⚖️ Academics supporting AI case against Meta

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Legal Scholars Challenge Meta’s Fair Use Defence in AI Training Case

A group of prominent copyright law professors has filed an amicus brief supporting authors who allege Meta infringed their copyrights by using e-books to train its LLaMA AI models. The brief rejects Meta’s argument that AI training qualifies as “transformative” fair use, asserting that such training is functionally similar to teaching a human author—and that, in this case, it serves a commercial goal by enabling content that competes with the original works. This argument has been echoed by several publishing industry groups, including the Association of American Publishers and the Copyright Alliance, who also filed amicus briefs in support of the authors.

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Implications for AI Startups: Fair Use Defense Faces New Limits
This case, Kadrey v. Meta, and the growing number of similar lawsuits suggest that courts are increasingly skeptical of the tech industry’s broad reliance on “fair use” as a shield for AI training practices. U.S. District Judge Vince Chhabria’s decision to allow the authors’ copyright claims to move forward—particularly on allegations that Meta stripped copyright management info to conceal infringement—signals that courts may scrutinize how training data is acquired and labeled. For startups training AI models, this raises the stakes significantly. Simply relying on data scraped from the internet, even if it’s publicly accessible, may no longer be defensible without proper licensing or clear exemptions.

What Founders Should Do Now
For AI and generative content startups, this case is a reminder that legal exposure around training data is growing—and that enforcement could accelerate. Founders should (i) audit their training data sources and remove any clearly copyrighted content lacking a license. (ii) consult legal counsel before relying on a “fair use” rationale for large-scale ingestion of third-party works. (iii) consider adopting “opt-in” licensing models or using synthetic and public domain data. In short, the days of "scrape now, defend later" may be over. Courts are beginning to draw hard lines, and the risk of litigation—especially from well-organized creator groups—is no longer theoretical.

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