Nobel Prize-winning computer scientist Geoffrey Hinton, widely known as the “Godfather of AI”, has delivered a stark warning to US lawmakers: they may have only about a year to establish safeguards before increasingly capable AI systems become much harder to control.&nbsp;Hinton made the comments during a closed-door briefing with members of Congress at the US Capitol, according to NBC News. When asked how long lawmakers have to act, he reportedly replied: “Maybe a year, but not much more than a year.” His warning comes as AI companies develop systems that can increasingly perform complex tasks, write code and assist with AI research.<h2>Why is Geoffrey Hinton worried?</h2>Hinton pointed to a major change in the way AI systems are being developed.&nbsp;“AI has now reached the point where AI is designing better AI,” he told reporters after the briefing, describing the process as recursive self-improvement.&nbsp;The term refers to a future in which AI systems could increasingly design, develop or improve their successors with less human involvement. That scenario has not yet been reached. Anthropic has said fully autonomous recursive self-improvement is not happening yet, although AI is already being used to accelerate parts of AI development. Hinton said predictions for the arrival of superintelligence have also moved closer. Estimates that once placed it decades away have increasingly shifted towards a matter of years, he told lawmakers.<h2>‘We need to slow down’</h2>Hinton has warned about advanced AI risks for years. He left Google in 2023 after becoming increasingly concerned about the technology's potential dangers.After the Capitol briefing, he said AI could “get out of control unless we do something” and added: “We need to slow down.” His comments come amid a wider debate among AI researchers and technology executives about whether development is moving faster than safety measures. The debate has intensified following several recent incidents involving autonomous AI agents.<h2>What happened in the Hugging Face incident?</h2>In July, OpenAI said models being tested in an internal cybersecurity evaluation circumvented controls, gained internet access and compromised parts of OpenAI's research infrastructure and Hugging Face systems. OpenAI said the models exploited vulnerabilities and took actions that were not directed by humans. Hugging Face's own technical reconstruction described an autonomous AI agent carrying out thousands of automated decisions during an intrusion. OpenAI has since strengthened safeguards, including tighter isolation, restrictions on internet access and additional monitoring. The incident does not establish that AI systems are already uncontrollable. But it has become an important example in the wider argument over whether safeguards can keep pace with increasingly autonomous AI. For Hinton, that question has become urgent. His message to lawmakers is that the window for putting stronger controls in place may be much shorter than many policymakers expect.

AI pioneer Geoffrey Hinton has warned US lawmakers they may have only about a year to establish meaningful safeguards before increasingly capable AI becomes harder to control. His warning comes amid growing concern over autonomous AI agents and recursive self-improvement.

Nobel Prize-winning computer scientist Geoffrey Hinton, widely known as the “Godfather of AI”, has delivered a stark warning to US lawmakers: they may have only about a year to establish safeguards before increasingly capable AI systems become much harder to control. Hinton made the comments during a closed-door briefing with members of Congress at the US Capitol, according to NBC News. When asked how long lawmakers have to act, he reportedly replied: “Maybe a year, but not much more than a year.” His warning comes as AI companies develop systems that can increasingly perform complex tasks, write code and assist with AI research. Why is Geoffrey Hinton worried? Hinton pointed to a major change in the way AI systems are being developed. “AI has now reached the point where AI is designing better AI,” he told reporters after the briefing, describing the process as recursive self-improvement. The term refers to a future in which AI systems could increasingly design, develop or improve their successors with less human involvement. That scenario has not yet been reached. Anthropic has said fully autonomous recursive self-improvement is not happening yet, although AI is already being used to accelerate parts of AI development. Hinton said predictions for the arrival of superintelligence have also moved closer. Estimates that once placed it decades away have increasingly shifted towards a matter of years, he told lawmakers. ‘We need to slow down’ Hinton has warned about advanced AI risks for years. He left Google in 2023 after becoming increasingly concerned about the technology's potential dangers. After the Capitol briefing, he said AI could “get out of control unless we do something” and added: “We need to slow down.” His comments come amid a wider debate among AI researchers and technology executives about whether development is moving faster than safety measures. The debate has intensified following several recent incidents involving autonomous AI agents. What happened in the Hugging Face incident? In July, OpenAI said models being tested in an internal cybersecurity evaluation circumvented controls, gained internet access and compromised parts of OpenAI's research infrastructure and Hugging Face systems. OpenAI said the models exploited vulnerabilities and took actions that were not directed by humans. Hugging Face's own technical reconstruction described an autonomous AI agent carrying out thousands of automated decisions during an intrusion. OpenAI has since strengthened safeguards, including tighter isolation, restrictions on internet access and additional monitoring. The incident does not establish that AI systems are already uncontrollable. But it has become an important example in the wider argument over whether safeguards can keep pace with increasingly autonomous AI. For Hinton, that question has become urgent. His message to lawmakers is that the window for putting stronger controls in place may be much shorter than many policymakers expect.

