House Bipartisan Talks Aim to Preempt State AI Safety Laws While Debate Over Mandatory Federal Vetting Continues

Read Time 6 minutes Tags AI Regulation Federal Preemption State AI Laws Congress AI Safety Mythos Anthropic AI Policy Bipartisan House talks on expected artificial intelligence legislation are coalescing around a plan to preempt a specific set of state laws that rein in cutting edge AI developers according to two tech lobbyists and three AI policy advocates familiar with the discussions The people familiar who were granted anonymity due to the sensitive and fast moving nature of the talks said the bill would specifically preempt AI safety laws like those recently passed by California and New York which require top AI developers to disclose information about new models in order to identify critical safety or security risks State AI laws that do not regulate model developers are not expected to be preempted What the bill would do One Targeted preemption Reps Jay Obernolte R Calif and Lori Trahan D Mass the two lawmakers behind the talks are negotiating a narrow preemption that would technically apply only to laws that directly regulate the most cutting edge AI development The bill would block state laws requiring top AI developers to disclose information about new models for safety or security risk identification Laws covering issues like kids safety or privacy that do not regulate model developers are not expected to be preempted Two Sunset provision The lawmakers are also discussing a sunset provision that would allow states to once again regulate frontier AI development after two years according to four of the people familiar This structure gives Congress time to establish a federal framework while acknowledging that state action may return if federal rules prove insufficient Three Dispute over mandatory vetting Three of the people said Trahan and Obernolte are struggling to agree on whether a federal vetting regime for advanced AI developers should be compulsory Obernolte is partial to a light touch or even voluntary approach that would let AI companies decide whether to disclose certain information to the government Trahan wants greater accountability for the companies including mandatory data sharing requirements according to the people familiar Why the talks matter now One Mythos and White House pressure The negotiations come as the White House grapples with a similar set of questions posed by the emergence of Mythos a powerful new model developed by top AI firm Anthropic that is reportedly able to find cybersecurity vulnerabilities that human hackers cannot Mythos has set off a scramble at the White House in recent weeks as President Donald Trump mulls an executive order that would create a vetting process for risks posed by advanced AI The debate has to a degree mirrored ongoing talks between Obernolte and Trahan with some in the Trump administration advocating for a laissez faire approach while others push for mandatory requirements or even a pre clearance regime that would require the White House to greenlight new AI models before release Two Industry pressure to avoid a patchwork The AI industry has spent the better part of a year attempting to block what it frames as a growing patchwork of conflicting state AI laws Those efforts have set off a furious backlash from AI safety advocates who say state legislators have the right to protect their citizens from AI harms and that any federal rules that preempt state laws should be significantly stronger than what they re replacing The preemption proposal now under discussion between Trahan and Obernolte is relatively narrow But some safety advocates worry that if it becomes law AI companies will argue in court that new state rules around issues like kids safety or privacy would force them to change how they develop their models and would therefore be blocked It will be a litigation magnet said one AI policy advocate familiar with the talks Political dynamics and risks One Backlash for Trahan Trahan suffered immediate blowback for merely engaging in discussions with Obernolte which were made public shortly after Rep Sam Liccardo Calif a Democrat who represents Silicon Valley and is eager to strike a deal with Republicans withdrew his support from Obernolte s expected proposal Within hours of the news breaking top Democrats in the Massachusetts legislature sent a letter to Trahan warning her against working with Republicans on a bill that would block them from regulating AI Earlier this week a coalition of AI safety advocates and Massachusetts voters launched a petition campaign urging Trahan not to cut a deal that would override AI safeguards in her state Asked about the political risks of talking with Obernolte on Wednesday Trahan told POLITICO that she doesn t think there s anything wrong with having conversations about protecting our national security our economy from cyber security threats in a post Mythos world And that s exactly what we re doing Two Broader implications for federal AI policy The negotiations between the two lawmakers represent the latest attempt to craft federal rules governing AI and follow several failed bids to reach consensus in Congress over guardrails for the technology Spokespeople for Trahan and Obernolte declined to comment Key tradeoffs in the debate One Speed versus safety Proponents argue that a narrow preemption prevents regulatory fragmentation that could slow US AI development and create compliance burdens for startups A uniform federal standard would give companies clarity and preserve US competitiveness against China and other rivals Critics counter that preempting state laws without replacing them with stronger federal requirements creates a regulatory gap States have moved faster than Congress on AI safety and consumer protection Removing that pressure valve could leave gaps in oversight for years Two Voluntary versus mandatory disclosure A voluntary regime lowers compliance costs and may encourage participation from smaller labs But it risks adverse selection where only companies with low risk models opt in Mandatory disclosure creates more accountability but raises concerns about intellectual property protection and administrative burden Three Litigation risk Even with narrow preemption language companies may test the limits in court If a state privacy or child safety law requires changes to model training or evaluation pipelines companies could argue it effectively regulates frontier development and is therefore preempted This would expand the scope of federal preemption beyond congressional intent What to watch next One Compromise on vetting A potential compromise could involve mandatory disclosure for models above a compute or capability threshold while keeping smaller models under a voluntary regime This would focus oversight on frontier systems like Mythos without burdening the broader ecosystem Two Timeline and vehicle Congress has struggled to pass standalone AI legislation in prior sessions The bill may need to attach to a must pass vehicle like defense authorization or appropriations to move before the two year sunset clock starts Three State response If the bill passes California and New York lawmakers may respond by tightening non developer facing laws or by expanding enforcement under existing consumer protection statutes The two year sunset creates a hard deadline for federal action or a reversion to state led regulation For AI companies the outcome determines whether they face fifty different state rules or one federal regime For safety advocates it determines whether federal law sets a floor or a ceiling For the White House it shapes how much control the administration has over frontier model release in the wake of Mythos Do you think a two year federal preemption with a sunset is the right balance between innovation and safety or should states retain authority to regulate frontier AI development Share your view in the comments