Discussion
As I noted, Alsup draws a distinction between copying for training the model vs. copying as part of the output - and in doing so quotes Authors Guild v. Google:
> What matters in such cases is not so much “the amount and substantiality of the portion used” in making a copy, but rather the amount and substantiality of what is thereby made accessible to a public for which it may serve as a competing substitute.
That is the key point for the third factor.
He says that the test result *favours* a funding of no infringement. That's different. It means that less copying would have been more infringement.
To me, that makes no sense.
As Alsup quotes, what matters is "the amount and substantiality of what is thereby made accessible to a public". In Alsup's reasoning (which I agree with), you are focusing here on the wrong question -- what went into the model, vs. what it generates.
That said, I don't see the "less copying would have been more infringement" argument. Where do you see that in the text? AIUI, that would only be true if the model generated more infringing outputs.
Twice. Once for the "replacement* copies of the used books they bought and destroyed, and then again for the many copies they made of those copies.
That is very different from what the Google Books court said.
Can you quote the exact passage(s) you're referring to?
In the third factor test, Alsup says that plaintiffs' claim that they could have used other books, or no books at all, is simply not sufficient to hold against fair use: "Because using so many works was reasonably necessary, using any one work for actually training LLMs was about as reasonable as the next." Again, he points out that there were no "revelations to the public of any
portion of the works themselves".
(Copy from https://storage.courtlistener.com/recap/gov.uscourts.cand.434709/gov.uscourts.cand.434709.231.0_3.pdf, page numbers as in document.)
This is a good ruling, because even if you hate LLMs, other operations on legally acquired copies would almost certainly be adversely affected if LLM training was held not to be fair use. Indexing, summarization, improving translation models, etc.
I consider it a good ruling also because unlike a lot of folks on here, I don't hate LLMs -- they're an important foundational technology for things to come.
Just because you're no longer hungry after eating a package of wonder bread (a good result), doesn't make it a good meal. :-)
I see a badly argued ruling that screams for appeal, and that may be bad for Anthropic. It may be possible to get the same or a similar result with an actually good ruling (but of course that's more work), which could be more helpful to LLM developers.
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