Deepmind CEO Hassabis says "nobody in the world knows what happens next" so "cautious optimism" means building guardrails now

Now, Hassabis proposes a new US standards body modeled after the financial regulator FINRA. It would develop evaluation protocols for frontier models, starting on a voluntary basis and later becoming mandatory. The agency would be funded by industry and use regularly updated benchmarks. The international community would then need to follow suit and find consensus on the most critical points.

If necessary, the body could also coordinate a slowdown in development, similar to what Anthropic recently considered. Hassabis stresses that non-frontier models from startups or academic research would be exempt. That sidesteps the accusation of "regulatory capture," where established companies try to use regulation to hold back smaller competitors.

"Nobody in the world knows for sure what is going to happen from here"

The timing of Hassabis's proposal is likely no coincidence. Shortly before, a letter signed by a prominent group of AI researchers and economists warned of potentially sweeping consequences from massive AI-driven job losses. Hassabis did not sign that letter, even though his argument about the potential consequences sounds similar. His proposal, however, is more specific about countermeasures without being alarmist.

"Nobody in the world knows for sure what is going to happen from here, and even the experts disagree. When there is a large degree of uncertainty and the stakes are this high, proceeding with cautious optimism is the sensible and correct strategy," Hassabis writes.

The extent of that expert disagreement was on full display last December, when Hassabis himself got caught up in a public spat. Yann LeCun called the concept of general intelligence based on language models "complete BS" and "completely delusional." Hassabis pushed back publicly, saying LeCun was "just plain incorrect."

Gemini co-lead Oriol Vinyals offers a middle ground: today's models are strong in some areas, but the ability to truly innovate is still missing. Deep learning pioneer Richard Sutton holds a similar view and just announced his startup Oak Labs to tackle that problem. Deepmind co-founder Shane Legg considers a "minimal AGI" possible as early as 2028.