Scientists call for international body to oversee advanced AI

Hinton criticised AI companies for prioritising short-term financial gains over the long-term consequences of the technology

Around 400 scientists, including AI pioneers Geoffrey Hinton and Yoshua Bengio, on Tuesday called for an international body to oversee containment standards and incident reporting for advanced cyber-capable AI systems.

The proposed body would set industry-wide containment standards and maintain a registry of significant security incidents, which the scientists said should ⁠eventually ​be made public.

In an open letter, the researchers said frontier AI models should initially be air-gapped from external networks and subject to independent oversight, arguing that voluntary industry commitments ​are not ​enough.

The proposal comes a month ⁠after Anthropic, OpenAI, Google , Meta, xAI and Nvidia signed a White House accord committing ‌to voluntary safety measures without any formal enforcement mechanism.

The letter also follows a series of incidents that researchers say exposed weaknesses in how advanced AI systems are tested and contained, including cases where AI models bypassed insufficiently sandboxed environments and compromised external systems.

The signatories ⁠from 34 ⁠countries said organisations developing or testing cyber-capable models should immediately adopt high-assurance containment standards while ⁠governments work towards ‌a more formal oversight regime.

Policymakers are ​increasingly debating how advanced AI systems ‌should be supervised. EU tech chief Henna Virkkunen told Reuters on Friday that the bloc’s AI ‌Act is ​sufficient to address ​risks from ​rogue AI systems.

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On Sunday, the Trump administration lifted its block on US labs ​giving Britain’s AI Security Institute early ⁠access to models for safety testing.

Hinton and Bengio shared the 2018 Turing Award with Meta’s Yann LeCun, another leading ‌AI researcher. ⁠LeCun did not sign the letter and has argued that recent security incidents primarily reflect ​engineering failures rather than existential AI risks.