# 'Godfather of AI' Warns Tech Firms Are Selling AI That Will 'Do the Work of Workers Much Cheaper' > Source: > Published: 2026-08-17 12:17:59+00:00 # 'Godfather of AI' Warns Tech Firms Are Selling AI That Will 'Do the Work of Workers Much Cheaper' ## As Silicon Valley sells a trillion‑dollar dream of automated abundance, Geoffrey Hinton keeps returning to a blunter question who gets discarded while the machines learn to do our jobs cheaper [Geoffrey Hinton](https://www.ibtimes.co.uk/ai-incidents-highlight-growing-concerns-over-control-safety-1812912) named 'Godfather of AI' has warned that Big Tech is ploughing money into artificial intelligence systems designed to 'do the work of workers much cheaper,' saying the technology is 'very likely' to trigger massive unemployment across advanced economies. The British computer scientist, now 77, is not a passing critic lobbing stones from the sidelines. Hinton was one of the pioneers of modern machine learning, a figure so central to the field that Silicon Valley long ago settled on the nickname 'Godfather of AI.' After leaving Google in 2023 so he could speak more freely about AI's risks, he has steadily shifted from insider architect to public Cassandra, arguing that the industry's priorities have tilted away from science and towards profit at almost any social cost. Speaking in conversation with US senator Bernie Sanders at Georgetown, Hinton did not mince his words about what is funding the current AI boom. With tech giants, from chipmakers to cloud providers, racing to construct new data centres and buy specialised processors, he put a rough figure on the scale of the bet. Companies are committing 'roughly a trillion dollars,' he said, and they expect that money back. 'If you ask where are these guys going to get the roughly trillion dollars they're investing in data centres and chips... one of the main sources of money is going to be by selling people AI that will do the work of workers much cheaper,' Hinton said. 'And so these guys are really betting on AI replacing a lot of workers.' ## Geoffrey Hinton and the Cost of Big Tech's AI Gamble The months of increasingly extravagant promises from the industry's most powerful figures. NVIDIA chief executive [Jensen Huang](https://www.ibtimes.co.uk/jensen-huangs-construction-careers-forecast-nvidia-ceo-predicts-six-figure-ai-infrastructure-jobs-1811917) has talked confidently about every job being 'transformed' by AI and floated the idea of a [four‑day working week](https://www.ibtimes.co.uk/sam-altman-ai-work-week-prediction-1813769) as productivity rises. Bill Gates has gone further, musing that humans may soon not be needed 'for most things.' Elon Musk, never shy of a bold timeline, has suggested that within 'less than 20 years' most people will not have to work at all. Hinton does not dismiss those scenarios as science fiction. He thinks they are plausible and, crucially, likely. But where some tech leaders frame that future as an almost frictionless upgrade to human life, Hinton's attention is fixed on the transition period. In his view, that is where the damage will land, with vast swathes of workers made redundant long before society has built a new settlement around who owns and benefits from AI. He is hardly alone in questioning the economics behind the enthusiasm. A recent analysis by HSBC, published in November 2025, suggested OpenAI the company behind ChatGPT and the poster child of generative AI may not turn a profit until at least 2030 and could require more than $207 billion to sustain its growth plans. Those numbers, if they hold, imply that investors will expect extraordinarily aggressive cost-cutting and revenue generation from AI tools over the next decade. Hinton has accused major technology firms of being driven primarily by those pressures. In an earlier interview with *Fortune*, he argued that Big Tech is now guided less by the pursuit of knowledge than by quarterly earnings, with automation of human labour placed at the centre of the business case for AI. He accepts that new categories of work will appear. What he does not believe is that they will balance out the millions of existing roles that can be partially or wholly automated. ## Geoffrey Hinton, Political Alarm and a Foggy Future If Hinton is the scientist raising the alarm, politicians such as Bernie Sanders are trying to put numbers to the threat. In October 2025, Sanders released a report drawing in part on estimates generated by ChatGPT that warned nearly 100 million jobs in the United States could be displaced by automation. The document highlighted obvious targets such as fast food, customer service and manual labour, but also listed white‑collar work in accounting, software development and even nursing as vulnerable. Sanders argued that the risk is not confined to lost wages or GDP figures. 'Work, whether being a janitor or a brain surgeon, is an integral part of being human,' he wrote. 'The vast majority of people want to be productive members of society and contribute to their communities. What happens when that vital aspect of human existence is removed from our lives?' US lawmaker Senator Mark Warner has warned that young workers may bear the brunt of the shift. In an interview, he suggested unemployment among recent college graduates could reach 25% within two to three years as [entry‑level positions](https://www.ibtimes.co.uk/ai-impact-junior-employee-training-1814107) are automated away. He drew an explicit comparison with social media regulation, or rather the lack of it, and said that failing to put 'guardrails' around AI now would be a mistake the US would 'come to rue.' For all his grim projections, Hinton is candid about how uncertain the future really is. Speaking to Sanders, he compared trying to see ten years ahead in AI to driving in thick fog. You can see 'clearly for 100 yards,' he said, but double that distance and visibility collapses. A year or two out, the trends feel obvious enough. A decade away, nobody not the 'Godfather of AI,' not the most bullish Silicon Valley founder, can say with confidence what kind of labour market will exist. What does seem beyond dispute is that AI is not going anywhere. Experts who are less pessimistic than Hinton still agree that workers who learn to use AI to amplify their skills will fare better than those who do not. Yet that advice, sound as it may be at the individual level, leaves the larger question hanging over the trillion‑dollar bet: if Hinton is even half right about the scale of disruption, who exactly will this new economy be for? © Copyright IBTimes 2025. All rights reserved.