Daron Acemoglu in Project Syndicate:
According to tech leaders and many pundits and academics, artificial intelligence is poised to transform the world as we know it through unprecedented productivity gains. While some believe that machines soon will do everything humans can do, ushering in a new age of boundless prosperity, other predictions are at least more grounded. For example, Goldman Sachs predicts that generative AI will boost global GDP by 7% over the next decade, and the McKinsey Global Institute anticipates that the annual GDP growth rate could increase by 3-4 percentage points between now and 2040. For its part, The Economist expects that AI will create a blue-collar bonanza.
Is this realistic? As I note in a recent paper, the outlook is far more uncertain than most forecasts and guesstimates suggest. Still, while it is basically impossible to predict with any confidence what AI will do in 20 or 30 years, one can say something about the next decade, because most of these near-term economic effects must involve existing technologies and improvements to them.
It is reasonable to suppose that AI’s biggest impact will come from automating some tasks and making some workers in some occupations more productive. Economic theory provides some guidance for assessing these aggregate effects. According to Hulten’s theorem (named for economist Charles Hulten), aggregate “total factor productivity” (TFP) effects are simply the product of the share of tasks that are automated multiplied by the average cost savings.
While average cost savings are difficult to estimate and will vary by activity, there have already been some careful studies of AI’s effects on certain tasks.
Enjoying the content on 3QD? Help keep us going by donating now.