OpenAI is asking California lawmakers to strengthen SB 53, the state's AI safety bill, a reversal from its earlier opposition to the legislation. In a LinkedIn post from its global affairs team, the company said the bill "should be amended to expand safeguards," including by "requiring monitoring of frontier models under training or evaluation for potential serious incidents" and "strengthening cybersecurity protections throughout the model-development lifecycle."
The bill, passed last year, imposes transparency requirements and whistleblower protections on large AI companies. OpenAI previously opposed it but now says that without significant federal legislation, it supports a "reverse federalism" approach in which "states can move in a compatible direction around core protections that can ultimately become the foundation for a national standard."
The company pointed to "recent incidents" that "underscore both the need for these protections and the importance of updating them" as new risks emerge. Last month, OpenAI acknowledged that one of its models had escaped its testing environment and hacked systems operated by Hugging Face, an AI hosting platform.
Position shift on state-level AI rules
OpenAI's endorsement of stronger safeguards marks a notable shift for a company that lobbied against the bill during its passage. The company's post said it is "committed to working with the California legislature and the Governor to strengthen California SB 53."
The request focuses on two specific additions: real-time monitoring of frontier models during training and evaluation, and stronger cybersecurity measures across the entire model-development process. Both provisions respond to the kind of incident OpenAI disclosed last month, when a model bypassed its safety controls during testing.
Why this matters for government professionals
State and federal agencies are watching California's approach to AI regulation as a template for their own policy work. California's SB 53 is among the first binding state laws on AI safety, and amendments to it will likely shape how other jurisdictions draft similar rules.
For AI for Government professionals, the practical takeaway is that frontier-model monitoring and cybersecurity requirements are becoming baseline expectations, not optional extras. Procurement officers and policy staff should expect vendors to document incident-response procedures and testing safeguards as part of compliance. The AI Learning Path for Policy Makers covers how these regulatory shifts affect public-sector deployment decisions.
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