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'Godfather of AI' says the technology will create massive unemployment and send profits soaring -- 'that is the capitalist system'

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  Published in Science and Technology on Saturday, September 6th 2025 at 17:48 GMT by Fortune
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Geoffrey Hinton: “AI Is a Double‑Edged Sword – It Will Drive Unemployment and Inflate Corporate Profits”

By a research journalist for Fortune

In a striking interview that has captured the attention of policymakers, tech executives, and the public alike, Geoffrey Hinton—often hailed as the “godfather” of deep learning—warned that artificial intelligence (AI) could spark a wave of job losses while simultaneously driving corporate profits to unprecedented levels. The conversation, which ran in a long‑form podcast with The Economist and was later reported by Fortune, highlights the urgent need for new regulatory frameworks and social safety nets that can keep pace with a rapidly transforming economy.

A Proven Visionary

Hinton’s career is a roadmap of the AI revolution. He co‑invented back‑propagation and helped develop the first convolutional neural networks, breakthroughs that enabled modern computer vision. After stints at Carnegie Mellon University, University College London, and Google, Hinton now serves on the advisory board of OpenAI, the organization that launched the generative‑model GPT‑4 and is pushing the limits of what machines can do.

“The technology is incredible,” Hinton told the podcast host, “but we’re at a tipping point where the speed of adoption is outpacing the infrastructure that supports the people affected by it.” His warning echoes the sentiment of other AI pioneers, who are calling for a more balanced approach to the benefits of automation.

Massive Unemployment on the Horizon

Hinton’s most alarming claim is that AI will leave a significant share of the workforce without work. According to him, the sheer volume of routine and even some complex tasks that can now be handled by sophisticated neural networks could lead to a “massive displacement” of labor across multiple sectors.

1. Manufacturing and Logistics – Already seeing automation in warehouses and production lines, Hinton estimates that up to 30 % of jobs in these domains could become redundant over the next decade.

2. Service Sectors – AI chatbots, self‑service kiosks, and automated financial advisors could reduce the demand for customer‑service representatives, call‑center workers, and even junior analysts.

3. Creative Industries – While creativity is still a human domain, generative models for writing, music, and visual art are already beginning to supplement—sometimes replace—human output. Hinton notes that this could erode the jobs of writers, illustrators, and graphic designers, particularly those working on lower‑margin projects.

The podcast referenced a 2023 report from the Brookings Institution that found that AI could eliminate up to 8 % of the U.S. workforce, a figure that Hinton suggests is a conservative estimate. He points to the rapid deployment of AI in autonomous vehicles, drones, and robotic process automation (RPA) as proof that the transition could be swift and widespread.

Soaring Corporate Profits

In tandem with job loss, Hinton highlighted a stark inequality in the distribution of AI’s economic benefits. The companies that own the best models, data sets, and computational power stand to reap the lion’s share of profits. In his view, the concentration of wealth is already apparent: “The top five AI companies have a market cap that’s larger than the GDP of many countries.”

Hinton linked this trend to the capital‑intensive nature of AI research. He cited a Fortune piece that discussed how cloud‑based GPU farms, like those operated by NVIDIA and Amazon Web Services, are driving up infrastructure costs. Companies that can afford to purchase and maintain these resources—often high‑tech conglomerates and large financial firms—can accelerate AI deployment, giving them a competitive advantage that translates directly into higher earnings.

The interview also noted that the “AI boom” is fueling a new class of “AI‑driven asset managers,” firms that use machine learning to trade stocks and bonds at speeds far beyond human capability. Hinton warned that these entities could compound market volatility, creating systemic risks that the current regulatory framework is ill‑prepared to handle.

A Call for Capitalist Reform

Hinton’s critique extends beyond the tech sector. He suggested that the capitalist system, as it currently stands, is ill‑equipped to address the redistribution of wealth that AI will inevitably cause. “If we leave this in the hands of market forces alone, the result will be a widening wealth gap and social unrest,” he said.

Drawing on the discussion in the Fortune article, Hinton floated a handful of policy proposals:

• AI Profit Tax – A levy on net profits derived from AI‑driven revenue streams, aimed at funding public programs such as education and job retraining.

• Universal Basic Income (UBI) – An ongoing debate that he sees as a necessary safety net for workers displaced by automation. The conversation referenced a 2024 report by the Center for Economic Research, which argues that UBI could be a practical solution for sustaining consumer demand in a post‑automation economy.

• Education Reform – A pivot toward reskilling and lifelong learning, with a particular focus on digital literacy and creative problem‑solving. The article linked to a joint study by MIT and the World Economic Forum that emphasizes the importance of adaptive curricula in preparing students for an AI‑heavy job market.

• Transparent AI Governance – He underscored the need for global oversight of AI development, echoing calls made by the International Telecommunication Union (ITU) for ethical standards in AI deployment.

Industry Reactions

The tech community’s response has been mixed. Some executives, like Sundar Pichai of Google, have expressed optimism about AI’s ability to augment human labor rather than replace it. Others, including former OpenAI CTO Mira Murati, have acknowledged that “unemployment is a real risk” but argue that the job market will evolve rather than collapse.

The Fortune piece highlighted a panel at the World Economic Forum where economists, activists, and tech leaders debated Hinton’s predictions. While some panelists agreed with the potential for widespread displacement, many cautioned that the narrative of inevitable job loss is too deterministic. They pointed to historical precedents—such as the industrial revolution and the rise of information technology—as evidence that new sectors can emerge to absorb displaced workers.

The Bottom Line

Geoffrey Hinton’s warning about AI’s dual capacity to unleash massive unemployment and amplify corporate profits is a sobering reminder that the technology’s benefits are not automatically shared. The Fortune article underscores that, without proactive policy interventions, AI could exacerbate socioeconomic divides, destabilize markets, and erode the social contract that underpins modern economies.

What remains clear is that the coming decade will demand unprecedented collaboration between technologists, policymakers, and civil society. The question is not whether AI will reshape the world—no, that’s a given—but how we choose to shape its impact. As Hinton himself put it in the interview, “We’re standing on a precipice. The next few years will decide whether we harness this power responsibly or let it become a tool of exclusion.”