Yeah, I’ve struggled with that myself, since my first AI detection model was technically trained on potentially non-free data scraped from Reddit image links. The more recent fine-tune of that used only Wikimedia and SDXL outputs, but because it was seeded with the earlier base model, I ultimately decided to apply a non-commercial CC license to the checkpoint. But here’s an important distinction: that model, like many of the use cases you mention, is non-generative; you can’t coerce it into reproducing any of the original training material–it’s just a classification tool. I personally rate those models as much fairer uses of copyrighted material, though perhaps no better in terms of harm from a data dignity or bias propagation standpoint.
Y’all should really stop expecting people to buy into the analogy between human learning and machine learning i.e. “humans do it, so it’s okay if a computer does it too”. First of all there are vast differences between how humans learn and how machines “learn”, and second, it doesn’t matter anyway because there is lots of legal/moral precedent for not assigning the same rights to machines that are normally assigned to humans (for example, no intellectual property right has been granted to any synthetic media yet that I’m aware of).
That said, I agree that “the model contains a copy of the training data” is not a very good critique–a much stronger one would be to simply note all of the works with a Creative Commons “No Derivatives” license in the training data, since it is hard to argue that the model checkpoint isn’t derived from the training data.