Taylor Swift, Bad Bunny and many, many more artists have had their work fed into AI models.
We’re always glad to see more publications and groups digging deeper into artificial intelligence and its impact. Today, The Atlantic has published four searchable databases of music that has been used to train AI models. The scope is pretty staggering, with 12 million tracks in one database, 9 million in another, and the two final ones each containing about 100,000 songs.
The accompanying article by staff writer Alex Reisner gives further context to just how much copyrighted music was used for AI training, including hit tracks from Taylor Swift and Bad Bunny. He points to some of the legal cases already underway against generative AI music platforms, such as Suno and Udio, which have often made claims of fair use as a defense for wholesale scraping copyright-protected content to power their platforms. A similar case in book publishing didn’t make headway with a judge on claims of copyright infringement, but piracy allegations have proved to be a more compelling argument. The full results and payout from that suit are still pending, though the initial settlement was for $1.5 billion. Having sources such as these databases from The Atlantic could help parties in the music industry try for similar lawsuits in the future.
Many music streaming services have taken steps to prevent, identify or label generative AI creations, but those efforts have seen varying degrees of success. They also haven’t stopped scammers from creating imitations of existing bands and trying to benefit off their work with AI copycats.
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