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With two caveats: 1. Plagiarism. If you near-copy large chunks of a good piece, these chunks will be good. 2. Large-scale curation. If you generate thousands of samples and hand-pick the best, they may be good by happenstance (especially for music, where the space is smaller)
However, algorithms (and ML in particular) absolutely do have a role to play in music creation. What's broken is the general approach of statistical mimicry, e.g. raw deep learning. To generate good music programmatically, you need an algorithmic model of what makes music good.
If you understand what makes music good with a sufficient level of clarity, you can express it in rules form, and seek to algorithmically maximize this greatness factor.
As usual with AI, this requires first understanding the subject matter by yourself, instead of blindly throwing a large dataset at a large model -- an approach which could only ever achieve local interpolation. Find the model, don't just fit a curve.
Why do they have a role? What does AI “solve” in music? Why *should* it exist? Make movie scores cheaper? Music is broadly accessible- it’s not unlocking anything. Can it be art itself? Hard to imagine unless it’s 1st principles constructed - a student of music theory + math
This reminds me of research on whether other animals can truly dance. It turns out, only animals with the ability to mimic the sounds made by others (parrots, elephants, etc) are able to hear a beat and respond to it. Mimicry seems important. Composition and synthesis seems hard.
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