A Nobel economist figured out 60 years ago that people learn best on the job. The Atlanta Fed says AI is making that almost impossible
Sixty years ago, an economist named Kenneth Arrow sat down and figured out something that seemed almost too obvious to say: Workers do their jobs better by doing their jobs. This idea was simple, but Arrow, who would later win the Nobel Prize, formalized it into a theory with far-reaching implications. He’s learning wrote“it can only occur through an attempt to solve a problem and therefore can only occur during the event.” He argued that experience is not only good for workers, but also the engine of productivity growth for firms and ultimately the entire economy.
Now, as artificial intelligence eliminates entry-level jobs that once served as launchpads into 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 ways to reduce payroll costs may be cutting the branch they sit on.
Unemployment rate for young degree holders now constantly higher Rather than general unemployment, it’s a reversal of recent workforce trends that many blame on artificial intelligence replacing entry-level knowledge work. Some university graduates are now struggling with unemployment at a similar rate They suggest that as peers without degrees, it may be harder to justify a college education, and the appeal of a secure role in an office job may lose its appeal.
But if you eliminate enough entry-level jobs, white-collar employers will start to suffer, too. This is the result of a result paper A report published last week by researchers at the Federal Reserve Bank of Atlanta analyzed the trade-offs on both sides of the management aisle in automating lower-level office work.
Arrow argued that innovation and productivity growth are byproducts of experience and practice. Fed researchers applied this framework to the drudgery of entry-level jobs and argued that experience provides the foundation for building the expertise needed for senior roles. More importantly, the type of repetitive activity and skill development that occurs early in a young person’s career cannot be replicated in college or graduate school; entry-level roles effectively become a specialized crash course in preparing employees and ensuring a firm’s institutional knowledge remains intact.
“The tasks that fill entry-level positions are not just low-value jobs; they are curricula that enable workers to accumulate the human capital that will make them productive later in their careers,” the researchers wrote.
By automating more of these job roles, firms risk hollowing out the portfolio of competent senior workers they may need in the future, trading short-term cost savings now for long-term stability. Because Arrow’s theory suggests that experiential learning and productivity growth spread and ripple throughout the economy rather than being limited to a single firm, a single company’s choice to automate an entry-level task or role will eventually impact the rest of the industry.
