The United States government has entered one of the most consequential legal battles in artificial intelligence—and it is backing OpenAI’s argument that training large language models on copyrighted material can qualify as fair use. In this episode of The Daily AI Chat, we unpack TechCrunch’s report on a 20-page Trump administration brief filed in The New York Times’ copyright lawsuit against OpenAI.
The case goes to the heart of how modern AI systems are built. ChatGPT, Claude, Gemini, and other generative AI products learn from enormous collections of books, journalism, websites, images, and other creative works. Much of that material is copyrighted, and creators and publishers argue that technology companies should not be allowed to copy it into training datasets without permission or payment. AI companies respond that model training is transformative: the systems analyze patterns and produce new outputs rather than simply republishing the original works.
The government’s brief argues that restricting this process through an overly narrow interpretation of fair use could damage American scientific progress, economic mobility, and global leadership in artificial intelligence. That intervention does not decide the case, and the administration is not the judge. Still, the federal government’s position could influence the broader policy environment surrounding AI development and copyright.
We examine why the distinction between training and obtaining training data matters. Previous litigation involving Anthropic produced a $1.5 billion settlement over books sourced from illegal shadow libraries, yet the court’s reasoning was comparatively favorable toward the act of training itself. In other words, an AI company might have a stronger fair-use argument for learning from a lawfully acquired work while still facing liability for pirating the copy it used.
That distinction leaves difficult questions unresolved. If training is transformative, should creators receive compensation anyway? Does an AI model compete with the journalists, authors, artists, and publishers whose work helped make it capable? How should courts evaluate models that can reproduce passages or create substitutes for professional creative labor? And should national competitiveness outweigh the property rights and economic interests of individual creators?
This episode explores what the case could mean for OpenAI, The New York Times, publishers, independent writers, AI startups, investors, and anyone who relies on generative AI. A ruling favorable to OpenAI could strengthen the legal foundation for today’s data-hungry training practices. A ruling favoring The Times could force licensing deals, reshape datasets, increase development costs, and alter which companies can afford to build frontier models.
We also separate political advocacy from judicial authority. The administration’s brief is a statement of the government’s interests and legal interpretation—not a final ruling that settles whether OpenAI’s conduct was lawful. The litigation remains before the U.S. District Court for the Southern District of New York, where the specific facts, evidence, and application of copyright law will determine the outcome.
Source: TechCrunch, published September 2, 2026. Written by Amanda Silberling. No individual editor was listed on the article.
Follow The Daily AI Chat for clear, accessible analysis of artificial intelligence, copyright, technology policy, generative AI, business strategy, and the decisions shaping the future of the digital economy.
