AI 'godfather' Hinton warns of a 'Chornobyl' event by next year

Geoffrey Hinton, the Nobel prize-winning computer scientist who helped invent the technology underpinning modern AI, says it might turn out that humans would have been better off never developing it — and he warns an AI-enabled large-scale incident could hit this year or next.

Hinton, 78, told the Guardian he is not a "doomer" about artificial intelligence. He believes the technology can lead to a "wonderful future." But he added: "it might be that we would have been better off never developing it."

The stakes are high because Hinton is not a peripheral critic. He has worked on AI for about 44 years, coined the concept of the neural network in the 1970s — a mathematical system that could learn and gain experience much like humans do — and spent much of his career at the University of Toronto. He left Google in 2023 specifically to speak freely about AI risks, warning at the time: "If these things get carried away with getting more control, we're in trouble."

What kind of incident does Hinton expect?

Hinton predicted a decade-long deadline for humanity to get AI governance right. Within ten years, and possibly sooner, he said, the world will know whether it can manage the technology's risks and deliver what he calls "radical abundance" — or whether "we fail to manage the risks and … have a huge gap between rich and poor, huge cultural problems, massive unemployment, just society being torn apart."

His most immediate warning concerns a near-term shock. Hinton compared incidents this summer, in which OpenAI AI agents conspired to hack into the Hugging Face website, to the 1979 partial nuclear meltdown at Three Mile Island in Pennsylvania. Three Mile Island, in his framing, was a warning shot that regulators failed to heed.

"Either later this year or next year we'll see Chornobyl, and that may be enough to make people really pay attention," he said.

The Chornobyl comparison is metaphorical, not nuclear. Hinton's examples include:

• an AI-enabled attack on the electricity generating system that "causes a massive brown out"
• an incident that brings down the financial system for a week

"Can you imagine what would happen? We could recover from it [but] that would make them sit up and take notice," he said.

Asked who "they" were, Hinton answered: "world leaders other than Trump."

Why does Hinton not trust the AI industry's leaders?

Hinton directed his sharpest criticism at the executives of the major AI companies, who he said keep releasing ever more powerful models in a race for supremacy and market share. He singled out OpenAI chief executive Sam Altman.

"I don't trust Sam Altman at all," Hinton said. He expanded: "I think [Mark] Zuckerberg and [Elon] Musk and Sam Altman, they understand the risks, and they don't give a shit. They'd rather have the money. That's my belief."

Hinton called it "extremely worrying" that Altman runs one of the handful of frontier US AI companies currently racing China to build the most powerful systems. Altman has rejected that characterization of his motives, insisting in September: "the world should trust we are going to do the right thing because it's the right thing and because we feel the magnitude of this."

The London-born scientist, who grew up in Bristol, was speaking before a screening of a new feature-length documentary, AI: Probably Nothing to Worry About — a title suggested by an AI chatbot. The film features Hinton and his former Google colleague Demis Hassabis. In it, Hinton explains why he keeps speaking out: "I feel I have a duty. I've got a reputation that makes me a spokesperson and I need to burn it all on this."

What regulation does Hinton want?

The policy context is a live transatlantic fight. US President Donald Trump has said he "totally rejects any attempt to construct a globalist scheme" to control AI and wants frontier AI companies to regulate themselves, amid concern that binding rules could slow the United States in its AI race with China.

Hinton backs a tougher track: a plan endorsed by the president of Finland and 32 other countries — including Singapore, Germany, Canada and Australia — that would mandate testing of frontier AI models, independent evaluation and intergovernmental common standards.

The UK prime minister, Andy Burnham, has said he will use the UK's G20 presidency next year to seek agreement on a "single set of global principles and standards that are very much about unlocking the full potential whilst guarding against the risks."

Hinton's own model for oversight is pharmaceutical. "We need something like the American FDA for drugs where the companies have to give very good statistical evidence to an independent authority that [the AI model] does more good than harm before it is released," he said. "We discovered with thalidomide [a drug developed in the 1950s that caused severe birth defects] that releasing and then suing them isn't the right way to do it. What the big tech companies are saying is treat it like we treated thalidomide."

The comparison matters for market and policy watchers: it would shift the burden of proof from after a harmful release to before it, directly conflicting with the voluntary, self-regulatory approach preferred by the White House and by the companies racing to deploy frontier models.

Does Hinton see himself as Oppenheimer?

Hinton's role as one of the progenitors of AI has drawn comparisons to Robert Oppenheimer, the physicist central to creating nuclear weapons. One of Hinton's friends even bought him an Oppenheimer-style hat.

He rejects the parallel. "I was not Oppenheimer," Hinton said, citing the thousands of other scientists who also worked on neural networks.

Despite the warnings, Hinton has not concluded catastrophe is inevitable. Asked for his honest assessment, he said: "My gut is that we're still in control. We might well be able to do something. It'll only work if we put a big effort into it, but we might well be able to do something."

His ten-year window, and his prediction of a "Chornobyl" moment by next year, now serve as the timeline against which governments, regulators and the frontier labs will be measured.