December 5, 2025

In an interview with Senator Bernie Sanders, Geoffrey Hinton, often called the “Godfather of AI”, warned that tech giants are betting on artificial intelligence replacing many workers. He predicts mass unemployment and argues that profits from AI will come partly from selling systems that do human work cheaply. Hinton cautioned that the long‑term future of AI is unpredictable, likening it to driving in fog, and noted that even optimistic projections of new job creation may not offset losses. His comments add urgency to debates on universal basic income, worker retraining and ethical AI deployment.

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Few voices command as much respect in artificial intelligence as Geoffrey Hinton. His pioneering work on neural networks laid the groundwork for deep learning, earning him both the Turing Award and a Nobel Prize. In recent years Hinton has become one of the most outspoken critics of how the technology he helped birth is being deployed. Speaking at Georgetown University alongside Senator Bernie Sanders, Hinton delivered a stark warning: tech companies are pouring trillions of dollars into AI, and they expect to recoup that investment by replacing human workers. “Tech giants are betting on AI replacing a lot of workers,” he said. He added that if companies are spending $1 trillion on data centers 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’s critique goes beyond economics to question priorities. He contends that Big Tech is driven more by short‑term profits than by scientific progress, pushing to replace humans rather than augment them. He noted that OpenAI is not expected to turn a profit until at least 2030 and may need more than $207 billion to support its growth. This raises questions about whether the current AI boom is sustainable and what will happen if returns fail to materialize. Senator Sanders echoed these concerns, citing an October report that estimated nearly 100 million U.S. jobs could be displaced by automation. The at‑risk roles include not only factory workers and cashiers but also accountants, software developers and nurses. Another warning came from Senator Mark Warner, who cautioned that inaction on AI regulation could lead to regrets similar to those about social media.

Despite the dire outlook, Hinton maintains a sense of humility about forecasting. “Trying to predict the future of it is going to be very difficult,” he told Sanders. He compared our understanding of AI’s trajectory to driving in thick fog: you can see what is happening right ahead, but anything further out is a blur. This metaphor is important because it underscores the uncertainty inherent in technological revolutions. We may know that AI will have profound impacts, but we cannot accurately foresee its long‑term social and economic consequences. Hinton also acknowledged that AI will create new jobs—positions that don’t exist yet and perhaps require skills we cannot currently imagine. However, he doubts that job creation will keep pace with job destruction, echoing long‑standing concerns from economists.

For entrepreneurs, Hinton’s warnings are a call to action. First, consider the societal impact of the products you build. Systems that empower workers, enhance human creativity or open new markets may face less resistance than those designed solely to replace people. Second, anticipate regulation. Governments are already considering measures such as robot taxes, universal basic income and AI safety standards. Businesses that proactively align with ethical guidelines will be better prepared for future compliance and public scrutiny. Third, invest in workforce development. Companies that provide training and transition paths for workers displaced by automation can build goodwill and secure a more stable customer base. Finally, maintain humility. The “fog of prediction” means no one can say for certain how AI will unfold. Building flexible strategies and staying attuned to new information will be vital.

Hinton’s remarks also highlight a paradox: the very technology that creates the potential for mass unemployment could enable unprecedented prosperity. If AI can perform tedious or dangerous tasks, humans might have more time for creative, interpersonal and strategic work. But realizing that utopia requires careful planning, wealth redistribution and a commitment to human dignity. Future billionaires must therefore think beyond profits to consider the societal structures that will support a world where machines do much of the labor. Whether that means advocating for universal basic income, funding upskilling programs or championing ethical AI, the decisions made today will shape whether AI becomes an engine of liberation or a catalyst for inequality.

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