Sixty years ago, an economist named Kenneth Arrow sat down and worked out something that seemed almost too obvious to say: workers get better at their jobs by doing them. The insight was simple, but Arrow, who would go on to win the Nobel Prize, formalized it into a theory with sweeping implications. Learning, he wrote, “can only take place through the attempt to solve a problem and therefore only takes place during activity.” Experience wasn’t just good for workers, he argued—it was the engine of productivity growth for firms and, ultimately, the entire economy.
Now, as artificial intelligence chips away at the entry-level jobs that once served as the on-ramp to white-collar careers, researchers at the Federal Reserve Bank of Atlanta are dusting off Arrow’s 1962 paper and warning that companies racing to automate their way to lower payroll costs may be sawing off the branch they’re sitting on.
