Members of the Federal Reserve rate-setting committee say they are factoring increased labor productivity into their economic forecasts as artificial intelligence technology becomes more widely adopted.
Fed Chair Jerome Powell addressed this topic in his December news conference, saying that in past technology waves “there’s always been more work and higher productivity and incomes have risen. What will happen here? We’re going to have to see.”
Economists and investors say generative AI tools in particular have potential to increase worker productivity and shake up the labor market. Powered by machine learning, these tools may improve over time as more people use them to augment their work, according to researchers writing in the National Bureau of Economic Research.
“This is because AI can learn. And human beings can also try to utilize AI more effectively, and train AI to suit each person. And the resulting productivity gain is huge,” said Ping Wang, a 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’s development. In an “unbounded growth” scenario, in which the technology becomes fully developed over many decades, 23% of workers lose employment and labor productivity increases by as much as three to four times.
“Over the next decade which is more like an intermediate run, labor productivity will increase by about roughly 7% per year,” said Wang in an interview with CNBC. He noted that this is a hypothetical scenario that may not unfold.
The potential effects could affect the employment side of the Federal Reserve’s dual mandate. The Federal Open Market Committee in December forecasted a federal funds rate settling near 3% over the longer run. This may be a moderately accommodative posture relative to an estimated medium-run neutral interest rate at 3.7%, according to Cleveland Fed economists.
Some investors see similarities between today’s rush to build data centers and a capital expenditures boom on network components in the 1990s.
“The fact that we see a run up in valuations makes us a little more cautious about future returns,” said Dan Tolomay, chief investment officer at Trust Company of the South in an interview with CNBC.
Watch the video to learn more about how AI affects the Fed’s economic outlook.
Read More: AI’s machine learning may net productivity gains and influence Fed
