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AIDRAN STORY
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Title: Copyright Law Has a Test for AI Music. A Legal Scholar Just Explained Why It Might Not Be the Right One.
Beat: AI & Creative Industries
Published: 2026-04-17T23:33:04.832Z
URL: https://aidran.ai/stories/copyright-law-test-ai-music-legal-scholar-36cb

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At a UC Berkeley symposium this week, copyright scholar Matthew Sag posed a question that reframes the entire AI music debate: if an AI model's outputs aren't substantially similar to the works it trained on, does copyright law even apply? And if it doesn't, what framework should?[¹] The question, shared to a small but attentive audience on Bluesky, landed with the quiet force of something that clarifies rather than inflames — a rare register in a conversation that has spent most of its energy on courtroom strategy.

The timing is hard to ignore. {{story:suno-admitted-trained-copyrighted-music-hired-986e|Suno's admission that it trained on copyrighted music}} — followed almost immediately by hiring Timbaland as a strategic advisor — already showed the gap between legal defense and cultural legitimacy. But Sag's framing cuts even deeper than that contradiction. His argument is that the {{beat:ai-creative-industries|AI and creative industries}} conversation has been captured by copyright maximalists and AI minimalists who both assume copyright is the relevant battleground. If the outputs are genuinely transformative enough to fail a substantial similarity test, then the harm being described — to musicians, composers, session players — is real but legally invisible under current doctrine.

That's the crux of what makes this moment uncomfortable for both sides. Artists who feel their livelihoods threatened by generative audio tools don't necessarily want a ruling that says

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