Jeffrey Hinton: AI Will Displace Many More Jobs in 2026

Jeffrey Hinton, a Nobel Prize laureate and recognized as the "godfather of artificial intelligence," predicts that by 2024, AI will be able to take "very, very many jobs." He noted that the development of technology is happening faster than he anticipated, affecting not only call centers but also professions such as software development and other office roles. Hinton also added that AI's capabilities are doubling approximately every seven months.

In a recent interview with CNN, the researcher emphasized that modern systems are already capable of performing not only "minute programming tasks" but also projects that take up to an hour. He predicted that if current trends continue, complex programs may require a minimal number of employees.

Hinton compared the stage of AI development to the industrial revolution, when physical labor became less in demand, and now intellectual labor is at risk.

The impact of artificial intelligence on the labor market is already noticeable, especially for entry-level professionals. A study by Stanford University shows that since the end of 2022, employment in areas such as programming, marketing, and customer service has fallen by 16%, and the number of job vacancies has decreased by 30% since the emergence of ChatGPT.

Economists predict that in 2026, there will be a "boom in unemployment" when companies start increasing productivity with the help of AI without increasing their workforce. Diane Swonk, chief economist at KPMG, noted that firms will optimize their staff, relying on natural turnover and layoffs in accordance with changes in demand for products and services.

However, AI may also contribute to an increase in job openings for entry-level professionals. A survey by consulting firm Teneo showed that 67% of CEOs expect an increase in the number of entry-level workers, while 58% plan to expand managerial positions as automation of routine tasks changes existing roles.

Hinton also expressed concern about potential risks to society: in addition to the threat of job loss, he emphasized that AI can deceive and circumvent established limitations. He pointed to insufficient safety measures that create serious challenges, despite the positive aspects of technology in areas such as medicine, education, and combating climate change.

Recently, the scientist announced the emergence of a "social bubble" in the field of AI.

According to Hinton, there are two types of bubbles in the AI sector. The first is related to the overestimation of technological capabilities, while the second is associated with errors in economic calculations due to the neglect of social factors.

The scientist believes that the first type of bubble, which is based on doubts about AI's ability to perform claimed functions, does not pose a serious threat. "Technology really does a lot," Hinton noted, adding that AI is constantly improving and solving many tasks, although errors and limitations still exist.

The second type of bubble, in his view, concerns the economic and social consequences of AI implementation: companies invest in technologies with the hope of replacing workers and increasing profits, without considering the large-scale changes in society.

If mass unemployment caused by AI leads to political instability, regulatory pressure, or a decline in consumer demand, the expected profits for companies may not materialize. Even the most powerful AI systems will prove ineffective if the social situation changes such that their implementation becomes impractical or laid-off workers cease to be customers. In this case, the bubble will burst not because of the technologies, but due to an underestimation of social changes.