AI machine learning could drive productivity gains and influence the Fed

Members of the Federal Reserve’s rate-setting committee say they are factoring increased labor productivity into their economic forecasts as artificial intelligence technology becomes more widely adopted.

Fed Chairman Jerome Powell addressed this topic at his December press conference, saying that in past technology waves, “there has always been more work, higher productivity and higher incomes. What’s going to happen here? We’ll have to see.”

Economists and investors say generative AI tools in particular have the potential to increase worker productivity and disrupt the labor market. Powered by machine learning, these tools could improve over time as more people use them to augment their work, according to researchers writing in the National Bureau of Economic Research.

“That’s because AI can learn. And humans can also try to use it more efficiently and train it to adapt to each person. And the resulting productivity gain is enormous,” said Ping Wang, professor of economics at Washington University in St. Louis and co-author of “Artificial intelligence and technological unemployment.”

Wang and his co-author, Tsz-Nga Wong, a senior economist at the Federal Reserve Bank of Richmond, modeled various scenarios for AI development. In an “unlimited growth” scenario, in which technology is fully developed over several decades, 23% of workers would lose their jobs and labor productivity would increase three or four times.

“Over the next decade, which is more of an interim period, labor productivity will increase by about 7% per year,” Wang said in an interview with CNBC. He stressed that this is a hypothetical scenario that may not come true.

The potential effects could affect the employment side of the Federal Reserve’s dual mandate. In December, the Federal Open Market Committee forecast a federal funds rate of nearly 3% over the long term. This may be a moderately accommodating stance compared to a neutral interest rate estimated in the medium term at 3.7%, according to Cleveland Fed Economists.

Some investors see similarities between today’s rush to build data centers and the boom in capital spending on networking components in the 1990s.

“The fact that we’re seeing valuations rise makes us a little more cautious about future returns,” Dan Tolomay, chief investment officer at Trust Company of the South, said in an interview with CNBC.

Look at it video to learn more about how AI affects the Fed’s economic outlook.