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Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter?

Author

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  • Gries, Thomas

    (Universitat Paderborn)

  • Naude, Wim

    (UNU-MERIT, and Maastricht University, RWTH Aachen University, IZA Institute of Labor Economics, Bonn.)

Abstract

Rapid technological progress in artificial intelligence (AI) has been predicted to lead to mass unemployment, rising inequality, and higher productivity growth through automation. In this paper we critically re-assess these predictions by (i) surveying the recent literature and (ii) incorporating AI-facilitated automation into a product variety-model, frequently used in endogenous growth theory, but modified to allow for demand-side constraints. This is a novel approach, given that endogenous growth models, and including most recent work on AI in economic growth, are largely supply-driven. Our contribution is motivated by two reasons. One is that there are still only very few theoretical models of economic growth that incorporate AI, and moreover an absence of growth models with AI that takes into consideration growth constraints due to insuficient aggregate demand. A second is that the predictions of AI causing massive job losses and faster growth in productivity and GDP are at odds with reality so far: if anything, unemployment in many advanced economies is historically low. However, wage growth and productivity is stagnating and inequality is rising. Our paper provides a theoretical explanation of this in the context of rapid progress in AI.

Suggested Citation

  • Gries, Thomas & Naude, Wim, 2018. "Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter?," MERIT Working Papers 2018-047, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  • Handle: RePEc:unm:unumer:2018047
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    References listed on IDEAS

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    Cited by:

    1. Gries, Thomas & Naudé, Wim, 2020. "Artificial Intelligence, Income Distribution and Economic Growth," GLO Discussion Paper Series 632, Global Labor Organization (GLO).
    2. Gries, Thomas & Naudé, Wim, 2020. "Extreme Events, Entrepreneurial Start-Ups, and Innovation: Theoretical Conjectures," IZA Discussion Papers 13835, Institute of Labor Economics (IZA).
    3. Gries, Thomas & Naudé, Wim, 2021. "The Race of Man and Machine: Implications of Technology When Abilities and Demand Constraints Matter," IZA Discussion Papers 14341, Institute of Labor Economics (IZA).
    4. Giacomo Damioli & Vincent Van Roy & Daniel Vertesy, 2021. "The impact of artificial intelligence on labor productivity," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 11(1), pages 1-25, March.

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    More about this item

    Keywords

    Technology; artificial intelligence; productivity; labour demand; innovation; growth theory;
    All these keywords.

    JEL classification:

    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E25 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Aggregate Factor Income Distribution

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