SZA, Kenneth Blume Decry Use of Their Songs in AI Training Data Sets

Last week, the Atlantic debuted a new AI detection tool that allows artists to see, with a brief name search, if their music appears in data sets used to train AI music generators.Created by researcher Alex Reisner, the tool draws on four different sets available to AI developers.

These sets, which Reisner emphasizes is not comprehensive, encompasses over 21 million songs.They pull from the catalogs of massive stars like Bad Bunny, Taylor Swift, and Beyoncé, and smaller, independent artists alike.In the days following the tool’s launch, multiple musicians have expressed anger and concern over discovering their work in the data sets.

SZA was among them, sharing in an Instagram story: “Jus checked and music AI has trained off 238 of my songs.I’m certain some unreleased.

If your a musician and you support this degenerate shit? Your disgusting and there’s NOTHING YOU COULD EVER SAY TO ME TO MAKE THIS OKAY.” On a separate account, she also asserted that AI companies specifically exploit black artists, writing: “I AINT HEARD A WHITE AI SONG YET..why so disproportionate? We have no protection in legislature medical or creative.

The easiest to steal from .”In his own post, the producer Kenneth Blume (FKA Kenny Beats) specifically called out the AI music company Suno.“I can’t imagine going into work daily knowing you are stealing from countless struggling musicians,” he wrote.

“I can’t imagine being proud to earn a paycheck obliterating the work and dreams of artists.” On Bluesky, DJ Sabrina the Teenage DJ aired her own frustrations, writing: “To everyone who thought my music sounded like AI slop, did you ever think it was because Suno was using a dataset that contained 22 of my songs? It’s funny how there were no accusations of my music sounding like AI slop until these datasets started getting used to generate slop.”Although some companies, including Google and Stability, have admitted to using these data sets to train their AI models,...

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Publisher: Pitchfork

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