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It’s the biggest puzzle in the economy today: We are surrounded by technological advances, from artificial intelligence to robotics, but you can find no sign of it in wages or productivity. Apocalyptic warnings of jobs destroyed by automation look increasingly ludicrous amid a record streak of employment growth.
In the past year I’ve dug into this in columns and articles and concluded there isn’t a paradox: automation hasn’t advanced nearly as far as evangelists claim, and where it has, it’s often created more jobs than it’s destroyed. But that’s the past; what about the future? Forecasts about technology are seldom more than wild guesses, yet a case could be made that the economic payoff may now be coming.
History shows that technological breakthroughs commonly take decades to move the needle on economic growth. Blame it on false starts, costly implementation, human resistance, and simple math: It’s years before a new industry is big enough to make a ripple in what is now an $80 trillion global economy.
In a recent paper Erik Brynjolfsson and Daniel Rock of the Massachusetts Institute of Technology and Chad Syverson of the University of Chicago note electric motors based on alternating current were introduced in the late 1800s but even by 1919 half of U.S. factories still weren’t electrified. The integrated circuit was commercialized in the 1960s yet 25 years later computers still represented just 5% of the value of all business equipment. Indeed, since the introduction of computers labor productivity has behaved much as it did after the introduction of electric motors and the internal combustion engine.
The authors blame these lags on the cost and time it takes for businesses to adapt to new technologies, obstacles they see at work today. Online shopping came along in the 1990s but retailers struggled to adapt business processes to the internet. They needed to build complementary infrastructure such as fulfillment centers, and, the authors note, customers had to adapt their habits, as well. The enormous cost of designing and building autonomous cars means the labor needed to build a new car initially goes up, which depresses productivity.
What about AI? Banks first used machine learning—a type of artificial intelligence that spots patterns in massive data sets—to spot credit-card fraud in 1987. But to gain widespread acceptance first computing power had to get a lot cheaper, datasets a lot bigger, and lots of people had to spend lots of hours deciding what questions to ask and then training algorithms to answer them.
Hype always runs well ahead of reality, bringing failure and dashed expectations. Jeffrey Funk, an independent researcher, studied the predictions of breakthrough technologies made by MIT Technology Review, a magazine published by Massachusetts Institute of Technology. Of 40 predictions it made between 2001 and 2005, most never became a market worth more than $5 billion by 2015, and only one—data mining—become a market worth more than $100 billion. Meanwhile, the magazine completely missed smartphones ($400 billion), cloud computing ($175 billion), social networking, e-books, fintech and wearable computing. Mr. Funk says the lists better reflected ?the hottest trends in scientific laboratories whereas commercial breakthroughs are more often extrapolations of existing technology.
Much of that hype is reflected in the stock market valuations attached to early-stage companies, most of which eventually fail.
Yet when a company achieves the value that today’s tech leaders have, it tells you something important. A third of the rise in the S&P 500 stock market index this year is attributable to Apple Inc., Amazon.com Inc., Google parent Alphabet Inc., Facebook Inc. and Microsoft Corp. That may mean the advances these companies represent are becoming economically significant. Internet sales, for example, now represent 9% of total retailing, putting discernible downward pressure on inflation.
This hasn’t yet produced a broader economic boom. Mark Muro of the Brookings Institution has found that the industries with the fastest productivity growth between 2010 and 2016 also tended to more intensively employ digital skills.
Two such industries are information and communications technology and media, but the two represent just 5.5% of economic output, too little to affect the overall picture.
True, U.S. growth has accelerated in 2017, but productivity, which J.P. Morgan estimates to have been 1.2%, is in line with the sluggish pace of the expansion, and one of the best performing industries, oil and gas, is responding mostly to the price of oil.
But perhaps the U.S. is at a point when technology and an economy growing solidly with low unemployment become mutually reinforcing. “Entrepreneurs are more willing to take risks, including investments in new technologies and new business models when the economy is running hotter,” says Mr. Brynjolfsson. “This will speed up the adoption of the kinds of conventions needed to take full advantage of artificial intelligence and other new technologies.”
Consider the parallels between the present and 1998: President Bill Clinton and Congress cut the capital-gains tax rate in 1997 and, with inflation quiescent, the Federal Reserve declined to jack up interest rates as unemployment dropped to new lows, creating the ideal environment for the dot-com boom. As stock wealth stoked spending, economic growth picked up sharply.
The party ended when the tech bubble burst in 2000 and the economy went into recession in 2001. Similarly, Marc Sumerlin, who runs the research firm Evenflow Macro, predicts that the next two years could be the best of the expansion yet—but they will be “the last hurrah.”
Write to Greg Ip at firstname.lastname@example.org
Appeared in the December 28, 2017, print edition as ‘Technology-Driven Boom Is Finally Coming.’
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