‘A talent scout can’t go to 100 shows a night’ – how big data is choosing the next pop stars

Faced with so much new music, major labels are using algorithms to hunt down tomorrow’s hits. Is this great news for rising stars – or the recipe for a bland new future?

One lunchtime about three years ago, Hazel Savage and Aron Pettersson set a new piece of software running on a laptop then went to a nearby mall for a sandwich. They hoped, on their return, to have the answer to a question that would change the music industry: can a computer pick a hit record?

The pair had just founded their firm, Musiio, in Singapore’s Boat Quay district. Pettersson, who is Swedish, was a specialist in artificial intelligence (AI) with a background in neuroscience; Savage, a British music industry professional with tech pedigree, had worked for Shazam and the Pandora streaming service. They let their software loose on the Free Music Archive, one of the world’s largest collections of copyright-free songs. These are written by little-known artists and commonly used for soundtracks and podcasts. They asked their computer to pick 20 songs from the archive, based on their similarity to a tune Savage liked: I Wanted Everything by the US indie star Kurt Vile. Back in the office, they listened. “Every song was great,” says Savage, “and every song was of a similar genre.”

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