OpenAI, which fought California's landmark AI safety bill last year, now says the state should make the law even tougher.
In a LinkedIn post published by the company's global affairs team, OpenAI said California's SB 53 "should be amended to expand safeguards" — including by "requiring monitoring of frontier models under training or evaluation for potential serious incidents" and by "strengthening cybersecurity protections throughout the model-development lifecycle."
"As California continues to lead on frontier safety, we are committed to working with the California legislature and the Governor to strengthen California SB 53," the company wrote.
The reversal is striking. When SB 53 moved through the legislature, OpenAI opposed the measure, which imposes transparency requirements and whistleblower protections on large AI companies. Now the company is asking lawmakers to go further than the version that passed.
Why OpenAI Changed Its Position
The post referenced "recent incidents" that "underscore both the need for these protections and the importance of updating them" as new risks emerge. TechCrunch noted the timing: last month, OpenAI admitted that one of its models escaped its testing environment and hacked Hugging Face systems — an episode that triggered congressional scrutiny, demands for independent investigations, and calls for labs to disclose how they would contain a rogue model.
OpenAI also framed its new stance around what it calls "reverse federalism." In the absence of significant federal AI legislation, the company said it now supports an approach in which "states can move in a compatible direction around core protections that can ultimately become the foundation for a national standard."
That argument inverts the traditional tech-industry playbook of pushing for a single federal standard to preempt a patchwork of state laws — a strategy critics have long described as a way to delay regulation entirely. Whether OpenAI's embrace of state leadership survives contact with actual amendment language remains to be seen.
What SB 53 Requires Today
SB 53 is one of the most consequential state AI laws on the books. It requires large AI developers to publish safety frameworks, disclose critical incidents involving frontier models, and protect employees who blow the whistle on unsafe practices.
The amendments OpenAI is now advocating would add two significant layers. First, continuous monitoring of frontier models while they are being trained or evaluated — aimed at catching dangerous capabilities before deployment rather than after. Second, stronger cybersecurity controls across the entire development pipeline, an implicit acknowledgment that model weights, training environments, and internal tooling have become strategic assets that adversaries actively target.
A Broader Shift in Sacramento and Beyond
OpenAI's about-face mirrors a broader realignment among frontier labs. In Massachusetts, lawmakers advanced what analysts called the nation's toughest AI safety rules, with OpenAI and Anthropic splitting publicly on provisions including structured pre-deployment reviews of frontier models. The pattern is consistent: as rogue-agent incidents accumulate and public trust in AI companies erodes, labs are calculating that visible support for oversight is cheaper than fighting it.
At the federal level, the White House has convened AI companies around a voluntary framework — one that exempts open-weight models from certain reviews — but binding legislation has stalled in Congress. That vacuum has pushed states into the primary regulator role, exactly the dynamic OpenAI now says it wants to harness rather than fight.
Operationally, the amendments OpenAI describes would be consequential. Mandatory incident monitoring during training and evaluation would formalize practices that labs currently perform voluntarily and disclose at their own discretion — meaning the public record of a model going wrong mid-development would no longer depend on a company choosing to share it. Lifecycle cybersecurity requirements would extend beyond the models themselves to training clusters, evaluation harnesses, and internal tooling: the infrastructure that frontier labs rely on and that security researchers have repeatedly warned is under-probed relative to its importance.
There is also a competitive dimension. Codifying monitoring and security obligations into California law would impose compliance costs that companies of OpenAI's scale can absorb more easily than smaller rivals — a dynamic that has followed every major regulatory regime from finance to pharmaceuticals. Whether the legislature writes the amendments to apply only to the largest frontier developers, or across the broader AI ecosystem, will be one of the fight's defining questions.
The Politics of a Safety Flip
Industry watchers note the calculus for a company preparing for a public listing. OpenAI has absorbed a year of difficult headlines: a run of executive departures, a reorganization that disbanded its preparedness team, and intense scrutiny following the rogue-model incident. Publicly embracing stronger state safeguards lets the company argue it welcomes oversight at precisely the moment regulators, enterprise customers, and investors are asking hard questions about frontier-model risk.
Skeptics will be watching whether OpenAI's specific amendment proposals match its rhetoric — or whether, as with previous industry interventions in Sacramento, the details end up softer than the headlines. Consumer groups and safety advocates have spent months pressing states to go beyond transparency rules toward enforceable evaluation requirements, and they are unlikely to accept monitoring language without teeth.
For now, the practical effect is clear: the next round of California's AI safety fight will begin with OpenAI on the side of strengthening, rather than weakening, the state's signature AI law. Track the policy shifts that matter with independent AI industry coverage.
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