A federal judge in California ruled in favor of Meta regarding a lawsuit initiated by 13 book authors, including Sarah Silverman, concerning the alleged unauthorized use of their copyrighted works for training artificial intelligence models.
Federal Judge Vince Chhabria issued a summary judgment, which allowed for a judicial decision without a jury, determining that Meta’s AI model training, in this specific instance, conformed to the “fair use” doctrine of copyright law, thereby deeming it lawful. This decision follows a recent ruling where a federal judge similarly sided with Anthropic in a comparable lawsuit. These judicial outcomes are observed as favorable to the technology sector, which has engaged in ongoing legal disputes with media entities, asserting that training AI models on copyrighted materials constitutes fair use under existing legal frameworks.
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Judge Chhabria clarified that his decision does not universally legalize all instances of AI model training on copyrighted materials. He stated that the plaintiffs in the Meta case “made the wrong arguments” and did not provide sufficient evidence to support their claims. The judge remarked, “This ruling does not stand for the proposition that Meta’s use of copyrighted materials to train its language models is lawful.” He further elaborated, “In cases involving uses like Meta’s, it seems like the plaintiffs will often win, at least where those cases have better-developed records on the market effects of the defendant’s use.”
The court found Meta’s use of the copyrighted works to be “transformative,” indicating that the company’s AI models did not merely replicate the authors’ original books. Additionally, the plaintiffs failed to demonstrate that Meta’s copying of the books caused harm to the market for those authors’ works, a crucial element in assessing copyright infringement. Judge Chhabria noted, “The plaintiffs presented no meaningful evidence on market dilution at all.”
Judge Chhabria emphasized that fair use defenses are highly dependent on the specific facts of each case, suggesting that certain industries might possess stronger fair use arguments than others. He indicated that “markets for certain types of works (like news articles) might be even more vulnerable to indirect competition from AI outputs.”
