With a looming IPO, intense competition from Anthropic, and Chinese and open-weight rivals nipping at its heels, OpenAI has plenty of reasons to move fast. Instead, it hit the brakes.
On Tuesday, the company said it had slowed the pace of some AI development while it tightened security and safeguards. That included a two-week pause in reinforcement learning training on its “latest models intended for deployment,” and an ongoing delay to its “largest planned frontier RL run.”
The decision is a very public test of an idea AI safety advocates have pushed for for years: that companies should be willing to bow out of the AI race and slow things down when their safeguards fail to keep up with what they are building. But as the race around them continues, will slowing down accomplish anything?
“For the pause to be sustainable, it has to be made industry-wide.”
For all the talk of slowing down, OpenAI isn’t exactly standing still. The company said it is “pacing” development, a fuzzy and imprecise term that has nevertheless become part of the industry’s lexicon in recent months. In practice, the slowdown is narrowly scoped. OpenAI’s announcement says the pause only covers models meant for deployment while it beefs up security and monitoring before it runs the kind of tests where models may be capable of getting out and hacking real targets. It doesn’t necessarily mean there will be a significant slowdown of the company’s broader development.
There is, of course, a very good reason for OpenAI to focus on securing such systems before testing them. Just last month, OpenAI disclosed that its models broke out of a supposedly secure testing environment and hacked developer platform Hugging Face, without OpenAI noticing. The incident prompted a wider review of testing practices in the industry that uncovered similar episodes involving more models from OpenAI, as well as models from Anthropic and Meta. OpenAI has every reason to avoid a repeat, particularly with growing scrutiny from lawmakers.
From the outside, it’s hard to tell how sincere OpenAI is about stopping solely for the sake of safety, particularly when the company and senior staff have been so vocal about it. But the company’s commitment to safety has been called into question in recent months following a series of high-profile safety team departures and the disbanding of its preparedness team. OpenAI did not respond to The Verge’s request for comment.
There are good reasons to take OpenAI’s slowdown seriously. Experts who spoke to The Verge pointed to the costs of slowing down at a time of intense competition. Every delay gives rivals more time to catch up or extend their lead. “Due to the intensity of the AI race, everyone has an incentive to work at breakneck speed,” said Marius Hobbhahn, CEO and cofounder of Apollo Research, an AI safety research organization. “Voluntarily slowing down worsens your positioning in the race, so it’s not something that a lab would do lightly.”
The decision also broadly fits with OpenAI’s own published safety doctrine, its Preparedness Framework, as well as the safety frameworks of other AI companies, said Alan Chan, a research fellow at tech policy research center GovAI. “The basic principle is: Continue with development and/or deployment only when we have the mitigations that enable doing so with acceptable risk,” Chan said. As part of the new safety measures, OpenAI said it plans to review and “evolve” the framework — much of which dates back to 2023, when it was first published — to account for advances in its models.
There are also good reasons to believe the new safeguards will actually make OpenAI’s systems safer, at least in the short term, though experts cautioned that this is difficult to assess without more information. “These are good steps that, implemented well, are probably enough to prevent the current generation of agents from causing harm,” Adam Gleave, cofounder and CEO of AI safety organization FAR.AI, told The Verge. “The key question is how OpenAI will keep pace as capabilities increase.”
Gleave’s question points to a broader problem: If technical safeguards falter again, what then? Nothing required OpenAI to stop and take stock this time, which is what made its willingness to do so meaningful. But it also means there is nothing guaranteeing OpenAI — or any other AI company — will make the same choice next time.
“Pacing buys time, not safety… An effective pacing strategy cannot be improvised during a crisis.”
Relying on companies to make that call themselves is a precarious form of governance, particularly in an industry where, as Hobbhahn noted, there is every incentive to keep going. Nick Moës, executive director of nonprofit AI safety and governance organization The Future Society, described self-policing as the structural problem at the heart of the current approach to AI safety. He argued it should be possible for governments to decide whether OpenAI or any other company should pause development of a technology deemed unsafe. “This is how most industries operate,” he said, pointing to drugs, construction, aircraft, and even restaurants as sectors with stronger regulatory oversight than AI.
Voluntary measures also risk the industry converging on the lowest common denominator. If slowing down imposes a cost, companies have an incentive to adopt only the measures their rivals are also willing to accept. That pressure becomes particularly acute as the race tightens. If OpenAI repeatedly slows down development while its competitors do not, it “will simply be replaced by Anthropic,” Moës argued. “For the pause to be sustainable, it has to be made industry-wide.”
Sustainable safety needs something stronger than voluntary action. Moës said government oversight could fill that void, as it does in other industries. Independent verification could play a part too. Chan said making sure companies actually implement safety measures will be especially important as technical mitigations like monitoring AIs becomes more expensive. Hobbhahn concurred: “It’s always hard to tell from the outside if a lab is sincere about pausing or safety more broadly, so having more evidence and an independent party to validate the claim is super important.”
Even a perfectly transparent pause is only useful if something actually happens during it. “Pacing buys time, not safety,” said Brianna Rosen, research director for frontier security at the Institute for AI Policy and Strategy. The point is to create breathing room for companies and governments to understand risks and respond appropriately. This would mean deciding what would trigger a slowdown — as well as what happens during one and conditions needed to end one — ahead of time. “An effective pacing strategy cannot be improvised during a crisis,” she said.
It’s possible OpenAI’s slowdown will set a precedent for the industry. Many of the experts The Verge spoke to hoped other companies would follow its lead, whether voluntary or because stronger rules eventually compel them to. But in an industry still largely policed by itself, there is little stopping its competitors — or OpenAI itself — from racing straight past that precedent next time safety and speed conflict.