Sources: USPTO and US Copyright Office surprised by DOJ's brief backing OpenAI and Microsoft in New York Times dispute
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| Source: Techmeme | Original article
The Department of Justice filed a brief backing OpenAI and Microsoft in a copyright lawsuit brought by the New York Times, surprising the USPTO and Copyright Office.
The U.S. Department of Justice has entered a statement of interest in the New York Times’ copyright‑infringement lawsuit against OpenAI and Microsoft, arguing that the use of copyrighted works to train large language models (LLMs) should be treated as fair use. The 20‑page filing, submitted on Sept. 1, 2026, contends that training is “exceedingly transformative” because the output does not reproduce source material in a recognizable form and therefore does not harm the market for the original works.
The filing caught two key federal agencies off guard. Officials at the United States Patent and Trademark Office and the U.S. Copyright Office said the DOJ’s position was unexpected, noting that the agencies had not been consulted before the brief was filed. Their surprise underscores how quickly the legal debate over AI training is moving beyond the courts and into the broader regulatory ecosystem.
The case matters because a ruling in the defendant’s favor could cement a broad fair‑use shield for AI developers, lowering the risk of copyright liability for the massive datasets that power today’s models. Creators and publishers, who have long warned that unchecked scraping erodes their revenue, see the argument as a potential tipping point that could reshape how copyrighted content is accessed and monetised online.
The next steps will hinge on the Southern District of New York’s response to the DOJ’s arguments. Observers will watch for a court ruling on the fair‑use claim, any subsequent appeals, and whether the USPTO or Copyright Office issue formal guidance. Industry players, from AI startups to media companies, are likely to adjust their data‑collection strategies based on how the judiciary balances transformation against market impact.
Sources
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