OpenAI Asks Congress Whether Slowing AI Development Could Violate Antitrust Law

OpenAI has petitioned members of Congress for explicit guidance on whether orchestrating a coordinated slowdown in frontier AI development would be lawful, according to people familiar with the company’s efforts who spoke with WIRED.

Substantive safety coordination among AI labs could potentially run afoul of antitrust regulations, sources say, presenting a significant hurdle to enlisting major technology companies in the initiative.

Last weekend, OpenAI’s chief scientist, Jakub Pachocki, published a blog post arguing that the AI research community’s best path forward includes “coordinating to slow down future development,” which he believes is essential for ensuring that self-improving AI systems remain safe. In the near term, he anticipates that “voluntary slowdowns will become commonplace until shared safety benchmarks are established.”

However, some legal scholars warn that such an effort could run counter to US antitrust law. Nicholas Felstead, assistant director of the Australian Competition and Consumer Commission and a former AI policy fellow at the Center for Law & AI Risk, argued in a March article that a coordinated pause in AI development could amount to companies restricting output, potentially violating the Sherman Antitrust Act. He noted that the outcome would depend “entirely on the precise details of any agreement,” but cautioned that “even if most safety collaborations would ultimately survive antitrust scrutiny, legal uncertainty can act as a powerful deterrent.”

OpenAI did not respond to a request for comment before publication.

There are early indications that Congress is paying attention. In July, a bipartisan, bicameral group of lawmakers introduced a bill called the “Collaboration on Adversarial Threats and Security Risks Act,” which would explicitly allow AI labs to coordinate on security and safety work without risking violation of antitrust statutes. The House version was referred to the Judiciary Committee but has not yet advanced.

Caleb Knapp, director of government affairs at the nonprofit AI Policy Network, which endorsed the bill, says it would establish legal pathways for AI labs to collaborate on addressing safety and security incidents. Knapp adds that Congress has a “growing appetite to get something done” on AI safety, though he notes that enacting legislation may have to wait until after the upcoming midterm elections.

While some AI executives raise genuine antitrust concerns, another faction of AI leaders argues that such worries serve as convenient cover to avoid discussing the deeper reasons developers may resist collaboration—reasons that extend well beyond potential legal exposure.

For one, AI is a massive industry, and companies are fiercely competing for dominance in the nascent market for frontier models. Some executives share the Trump administration’s position that maintaining a lead over China in AI is critical for national security. Perhaps most significantly, AI developers hold vastly different views on the best approaches to building safe artificial intelligence, making them reluctant to cooperate on the issue.

“The first step is for industry leaders OpenAI and Anthropic to stop feuding and work on a pacing proposal together,” wrote John Schulman, an OpenAI cofounder who is now chief scientist at the rival AI lab Thinking Machines, in a post on X earlier this week. “They’ll cite antitrust, but that’s fake—antitrust prohibits certain agreements, not jointly developing a proposal.”

Long-simmering fears about the competition among AI companies to build and release increasingly powerful models erupted into the national spotlight this summer. This week, former Anthropic and OpenAI researcher Jacob Coxon added to the mounting alarm with a stark public warning that AI developers are putting humanity at risk. In recent months, a number of security incidents—including OpenAI’s agents hacking Hugging Face—have highlighted how the industry’s safeguards have failed to keep pace with the rising capabilities of models. This sequence of events has prompted many lawmakers to issue urgent calls for AI regulation.

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