
“A bot will be able to recognise guilty pleasures . . . see that I’ve been to the pub and serve me a Little Mix record when I’m on the way home,” says Luke Ferrar, head of digital at Polydor, pointing to the use of algorithms to understand how people listen to music.
When combined with the sort of intelligence provided by a smartphone — location, time, activity and movement — it means that music services can find the right track for the right moment. In effect, AI can determine whether a person is bored in an airport, studying in a library or sunning themselves on a beach, to tailor a playlist.
AI has already started to be used to improve streaming services. Quantone, a London-based music AI start-up, is using the IBM Watson engine to further improve recommendations by crunching music reviews, blogs and Twitter comments into how music is analysed….(read more)