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Artificial Intelligence, Jobs, Inequality and Productivity: Does Aggregate Demand Matter?

Author

Listed:
  • Gries, Thomas

    (University of Paderborn)

  • Naudé, Wim

    (RWTH Aachen University)

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 insufficient 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 & Naudé, Wim, 2018. "Artificial Intelligence, Jobs, Inequality and Productivity: Does Aggregate Demand Matter?," IZA Discussion Papers 12005, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp12005
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    Cited by:

    1. Naudé, Wim, 2019. "The Race against the Robots and the Fallacy of the Giant Cheesecake: Immediate and Imagined Impacts of Artificial Intelligence," IZA Discussion Papers 12218, Institute of Labor Economics (IZA).
    2. Mutascu, Mihai, 2021. "Artificial intelligence and unemployment: New insights," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 653-667.
    3. Mandal, Biswajit & Roy Chakraborty, Labani & Sanyal, Alapan, 2023. "Hybrid Mode of Production, Transaction, and Economic Growth: Implication of Digitalization," GLO Discussion Paper Series 1264, Global Labor Organization (GLO).
    4. Gries, Thomas & Naudé, Wim, 2020. "Artificial Intelligence, Income Distribution and Economic Growth," GLO Discussion Paper Series 632, Global Labor Organization (GLO).
    5. Kerstin Hotte & Taheya Tarannum & Vilhelm Verendel & Lauren Bennett, 2022. "Measuring artificial intelligence: a systematic assessment and implications for governance," Papers 2204.10304, arXiv.org, revised Jul 2024.
    6. Jing Wang & Zeyu Xing & Rui Zhang, 2023. "AI technology application and employee responsibility," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-17, December.
    7. Zhu, Jun & Zhang, Jingting & Feng, Yiqing, 2022. "Hard budget constraints and artificial intelligence technology," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    8. Naudé, Wim, 2020. "From the Entrepreneurial to the Ossified Economy: Evidence, Explanations and a New Perspective," GLO Discussion Paper Series 539, Global Labor Organization (GLO).
    9. Naudé, Wim, 2019. "The decline in entrepreneurship in the West: Is complexity ossifying the economy?," MERIT Working Papers 2019-030, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    10. Thomas Gries & Wim Naudé, 2021. "Extreme Events, Entrepreneurial Start-Ups, and Innovation: Theoretical Conjectures," Economics of Disasters and Climate Change, Springer, vol. 5(3), pages 329-353, October.
    11. Bäck, Asta & Hajikhani, Arash & Jäger, Angela & Schubert, Torben & Suominen, Arho, 2022. "Return of the Solow-paradox in AI? AI-adoption and firm productivity," Papers in Innovation Studies 2022/1, Lund University, CIRCLE - Centre for Innovation Research.
    12. 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).
    13. Jean-Philippe Deranty & Thomas Corbin, 2022. "Artificial Intelligence and work: a critical review of recent research from the social sciences," Papers 2204.00419, arXiv.org.
    14. 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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