“Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics”, 2019-05-01 (; similar):
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 explanation, 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 adjustment costs, organizational changes, and new skills needed for successful AI 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.
…The discussion around the recent patterns in aggregate productivity growth highlights a seeming contradiction. On the one hand, there are astonishing examples of potentially transformative new technologies that could greatly increase productivity and economic welfare (see Brynjolfsson and 2014 [Race Against The Machine]). There are some early concrete signs of these technologies’ promise, recent leaps in artificial intelligence (AI) performance being the most prominent example. However, at the same time, measured productivity growth over the past decade has slowed importantly. This deceleration is large, cutting productivity growth by half or more in the decade preceding the slow-down. It is also widespread, having occurred throughout the Organization for Economic Cooperation and Development (OECD) and, more recently, among many large emerging economies as well (2017).1
We thus appear to be facing a redux of the Solow (198737ya) paradox: we see transformative new technologies everywhere but in the productivity statistics.
In this chapter, we review the evidence and explanations for the modern productivity paradox and propose a resolution. Namely, there is no inherent inconsistency between forward-looking technological optimism and backward-looking disappointment. Both can simultaneously exist. Indeed, there are good conceptual reasons to expect them to simultaneously exist when the economy undergoes the kind of restructuring associated with transformative technologies. In essence, the forecasters of future company wealth and the measurers of historical economic performance show the greatest disagreement during times of technological change. In this chapter, we argue and present some evidence that the economy is in such a period now.