There may be no more important question for the future of the US economy than whether the ongoing advances in information technology and artificial intelligence will eventually (and this “eventually” is central to their argument) translate into substantial productivity gains. Erik Brynjolfsson, Daniel Rock, and Chad Syverson make the case for optimism in “Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics” (NBER Working Paper 24001, November 2017). The paper isn’t freely available online, but many readers will have access to NBER working papers through their library. The essay will eventually be part of a conference volume on The Economics of Artificial Intelligence. 

Brynjolfsson, Rock, and Syverson are making several intertwined arguments. One is that various aspects of machine learning and artificial intelligence are crossing important thresholds in the last few years and the next few years. Thus, even though we tend to think of the “computer age” as having already been in place for a few decades, there is a meaningful sense in which we are about to enter another chapter. The other argument is that when a technological disruption cuts across many parts of the economy–that is, when it is a “general purpose technology” as opposed to a more focused innovation–it often takes a substantial period of time before producers and consumers fully change and adjust. In turn, this means a substantial period of time before the new technology has a meaningful effect on measured economic growth. 

As one example of a new threshold in machine learning, consider image recognition. On various standardized tests for image recognition, the error rate for humans is about 5%. In just the last few years, the error rate for image-recognition algorithms is now lower than the human level–and of course the algorithms likely to keep improving. 

There are of course a wide array of similar examples. The authors cite one study in which an artificial intelligence system did as well as a panel of board-certified dermatologists in diagnosing skin cancer. Driverless vehicles are creeping into use. Anyone who uses translation software or software that relied on voice recognition can attest to how much better it has become in the last few years.