Shiller says fear of AI job losses could help cause a slump
The Yale economist argues that pessimistic narratives about AI and work could weigh on spending and hiring before broad displacement shows up.
By Sofia Marchetti · World Affairs Correspondent
3 min read
Nobel Prize-winning economist Robert Shiller is warning that fear over AI-driven job losses could help produce the economic damage people are worried about. His argument matters because surveys show Americans have grown wary of AI while some labor research has not found broad job-category disruption from the technology.
In a June 22 guest essay in The New York Times, Shiller, a Yale University economist, argued that stories people tell about the economy can shape the choices of households, companies and investors. Shiller tied the point to his Nobel-recognized work on how markets misprice risk, writing that pessimistic expectations can feed decisions that make a feared outcome more likely.
Public opinion has supplied fuel for that concern. A recent Pew survey found that 16% of Americans expect AI to have a positive effect on society over the next 20 years, while 40% expect a negative effect, according to Fortune. In a March Quinnipiac survey cited in the report, 70% of Americans said they expected AI to mean fewer jobs for people, up from 56% a year earlier.
Shiller points to older technology scares
Shiller argued in the Times that fear of machines replacing workers has appeared before, often running ahead of the actual employment effect. He cited the 1830s Luddite revolt against looms and the 1920s play R.U.R., which helped popularize the idea of robots turning against their makers, according to Fortune.
He also used financial history to make his case about narratives. Shiller wrote that the 1929 stock market crash alone could not explain the Great Depression because only about 2% of U.S. households owned stock at the time, according to Fortune. He argued that a collapse in consumer spending, driven by sudden anxiety about future income, helped worsen the downturn.
Shiller also pointed to the 1957-58 downturn, which journalists called the “Automation Recession” because they blamed factory machines, according to Fortune. The episode was later described as a normal cyclical downturn, Shiller wrote.
Evidence of AI disruption remains mixed
Shiller said the current labor market has slowed for several reasons, according to Fortune. He warned that reports tying the slowdown to fears of an AI jobs crisis could be worsening hiring caution and weighing on consumer confidence.
At the same time, the Yale Budget Lab has found no significant shift in the occupational mix of jobs most exposed to AI since ChatGPT’s late-2022 launch, according to Fortune. Shiller used that finding to argue that the public discussion may be moving faster than the available labor-market evidence.
Shiller also criticized warnings from AI industry leaders, saying they have amplified public anxiety. Anthropic CEO Dario Amodei has said AI could wipe out half of entry-level white-collar jobs within five years, while Microsoft AI chief Mustafa Suleyman has put broad white-collar automation on a 12-to-18-month timeline, according to Fortune. Both executives later softened those timelines, Fortune reported.
Shiller said leadership can change economic expectations, pointing to research that found President Franklin Roosevelt’s 1935 fireside chat increased spending in cities with greater radio exposure, according to Fortune. He argued that Washington has limited power over today’s AI narrative and urged Silicon Valley leaders to be more careful about promoting claims that could damage confidence.
This story draws on original reporting from Fortune.