This seems to logically follow. The copy of a copy of a copy paradigm. We train AI on what humans like. By running stuff back through the trainig data, we're adding noise back in.

To be fair, we already add noise, in that human art has its own errors, which we try to filter out using additional data featuring more of what we want and less of what we don't want.