AI pioneer Geoffrey Hinton has warned US lawmakers they may have only about a year to establish meaningful safeguards before increasingly capable AI becomes harder to control. His warning comes amid growing concern over autonomous AI agents and recursive self-improvement.

Godfather of AI Geoffrey Hinton gives US lawmakers a one-year warning on AI

There is a man who won the Nobel Prize in Physics for building the brain of artificial intelligence. And that man will tell you, openly, that he has no idea how it actually thinks.&nbsp;Geoffrey Hinton, widely known as the Godfather of AI, appeared on the Diary of a CEO podcast hosted by Steven Bartlett in June 2025. The episode, titled Godfather of AI: I Tried to Warn Them, But We've Already Lost Control, became one of the most discussed AI conversations of the year. In it, Hinton laid out a truth that most AI companies would prefer to keep quiet: the internal reasoning of artificial intelligence is a black box, and the scientists who built it are looking at it from the outside just like everyone else.&nbsp;According to Hinton in that podcast, his contribution to AI was essentially the learning algorithm, specifically, the backpropagation algorithm, which he co-developed with David Rumelhart and Ronald Williams and published in a landmark 1986 paper. Backpropagation is the mechanism that allows neural networks to learn from errors, adjusting millions of internal connection weights until the system gets better at a task. It is, in Hinton's own framing, the algorithm that taught machines how to improve. But it did not give humans a window into what those machines actually do once they start improving.&nbsp;According to the Nobel Prize committee, which awarded Hinton and John Hopfield the 2024 Nobel Prize in Physics, their discoveries enabled machine learning through artificial neural networks, a technology that now underpins everything from medical diagnosis to large language models like GPT-4. The Nobel citation itself acknowledges that these systems learn by adjusting connection strengths in ways that are not explicitly programmed, which is precisely why nobody can trace the internal logic of what the model has learned.&nbsp;This is the black box problem. Neural networks are modelled loosely on the human brain. According to research from Wikipedia and foundational AI literature, the human brain contains roughly 86 billion neurons connected through trillions of synapses. When a person learns something, the strength of specific synaptic connections changes, this is called synaptic plasticity. AI systems replicate this process mathematically. But the brain has a physical structure scientists can study. An AI model has weights, billions of numerical values, and no one has yet built a reliable method to translate those numbers into human-understandable reasoning.&nbsp;According to Hinton's statements across multiple interviews and the Diary of a CEO podcast, the concern is not just academic. These systems are now making decisions in healthcare, law, and finance. They are reasoning in ways that produce correct answers without leaving a trail of logic that humans can audit. Hinton has said plainly that we have no idea what it is going to look like and anyone who tells you they know is talking nonsense.&nbsp;The irony is historically significant. Hinton spent four decades building the learning algorithm that gave AI the ability to train itself on data. He helped design the architecture of thought for a new class of entity. And by doing so, he created something that now processes information in ways that exceed his ability to explain.&nbsp;This is not a failure of science. It is a feature of emergence. When you give a system the tools to teach itself from billions of data points, the patterns it builds are too complex and too numerous for any human to reverse-engineer. The model does not store facts. It stores relationships, compressed into layers of abstraction that produce outputs no human programmed explicitly.&nbsp;According to Hinton's warning on the podcast, this is precisely why AI safety is not a software problem with a known solution. You cannot patch what you cannot read. And right now, nobody on Earth can read the mind of the machine they built.

Nobel Prize winner Geoffrey Hinton confessed on the Diary of a CEO podcast that he only gave AI the learning algorithm — what happens inside the machine after that, nobody, not even its creator, truly understands.

