House Bill Would Require AI Transparency for Copyright Holders

There has been a substantial push and pull in the AI world surrounding copyright law. One key area of concern is the use of copyrighted material in AI training data. This was the central controversy in a case against Anthropic brought by several major publishers. While that case settled, AI training is rife with similar potential infringements. New legislation introduced in the US House of Representatives would make it easier for copyright holders to gain information about what content AI is trained on. A Sheppard Mullin memo discusses the proposed law:

“At the heart of the bill is a new administrative subpoena process added to the Copyright Act. Under the TRAIN Act, a copyright owner who has a good-faith belief that their work was used to train a generative AI model could request a subpoena, issued by the clerk of a U.S. district court, compelling an AI developer to disclose copies of training materials or records sufficient to identify them with certainty. The bill applies not just to original models, but also to substantially modified versions, including those retrained or fine-tuned after initial release.”

If the TRAIN Act becomes law, it could arm potential plaintiffs with evidence needed for litigation. This would likely make pleading infringement easier and lead to more lawsuits like the one againstAnthropic. It would also constitute the first major AI copyright law at the federal level. The bill may face an uphill battle. The administration has shown continued support for AI development and is unlikely to back any law that may impede that.