Sony Targets 135,000 Deepfake Songs to Protect Artists
Music giant Sony Music says it has requested the removal of more than 135,000 songs by fraudsters impersonating its artists on streaming services. The so-called deepfakes were created using generative AI and targeted some of the company's biggest acts, including Beyoncé, Queen, and Harry Styles.
The proliferation of such counterfeits causes direct commercial harm to legitimate recording artists, Sony stated, noting that the deepfakes often appear at critical times when artists are promoting new albums. Dennis Kooker, president of Sony's global digital business, emphasized that these fraudulent songs can damage release campaigns and tarnish artist reputations.
Since March of the previous year, Sony has identified around 60,000 additional songs falsely claiming to feature artists from their roster. Other affected acts include Bad Bunny, Miley Cyrus, and Mark Ronson.
The number of identified deepfake tracks merely represents a fraction of the total believed to be uploaded on streaming platforms. With advancements in AI technology making it easier and cheaper to produce such content, the music industry is grappling with an increasing challenge.
Kooker noted that deepfakes are often created during periods of heightened popularity, taking advantage of the demand generated around an artist's music. As the music industry evolves, the conversation about regulatory measures to combat such fraud is becoming increasingly crucial.
Industry Revenues Grow Amidst Challenges
The rise of deepfakes coincides with the recent launch of the music industry's Global Music Report, revealing that recorded music revenues grew by 6.4% over the past year, reaching $31.7 billion. Despite the growth, concerns over AI-generated content and streaming fraud continue to loom over the industry.
As the music landscape evolves, industry leaders are advocating for clear regulations regarding the use of AI, with an emphasis on the need for labeling AI-generated material to help consumers distinguish between authentic and artificial content.





















