IDEAS home Printed from https://ideas.repec.org/h/nbr/nberch/15299.html
   My bibliography  Save this book chapter

Artificial Intelligence in Research and Development

In: The Economics of Transformative AI

Author

Listed:
  • Benjamin F. Jones

Abstract

How much can AI accelerate progress in different research fields? This paper shows that three features—the share of research tasks AI performs, the productivity of AI at those tasks, and the strength of bottlenecks—are key determinants of AI’s implications in any area, from cancer therapeutics to software design. The model maps changes in AI capabilities to research outcomes, quantifies the “marginal returns to intelligence,” and shows how AI can shift returns to R&D investment. Concepts like superintelligence, Powerful AI, and Transformative AI are further engaged and disciplined. Finally, the framework sets a measurement agenda linking AI benchmarks to field-specific opportunities for accelerating progress.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Benjamin F. Jones, 2025. "Artificial Intelligence in Research and Development," NBER Chapters, in: The Economics of Transformative AI, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberch:15299
    Note: PR
    as

    Download full text from publisher

    File URL: http://www.nber.org/chapters/c15299.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    2. Benjamin F. Jones, 2009. "The Burden of Knowledge and the "Death of the Renaissance Man": Is Innovation Getting Harder?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(1), pages 283-317.
    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.
    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. Balland, Pierre-Alexandre & Broekel, Tom & Diodato, Dario & Giuliani, Elisa & Hausmann, Ricardo & O'Clery, Neave & Rigby, David, 2022. "Reprint of The new paradigm of economic complexity," Research Policy, Elsevier, vol. 51(8).
    2. Marialuisa Divella & Alessia Lo Turco & Alessandro Sterlacchini, 2023. "Local labour tasks and patenting in US commuting zones," Journal of Economic Geography, Oxford University Press, vol. 23(5), pages 1097-1119.
    3. Koehler, Maximilian & Sauermann, Henry, 2024. "Algorithmic management in scientific research," Research Policy, Elsevier, vol. 53(4).
    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.
    5. Philippe Aghion & Benjamin F. Jones & Charles I. Jones, 2018. "Artificial Intelligence and Economic Growth," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 237-282, National Bureau of Economic Research, Inc.
    6. David J Deming & Kadeem Noray, 2020. "Earnings Dynamics, Changing Job Skills, and STEM Careers," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(4), pages 1965-2005.
    7. Titan Alon, 2018. "Earning More by Doing Less: Human Capital Specialization and the College Wage Premium," 2018 Meeting Papers 497, Society for Economic Dynamics.
    8. 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).
    9. Balland, Pierre-Alexandre & Broekel, Tom & Diodato, Dario & Giuliani, Elisa & Hausmann, Ricardo & O'Clery, Neave & Rigby, David, 2022. "The new paradigm of economic complexity," Research Policy, Elsevier, vol. 51(3).
    10. Philipp Ehrl & Leonardo Monasterio, 2021. "Spatial skill concentration agglomeration economies," Journal of Regional Science, Wiley Blackwell, vol. 61(1), pages 140-161, January.
    11. Samantha A. Sharpe & Cristina M. Martinez-Fernandez, 2021. "The Implications of Green Employment: Making a Just Transition in ASEAN," Sustainability, MDPI, vol. 13(13), pages 1-19, July.
    12. Tommaso AGASISTI & Geraint JOHNES & Marco PACCAGNELLA, 2021. "Tasks, occupations and wages in OECD countries," International Labour Review, International Labour Organization, vol. 160(1), pages 85-112, March.
    13. Katrin Huber & Geske Rolvering, 2023. "Public child care and mothers’ career trajectories," Working Papers 228, Bavarian Graduate Program in Economics (BGPE).
    14. Loebbing, Jonas, 2018. "An Elementary Theory of Endogenous Technical Change and Wage Inequality," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181603, Verein für Socialpolitik / German Economic Association.
    15. Patrick Mellacher, 2021. "Growth, Inequality and Declining Business Dynamism in a Unified Schumpeter Mark I + II Model," Papers 2111.09407, arXiv.org, revised Nov 2023.
    16. Nicholas Bloom & Tarek Alexander Hassan & Aakash Kalyani & Josh Lerner & Ahmed Tahoun, 2021. "The diffusion of disruptive technologies," CEP Discussion Papers dp1798, Centre for Economic Performance, LSE.
    17. Rabensteiner, Thomas & Guschanski, Alexander, 2022. "Autonomy and wage divergence: evidence from European survey data," Greenwich Papers in Political Economy 37925, University of Greenwich, Greenwich Political Economy Research Centre.
    18. 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.
    19. Nunes, Ashley, 2016. "Increased productivity efforts yield few rewards in the knowledge economy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 338-347.
    20. Aleksandra Parteka & Joanna Wolszczak-Derlacz, 2020. "Wage response to global production links: evidence for workers from 28 European countries (2005–2014)," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 156(4), pages 769-801, November.

    More about this item

    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

    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:nberch:15299. 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.