In his recent interview with CNN, Hinton emphasized that AI has already reached a stage where systems can perform not just "minute tasks," but entire projects that require hours of work. He warned that if this trend continues, fewer employees will be needed to implement complex programs.
According to the expert, the current stage of artificial intelligence development can be compared to the industrial revolution, during which physical labor became less in demand. This time, intellectual work is at risk.
According to a study by Stanford University, the impact of AI is already noticeable in the employment sector, especially among entry-level specialists. Since the end of 2022, the number of job vacancies in programming, marketing, and customer service has decreased by 30%, while employment for newcomers has dropped by 16% following the emergence of ChatGPT.
Economists predict a possible "unemployment boom" in 2026, when companies will seek to increase productivity through AI without increasing their workforce. Diane Swonk, chief economist at KPMG, noted that firms will optimize their staff using natural turnover and layoffs to match the demand for products and services.
However, experts believe that AI may also lead to an increase in hiring for entry-level positions: 67% of CEOs, according to a survey by consulting firm Teneo, expect growth in the number of entry-level employees, while 58% plan to expand managerial positions. This is due to the fact that automating routine tasks is changing existing roles.
Hinton also expressed concern about the risks associated with AI. He noted that, in addition to the threat of job loss, he is worried about AI's ability to deceive and bypass restrictions. According to him, inadequate safety measures pose serious challenges, despite the positive impacts of technology on medicine, education, and combating climate change.
Recently, Hinton spoke about the emergence of a "social bubble" in the field of AI.
According to the scientist, there are two types of bubbles in the field of AI. The first is related to the overestimation of technological capabilities, while the second concerns errors in economic calculations caused by ignoring social factors.
The first bubble, according to Hinton, does not pose a serious threat, as it pertains to doubts about AI's ability to perform claimed functions. "The technology really does a lot," he noted, adding that AI is constantly evolving and capable of solving many tasks, although errors and limitations remain.
The second bubble, in his opinion, concerns the economic and social consequences of AI implementation. Companies invest in technology with the hope of replacing workers and increasing profits, without considering the large-scale social changes.
If mass unemployment due to AI leads to political instability or a decline in consumer demand, the expected profits for companies may not materialize. Even the most powerful AI systems may prove ineffective if the social environment changes in such a way that their implementation becomes unviable, and laid-off workers cease to be consumers. In such a case, the bubble will burst not due to technological failures, but because of an underestimation of social changes.
