Will the AI revolution cause a great divergence?

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Publisher: Elsevier B.V.
Document Type: Report; Brief article
Length: 292 words

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Abstract :

Keywords Automation; Robots; Divergence; Development; Technological change Highlights * Emerging technologies (AI, "robots") threaten to cause cross-county divergence. * Just assuming that robots substitute more for unskilled yields three mechanisms: * High-wage countries use robots more so gain more from higher robot productivity. * Relative wage of unskilled labor, and so price of poor-country exports, falls. * In transition, capital flows "uphill" given high return to robot capital. Abstract Implications of a new wave of technological change that substitutes pervasively for labor are examined with particular focus on developing countries. While the model considered is minimalist by design, the resulting conclusions are powerful: improvements in the productivity of "robots" drive divergence, as advanced countries differentially benefit from their initially higher robot intensity, driven by their endogenously higher wages and stock of complementary traditional capital. Capital--if internationally mobile--is pulled "uphill", resulting in a transitional GDP decline in the developing country. When robots substitute only for unskilled labor, the terms of trade, and hence GDP, may decline permanently. Author Affiliation: International Monetary Fund, United States * Corresponding author.:. Article History: Received 24 June 2020; Revised 23 January 2022; Accepted 26 January 2022 (footnote)[white star] We thank Aidar Abdychev, Emre Alper, Ed Buffie, Dominique Desruelle, Anton Korinek, Axel Schimmelpfennig, Preya Sharma, Felipe Zanna, and other colleagues at the IMF, and participants at the INET/IMF conference "Macroeconomics in the age of Artificial Intelligence" for valuable comments and suggestions. We acknowledge funding from the U.K. Foreign Commonwealth and Development Office (FCDO). The views expressed in this paper are the sole responsibility of the authors and should not be attributed to the International Monetary Fund, its Executive Board, or its management. Byline: Cristian Alonso [CAlonso@imf.org], Andrew Berg [ABerg@imf.org] (*), Siddharth Kothari [SKothari@imf.org], Chris Papageorgiou [CPapageorgiou@imf.org], Sidra Rehman [SRehman@imf.org]

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Gale Document Number: GALE|A700885614