SB 53, California’s recently approved AI safety and transparency law, sends a clear message to the industry that it regulates: developing breakthrough systems and addressing high-stakes risks is possible at the same time. Instead of squelching research, the law establishes a floor of acceptable practice — one that serious labs already insist they’re above — while allowing for rapid iteration and market competition.
That balance carries weight in the state that serves as the anchor of the global AI economy. And when the leading labs, the other high-value-added firms that feed off it and most of the foundational model talent are clustered in the Bay Area and Southern California, it’s tough to get away from a policy signal from Sacramento.
What SB 53 Requires From Large AI Developers and Labs
SB 53 is aimed at large AI developers and asks for transparency around safety and security parameters of models with catastrophic risks. Think misuse cases such as automating sophisticated cyber intrusions against infrastructure or helping to develop biological weapons — low-probability but high-impact tail risks that should be addressed proactively before systems scale.
The law goes beyond “publish and forget.” It imposes a requirement that companies adhere to their protections, with enforcement by California’s Office of Emergency Services. Risk claims would be verifiable commitments, not marketing copy. It also pushes labs toward established frameworks, like the NIST AI Risk Management Framework and CISA’s secure-by-design guidance, without stalling technical advancements.
Why the AI Industry Can Live With SB 53 Safety Rules
Importantly, SB 53 is scoped at the developers most capable of deploying models on the scale where misuse could do real systemic damage. That leaves startups, open-source researchers and applied AI teams remaining plenty of room to innovate without as much compliance drag. The rule is straightforward: if you have a safety bar, qualify for it — and prepare to show how.
This becomes more important in competitive cycles when companies might be tempted to trim guardrails in response to a rival’s splashy release. Public statements by major labs have included admissions that there are pressures to “tweak” safety systems in fast-moving markets. SB 53 makes it harder for those safety baselines to be chipped away during a product sprint, benefiting not only users but also other companies that don’t want to race to the bottom.
Investors also have a tendency to reward clarity. Venture capitalists and enterprise buyers are increasingly requesting model cards, red-teaming results and security attestations. Standardizing expectations for the biggest players, California is aiming to cut diligence friction and to make a common language between builders, auditors and customers.
Federal Crosscurrents and the Preemption Battle
SB 53 came against the backdrop of a larger tug-of-war between who gets to make rules. In Washington, a new wave of proposals has aimed to head off state action, including what are commonly called sandbox-like waivers that would allow AI firms to bypass certain federal rules for lengthy periods. Supporters tout uniformity; critics detect a backdoor to nudge aside the states as laboratories of democracy.
But some advocacy groups, like Encode AI, which amassed a coalition of more than 200 organizations to fight blanket moratoriums on state jurisdiction, believe that should not be the default. Their case is simple: states are closer to the impacts and can pilot workable standards more quickly. The National Conference of State Legislatures has been following AI-related bills in over 40 states, from deepfake disclosures to procurement rules — proof that local innovation could already be defining best practices.
The China Argument Requires the Correct Tools
One frequently invoked argument is geopolitical: Any regulation makes the U.S. slower in a technology race with China. But SB 53 is aiming at safety governance, not model performance. If the objective is to gain an advantage, far more forceful levers are available — advanced chip export controls, supply-chain security and manufacturing incentives at home.
Congress has already taken initial steps through the CHIPS and Science Act to increase domestic semiconductor capacity. Measures such as the Chip Security Act propose toughening up export controls and tracking of high-end accelerators. Industry reaction is mixed; companies with heavy revenue exposure hold divergent views and remain skeptical about the industry’s prospects in Europe. Businesses that rely on those suppliers, however, are weighing national security arguments against supply needs. This is the right debate to have — about inputs that really shape long-run capability — not whether safety documentation inhibits progress.
A Model for Pragmatic AI Governance That Scales
SB 53 provides a good example: Find that particular narrow slice of AI deployment where the risks could have societal-scale effects, require transparent safety plans for those situations, hold companies to their own standards with teeth and enforce this through an agency with expertise in navigating corporate crises. It’s the kind of risk-tiered approach well known in aviation, biotech and financial services — areas where oversight and innovation coexist.
The move is also consistent with developing international standards. The OECD’s AI principles, NIST framework and guidance from top civil society groups all prioritize rigorous testing, incident response and post-deployment monitoring. California’s law puts those notions into action by directly obligating the largest developers, without specifying research methodologies or limiting model design.
The lesson is less ideological than practical: Guardrails can de-risk the ecosystem and accelerate adoption by building trust. The upside for companies is predictability; for policymakers, measurable safety outcomes; and for users, systems less likely to fail catastrophically. Innovation and regulation need not be rivals if policy is scoped to the problem and rooted in operational reality.
California just demonstrated how to thread that needle. Others will likely follow.
