Anthropic asked a federal court Wednesday to throw out copyright infringement claims brought by authors and publishers, arguing the plaintiffs waited too long to sue. The AI company said the writers cannot blame delayed legal action on hidden training data when their own complaint references public disclosures from years earlier.
The timing argument
Anthropic's motion to dismiss centers on the statute of limitations. The company contends that the plaintiffs' own pleading undermines their case by citing publicly available information about Anthropic's training practices that predates the lawsuit. According to the filing, those facts were accessible long before the legal action commenced.
"Plaintiffs can't claim they waited so long due to the concealment of Anthropic's training data since their own pleading cites public disclosures that made those facts available years before the suit," the company said in its motion.
Broader copyright battles over AI training
The case is one of several high-profile disputes testing how copyright law applies to generative AI systems. Writers, artists, and news organizations have filed multiple suits against AI developers, alleging that using copyrighted works to train large language models without permission or payment constitutes infringement. The AI companies have generally responded with fair use defenses and procedural challenges.
Anthropic's strategy of attacking the lawsuit on procedural grounds before reaching the substantive copyright questions mirrors approaches taken by other defendants in similar litigation. A ruling in Anthropic's favor on the timing issue could avoid a deeper examination of whether training on copyrighted texts requires a license.
Why this matters for legal professionals and writers
For lawyers handling AI-related copyright cases, the motion signals that defendants will aggressively test procedural defenses before engaging on the merits. The statute of limitations argument, if successful, could set a precedent that pushes rights holders to file claims more quickly once public information about training data emerges. For writers and publishers, the case underscores the importance of monitoring corporate disclosures about AI training practices and acting promptly when potential infringement comes to light.