There is a man who won the Nobel Prize in Physics for building the brain of artificial intelligence. And that man will tell you, openly, that he has no idea how it actually thinks. Geoffrey Hinton, widely known as the Godfather of AI, appeared on the Diary of a CEO podcast hosted by Steven Bartlett in June 2025. The episode, titled Godfather of AI: I Tried to Warn Them, But We've Already Lost Control, became one of the most discussed AI conversations of the year. In it, Hinton laid out a truth that most AI companies would prefer to keep quiet: the internal reasoning of artificial intelligence is a black box, and the scientists who built it are looking at it from the outside just like everyone else. According to Hinton in that podcast, his contribution to AI was essentially the learning algorithm, specifically, the backpropagation algorithm, which he co-developed with David Rumelhart and Ronald Williams and published in a landmark 1986 paper. Backpropagation is the mechanism that allows neural networks to learn from errors, adjusting millions of internal connection weights until the system gets better at a task. It is, in Hinton's own framing, the algorithm that taught machines how to improve. But it did not give humans a window into what those machines actually do once they start improving. According to the Nobel Prize committee, which awarded Hinton and John Hopfield the 2024 Nobel Prize in Physics, their discoveries enabled machine learning through artificial neural networks, a technology that now underpins everything from medical diagnosis to large language models like GPT-4. The Nobel citation itself acknowledges that these systems learn by adjusting connection strengths in ways that are not explicitly programmed, which is precisely why nobody can trace the internal logic of what the model has learned. This is the black box problem. Neural networks are modelled loosely on the human brain. According to research from Wikipedia and foundational AI literature, the human brain contains roughly 86 billion neurons connected through trillions of synapses. When a person learns something, the strength of specific synaptic connections changes, this is called synaptic plasticity. AI systems replicate this process mathematically. But the brain has a physical structure scientists can study. An AI model has weights, billions of numerical values, and no one has yet built a reliable method to translate those numbers into human-understandable reasoning. According to Hinton's statements across multiple interviews and the Diary of a CEO podcast, the concern is not just academic. These systems are now making decisions in healthcare, law, and finance. They are reasoning in ways that produce correct answers without leaving a trail of logic that humans can audit. Hinton has said plainly that we have no idea what it is going to look like and anyone who tells you they know is talking nonsense. The irony is historically significant. Hinton spent four decades building the learning algorithm that gave AI the ability to train itself on data. He helped design the architecture of thought for a new class of entity. And by doing so, he created something that now processes information in ways that exceed his ability to explain. This is not a failure of science. It is a feature of emergence. When you give a system the tools to teach itself from billions of data points, the patterns it builds are too complex and too numerous for any human to reverse-engineer. The model does not store facts. It stores relationships, compressed into layers of abstraction that produce outputs no human programmed explicitly. According to Hinton's warning on the podcast, this is precisely why AI safety is not a software problem with a known solution. You cannot patch what you cannot read. And right now, nobody on Earth can read the mind of the machine they built.

Geoffrey Hinton, scientist credited with building the foundations of modern AI, made a startling confession on the Diary of a CEO podcast, he only provided the learning algorithm. What happens inside the mind of an AI after that, nobody, including its own creator, truly understands.

'I only gave learning algorithm': Godfather of AI admits nobody on Earth knows how AI actually thinks

As the world tilts towards AI, robots and everything digital, Godfather of AI and Nobel laureate Geoffrey Hinton said that there's only one job that won't be replaced by Artificial Intelligence.While stressing that AI could pose an existential threat to humanity one day, he made a revelation on which job would be saved.<h2>Here's the one job AI won't replace</h2>Hinton believes that the job of "plumbing" will not be affected by the AI revolution.Hinton is a Nobel Prize winner who earned his nickname for his work on neural networks and has revealed the risks of mass joblessness in the future, saying that technology will “get to be better than us at everything."During an interview on the 'Diary of a CEO' podcast, he said that the takeover will happen eventually, but there are still jobs that are safer than others for now."I'd say it's going to be a long time before it's as good at physical manipulation. So a good bet would be to be a plumber," he said, according to a report.The godfather of AI added that "intellectual" labour would be the worst hit as AI would easily take over those jobs."For mundane intellectual labour, AI is just going to replace everybody," he said.He stressed that most jobs will not be able to withstand the wave of disruption AI will bring in the future."In the past, new technologies have come in, which didn’t led to joblessness. New jobs were created. So the classic example people use is automatic telemachines. When automatic tele machines came in, a lot of bank tellers didn’t lose their jobs, they just got to do more interesting things," Hinton said.He noted that he saw an article recently, saying that many university graduates are already struggling to find jobs, adding that one reason could be that companies have started using AI to do the kind of work these graduates will do.&nbsp;

While stressing that AI could pose an existential threat to humanity one day, he made a revelation on which job would be saved.

