The US Government has told a court that AI companies do not break copyright law when they train their models on written work without a license.
The Department of Justice set out that position on Tuesday (September 1), in a filing in the copyright lawsuit brought against OpenAI by The New York Times.
It appears to be the first time Washington has intervened in any of the copyright cases now stacked up against AI companies.
Those cases include the lawsuits filed against Anthropic, Suno, and Udio by the world’s largest music companies.
Every one of them turns on “fair use,” the exception in US copyright law that allows copyrighted material to be reused without permission.
The DOJ has now come down on the AI industry’s side of that question – at least, that is, when it comes to copyrighted text.
The DOJ’s filing – a ‘Statement of Interest Of The United States’, which you can read here – is advice rather than a ruling, and Judge Sidney Stein is free to ignore it in the OpenAI case.
The 20-page document was signed by Stanley Woodward, the Associate Attorney General.
It reads: “The United States has a strong interest in this Court rejecting any argument that training LLMs on copyrighted texts violates copyright law.”
“The United States has a strong interest in this Court rejecting any argument that training LLMs on copyrighted texts violates copyright law.”
Statement of Interest Of The United States
The filing rests on Donald Trump‘s own AI policy, citing two of the President‘s executive orders, from January 2025 and June 2026.
It also quotes his National Policy Framework for Artificial Intelligence, published in March, which states that the “training of AI models on copyrighted material,” in and of itself, “does not violate copyright laws.”
The DOJ takes on the two questions that decide most fair use rulings: (i) how far the new use transforms the original, and (ii) whether it damages the market for it.
On the first, the brief argues that copying text (like the New York Times’) to train a model like ChatGPT is “a use of a different kind or character,” and “extraordinarily transformative.”
On the second, the Justice Department argues that a training copy does not “serve as a substitute for the original,” because training “does not reveal anything to the public at all.”
Large AI companies paying licensing fees to publishers of titles like the NYT “would disproportionately benefit legacy media outlets due to the sheer volume of their written publications,” the US Government adds.
It is not in the public’s interest, the DOJ argues, for the largest tech companies to hold “an oligopoly on LLM training due to licensing entry barriers that function primarily as large subsidies for old mainstream media companies.”
Why this matters for music
To be very clear: the DOJ‘s filing is about words, not songs.
It argues about “copyrighted texts,” “written works,” and “text articles.” Meanwhile, a footnote limits the DOJ‘s reasoning to this case and, specifically, related suits brought by “book authors and publishers.”
Recordings and compositions go completely unmentioned across its 20 pages.
But fair use is fair use. And, obviously, a judge weighing Suno‘s defense may read what the US Government now says the test means.
The DOJ splits the building of an AI model into three stages: (i) acquiring the material, (ii) training the model on it, and (iii) generating outputs.
“Each stage may present distinct questions of copyright law,” the DOJ says – and it defends only the middle one.
In their banner cases against AI companies, the majors and their publishers are attacking all three.
The first stage is how the material was obtained, and it’s an area where the AI industry has already lost ground.
In the precedential book authors’ case against Anthropic, Judge William Alsup ruled in 2025 that downloading books from pirate libraries was not fair use, calling it “straightforward piracy but at massive scale.”
Anthropic settled with those authors for $1.5 billion in September 2025 over the same torrenting.
Two of the four counts in Sony Music Publishing and Warner Chappell Music’s new suit against Anthropic, the fifth music copyright case against the Claude developer, concern torrenting.
The DOJ‘s filing says nothing about any of that.
The second stage at question in AI cases is the training itself (i.e. models being fed information/content, and learning from it).
It’s this stage the DOJ defends, and the one place it goes straight at music’s reasoning.
In 2025, book authors who had sued Meta over AI training lost on fair use. But the judge who decided it, Vince Chhabria, raised a theory that could help rightsholders in future cases.
Chhabria suggested that AI outputs carry the “potential to flood the market with competing works” – and that developers should therefore “generally need to pay copyright holders for the right to use their materials”… even for training.
In other words: for Chhabria, what comes out is evidence that what went in should have been licensed.
Lawyers call that market dilution, and it is the argument music has been building on ever since.
In a brief filed on March 30, the RIAA, NMPA, A2IM, SoundExchange, and four other groups asked a court to reject Anthropic‘s fair use defense (in a legal fight with UMG, Concord, and ABKCO) on similar market harm grounds.
However, the DOJ now calls Chhabria‘s reasoning “deeply flawed,” and says he “improperly collapsed LLM training and LLM outputs into a single continuous use.”
Training and outputs are two separate legal questions, the US Government argues, and what a model produces has no bearing on whether training it was lawful.
If a court accepts that, music can no longer point at a flood of AI tracks as proof that training on UMG or Sony recordings was unlawful.
That wall cuts both ways, which brings us to the third stage of the ‘AI wars’: what the models actually puts out.
