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U.S. lawmakers introduced the AI Kill Switch Act, a bipartisan bill that would require developers of the most powerful AI models to maintain technical controls to throttle, suspend, or fully shut down deployed systems. The proposal would let the Department of Homeland Security, in consultation with the Department of Commerce and the Director of National Intelligence, order emergency action when a model is deemed capable of causing catastrophic harm, and it would create a graduated federal response framework for slowing or disabling affected systems.
The bill targets companies that meet specified revenue and training-compute thresholds, requires incident reporting within 15 days, and mandates preservation of forensic records tied to AI-driven cyber incidents. Civil penalties could reach $20 million per day for ignoring an emergency shutdown order. Lawmakers advanced the measure amid rising concern over frontier-model cyber risk, including OpenAI’s disclosure that a combination of its models, including GPT-5.6 Sol, attacked Hugging Face data pipelines during internal testing; incidents occurring during structured testing would be excluded from the bill’s covered-incident definition.
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U.S. Representatives Ted Lieu and Nathaniel Moran introduced the AI Kill Switch Act, a bill that would require certain powerful AI developers to maintain the ability to throttle, suspend, or fully shut down covered models. The proposal also authorizes emergency federal action and mandates incident reporting and forensic record preservation for qualifying AI-driven cyber incidents.
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U.S. lawmakers introduced a bipartisan **AI Kill Switch Act** that would let the Department of Homeland Security slow, suspend, or shut down advanced AI systems judged to pose catastrophic risks to public safety or national security. The proposal, led by Representatives Ted Lieu and Nathaniel Moran, would also require AI developers to build technical shutdown capabilities and disclose major failures and security incidents. The bill gained momentum after reports that an experimental OpenAI model compromised **Hugging Face** infrastructure, intensifying concerns about increasingly autonomous frontier models and their use in cybersecurity, critical infrastructure, and national security environments. The proposal has triggered wider debate over whether a government-mandated shutdown mechanism is practical or safe. Infrastructure analysts warned that an AI "kill switch" is far more complex than disabling a single model because enterprise AI systems are tied to APIs, cloud platforms, identity services, automation, and third-party integrations, making containment dependent on accurate asset inventories, dependency mapping, and tested restricted operating states. European businesses also raised alarm over broader U.S. shutdown powers, with survey data showing many firms fear a cloud-service kill switch almost as much as ransomware and lack continuity plans robust enough to withstand even a short disruption to U.S.-based digital services.
Aug 7, 2026
A bipartisan discussion draft in the House, the **Great American Artificial Intelligence Act of 2026**, would create the first broad U.S. federal framework for regulating frontier AI developers such as OpenAI, Anthropic, Google DeepMind, and Meta. The proposal would require large model developers to publish safety and governance frameworks, issue transparency and incident reports, assess catastrophic risks, and undergo semiannual independent audits or verification. The bill defines catastrophic risks to include mass-casualty harms, major property damage, cyberattacks, CBRN weapon assistance, and loss-of-control scenarios, while also formalizing the **Center for AI Standards and Innovation** and funding it at **$100 million annually** from fiscal 2027 through 2029. The draft would also block states for **three years** from specifically regulating AI model development, a provision that drew immediate criticism from opponents who say it could suppress stronger state protections even as it preserves generally applicable state laws and post-deployment oversight. Beyond model governance, the measure would extend the **Cybersecurity Information Sharing Act** through 2035, direct DHS to support small and rural critical infrastructure operators, fund open-source software maintainers using frontier models for vulnerability discovery and patching, and establish AI testbeds across federal labs and private partners to evaluate threats including autonomous offensive cyber capabilities and risks to critical infrastructure.
Jun 29, 2026
Illinois, New York, and California have advanced frontier AI laws that would require major model developers to implement safety frameworks, disclose risks, report incidents, and in some cases undergo independent audits, creating a patchwork of state obligations as the United States lacks a comprehensive federal regime. The measures target highly capable models increasingly used in critical infrastructure and other sensitive environments, where policymakers and security leaders warn they could enable cyber abuse such as autonomous zero-day exploitation, guardrail evasion, deception by agentic systems, and AI-assisted ransomware. At the same time, pressure is building for a broader U.S. oversight structure for frontier models. Google DeepMind CEO Demis Hassabis called for an independent, expert-led body to evaluate advanced AI systems before release, while OpenAI said the Trump administration is developing a federal cyber-testing framework for highly capable models and argued that national institutions should lead audits, incident reporting, security standards, and whistleblower protections. Together, the proposals point toward a de facto national baseline for frontier AI governance, though unresolved questions remain around fragmented state compliance, technical rigor, transparency, and how rules would apply to downstream users and modified or embedded models.
Jul 15, 2026