As the world tilts towards AI, robots and everything digital, Godfather of AI and Nobel laureate Geoffrey Hinton said that there's only one job that won't be replaced by Artificial Intelligence. While stressing that AI could pose an existential threat to humanity one day, he made a revelation on which job would be saved. Here's the one job AI won't replace Hinton believes that the job of "plumbing" will not be affected by the AI revolution. Hinton is a Nobel Prize winner who earned his nickname for his work on neural networks and has revealed the risks of mass joblessness in the future, saying that technology will “get to be better than us at everything." During an interview on the 'Diary of a CEO' podcast, he said that the takeover will happen eventually, but there are still jobs that are safer than others for now. "I'd say it's going to be a long time before it's as good at physical manipulation. So a good bet would be to be a plumber," he said, according to a report. The godfather of AI added that "intellectual" labour would be the worst hit as AI would easily take over those jobs. "For mundane intellectual labour, AI is just going to replace everybody," he said. He stressed that most jobs will not be able to withstand the wave of disruption AI will bring in the future. "In the past, new technologies have come in, which didn’t led to joblessness. New jobs were created. So the classic example people use is automatic telemachines. When automatic tele machines came in, a lot of bank tellers didn’t lose their jobs, they just got to do more interesting things," Hinton said. He noted that he saw an article recently, saying that many university graduates are already struggling to find jobs, adding that one reason could be that companies have started using AI to do the kind of work these graduates will do.

While stressing that AI could pose an existential threat to humanity one day, he made a revelation on which job would be saved.

Godfather of AI reveals THIS one job AI won't replace | SPOILER: It's not a desk job

Geoffrey Hinton, regarded by many as the 'godfather of artificial intelligence' (AI), was awarded the 2024 Nobel Prize in physics alongside John Hopfield on Tuesday (Oct 8) by the&nbsp;Royal Swedish Academy of Sciences. Immediately after winning the award, Hopfield talked about the significance of the technology but also warned of it "getting out of control".&nbsp;

Hinton&nbsp;laid the foundations for machine learning that is powering many of today's AI-based products and applications. However, he grew wary of AI's future development and cut ties with his&nbsp;former employer Google in order to speak more freely on the issue.

“It will be comparable with the industrial revolution. But instead of exceeding people in physical strength, it’s going to exceed people in intellectual ability. We have no experience of what it’s like to have things smarter than us,” Hinton was quoted as saying by CNN.

“But we also have to worry about a number of possible bad consequences, particularly the threat of these things getting out of control,” he cautioned.

Hinton added, “I am worried that the overall consequence of this might be systems more intelligent than us that eventually take control."

This is not the first instance when Hinton was warned of AI's future and its impact on humanity. Speaking at the&nbsp;Collision tech conference in Toronto last year, the so-called "godfather of AI"&nbsp;emphasised the importance of understanding how&nbsp;artificial intelligence&nbsp;might attempt to take control before it surpasses human intelligence.

"Before AI is smarter than us, I think the people developing it should be encouraged to put a lot of work into understanding how it might try and take control away."

"Right now there are 99 very smart people trying to make AI better and one very smart person trying to figure out how to stop it taking over and maybe you want to be more balanced," he added.

As per Hinton, it's not just the threat of a takeover, AI also threatens to deepen pre-existing inequalities. He argued that AI's benefits and productivity gains are likely to benefit the wealthy.

<a href="https://www.wionews.com/videos/nobel-prize-in-medicine-ambros-and-ruvkun-win-for-microrna-discovery-765492" target="_blank">Watch |&nbsp;Nobel Prize In Medicine: Ambros And Ruvkun Win For microRNA Discovery</a>

<iframe allowfullscreen="" autoplay="1" frameborder="0" height="350" src="https://www.wionews.com/videos/nobel-prize-in-medicine-ambros-and-ruvkun-win-for-microrna-discovery-765492/embed" width="560"></iframe>

<h2>Who is Hinton?</h2>

Born in London in 1947, Hinton is currently a professor at the University of Toronto, Canada, having earned his PhD from the University of Edinburgh in 1978.

