OpenAI has asked members of Congress in recent weeks for clear guidance about whether orchestrating an industry-wide slowdown on frontier AI development would be legal, people close to the company tell WIRED.

Substantive coordination on safety between AI labs may risk running afoul of antitrust law, the people say, which poses a significant obstacle to bringing major tech giants on board with the effort.

Last weekend, OpenAI’s chief scientist, Jakub Pachocki, published a blog post arguing that the best path forward for the AI research world includes “coordinating to slow down future development,” which he thinks will be key to ensuring that self-improving AI systems are safe. In the short term, he expects “voluntary slowdowns to become commonplace until shared safety bars are established.”

But some legal scholars say such an effort could conflict with US antitrust laws. 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 may amount to companies restricting output, potentially violating the Sherman Antitrust Act. It would depend “entirely on the precise details of any agreement,” Felstead wrote. “But 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 ahead of publication.

There are some early signs that Congress is listening. In July, a bipartisan, bicameral group of lawmakers introduced a bill titled “Collaboration on Adversarial Threats and Security Risks Act,” which would explicitly permit AI labs to coordinate on security and safety work without the risk of violating antitrust statutes. The House version was referred to the Judiciary Committee but has yet to be taken up.

Caleb Knapp, director of government affairs at the nonprofit AI Policy Network, which endorsed the bill, says it would create legal channels for AI labs to work together to address safety and security incidents. Knapp adds that Congress has a “growing appetite to get something done” on AI safety but says enacting anything into law may have to wait until after the upcoming midterm elections.

While some AI executives may have genuine concerns about antitrust, another camp of AI leaders argue those worries are just convenient cover to avoid discussing the real reasons that AI developers may be wary about collaborating, which go far beyond potential legal liabilities.

For one, AI is a massive business, and these companies are fiercely competing to capture a slice of the nascent market for frontier models. Some executives share the Trump administration’s view that staying ahead of China in AI is crucial for national security. Perhaps most importantly, different AI developers have vastly different opinions about the best way to develop safe artificial intelligence, and therefore may be reluctant to work with one another on the issue.

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

Long-simmering fears about the race among AI companies to build and release ever more powerful models erupted into the national spotlight this summer. This week, former Anthropic and OpenAI researcher Jacob Coxon added to the growing alarm when he issued a stark public warning that AI developers were putting humanity at risk. In recent months, a number of security incidents, including OpenAI’s agents hacking Hugging Face, highlighted how the industry’s safeguards have failed to keep pace with the rising capabilities of models. The succession of events has led many lawmakers to make urgent calls for AI regulation.

This is an edition of Maxwell Zeff’s Model Behavior newsletter. Read previous newsletters here.