Who Gets Credit When Anyone Can Train a Music AI?

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  "description": "Open-source models like MusicGen and LLaRK have made it possible for anyone to generate music trained on unlicensed datasets, with no metadata, no audit trail, and no path to compensation. This panel unpacks the growing attribution crisis: how metadata is breaking down, how local models make enforcement impossible, and how startups and regulators are working to rebuild trust and traceability. Can ethical licensing survive when the tools of mass creation are in everyone’s hands?",
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