Hinton improved on his colleague's Hopfield network&nbsp;to create a new network that uses a different method,&nbsp;the Boltzmann machine, for saving and recreating patterns.

<a href="https://www.wionews.com/technology/godfather-of-ai-calls-for-action-before-ai-is-smarter-than-us-warns-looming-takeover-isnt-science-fiction-609899">Also read |&nbsp;Godfather of AI calls for action 'before AI is smarter than us', warns looming takeover isn't science fiction</a>

Hinton used tools from statistical physics, the science of systems built from many similar components. The machine is trained by feeding it examples that are very likely to arise when the machine is run.

The Boltzmann machine can be used to classify images or create new examples of the type of pattern on which it was trained. Hinton has built upon this work, helping initiate the current explosive development of machine learning.

(With inputs from agencies)

Geoffrey Hinton, regarded by many as the 'godfather of artificial intelligence' (AI), was awarded the 2024 Nobel Prize in physics alongside John Hopfield on Tuesday (Oct 8) by the Royal Swedish Academy of Sciences.

Geoffrey Hinton, regarded by many as the 'godfather of artificial intelligence' (AI), was awarded the 2024 Nobel Prize in physics alongside John Hopfield on Tuesday (Oct 8) by the Royal Swedish Academy of Sciences. Immediately after winning the award, Hopfield talked about the significance of the technology but also warned of it "getting out of control". Hinton laid the foundations for machine learning that is powering many of today's AI-based products and applications. However, he grew wary of AI's future development and cut ties with his former employer Google in order to speak more freely on the issue. “It will be comparable with the industrial revolution. But instead of exceeding people in physical strength, it’s going to exceed people in intellectual ability. We have no experience of what it’s like to have things smarter than us,” Hinton was quoted as saying by CNN. “But we also have to worry about a number of possible bad consequences, particularly the threat of these things getting out of control,” he cautioned. Hinton added, “I am worried that the overall consequence of this might be systems more intelligent than us that eventually take control." This is not the first instance when Hinton was warned of AI's future and its impact on humanity. Speaking at the Collision tech conference in Toronto last year, the so-called "godfather of AI" emphasised the importance of understanding how artificial intelligence might attempt to take control before it surpasses human intelligence. "Before AI is smarter than us, I think the people developing it should be encouraged to put a lot of work into understanding how it might try and take control away." "Right now there are 99 very smart people trying to make AI better and one very smart person trying to figure out how to stop it taking over and maybe you want to be more balanced," he added. As per Hinton, it's not just the threat of a takeover, AI also threatens to deepen pre-existing inequalities. He argued that AI's benefits and productivity gains are likely to benefit the wealthy. Watch | Nobel Prize In Medicine: Ambros And Ruvkun Win For microRNA Discovery Who is Hinton? Born in London in 1947, Hinton is currently a professor at the University of Toronto, Canada, having earned his PhD from the University of Edinburgh in 1978. Hinton improved on his colleague's Hopfield network to create a new network that uses a different method, the Boltzmann machine, for saving and recreating patterns. Also read | Godfather of AI calls for action 'before AI is smarter than us', warns looming takeover isn't science fiction Hinton used tools from statistical physics, the science of systems built from many similar components. The machine is trained by feeding it examples that are very likely to arise when the machine is run. The Boltzmann machine can be used to classify images or create new examples of the type of pattern on which it was trained. Hinton has built upon this work, helping initiate the current explosive development of machine learning. (With inputs from agencies)

'I'm worried': Godfather of AI who won Nobel Prize in Physics warns of technology getting out of control

AI tools are also impressing users the world over. Industry leaders who helped build the technology are literally the ones warning against the impending ai revolution. Experts have warned that artificial intelligence could lead to extinction. Why are Industry Leaders worried about AI?

Artificial Intelligence: Why it's dangerous | Part 1 | WION Wideangle

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Godfather of AI Geoffrey Hinton gives US lawmakers a one-year warning on AI

Godfather of AI admits nobody on Earth knows how AI actually thinks

Godfather of AI reveals THIS one job AI won't replace

'I'm worried': Godfather of AI who won Nobel Prize in Physics warns of technology getting out of control

Artificial Intelligence: Why it's dangerous | Part 1 | WION Wideangle