There isn’t a clear answer yet. There are several lawsuits underway against companies like OpenAI, Microsoft, and Stability AI. Many artists and writers feel that AI is appropriating their work without consent or compensation, threatening their creative livelihoods. Others say that training AI models on copyrighted works is fair use. They argue that AI models learn from these works to generate transformative original content, so no infringement occurs.
A judge in class action lawsuit versus Anthropic AI in 2025 recently ruled that Anthropic's scanning of books to train data was Fair Use, but their use of pirated (illegally copied) works to train was not and that is still going to trial. The final outcome could change in higher court.
First, fair use decisions are highly fact-specific, and the quality of judicial analysis can vary widely from judge to judge. That makes lower court decisions like these challenging to generalize from. Yet these rulings, as the first on these issues, provide an important legal baseline for future AI and copyright disputes, especially as they share some key conclusions. In such an uncertain and new area, any decision provides useful guidance about how to stay on the right side of copyright law.
Second, it is also significant that these two decisions came on summary judgment motions, not after a full trial. What that means is that all the facts and inferences in dispute in the case are held against the moving party (in both cases, the AI company), meaning that these decisions are made with everything taken in the light most favorable to the authors. In some sense, that bolsters the strength of the legal conclusions, but it also means that these decisions are not the best source for learning about how courts understand the technology or the factual landscape around AI – and how they will apply these legal principles going forward.
Third, Judges Alsup and Chhabria approach the fair use analysis somewhat differently, and also seem to have different attitudes towards AI as a technology. That makes it difficult to compare their reasoning one-to-one. But this diversity may strengthen our extrapolations; despite the judges’ diverging views on copyright and technology, these decisions share significant common ground. Understanding the similarities between these two decisions is especially important in light of their differences and the different factual contours of each case. Extracting the consistent conclusions from these two cases points the way towards future legal outcomes, and where key areas of uncertainty or confusion remain.
Many scholars and librarians agree that training AI language models on copyrighted works is fair use and essential for research. If restricted to public domain materials, AI models would lack exposure to newer works, limiting the scope of inquiries and omitting studies of modern history, culture, and society from scholarly research.
This issue is complex, and it will likely take a long time before the lawsuits are settled. Some courts have thrown out parts of the lawsuits, but kept others. Some cases may be settled out of court.
Learn more by checking out the TCC Library copyright guide, where you can also find the below box of information.
This answer adapted under Creative Commons Attribution 4.0 International License from the University of Arizona Libraries.