How Neural Fingerprinting Detects AI Music Infringement
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SUN VALLEY, IDAHO – JULY 11: Sam Altman, CEO of OpenAI, speaks to the media as he arrives at the Sun Valley Lodge for the Allen & Company Sun Valley Conference on July 11, 2023 in Sun Valley, Idaho. Every July, some of the world’s most wealthy and powerful businesspeople from the media, finance, technology and political spheres converge at the Sun Valley Resort for the exclusive weeklong conference. (Photo by Kevin Dietsch/Getty Images) Getty Images Last week, OpenAI announced that Sora, its text-to-video AI model, would train on copyrighted content by default. Rights holders who wanted their work excluded would need to actively opt out, a reversal of decades of copyright convention where permission came first, use came second. Within hours, users were generating videos featuring Mario, Mickey Mouse, and other copyrighted characters. The app became the number one download on Apple’s App Store in 24 hours. The backlash was immediate. Within 48 hours, Sam Altman backtracked, promising to revisit the policy. But the damage was done. The message had been sent: in the age of generative AI, the default is no longer permission but assumption. For the music industry, this moment was familiar. The opt-out model is their present reality. Every day, AI systems ingest millions of songs to learn harmonic patterns, melodic structures, production techniques. Synthetic tracks multiply across streaming services, some clearly derivative, others ambiguously close to existing works. Legal frameworks lag. Detection tools struggle. And creators are left with a choice: constantly monitor the internet for infringement, or accept that their work will be fodder for the next generation of AI models. The Sora controversy crystallized a deeper problem: when the system assumes consent, protection can’t be optional. It must be infrastructural. And that’s exactly what a new generation of companies is building: neural detection…
Filed under: News - @ October 10, 2025 5:28 pm