IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/18928.html
   My bibliography  Save this paper

Scenarios for the Transition to AGI

Author

Listed:
  • Korinek, Anton
  • Suh, Donghyun

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 the distribution of task complexity exhibits a sufficiently thick infinite tail, 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

  • Korinek, Anton & Suh, Donghyun, 2024. "Scenarios for the Transition to AGI," CEPR Discussion Papers 18928, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:18928
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP18928
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
    ---><---

    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. Philip Trammell & Anton Korinek, 2023. "Economic Growth under Transformative AI," NBER Working Papers 31815, National Bureau of Economic Research, Inc.
    3. 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.
    4. 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.
    5. 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.
    6. Agrawal, Ajay & McHale, John & Oettl, Alexander, 2024. "Artificial intelligence and scientific discovery: a model of prioritized search," Research Policy, Elsevier, vol. 53(5).
    7. Ege Erdil & Tamay Besiroglu, 2023. "Explosive growth from AI automation: A review of the arguments," Papers 2309.11690, arXiv.org, revised Jul 2024.
    8. 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.
    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. Anton Korinek, 2023. "Language Models and Cognitive Automation for Economic Research," NBER Working Papers 30957, 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Daniele Angelini, 2023. "Aging Population and Technology Adoption," Working Paper Series of the Department of Economics, University of Konstanz 2023-01, Department of Economics, University of Konstanz.
    8. 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.
    9. Jerzmanowski, Michal & Tamura, Robert, 2019. "Directed technological change & cross-country income differences: A quantitative analysis," Journal of Development Economics, Elsevier, vol. 141(C).
    10. 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.
    11. Caleb Peppiatt, 2024. "The Future of Work: Inequality, Artificial Intelligence, and What Can Be Done About It. A Literature Review," Papers 2408.13300, arXiv.org.
    12. Yuki, Kazuhiro, 2012. "Mechanization, task assignment, and inequality," MPRA Paper 37754, University Library of Munich, Germany.
    13. 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.
    14. Ylenia Curci & Nathalie Greenan & Silvia Napolitano, 2024. "Innovating for the good or for the bad. An EU-wide analysis of the impact of technological transformation on job polarisation and unemployment," TEPP Working Paper 2024-02, TEPP.
    15. 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.
    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. repec:hal:spmain:info:hdl:2441/7n49nkmngd8448a5ts5gt5ade0 is not listed on IDEAS
    18. 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.
    19. Terry Gregory & A.M. Salomons & Ulrich Zierahn, 2016. "Racing With or Against the Machine? Evidence from Europe," Working Papers 16-05, Utrecht School of Economics.
    20. 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.
    21. Fossen, Frank M. & McLemore, Trevor & Sorgner, Alina, 2024. "Artificial Intelligence and Entrepreneurship," IZA Discussion Papers 17055, Institute of Labor Economics (IZA).

    More about this item

    Keywords

    Artificial General Intelligence; Automation; Capital accumulation; Tasks in compute space;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • 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
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

    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:cpr:ceprdp:18928. 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://www.cepr.org .

    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.