I strongly suspect you're right about that. My bet is the court will determine that whether the output of a model is or isn't subject to copyright isn't a blac

I strongly suspect you're right about that. My bet is the court will determine that whether the output of a model is or isn't subject to copyright isn't a black-and-white answer, but rather depends on the work. Fundamentally, the test as to whether a work represents a copyright violation is about "substantial similarity" (https://en.wikipedia.org/wiki/Substantial_similarity https://en.wikipedia.org/wiki/Substantial_similarity): > To win a claim of copyright infringement in civil or criminal court, a plaintiff must show he or she owns a valid copyright, the defendant actually copied the work, and the level of copying amounts to misappropriation. Under the doctrine of substantial similarity, a work can be found to infringe copyright even if the wording of text has been changed or visual or audible elements are altered Okay, so let's say I take a thousand copyright images, averaged their pixels, and produced a single uniform grey output. No jury is going to conclude that work has "substantial similarity" with any of the original works, and I'm clear. But now suppose I do the same, but weight it so 99% of the pixel colour comes from one image, and the remaining 1% comes from the rest. Well, in that case, odds are very good a jury would find me guilty of violating the copyright of that original work that represents 99% of the image. So my bet is the courts will conclude that the model, itself, doesn't in any way violate copyright, nor did the training itself run afoul of the law, but that any given output might, depending on the substantial similarity test. And that means every single work is suspect and a potential target for litigation.