IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/32255.html
   My bibliography  Save this paper

Scenarios for the Transition to AGI

Author

Listed:
  • Anton Korinek
  • Donghyun Suh

Abstract

We analyze how output and wages behave under different scenarios for technological progress that may culminate in Artificial General Intelligence (AGI), defined as the ability of AI systems to perform all tasks that humans can perform. We assume that human work can be decomposed into atomistic tasks that differ in their complexity. Advances in technology make ever more complex tasks amenable to automation. The effects on wages depend on a race between automation and capital accumulation. If automation proceeds sufficiently slowly, then there is always enough work for humans, and wages may rise forever. By contrast, if the complexity of tasks that humans can perform is bounded and full automation is reached, then wages collapse. But declines may occur even before if large-scale automation outpaces capital accumulation and makes labor too abundant. Automating productivity growth may lead to broad-based gains in the returns to all factors. By contrast, bottlenecks to growth from irreproducible scarce factors may exacerbate the decline in wages.

Suggested Citation

  • Anton Korinek & Donghyun Suh, 2024. "Scenarios for the Transition to AGI," NBER Working Papers 32255, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:32255
    Note: DAE EFG LS PR
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w32255.pdf
    Download Restriction: Access to the full text is generally limited to series subscribers, however if the top level domain of the client browser is in a developing country or transition economy free access is provided. More information about subscriptions and free access is available at http://www.nber.org/wwphelp.html. Free access is also available to older working papers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Joseph Zeira, 1998. "Workers, Machines, and Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1091-1117.
    2. Lawrence F. Katz & Kevin M. Murphy, 1992. "Changes in Relative Wages, 1963–1987: Supply and Demand Factors," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(1), pages 35-78.
    3. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    4. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    5. Korinek, Anton, 2023. "Language Models and Cognitive Automation for Economic Research," CEPR Discussion Papers 17923, C.E.P.R. Discussion Papers.
    6. Philip Trammell & Anton Korinek, 2023. "Economic Growth under Transformative AI," NBER Working Papers 31815, National Bureau of Economic Research, Inc.
    7. Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2023. "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models," Papers 2303.10130, arXiv.org, revised Aug 2023.
    8. Ege Erdil & Tamay Besiroglu, 2023. "Explosive growth from AI automation: A review of the arguments," Papers 2309.11690, arXiv.org, revised Oct 2023.
    9. Jones, Charles I, 1995. "R&D-Based Models of Economic Growth," Journal of Political Economy, University of Chicago Press, vol. 103(4), pages 759-784, August.
    10. Ajay K. Agrawal & John McHale & Alexander Oettl, 2023. "Artificial Intelligence and Scientific Discovery: A Model of Prioritized Search," NBER Working Papers 31558, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Benjamin Moll & Lukasz Rachel & Pascual Restrepo, 2022. "Uneven Growth: Automation's Impact on Income and Wealth Inequality," Econometrica, Econometric Society, vol. 90(6), pages 2645-2683, November.
    2. Jones, C.I., 2016. "The Facts of Economic Growth," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 3-69, Elsevier.
    3. Oschinski, Matthias, 2023. "Assessing the Impact of Artificial Intelligence on Germany's Labor Market: Insights from a ChatGPT Analysis," MPRA Paper 118300, University Library of Munich, Germany.
    4. Andreas Irmen, 2021. "Automation, growth, and factor shares in the era of population aging," Journal of Economic Growth, Springer, vol. 26(4), pages 415-453, December.
    5. Jakub Growiec, 2023. "Industry 4.0? Framing the Digital Revolution and Its Long-Run Growth Consequences," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 4, pages 1-16.
    6. T. Gries & R. Grundmann & I. Palnau & M. Redlin, 2017. "Innovations, growth and participation in advanced economies - a review of major concepts and findings," International Economics and Economic Policy, Springer, vol. 14(2), pages 293-351, April.
    7. Jerzmanowski, Michal & Tamura, Robert, 2019. "Directed technological change & cross-country income differences: A quantitative analysis," Journal of Development Economics, Elsevier, vol. 141(C).
    8. Youssef Benzarti & Jarkko Harju, 2021. "Using Payroll Tax Variation to Unpack the Black Box of Firm-Level Production," Journal of the European Economic Association, European Economic Association, vol. 19(5), pages 2737-2764.
    9. Ana L. Abeliansky & Klaus Prettner & Roman Stoellinger, 2023. "Infection Risk at Work, Automatability, and Employment," Department of Economics Working Papers wuwp352, Vienna University of Economics and Business, Department of Economics.
    10. Hémous, David & Dechezleprêtre, Antoine & Olsen, Morten & Zanella, carlo, 2019. "Automating Labor: Evidence from Firm-level Patent Data," CEPR Discussion Papers 14249, C.E.P.R. Discussion Papers.
    11. repec:hal:spmain:info:hdl:2441/7n49nkmngd8448a5ts5gt5ade0 is not listed on IDEAS
    12. Julieta Caunedo & David Jaume & Elisa Keller, 2023. "Occupational Exposure to Capital-Embodied Technical Change," American Economic Review, American Economic Association, vol. 113(6), pages 1642-1685, June.
    13. David Hémous & Morten Olsen, 2022. "The Rise of the Machines: Automation, Horizontal Innovation, and Income Inequality," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(1), pages 179-223, January.
    14. Gallipoli, Giovanni & Makridis, Christos A., 2018. "Structural transformation and the rise of information technology," Journal of Monetary Economics, Elsevier, vol. 97(C), pages 91-110.
    15. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
    16. Daron Acemoglu & Pascual Restrepo, 2020. "The wrong kind of AI? Artificial intelligence and the future of labour demand," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 25-35.
    17. Gregory, Terry & Salomons, Anna & Zierahn, Ulrich, 2016. "Racing With or Against the Machine? Evidence from Europe," VfS Annual Conference 2016 (Augsburg): Demographic Change 145843, Verein für Socialpolitik / German Economic Association.
    18. Dosi, G. & Pereira, M.C. & Roventini, A. & Virgillito, M.E., 2022. "Technological paradigms, labour creation and destruction in a multi-sector agent-based model," Research Policy, Elsevier, vol. 51(10).
    19. Philippe Aghion & Céline Antonin & Simon Bunel, 2019. "Artificial Intelligence, Growth and Employment: The Role of Policy," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 510-511-5, pages 149-164.
    20. Lerche, Adrian, 2022. "Investment Tax Credits and the Response of Firms," IZA Discussion Papers 15668, Institute of Labor Economics (IZA).
    21. Gasteiger, Emanuel & Prettner, Klaus, 2022. "Automation, Stagnation, And The Implications Of A Robot Tax," Macroeconomic Dynamics, Cambridge University Press, vol. 26(1), pages 218-249, January.

    More about this item

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:32255. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.