And whether intentionally or not a lot of popular news outlets sort of picked up on the neuro part of neuro physiological response. Tu: Yeah, great catch! So at face value, the researchers in this recent study, say they measured listeners' neurophysiological response to different songs. And it's also unique because the study claims to train its AI on the brain data of listeners rather than a song's intrinsic features like it's DanceAbility or it's explicitness.īushwick: That sounds like science fiction, just like it’s AI reading your mind to predict if you like the song, but I can’t help but notice that it claims to use brain data. One being it's near perfect accuracy, a 97 percent success rate is much, much higher than any approach we've seen before. Tu: And so this new approach, it's different for a few reasons. So you're honestly better off flipping a coin. But even with all of that data, the existing AI algorithms have only been able to correctly predict whether a song will be a hit or not less than 50 percent of the time. But they've focused primarily on characteristics like a song artist and genre, as well as the music itself. Streaming services and music industry companies have been relying heavily already on algorithms to try and predict hit songs. So what’s so special about this new approach? You’re listening to Tech, Quickly, the all-things-tech part of Scientific American’s Science, Quickly podcast.īushwick: I thought the music industry has been using AI to create songs and analyze them for a while. Sophie Bushwick: I’m Sophie Bushwick, tech editor at Scientific American. I’m Lucy Tu, the 2023 AAAS Mass Media fellow for Scientific American. Lucy Tu: But it might be too soon to anoint AI as the next big talent scout for the music industry.
And it does this by measuring how the listener’s body responds to the music. They published a paper showing that AI can predict, with 97 percent accuracy, if any song will be a hit. Sophie Bushwick: Last month, AI researchers claimed an impressive breakthrough.
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