SB 53
In plain wordsA 2025 California law requiring developers of the most powerful AI models to publish their safety plans, report serious safety incidents to the state and protect employees who raise alarms.
California's Transparency in Frontier Artificial Intelligence Act, in force since January 1, 2026, the first US state law aimed specifically at catastrophic risk from frontier modelsfrontier model, n.: One of the most capable AI models in existence at a given time, built by a handful of leading labs at great cost, and the main target of AI safety rules.. It applies to developers that have trained a model with more than 10²⁶ integer or floating-point operations, counting fine-tuning and other modifications. 'Large frontier developers' (over $500 million in annual revenue) must publish a frontier AI framework explaining how they identify and mitigate catastrophic risk, use standards and third-party assessments and secure model weights, and must periodically summarize internal catastrophic-risk assessments for the state Office of Emergency Services. All covered developers publish transparency reports when releasing new or substantially modified models and report critical safety incidents within 15 days, or 24 hours where life is at imminent risk. Catastrophic risk means material contribution to more than 50 deaths or serious injuries, or over $1 billion in damage, through CBRN weapons, cyberattacks or crimes committed without meaningful human oversight, or through loss of control. The act protects whistleblowersAI whistleblower protections, n.: Legal and company safeguards that protect employees of AI companies who report safety dangers or legal violations — to regulators or inside the company — from being fired, sued or otherwise punished., lets the Attorney General seek civil penalties of up to $1 million per violation from large frontier developers, and begins planning for a public computing cluster, CalCompute.
Our SB 53 transparency report went up the same day the new model shipped.
Origin
Introduced by State Senator Scott Wiener after the veto of his SB 1047SB 1047, prop. n.: A 2024 California bill that would have required makers of the biggest AI models to adopt safety plans and take care to prevent catastrophes. It passed the legislature, but the governor vetoed it. and rewritten in 2025 to follow the California Report on Frontier AI Policy (June 2025), commissioned by Governor Gavin Newsom from a group led by Fei-Fei Li, Mariano-Florentino Cuéllar and Jennifer Tour Chayes. Anthropic endorsed it; Newsom signed it on September 29, 2025.
Usage note
Unlike SB 1047 it imposes no duty of care, shutdown capability or mandatory audit: its tools are disclosure, incident reporting and whistleblower protection. New York's RAISE ActRAISE Act, prop. n.: A New York law requiring the largest AI developers to publish how they manage catastrophic risks and to report serious safety incidents quickly to a new state office. It takes effect in 2027. was amended in 2026 to follow its model, and it is central to debates over federal AI preemptionAI preemption, n.: The push in the United States for a single national AI law that would override the states' own AI laws, and the fight over whether that is wise or even lawful..
Related
- SB 1047SB 1047, prop. n.: A 2024 California bill that would have required makers of the biggest AI models to adopt safety plans and take care to prevent catastrophes. It passed the legislature, but the governor vetoed it.
- RAISE ActRAISE Act, prop. n.: A New York law requiring the largest AI developers to publish how they manage catastrophic risks and to report serious safety incidents quickly to a new state office. It takes effect in 2027.
- compute thresholdcompute threshold, n.: A legal cutoff based on how much computation was used to train an AI model. Models trained with more than that amount face extra rules, on the theory that bigger training runs produce more capable models.
- frontier modelfrontier model, n.: One of the most capable AI models in existence at a given time, built by a handful of leading labs at great cost, and the main target of AI safety rules.
- AI whistleblower protectionsAI whistleblower protections, n.: Legal and company safeguards that protect employees of AI companies who report safety dangers or legal violations — to regulators or inside the company — from being fired, sued or otherwise punished.
- responsible scaling policyresponsible scaling policy, n.: A public rulebook in which an AI company promises to test each new model for dangerous abilities and to add stronger safeguards, or slow down, as its models become more capable.
- AI preemptionAI preemption, n.: The push in the United States for a single national AI law that would override the states' own AI laws, and the fight over whether that is wise or even lawful.
Sources
- California Legislature (2025). SB-53 Artificial intelligence models: large developers (Transparency in Frontier Artificial Intelligence Act). Stats. 2025, ch. 138.
- Joint California Policy Working Group on AI Frontier Models (2025). The California Report on Frontier AI Policy.
Defined in law or standards
California SB 53 (Stats. 2025, ch. 138), Transparency in Frontier Artificial Intelligence Act, Bus. & Prof. Code §§ 22757.10–22757.16 (definitions in § 22757.11)
Mentioned in
frontier modelfrontier model, n.: One of the most capable AI models in existence at a given time, built by a handful of leading labs at great cost, and the main target of AI safety rules., loss of controlloss of control, n.: A situation in which people can no longer oversee, correct or switch off an AI system, and have no reliable way of getting that power back., AI incidentAI incident, n.: A real-world case in which an AI system, through a flaw, a breakdown or the way someone used it, ends up hurting people, property or rights, as in an injury, a wrongful arrest or a privacy breach., AI preemptionAI preemption, n.: The push in the United States for a single national AI law that would override the states' own AI laws, and the fight over whether that is wise or even lawful., AI whistleblower protectionsAI whistleblower protections, n.: Legal and company safeguards that protect employees of AI companies who report safety dangers or legal violations — to regulators or inside the company — from being fired, sued or otherwise punished., catastrophic riskcatastrophic risk, n.: The risk that AI could cause disaster on a massive scale — many deaths or enormous damage — through weapons, cyberattacks or systems escaping human control. Several laws now define it precisely., compute thresholdcompute threshold, n.: A legal cutoff based on how much computation was used to train an AI model. Models trained with more than that amount face extra rules, on the theory that bigger training runs produce more capable models., Frontier AI Safety CommitmentsFrontier AI Safety Commitments, prop. n.: Promises made in 2024 by major AI companies to publish safety plans for their most advanced models, including the danger points at which they would stop if the risks could not be controlled., frontier labfrontier lab, n.: One of the handful of companies building the most advanced AI models of the moment, spending billions of dollars on computing power to train them., RAISE ActRAISE Act, prop. n.: A New York law requiring the largest AI developers to publish how they manage catastrophic risks and to report serious safety incidents quickly to a new state office. It takes effect in 2027., responsible scaling policyresponsible scaling policy, n.: A public rulebook in which an AI company promises to test each new model for dangerous abilities and to add stronger safeguards, or slow down, as its models become more capable., SB 1047SB 1047, prop. n.: A 2024 California bill that would have required makers of the biggest AI models to adopt safety plans and take care to prevent catastrophes. It passed the legislature, but the governor vetoed it., system cardsystem card, n.: A public report released with an AI model that explains what it can do, how it was tested for safety, what risks were found and what protections were put in place., third-party AI evaluationthird-party AI evaluation, n.: Testing of an AI system by someone other than the company that made it — a government institute, a nonprofit lab or independent researchers — to check what it can do and how risky it is., global catastrophic riskglobal catastrophic risk, n.: A risk of disaster big enough to badly damage human civilization worldwide, such as killing a large share of humanity, even if humanity eventually recovers., internal deploymentinternal deployment, n.: When an AI company uses its own newest, unreleased AI systems inside the company — for example to write code or do research — before or instead of offering them to the public., SB 243SB 243, prop. n.: A 2025 California law requiring AI companion chatbots to tell users they are not human, respond safely when people talk about suicide, and protect minors, including with regular reminders to take a break.