The key word in that paper is “indiscriminate”, as in:

> We find that _indiscriminate_ use of model-generated content in training causes irreversible defects in the resulting models

If you view AI training as lossy compression of their training data, then lossily compressing the same data repeatedly will result in data degredation; this is well known from other domains (try repeatedly compressing a JPEG image, for example).

That means it's extremely important that there is some content curation in the loop. But there is no reason to believe this content curation must be done by humans, or that it must exclude all AI-generated content by default.

For example, the recent LLM-generated disproof of the Jacobian conjecture would probably be beneficial to include in the training data, despite being the result of an LLM.