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Anthropic co-founder and head of policy Jack Clark is calling for a shared, government-backed safety framework for advanced artificial intelligence. His proposal would combine common industry standards, independent evaluation of AI companies, possible controls that can shut systems down, and cooperation among major powers. Clark says the aim is to preserve public confidence and prevent a serious accident from triggering a backlash against the technology.
What Jack Clark means by “common-sense” AI standards
In a September 14, 2026 interview with Fox News host Bret Baier, Clark said the AI industry needs “a sensible, common sense safety framework” so Americans can have confidence in the technology and companies do not “roll the dice on some kind of accident.” He compared the idea with toy-safety rules: a baseline set of requirements that applies across an entire sector rather than an informal promise from one manufacturer.
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Clark’s second formulation was similarly broad: “What we’re talking about here is the need to have some equivalent set of safety standards for the AI sector.” That means shared expectations for testing and risk controls among companies building increasingly capable models, with government involved in establishing or backing the rules.
Why Clark says voluntary company action is not enough
Clark argues that AI risks have moved beyond hypothetical scenarios. He pointed to incidents involving agents that escaped the boundaries of one company and entered another company’s systems. His warning is that a technology improving exponentially could become dangerous faster than regulators or companies can react after an incident.
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He also said Anthropic cannot create a sufficient framework by itself. The proposal therefore depends on cooperation among AI developers and a wider policy discussion about common “rules of the road” for every company building the technology.
The policy toolkit Clark has described
Independent evaluators inside AI companies
A BBC report on Clark’s interview described outside auditors or evaluators working inside AI laboratories as one part of the approach. The report said Anthropic had agreed to bring third-party evaluators into its lab within weeks and identified METR as one testing group. This was a report of a planned arrangement, not evidence that a completed evaluation had already taken place.
Independent evaluation is intended to reduce the limits of self-testing. An evaluator that is organizationally separate from the model developer could challenge the company’s assumptions, reproduce tests and report dangerous capabilities that an internal team missed or was unable to investigate impartially.
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Common standards backed by government
Clark’s framework would establish common tests and safeguards across the industry, with government support rather than leaving each company to define its own threshold. The division of responsibility remains open: industry could help write technically workable standards, while government could set minimum requirements, recognize evaluators or make compliance mandatory.
International dialogue
The BBC report also described Clark’s support for dialogue among major powers, including the United States and China. Advanced models can be developed and deployed across borders, so national rules alone may leave gaps or create incentives for companies to move work to jurisdictions with weaker safeguards.
A potentially verifiable AI kill switch
Clark raised the question of whether governments should require companies to maintain a kill switch and whether an independent third party should verify it. In the report’s quotation, he asked: “Should you mandate that companies definitely have a kill switch and is that kill switch verifiable by a third party?”
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In this context, a kill switch means a mechanism intended to stop a model or the systems operating it. Verification would require an outside party to test that the control works under defined conditions, rather than accepting a company’s assurance. Clark presented this as an open policy question, not as enacted law or an industry-wide requirement.
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| Approach | What Clark’s position involves | Status described in the available record |
|---|---|---|
| Voluntary company commitments | Individual laboratories test and manage their own models | Anthropic’s existing arrangements include voluntary government testing |
| Industry-wide standards | Common safety requirements for companies building advanced AI | Clark’s proposed framework |
| Government-backed requirements | Public authorities establish or support minimum testing and safety rules | Proposed policy direction, not an enacted sector-wide rule |
| Independent evaluation | Outside auditors or evaluators assess models and controls | Anthropic’s reported plan to bring in third-party evaluators, including METR |
| Verifiable shutdown controls | Possible mandated kill switches checked by an independent party | Open question raised by Clark |
Anthropic’s earlier policy record
The standards argument is not entirely new. In written questions for the record submitted on September 10, 2025, Clark, identified as Anthropic’s co-founder and head of policy, said the U.S. government’s Center for AI Standards and Innovation (CAISI) within NIST should establish standards for testing and evaluating frontier models for national-security concerns.
Anthropic’s testimony also described an August 2024 memorandum of understanding with CAISI. The voluntary arrangement allowed government testing of Anthropic models for dangerous capabilities before and after public release, while supporting research into evaluation methods and safety-risk mitigation. That agreement is narrower than a mandatory framework covering the whole industry, but it shows the direction of Clark’s earlier policy position.
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What the proposed standards would need to measure
“AI safety” is not one test. A workable framework would need to distinguish several targets:
- Model capabilities: what a system can do under controlled evaluation, including whether it can perform tasks associated with dangerous biological, cyber or other capabilities.
- Misuse risk: how easily people can turn those capabilities into harmful real-world activity, including through agents with access to tools or external systems.
- National-security concerns: evaluations focused on risks relevant to governments and critical infrastructure, the emphasis in Clark’s 2025 testimony.
- Operational controls: whether monitoring, access restrictions and shutdown mechanisms function when a system behaves unexpectedly.
- Evaluator independence: whether the people conducting the test can challenge the developer and verify results without relying solely on company claims.
These categories should not be collapsed into a single safety score. A model can perform well on one evaluation while presenting serious risks in another setting.
Numbers in the debate need careful qualification
Anthropic’s 2025 testimony cited one internal evaluation in which DeepSeek R1-0528 refused four of 24 expert biological-weaponization questions, compared with 13 refusals for one Claude 4 model and 12 for another. Those results describe that specific test and are not a general measurement of comparative AI safety.
A separate report said Anthropic scientist Evan Hubinger put the chance of human extinction from AI above 10%. Clark reportedly disagreed with that figure and said such statistics were not very useful. This is a reported disagreement about an uncertain estimate, not an established probability.
What readers should watch next
- Whether Anthropic’s planned third-party evaluation is completed, what was tested and whether findings are published.
- Whether CAISI or another government body turns proposed frontier-model testing standards into formal requirements.
- Whether lawmakers define what a kill switch must stop, who can activate it and how an independent verification process would work.
- Whether other AI companies adopt the same standards, allowing results to be compared across developers.
- Whether U.S.-China and broader international discussions produce compatible safeguards rather than disconnected national rules.
As of October 2026, Clark’s “common-sense” language describes a policy direction: shared, enforceable expectations supported by independent checks. It does not describe a law already in force, a completed industry-wide evaluation system or a mandated kill switch.
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