IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2501.17894.html

Progress in Artificial Intelligence and its Determinants

Author

Listed:
  • Michael R. Douglas
  • Sergiy Verstyuk

Abstract

We study long-run progress in artificial intelligence in a quantitative way. Many measures, including traditional ones such as patents and publications, machine learning benchmarks, and a new Aggregate State of the Art in ML (or ASOTA) Index we have constructed from these, show exponential growth at roughly constant rates over long periods. Production of patents and publications doubles every ten years, by contrast with the growth of computing resources driven by Moore's Law, roughly a doubling every two years. We argue that the input of AI researchers is also crucial and its contribution can be objectively estimated. Consequently, we give a simple argument that explains the 5:1 relation between these two rates. We then discuss the application of this argument to different output measures and compare our analyses with predictions based on machine learning scaling laws proposed in existing literature. Our quantitative framework facilitates understanding, predicting, and modulating the development of these important technologies.

Suggested Citation

  • Michael R. Douglas & Sergiy Verstyuk, 2025. "Progress in Artificial Intelligence and its Determinants," Papers 2501.17894, arXiv.org.
    • Handle: RePEc:arx:papers:2501.17894
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2501.17894
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Charles I. Jones, 2003. "Growth, capital shares, and a new perspective on production functions," Proceedings, Federal Reserve Bank of San Francisco, issue nov.
    3. Anton Korinek & Donghyun Suh, 2024. "Scenarios for the Transition to AGI," NBER Working Papers 32255, National Bureau of Economic Research, Inc.
    4. David J. Deming, 2022. "Four Facts about Human Capital," Journal of Economic Perspectives, American Economic Association, vol. 36(3), pages 75-102, Summer.
    5. Farmer, J. Doyne & Lafond, François, 2016. "How predictable is technological progress?," Research Policy, Elsevier, vol. 45(3), pages 647-665.
    6. David H. Autor, 2019. "Work of the Past, Work of the Future," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 1-32, May.
    7. Brent Neiman, 2014. "The Global Decline of the Labor Share," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(1), pages 61-103.
    8. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    9. Nicholas Bloom & Charles I. Jones & John Van Reenen & Michael Webb, 2020. "Are Ideas Getting Harder to Find?," American Economic Review, American Economic Association, vol. 110(4), pages 1104-1144, April.
    10. Nordhaus, William D., 2007. "Two Centuries of Productivity Growth in Computing," The Journal of Economic History, Cambridge University Press, vol. 67(1), pages 128-159, March.
    11. repec:oup:qjecon:v:129:y:2013:i:1:p:61-103 is not listed on IDEAS
    12. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    13. H. S. Houthakker, 1955. "The Pareto Distribution and the Cobb-Douglas Production Function in Activity Analysis," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 23(1), pages 27-31.
    14. Charles I. Jones, 2005. "The Shape of Production Functions and the Direction of Technical Change," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(2), pages 517-549.
    15. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    16. William D. Nordhaus, 2021. "Are We Approaching an Economic Singularity? Information Technology and the Future of Economic Growth," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 299-332, January.
    17. Long, John B, Jr & Plosser, Charles I, 1983. "Real Business Cycles," Journal of Political Economy, University of Chicago Press, vol. 91(1), pages 39-69, February.
    18. Matthew Rognlie, 2015. "Deciphering the Fall and Rise in the Net Capital Share: Accumulation or Scarcity?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 46(1 (Spring), pages 1-69.
    19. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
    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. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
    2. Hideki Nakamura & Joseph Zeira, 2024. "Automation and unemployment: help is on the way," Journal of Economic Growth, Springer, vol. 29(2), pages 215-250, June.
    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. Singh, Anuraag & Triulzi, Giorgio & Magee, Christopher L., 2021. "Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description," Research Policy, Elsevier, vol. 50(9).
    5. 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.
    6. Kemnitz, Alexander & Knoblach, Michael, 2020. "Endogenous sigma-augmenting technological change: An R&D-based approach," CEPIE Working Papers 02/20, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    7. Feld, Lars P. & Schmidt, Christoph M. & Schnabel, Isabel & Truger, Achim & Wieland, Volker, 2019. "Den Strukturwandel meistern. Jahresgutachten 2019/20 [Dealing with Structural Change. Annual Report 2019/20]," Annual Economic Reports / Jahresgutachten, German Council of Economic Experts / Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung, volume 127, number 201920.
    8. Zuzanna Helena Zarach & Aleksandra Parteka, 2023. "Productivity effects of trade in natural resources—comparison with mechanisms of technological specialisation," The World Economy, Wiley Blackwell, vol. 46(9), pages 2684-2706, September.
    9. Anuraag Singh & Giorgio Triulzi & Christopher L. Magee, 2020. "Technological improvement rate estimates for all technologies: Use of patent data and an extended domain description," Papers 2004.13919, arXiv.org.
    10. Lu, Chia-Hui, 2021. "The impact of artificial intelligence on economic growth and welfare," Journal of Macroeconomics, Elsevier, vol. 69(C).
    11. Basso, Henrique S. & Jimeno, Juan F., 2021. "From secular stagnation to robocalypse? Implications of demographic and technological changes," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 833-847.
    12. Diemer, Andreas & Regan, Tanner, 2022. "No inventor is an island: Social connectedness and the geography of knowledge flows in the US," Research Policy, Elsevier, vol. 51(2).
    13. David Kunst, 2019. "Deskilling among Manufacturing Production Workers," Tinbergen Institute Discussion Papers 19-050/VI, Tinbergen Institute, revised 30 Dec 2020.
    14. Lee Ohanian & Musa Orak & Shihan Shen, 2023. "Revisiting Capital-Skill Complementarity, Inequality, and Labor Share," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 479-505, December.
    15. Prettner, Klaus & Strulik, Holger, 2020. "Innovation, automation, and inequality: Policy challenges in the race against the machine," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 249-265.
    16. 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.
    17. Gomes, Orlando, 2007. "Externalities in R&D: a route to endogenous fluctuations," MPRA Paper 2850, University Library of Munich, Germany.
    18. Oussama Chemlal & Wafaa Benomar, 2024. "The Technological Impact on Employment in Spain between 2023 and 2035," Forecasting, MDPI, vol. 6(2), pages 1-30, April.
    19. Michael Knoblach & Fabian Stöckl, 2020. "What Determines The Elasticity Of Substitution Between Capital And Labor? A Literature Review," Journal of Economic Surveys, Wiley Blackwell, vol. 34(4), pages 847-875, September.
    20. Casey, Gregory, 2024. "Unemployment and the direction of technical change," European Economic Review, Elsevier, vol. 168(C).

    More about this item

    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:arx:papers:2501.17894. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.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.