The DOJ is not defending outputs – it is saying they must be fought over separately.
At the output stage, the US Government concedes, “certain uses may not be transformative if the LLM reconstructs and disseminates an original copyrighted work.”
As MBW reported in July, that is the ground UMG and Sony Music have chosen against Suno and Udio: that AI-generated songs compete directly with the recordings used to train the models that made them.
Music publishers make the same argument about Claude reproducing lyrics on demand. (A fourth claim sits outside fair use altogether: Sony Music Publishing and Warner Chappell accuse Anthropic of stripping out copyright management information, the ownership data attached to a work.)
The New York Times said on Wednesday (September 2) that the Trump administration “is siding with a handful of trillion-dollar AI companies at the expense of the countless American creators whose work they stole.”
“Both AI and creators can thrive – AI companies simply need to pay fairly for the content that makes their products possible, as copyright law requires,” said Graham James, a spokesperson for the paper.
“The Administration’s proposal to let companies take that content without permission or compensation would undermine the sustainability of the human-created content that a healthy society depends on, and which AI needs to function.”Music Business Worldwide
On September 1, 2023, the U.S. Department of Justice (DOJ) submitted a significant filing in a copyright lawsuit involving OpenAI and The New York Times, asserting that AI companies do not infringe copyright law when training their models on copyrighted written materials without a license. This intervention marks the first instance of the U.S. government engaging in the ongoing copyright disputes facing AI firms, including cases against Anthropic, Suno, and Udio, initiated by major music companies.
Central to these cases is the concept of “fair use,” a provision within U.S. copyright law that permits certain uses of copyrighted material without permission. The DOJ’s position supports the AI industry regarding the use of copyrighted text, emphasizing that the training of AI models on such material does not violate copyright laws. The DOJ’s filing, termed a « Statement of Interest, » was signed by Associate Attorney General Stanley Woodward and articulates the government’s strong interest in affirming that training large language models (LLMs) on copyrighted texts should not be seen as a copyright violation.
The filing references policies established during Donald Trump’s presidency, including executive orders and a National Policy Framework for Artificial Intelligence, which assert that training AI models on copyrighted content does not constitute an infringement. The DOJ’s argument hinges on two primary fair use considerations: the transformative nature of the AI’s use of the original work and the impact on the market. The DOJ contends that using copyrighted text to train models like ChatGPT transforms the original work significantly and that such training does not serve as a substitute for the original content, as it does not disclose the training material to the public.
Furthermore, the DOJ argues that imposing licensing fees for training data could unfairly benefit established media companies, thus limiting competition in AI development. The government claims that allowing large tech firms to dominate AI training through licensing would create an oligopoly that is not in the public interest.
While the DOJ’s argument specifically addresses written works, implications for the music industry are notable. The DOJ’s reasoning may influence courts in ongoing music copyright cases, even though the government did not address the nuances of music copyright directly. The DOJ breaks down the AI model training process into three stages: acquiring material, training the model, and generating outputs. Its defense focuses primarily on the training stage, as this is where fair use is contested heavily.
In prior cases, such as those involving Anthropic and Meta, courts have ruled that the manner in which material was obtained is crucial and can lead to significant legal ramifications. For example, a court ruled against Anthropic for downloading books from pirated sources, which was deemed “straightforward piracy.” The DOJ’s filing does not discuss these aspects.
The second stage, the training process, is where the DOJ challenges existing interpretations of fair use, particularly concerning music. A 2025 ruling involving Meta suggested that AI outputs could potentially harm markets for original works, implying that AI developers should pay copyright holders for using their materials for training. This perspective has been a cornerstone of arguments made by music rights holders.
The DOJ counters this viewpoint, arguing that the training of AI and the outputs generated should be treated as separate legal questions. The government posits that the legality of training does not hinge on the potential market impact of the outputs produced, thus weakening the music industry’s case against AI companies.
At the output stage, the DOJ acknowledges that certain uses may not be transformative if AI outputs directly replicate original copyrighted works. Major music companies like UMG and Sony Music argue that AI-generated songs compete with existing recordings and that AI models reproduce lyrics without authorization. These arguments are integral to the lawsuits filed against AI companies, asserting that outputs can infringe upon copyrights.
Critics of the DOJ’s position, including representatives from The New York Times, assert that the administration’s stance favors large AI corporations at the expense of individual creators. They argue that allowing companies to utilize copyrighted content without compensation undermines the sustainability of original human-created works, which are essential for a healthy creative ecosystem.
Overall, the DOJ’s filing represents a pivotal development in the intersection of copyright law and AI technology, potentially reshaping the legal landscape for how AI companies engage with copyrighted materials. As the conversation around AI and copyright continues to evolve, the outcomes of these lawsuits will likely have far-reaching implications for both the technology and creative industries.
