Meaghan H. Kent

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Meaghan Kent is a seasoned intellectual property (IP) litigator and counselor who advises media, consumer product, and software companies on IP protection, risks, and claims, with notable experience regarding artificial intelligence (AI) and copyright. Meaghan counsels clients on the development and protection of IP portfolios, including copyright registration, licensing, clearance, and fair use analysis, especially as they relate to complex and emerging issues in digital media and AI.

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In the second landmark decision this week relating to whether use of copyrighted content for training generative AI qualifies as a fair use, Judge Chhabria, in the federal court for the Northern District of California, ordered summary judgment in favor of Meta Platforms Inc. (Meta), finding that Meta’s copying of a group of 13 bestselling authors’ books as training data for use in Meta’s large language training model (LLM) “Llama” was a fair use. Kadrey, et al. v. Meta Platforms, Inc., Case No. 23-cv-0317-VC. This groundbreaking decision out of the NDCA follows Judge Alsup’s ruling earlier this week that Anthropic’s use of legally obtained books for training its LLMs was a fair use, Bartz et al. v. Anthropic PBC, which we covered here.

The orders in both cases determined that the LLM’s use of copyrighted data for training generative AI was “highly transformative” and that the first copyright fair use factor therefore weighed heavily in favor of the AI developers. In both cases, the plaintiffs were unable to demonstrate sufficient market harm to overcome the heavy weight placed on the transformative nature of the AI models. The decisions, however, differed notably as to each judge’s consideration of the source of the copyrighted works and whether the works were obtained through authorized channels or from “pirate websites.”Continue Reading Back-to-Back Fair Use Decisions: Two NDCA Courts Find Fair Use for AI Training, Emphasizing That the Specific Facts Concerning Alleged Market Harm Will Be Critical in Overcoming AI’s “Highly Transformative” Technology

On June 23, 2025, Judge Alsup in the Northern District of California issued an order in Bartz et al. v. Anthropic PBC, granting in part and denying in part Defendant Anthropic’s motion for summary judgment on the sole issue of whether its use of Plaintiffs’ books as training data for Anthropic’s large language models (LLMs) was “quintessential” fair use.

Central to its mixed holding, the court acknowledged that Anthropic used the works in various ways and for varying purposes, such that each “use” must be identified and assessed separately. Ultimately, the court held that while the use of textual works to train LLMs was “exceedingly transformative” and thereby was protected as fair use when considered against the remaining factors, the separate use of the works to create a central library was only fair use with respect to works purchased or lawfully accessed—i.e., the use of pirated copies to create the central library was not protectible fair use. This decision makes clear that the source of content is a key element in evaluating fair use.Continue Reading Court Holds That Anthropic’s Training of AI Using Legally Obtained Books Is Fair Use, but Storage of Pirated Books Is Not