OpenAI highlights diverse support for fair use in AI training

The fair use argument

OpenAI recently shared excerpts from various legal briefs to support its stance on fair use in U.S. copyright litigation. The company is highlighting a broad coalition of supporters who argue that training large language models is a legally distinct activity from copying works for substitution. They want to frame the issue as a test of how existing copyright principles apply to generative AI technology.

The core of the argument is that AI training serves a different purpose than the underlying works themselves. Supporters claim that the process of training a model does not provide substitute access to copyrighted material. Because of this, they argue it does not create the specific kind of market harm that copyright laws were originally designed to prevent.

OpenAI noted that the New York Times lawsuit specifically asks the court to set aside what the company calls a longstanding fair-use principle. By highlighting these briefs, OpenAI is attempting to show that many different types of organizations believe the current legal trajectory is incorrect. They are positioning the technology as a tool for progress rather than a mechanism for theft.

A broad coalition of voices

The list of entities backing the fair use position is notably diverse, spanning across many different sectors of society. OpenAI cited filings from creators, academics, and legal experts, as well as accessibility advocates and librarians. This includes high-profile figures like Kevin Kelly and Ron Suskind, along with organizations like the American Library Association and the American Council of the Blind.

Business groups and technology associations are also weighing in on the issue. The Consumer Technology Association and the Business Software Alliance are among those who have filed briefs in support of the fair use doctrine. Their involvement suggests that the debate is not just about art or literature, but also about the infrastructure of modern software and business operations.

Even the United States government has weighed in on the matter. The government stated that narrowing the fair-use doctrine to exclude large language model training would be inconsistent with copyright principles. They warned that such a move could potentially hinder both scientific and economic progress for the country.

Historical and practical context

Many of the filings quoted by OpenAI point to historical precedents where fair use supported new technologies. They mention tools such as image search and full-text book search as examples of how copyright law has adapted to new ways of organizing information. These tools allow people to find and interact with data without replacing the original source of that data.

The briefs also highlight how AI tools can provide practical benefits to independent creators and businesses. By reducing operational costs and expanding creative output, these models can help smaller entities compete in a larger market. This perspective frames AI as a productivity multiplier that empowers human creativity rather than a replacement for it.

The argument also touches on accessibility, which is a significant factor for groups like the American Council of the Blind. For these advocates, the ability to process and summarize information through AI is a vital tool for navigation. They see the fair use of training data as a necessary step for making information more accessible to everyone.

The current legal landscape

The legal environment for AI training has been shaped by a series of rulings and settlements throughout 2025. For instance, a court in the Kadrey v. Meta case found that AI training was fair use based on the evidence presented. This specific ruling provided a piece of the puzzle in the ongoing debate over how these models are built.

Other cases have shown more complexity, such as the Bartz v. Anthropic litigation. In that case, the court distinguished between fair-use AI training and the acquisition of pirated books. A court memorandum recently approved a $1.5 billion settlement regarding pirated-book claims, showing that while training might be fair use, the method of acquiring data is still a major legal hurdle.

It is important to note that these rulings do not establish a universal exemption for all AI training. Because U.S. fair-use law is fact-specific, the legal questions remain complex and vary from case to case. Courts may continue to treat training, source-copy acquisition, retention, and output distribution as separate issues rather than one single category.

What comes next for creators

The outcome of these copyright cases will determine the economic model for the next generation of AI. If the courts adopt a broad fair use interpretation, AI companies may continue to train models on massive datasets without seeking individual licenses. This could lead to a faster pace of development but may leave many content creators feeling that their work is being used without compensation.

Conversely, if the courts rule against fair use, it could create a significant barrier for AI development. Companies would need to establish complex licensing agreements with every publisher and creator, potentially slowing down the release of new tools. This would likely increase the cost of AI services for businesses and individual consumers alike.

For now, the legal battle remains in a state of flux as more cases move through the courts. OpenAI’s move to publicize these briefs is a strategic effort to shape public opinion and influence the judicial process. The final decisions will likely hinge on whether judges view AI training as a transformative use of data or a direct substitute for the original works.