Wikimedia Files Amicus Brief in NYT v. OpenAI Case: Argues AI Training Is Fair Use, But Substitutive Outputs Require Licensing

The Wikimedia Foundation, the nonprofit operator of Wikipedia, filed an amicus brief on Friday in the landmark copyright lawsuit brought by The New York Times against OpenAI and Microsoft, proposing a nuanced legal distinction. The organization argues that large language models (LLMs) should be legally protected when training on copyrighted work under the doctrine of fair use, but that chatbots which regurgitate articles to users—effectively substituting for the original content—should require licensing.

Stephen LaPorte, General Counsel at the Wikimedia Foundation, stated that an overly black-and-white ruling could threaten the sustainability of free knowledge. He warned that a victory for publishers might allow copyright holders to "gatekeep" even innovative and transformative uses of their work, while a victory for AI companies could constitute "a green light to snub licensing terms and fragment the flow of knowledge between human authors and audiences."

The filing highlights Wikipedia's dual role as both a critical data source for AI training and a platform undermined by AI-driven traffic diversion. Wikimedia notes that its websites have become "one of the most critical sources of data for all artificial intelligence and machine learning training," yet these same systems siphon away visitors, weakening the communities that maintain the sites. Furthermore, Wikimedia argues that services like ChatGPT violate copyright by reproducing text licensed under Creative Commons without adhering to the license's attribution and share-alike requirements.

Despite these concerns, the Foundation acknowledges the utility of LLMs for Wikipedia editors, who use them to fight vandalism, detect copyright violations, and identify articles needing improvement. By advocating for a split ruling, Wikimedia seeks to balance the development of open-source technologies with the protection of the collaborative human knowledge ecosystem.