Is AI Training on Copyrighted Books Legal? Anthropic’s $1.5 Billion Settlement, Fair Use, Piracy and the Court Battles Reshaping ChatGPT, Claude and Gemini | Daily AI Chat

Can AI companies legally train models on copyrighted books without asking authors for permission? The answer is more complicated than a simple yes or no. In this episode of The Daily AI Chat, we unpack the rapidly evolving court battles over artificial-intelligence training, fair use, piracy, market competition, and ownership of AI-generated work.

TechCrunch senior writer Amanda Silberling explains that models behind ChatGPT, Gemini, Claude, and other chatbots were trained on enormous collections of books, articles, academic papers, and online material. Many authors never knowingly consented to their writing becoming training data, even as generative AI threatens to compete with their work. Yet current copyright law does not automatically make every use of a protected work illegal.

The episode examines the landmark Anthropic litigation in which Judge William Alsup approved a $1.5 billion settlement involving writers. The headline number sounded like a sweeping victory against AI training, but the legal distinction was crucial: the court treated Anthropic’s training process as lawful and penalized the company for obtaining books through pirated shadow libraries. The judge compared model training to an aspiring writer reading literature to learn and create something different rather than reproducing the original works.

That distinction could benefit AI companies. Copyright law focuses heavily on copying and unauthorized reproduction, while merely learning from, experiencing, or using a work can be treated differently. Intellectual-property attorney Cathy Gellis argues that the ruling’s analogy between machine training and human reading may offer AI developers a powerful fair-use framework—even when the associated settlement is financially enormous.

But courts have not adopted one universal rule. Copyright law was last comprehensively updated in 1976, leaving judges to apply decades-old principles to generative AI. Fair-use decisions often turn on whether the new use is transformative, how much of the original work was taken, why it was used, and whether the resulting product damages or replaces the original market.

We compare the Anthropic ruling with Thomson Reuters’ successful case against Ross Intelligence. Ross copied Reuters content to build an AI-powered legal-research platform that directly competed with the original service. Judge Stephanos Bibas found that use was not transformative because the new product served substantially the same market purpose. The contrast suggests that competitive harm may be one of the most important factors in future AI copyright cases.

Authors may argue that chatbots trained on their books can generate synthetic writing that competes with them, but that theory has not yet decisively prevailed. Many major lawsuits remain pending, and early rulings can still be overturned, limited, or contradicted by other courts. AI companies, publishers, writers, investors, and developers are therefore making long-term decisions while the law remains unsettled.

The episode also explores a separate but related question: can AI-generated work itself receive copyright protection? In Thaler v. Perlmutter, a court held that a work generated entirely by AI was not copyrightable because copyright requires human authorship. That raises difficult practical questions about mixed human-and-AI creation. Spell-checking a novel in Microsoft Word does not make Microsoft the author, but where should the law draw the line when an AI system contributes dialogue, structure, images, research, or entire passages?

Source: TechCrunch, published August 23, 2026. Author: Amanda Silberling, Senior Writer. The article includes analysis from intellectual-property attorney Cathy Gellis and attorney Jason Henderson of JWL International. No separate editor was listed.