Generative AI: Small Boosts in Productivity with Big Economic Potential
Researchers, including economist David Deming, have been exploring the potential impact of generative AI on productivity. To estimate how much AI could boost productivity, Deming and his colleagues examined five randomized studies that measured productivity increases in various work environments due to generative AI. From these studies, they found a median productivity boost of about 25%.
They then multiplied this figure by their estimate of the percentage of work hours currently assisted by AI, which they calculated to be between 0.5% and 3.5% of total work hours in the U.S. From this, they predicted that AI could lead to an increase in labor productivity of between 0.125 and 0.875 percentage points at current usage levels. While this may seem small, Deming points out that it would still represent a significant contribution to productivity growth, considering that the U.S. has averaged around 1.5% productivity growth per year in recent decades.
Economist Daron Acemoglu conducted similar calculations, arriving at comparable estimates of AI’s potential productivity impact. However, while Acemoglu emphasizes the limits of AI’s transformative potential in the short term, Deming highlights that even a modest boost could result in millions of dollars of GDP growth and improved living standards.
Both economists agree that AI is unlikely to drive massive productivity growth immediately, but as its integration into tools like smartphones and everyday technology increases, AI’s potential impact may grow over time. Deming notes that, as AI becomes more embedded in daily activities, it will be increasingly difficult to measure how much people rely on it.
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