Many observers hope that generative artificial intelligence will lead to major productivity gains. Two recently published studies from the UK-based think tank Autonomy – which is dedicated to tackling climate change, the future of work, and economic planning – support this theory, and even suggest it could lead to the adoption of a four-day working week.
Analysing the effects of AI use on British and American workforces, Autonomy reports that this technology could enable 28% of UK workers to see their working week cut from 40 to 32 hours by 2033. This means they could easily complete their work tasks in four days instead of five.
This could also be the case for some 35 million workers in the United States: the think tank estimates that 28% of the American payroll could switch to a four-day week within the next 10 years.
In addition, 71% of US workers could see their working time reduced by at least 10% if they use large language models (LLMs) in their day-to-day work: programs capable of generating automatic responses to questions formulated in writing. This percentage rises to 88% in the UK.
These productivity gains can be explained by the fact that generative AI tools will likely automate repetitive and time-consuming tasks, enabling employees to devote themselves to higher value-added missions – as well as their lives outside the office.
The question of creativity
Autonomy believes that deploying LLMs in the workplace to shorten the working week while maintaining pay “offers the possibility of avoiding mass unemployment, reducing widespread mental health illnesses as well as physical ailments associated with overwork, and creating free time for leisure consumption and social cohesion in general”.
Still, experts remain divided on the impact of AI on the job market.
Researchers from Harvard Business School, MIT Sloan School of Management, the University of Pennsylvania, the University of Warwick, and the BCG Henderson Institute found that the new generation of AI tools only improves performance in so-called “creative” tasks, such as writing emails, summarising documents, or finding names for a product/service.
These tools, however, don’t help workers solve complex problems. Worse, they tend to drastically reduce their creativity and standardise output.
“Time and again, GPT-4 provides responses with very similar meaning to the same sorts of prompts; so the output provided by participants who used the technology was individually better but collectively repetitive,” the researchers noted.
Companies will, therefore, need to think hard about how to harness the benefits of AI without restricting the creative capacity of their teams. The challenge is to ensure that the relationship between humans and technology is one of collaboration, not dependence.