Google DeepMind CEO Demis Hassabis has proposed creating an independent standards body to regulate frontier AI model releases, drawing inspiration from the Financial Industry Regulatory Authority (FINRA).

The proposed organization would test frontier models and develop best practices for their deployment. Under Hassabis's framework, AI labs would voluntarily share models with the standards body for review up to 30 days before release.

"Once the assessment protocol is shown to be effective and robust, formalization could quickly follow, meaning that Frontier Models would be required to pass it to be deployed in the US market," Hassabis wrote in an X post titled "A Framework for Frontier AI and the Dawning of a New Age."

The proposal builds on recent ad hoc government reviews of Anthropic's Mythos and OpenAI's Sol models. Those reviews drew criticism for lacking technical expertise and opaque decision-making processes.

Hassabis envisions the regulator being funded by the AI industry but operated independently with government backing. The organization would be staffed by open source representatives and technical experts from within the industry.

Why self-regulation appeals

The standards body structure addresses political concerns about AI regulation. White House AI advisor Sriram Krishnan recently said "there will not be an FDA for AI," discounting executive branch regulation.

Establishing a self-regulatory organization like FINRA could sidestep those objections while maintaining technical oversight. The body could outsource specific evaluations to specialized AI safety groups.

"The strength of this approach is it would be technically focused, while at the same time supporting innovation and incentivizing responsible behavior," Hassabis argued.

The proposal comes as the AI industry faces growing scrutiny over frontier model capabilities and safety protocols. Labs would work with the standards body to address critical post-release vulnerabilities under the framework.

Hassabis said the system could "ratchet up if the seriousness of the situation demands" and adapt to emerging risks as they're identified.