That factor is relative to what is reproduced, not to what is ingested. A company is allowed to scrape the web all they want as long as they don’t republish it.

The work is reproduced in full when it’s downloaded to the server used to train the AI model, and the entirety of the reproduced work is used for training. Thus, they are using the entirety of the work.

I would argue that LLMs devalue the author’s potential for future work, not the original work they were trained on.

And that makes it better somehow? Aereo got sued out of existence because their model threatened the retransmission fees that broadcast TV stations were being paid by cable TV subscribers. There wasn’t any devaluation of broadcasters’ previous performances, the entire harm they presented was in terms of lost revenue in the future. But hey, thanks for agreeing with me?

Again, that’s the practice of OpenAI, but not inherent to LLMs.

And again, LLM training so egregiously fails two out of the four factors for judging a fair use claim that it would fail the test entirely. The only difference is that OpenAI is failing it worse than other LLMs.

It’s honestly absurd to try and argue that they’re not transformative.

It’s even more absurd to claim something that is transformative automatically qualifies for fair use.