Geoffrey Hinton Warns Rapid AI Adoption Could Trigger Massive Unemployment, Enrich Few
The veteran researcher and ‘Godfather of AI’ says unchecked scaling will concentrate wealth and urges caution as industry leaders press ahead
Geoffrey Hinton, a leading figure in artificial intelligence research, warned that the technology’s rapid adoption will cause massive unemployment and concentrate wealth among a small number of owners unless safe scalability is prioritized.
"It’s going to create massive unemployment and a huge rise in profits. It will make a few people much richer and most people poorer," Hinton told the Financial Times, adding that the outcome would reflect the structure of capitalist systems rather than the intrinsic nature of AI.
Hinton, who last year won the Nobel Prize in physics and formerly led work at Google’s Brain team, has been publicly urging restraint since leaving Google in 2023. He joined Google after the company acquired his startup and spent two decades on AI research at the University of Toronto. The researcher, often referred to in media as a founder of modern deep learning, said CEOs who portray AI as a ready-made solution to problems such as hunger, poverty and disease are offering an overly optimistic picture.
Hinton described a likely near-term social outcome in which wealth concentrates with owners of AI systems while many workers are displaced. He said many scientists agree that systems could reach superintelligence — abilities to outperform humans across many domains — within five to 20 years. He has previously called for pauses in development to allow time for safety measures.
Hinton also urged a particular approach to aligning AI systems with human values. "Engineering AI to act like mothers is the only hope for humanity, because the mother is very concerned about the baby, preserving the life of the baby," he told the newspaper.
At the same time, he acknowledged personal use of AI tools in everyday tasks, from scientific work to household fixes, and noted his advancing age in explaining his perspective: "I am 77 and the end is coming for me soon anyway," he said.
Industry leaders continue to press ahead with rapid development and deployment of advanced AI. Hinton contrasted that momentum with what he described as an insufficiently proactive regulatory posture, saying he is not optimistic that government intervention in the United States will meaningfully slow the industry’s pace.
Hinton drew pointed comparisons when asked which industry figures he trusted more, borrowing a 2016 political quip: choosing between some tech executives was "like being shot or poisoned," he said. He also discussed longer-term scenarios in which humans and machines merge, responding to questions about cyborg futures and extinction by saying, "What’s wrong with that?" and answering "Yep" when asked whether such a transformation would qualify as a form of extinction.
The warnings add to a growing chorus of concern among researchers, policymakers and some industry figures over the social and economic impacts of powerful AI systems. While proponents of rapid development argue for the technology’s potential to boost productivity and address complex challenges, critics cite risks that include job displacement, concentration of economic power, and insufficient safeguards.
Hinton’s remarks follow years of debate inside and outside companies building large models about how to balance innovation, governance and safety. They underscore tensions between commercial incentives to deploy capabilities quickly and calls from some researchers for slower, more deliberate development to manage societal risks.
Policymakers and industry groups have responded in varied ways, including voluntary safety commitments, targeted regulations, and proposals for broader oversight of advanced AI capabilities. Hinton and others who have sounded alarms say those measures must be robust and enforced to prevent scenarios in which a small number of actors capture disproportionate benefits while large segments of the workforce face displacement.
As the technology progresses, Hinton said, outcomes could be "amazingly good" or "amazingly bad," and the present moment is one of significant uncertainty. His comments add urgency to ongoing discussions about governance, labor policy and the social distribution of AI-generated gains.