Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics

46 Pages Posted: 6 Nov 2017 Last revised: 24 Jun 2022

See all articles by Erik Brynjolfsson

Erik Brynjolfsson

National Bureau of Economic Research (NBER); Stanford

Daniel Rock

University of Pennsylvania - Operations & Information Management Department

Chad Syverson

University of Chicago - Booth School of Business; National Bureau of Economic Research (NBER)

Date Written: November 2017

Abstract

We live in an age of paradox. Systems using artificial intelligence match or surpass human level performance in more and more domains, leveraging rapid advances in other technologies and driving soaring stock prices. Yet measured productivity growth has declined by half over the past decade, and real income has stagnated since the late 1990s for a majority of Americans. We describe four potential explanations for this clash of expectations and statistics: false hopes, mismeasurement, redistribution, and implementation lags. While a case can be made for each, we argue that lags have likely been the biggest contributor to the paradox. The most impressive capabilities of AI, particularly those based on machine learning, have not yet diffused widely. More importantly, like other general purpose technologies, their full effects won’t be realized until waves of complementary innovations are developed and implemented. The required adjustment costs, organizational changes, and new skills can be modeled as a kind of intangible capital. A portion of the value of this intangible capital is already reflected in the market value of firms. However, going forward, national statistics could fail to measure the full benefits of the new technologies and some may even have the wrong sign.

Suggested Citation

Brynjolfsson, Erik and Rock, Daniel and Syverson, Chad, Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics (November 2017). NBER Working Paper No. w24001, Available at SSRN: https://ssrn.com/abstract=3065841

Erik Brynjolfsson (Contact Author)

National Bureau of Economic Research (NBER) ( email )

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Stanford ( email )

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HOME PAGE: http://brynjolfsson.com

Daniel Rock

University of Pennsylvania - Operations & Information Management Department ( email )

Philadelphia, PA 19104
United States

Chad Syverson

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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