How AI will divide the best from the rest

At a summit in Paris on February 10th and 11th, tech bosses vied to issue the most grandiose claim about artificial intelligence. “AI will be the most profound shift of our lifetimes,” is how Sundar Pichai, Alphabet’s boss, put it. Dario Amodei, chief executive of Anthropic, said that it would lead to the “largest change to the global labour market in human history”. In a blog post, Sam Altman of OpenAI wrote that “In a decade perhaps everyone on earth will be capable of accomplishing more than the most impactful person can today.”

Mr Altman’s prediction taps into an established school of thought. As large language models first gained popularity in the early 2020s, economists and bosses were hopeful that they, and other AI tools, would level the playing field, with lower-skilled workers benefiting most. Software capable of handling tasks such as protein-folding and poetry-writing would surely democratise opportunity. Jensen Huang, chief executive of Nvidia, a chip designer, envisioned a future in which workers “are all going to be CEOs of AI agents”.

More recent findings have cast doubt on this vision, however. They instead suggest a future in which high-flyers fly still higher—and the rest are left behind. In complex tasks such as research and management, new evidence indicates that high performers are best positioned to work with AI. Evaluating the output of models requires expertise and good judgment. Rather than narrowing disparities, AI is likely to widen workforce divides, much like past technological revolutions.

The case for AI as an equaliser was supported by research showing that the tech enhances output most for less experienced workers.  The problem is that this is swamped by another effect. A job can be considered as a bundle of tasks, which tech may either commoditise or assist with.  Thus despite the early optimism, customer-service agents and other low-skilled workers may face a future akin to cashiers. Their repetitive tasks are susceptible to automation.  

Unlike earlier automation, which replaced routine jobs such as assembly-line work and book-keeping, AI may extend its reach to non-routine and creative work. It can learn tacitly, recognise patterns and make predictions without explicit instruction; perhaps, in time, it will be able to write entertaining scripts and design useful products. For the moment it seems as though, in high-wage industries, it is junior staff who are the most vulnerable to automation.

The shift in recent economic research supports his observation. Although early studies suggested that lower performers could benefit simply by copying AI outputs, newer studies look at more complex tasks, such as scientific research, running a business and investing money. In these contexts, high performers benefit far more than their lower-performing peers. In some cases, less productive workers see no improvement, or even lose ground.

Labour markets have always been defined by the destruction of old roles and the creation of new ones. David Autor of MIT has estimated that 60% or so of work in America in 2018 did not exist in 1940.  who will take AI’s new jobs when they emerge? History suggests that technological upheavals favour the skilled.  AI appears poised to follow a similar path, benefiting those with the judgment, agility and expertise to navigate complex, information-rich environments.

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