
Deepmind CEO Hassabis says "nobody in the world knows what happens next" so "cautious optimism" means building guardrails now
Quick Answer
DeepMind CEO Demis Hassabis proposes a new US standards body for AI governance, emphasizing 'cautious optimism' as AGI approaches.
Quick Take
DeepMind CEO Demis Hassabis proposes a new US standards body for AI governance, emphasizing 'cautious optimism' as AGI approaches. He warns that the impact of AGI could be ten times greater than the Industrial Revolution, advocating for voluntary evaluation protocols that may become mandatory, while exempting non-frontier models to avoid regulatory capture.
Key Points
- Hassabis claims AGI could arrive in a few years, with massive societal impacts.
- Proposed standards body would develop evaluation protocols for frontier AI models.
- The agency would be funded by industry and regularly update benchmarks.
- Non-frontier models from startups would be exempt to prevent regulatory capture.
- Hassabis emphasizes cautious optimism amid high uncertainty in AI development.
📖 Reader Mode
~2 min readGoogle Deepmind CEO Demis Hassabis has published a detailed framework proposal for governing advanced AI.
Artificial general intelligence (AGI) is likely just a few years away, according to Hassabis, who just repeated a claim he made in April: the impact could be ten times greater than the Industrial Revolution and arrive ten times faster. At the same time, progress is outpacing our understanding of the technology. Back in May, the Deepmind chief saw humanity already "in the foothills of the singularity," a widely debated statement.
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.
— Originally published at the-decoder.com
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from The Decoder
See more →
An AI model programmed nonstop for 19 days on a single MirrorCode task that cost $2,600 to run
Epoch AI's MirrorCode benchmark reveals Claude Opus 4.7 as the leader with a 56% solve rate, reconstructing a 16,000-line toolkit in 14 hours. Despite this, all models tested struggle with the most complex tasks, highlighting limitations in current AI capabilities. The single task consumed $2,600 over 19 days, raising questions about cost-effectiveness in AI development.

