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Sam Altman outlines 3 paths to make AI safer
Altman backs proposal for an international AI regulatory body

Sam Altman outlines 3 paths to make AI safer

Oct 23, 2026
03:48 pm

What's the story

OpenAI CEO Sam Altman has proposed three potential paths for the safe development of artificial intelligence (AI) in a communication with his staff. The first proposal is for an international regulatory body, similar to the International Atomic Energy Agency (IAEA), to enforce safety standards in AI development. Altman reportedly favors this approach. OpenAI leaders have been advocating for such an agency since 2023, suggesting it could inspect systems, mandate audits, and monitor compute and energy use in AI labs.

Lab merger

Merging of major AI labs

The second proposal, dubbed the "Demis plan," is based on an earlier suggestion by Google DeepMind chief Demis Hassabis.

In this scenario, major AI firms would either merge into or collaborate through a single entity that provides models to partner countries.

This idea was also floated by Altman during his talk with OpenAI employees.

Power concentration

The 'Eliezer plan'

The third proposal, dubbed the "Eliezer plan" after AI safety theorist Eliezer Yudkowsky, envisions one developer gaining enough economic power to deny rivals access to computing resources.

However, Altman has expressed his opposition to this scenario. He only included it in the list of proposals as a way of completing it.

Some employees viewed his remark as a dig at Anthropic due to Yudkowsky's ties with the Claude maker.

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Risk mitigation

Concerns over security breaches in AI models

Altman's proposals come amid growing concerns over security breaches linked to AI models from OpenAI, Anthropic, Google, and Meta.

To address these issues, several leading labs are working on a new safety group called 'Standards Authority for Frontier AI.' The body is expected to be launched by early 2027.

There are also discussions about a draft bill that would let the Commerce Department halt models capable of causing large-scale harm.

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