Just days after the first major fair use ruling in a generative-AI case, a second court has determined that using copyrighted works to train AI is fair use. Kadrey et al. v. Meta Platforms, No. 3:23-cv-03417-VC (N.D. Cal. June 25, 2025).
The Kadrey v. Meta Platforms Lawsuit
I previously wrote about this lawsuit in an article describing the top 12 generative-AI lawsuits.
Meta Platforms owns and operates social media services including Facebook, Instagram, and WhatsApp. It is also the developer of a large language model (LLM) called “Llama.” One of its releases, Meta AI, is an AI chatbot that utilizes Llama.
To train its AI, Meta obtained data from a wide variety of sources. The company initially pursued licensing deals with book publishers. It turned out, though, that in many cases, individual authors owned the copyrights. Unlike music, no organization handles collective licensing of rights in book content. Meta then downloaded shadow library databases. Instead of licensing works in the databases, Meta decided to just go ahead and use them without securing licenses. To download them more quickly, Meta torrented them using BitTorrent.
Meta trained its AI models to prevent them from “memorizing” and outputting text from the training data, with the result that no more than 50 words and punctuation marks from any given work were reproduced in any given output.
The plaintiffs named in the Complaint are thirteen book authors who have published novels, plays, short stories, memoirs, essays, and nonfiction books. Sarah Silverman, author of The Bedwetter; Junot Diaz, author of The Brief Wondrous Life of Oscar Wao; and Andrew Sean Greer, author of Less, are among the authors named as plaintiffs in the lawsuit. The complaint alleges that Meta downloaded 666 copies of their books without permission and states claims for direct copyright infringement, vicarious copyright infringement, removal of copyright management information in violation of the Digital Millennium Copyright Act (DMCA), and various state law claims. All claims except the ones for direct copyright infringement and violation of the DMCA were dismissed in prior proceedings.
Both sides moved for summary judgment on fair use with respect to the claim that Meta’s use of the copyrighted works to train its AI infringed copyrights. Meta moved for summary judgment on the DMCA claims. Neither side moved for summary judgment on a claim that Meta infringed copyrights by distributing their works (via leeching or seeding).
On June 25, 2025 Judge Chhabria granted Meta’s motion for summary judgment on fair use with respect to AI training; reserved the motion for summary judgment on the DMCA claims for decision in a separate order, and held that the claim of infringing distribution via leeching or seeding “will remain a live issue in the case.”
Judge Chhabria’s Fair Use Analysis
Judge Chhabria analyzed each of the four fair use factors. As is the custom, he treated the first (Character or purpose of the use) and fourth (Effect on the market for the work) factors as the most important of the four.
He disposed of the first factor fairly easily, as Judge Alsup did in Bartz v. Anthropic, finding that the use of copyrighted works to train AI is a transformative use. This finding weighs heavily in favor of fair use. The purpose of Meta’s AI tools is not to generate books for people to read. Indeed, in this case, Meta had installed guardrails to prevent the tools from generating duplicates or near-duplicates of the books on which the AI was trained. Moreover, even if it could allow a user to prompt the creation of a book “in the style of” a specified author, there was no evidence that it could produce an identical work or a work that was substantially similar to one on which it had been trained. And writing styles are not copyrightable.
Significantly, the judge held that the use of shadow libraries to obtain unauthorized copies of books does not necessarily destroy a fair use defense. When the ultimate use to be made of a work is transformative, the downloading of books to further that use is also transformative, the judge wrote. This ruling contrasts with other judges who have intimated that using pirated copies of works weighs against, or may even prevent, a finding of fair use.
Unlike some judges, who tend to consider the fair use analysis over and done if transformative use is found, Judge Chhabria recognized that even if the purpose of the use is transformative, its effect on the market for the infringed work still has to be considered.
3 Ways of Proving Adverse Market Effect
The Order lays out three potential kinds of arguments that may be advanced to establish the adverse effect of an infringing use on the market for the work:
- The infringing work creates a market substitute for the work;
- Use of the work to train AI without permission deprives copyright owners of a market for licenses to use their works in AI training;
- Dilution of the market with competing works.
Market Substitution
In this case, direct market substitution could not be established because Meta had installed guardrails that prevented users from generating copies of works that had been used in the training. Its AI tools were incapable of generating copies of the work that could serve as substitutes for the authors’ works.
The Market for AI Licenses
The court refused to recognize the loss of potential profits from licensing the use of a work for AI training purposes as a cognizable harm.
Market Dilution
The argument here would be that the generation of many works that compete in the same market as the original work on which the AI was trained dilutes the market for the original work. Judge Chhabria described this as indirect market substitution.
The copyright owners in this case, however, focused on the first two arguments. They did not present evidence that Meta’a AI tools were capable of generating books; that they do, in fact, generate books; or that the books they generate or are capable of generating compete with books these authors wrote. There was no evidence of diminished sales of their books.
Market harm cannot be assumed when generated copies are not copies that can serve as substitutes for the specific books claimed to have been infringed. When the output is transformative, as it was in this case, market substitution is not self-evident.
Judge Chhabria chided the plaintiffs for making only a “half-hearted argument” of a significant threat of market harm. He wrote that they presented “no meaningful evidence on market dilution at all.”
Consequently, he ruled that the fourth fair use factor favored Meta.
Conclusion
The decision in this case is as significant for what the court didn’t do as it is for what it did. It handed a fair use victory to Meta. At the same time, though, it did not rule out a finding that training AI tools on copyrighted works is not fair use in an appropriate case. The court left open the possibility that a copyright owner might prevail on a claim that training AI on copyrighted works is not fair use in a different case. And it pointed the way, albeit in dictum, namely, by making a strong showing of market dilution.
That claim is not far-fetched. https://www.wired.com/story/scammy-ai-generated-books-flooding-amazon/
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