In Pillar 2 of our framework for ethical AI for music, we call out that traceability is key. Knowing which source tracks went into an AI-generated song is a big part of traceability and fair use. Doing this well will be technically challenging. Identifying if a song was AI-generated or not is a good starting point. How can we tell if a song was built with artificial intelligence, or only with human intelligence?

Machine learning is commonly used for this kind of 'binary classification' (yes=AI generated, no=not AI generated). This episode is a quick look at some tools using AI / ML for detecting AI in songs, and some concerns.

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