California

California's Senate Bill 53, enacted in September 2025, establishes the nation's first state-level AI whistleblower protections through Labor Code §§ 1107-1107.2. Yet SB 53 perpetuates a structural conflict that creates significant barriers to effective disclosure. Evidence required to substantiate catastrophic AI risk claims (model architectures, training data compositions, safety evaluation results, internal capability assessments) would likely qualify as trade secrets protected under California's Uniform Trade Secrets Act. Labor Code § 1102.5(g) explicitly provides that whistleblower protections do not apply to employer actions against employees who disclose trade secrets, meaning CUTSA-protected information falls outside the statute's shield. The collision creates a legal Catch-22: whistleblowers who make generic claims are dismissed; those who provide specifics face civil damages, criminal prosecution, and exclusion from statutory protection. This paper demonstrates that the conflict is structural rather than incidental, that existing trade secret exceptions are unlikely to resolve it, and that case studies at Google, OpenAI, and Meta confirm the pattern empirically. This paper recommends two reforms: first, a narrow amendment to Civil Code § 3426.1 creating a safe harbor that excludes from "misappropriation" disclosures of reasonably necessary information to designated state bodies for reporting significant AI-related public harm; second, establishing a technically competent recipient body, as neither the Office of Emergency Services nor the Attorney General currently possesses AI safety expertise.