Automation will replace white-collar jobs; manual trades safe: Father of AI

Geoffrey Hinton said for mundane intellectual labour, AI is just going to replace everybody

Geoffrey Hinton, a pioneering figure in the development of artificial intelligence (AI), has voiced deep concern over the looming threat of job displacement as AI systems become further embedded in professional workspaces.

 

Speaking on the Diary of a CEO podcast, Hinton—often dubbed the “Godfather of AI”—highlighted the risk that automation poses to white-collar employment. “For mundane intellectual labour, AI is just going to replace everybody,” he said.

 

Jobs at risk: paralegals to call centres 

Hinton, who was awarded the Nobel Prize in Physics in 2024 for his contributions to machine learning, identified professions such as paralegals and call centre operators as especially vulnerable. “I’d be terrified if I had a job as a call centre operator,” he remarked, noting the rapid pace at which AI is transforming customer service roles.

 

 

He explained that AI’s scalability means fewer people will be needed for tasks once handled by large teams. “That means one person will do what used to be the work of 10 people,” Hinton said.

 

Safer bets in the age of AI: physical labour 

Suggesting where job security may lie, Hinton pointed to roles that require physical manipulation—areas where AI still lags behind. “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 advised.

 

He also noted that AI has started performing work typically assigned to recent graduates, raising concerns that new workforce entrants could be squeezed out. He questioned the assumption that automation will simply give rise to new kinds of jobs: “You’d have to be very skilled to have a job that it just couldn’t do.”

 

AI’s social impact: beyond employment 

Hinton underscored widespread unemployment as one of the most urgent societal risks posed by AI. While universal basic income is frequently proposed as a solution, he expressed scepticism about whether it could preserve people’s sense of purpose. “It’s not just about money—it’s also about meaning,” he suggested.

 

From pioneer to critic: Hinton’s transformation 

Hinton played a key role in the development of deep learning. In 2012, alongside two graduate students at the University of Toronto, he created a neural network system that laid the foundation for today’s AI revolution.

 

He later joined Google, where he worked for over a decade. However, in 2023, he resigned to speak openly about the ethical and societal implications of the technology he helped pioneer.

 

Reflecting on his work, Hinton said, “A part of me now regrets my life’s work,” as reported by The New York Times. “I console myself with the normal excuse: If I hadn’t done it, somebody else would have.” Regarding the threat of misuse, he warned, “It is hard to see how you can prevent the bad actors from using it for bad things.”