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Superhuman science: How artificial intelligence may impact innovation

Author

Listed:
  • Ajay Agrawal

    (University of Toronto
    National Bureau of Economic Research (NBER))

  • John McHale

    (J.E. Caines School of Business and Economics, University of Galway)

  • Alexander Oettl

    (National Bureau of Economic Research (NBER)
    Scheller College of Business, Georgia Institute of Technology)

Abstract

New product innovation in fields like drug discovery and material science can be characterized as combinatorial search over a vast range of possibilities. Modeling innovation as a costly multi-stage search process, we explore how improvements in artificial intelligence (AI) could affect the productivity of the discovery pipeline in allowing improved prioritization of innovations that flow through that pipeline. We show how AI-aided prediction can increase the expected value of innovation and can increase or decrease the demand for downstream testing, depending on the type of innovation, and examine how AI can reduce costs associated with well-defined bottlenecks in the discovery pipeline.

Suggested Citation

  • Ajay Agrawal & John McHale & Alexander Oettl, 2023. "Superhuman science: How artificial intelligence may impact innovation," Journal of Evolutionary Economics, Springer, vol. 33(5), pages 1473-1517, November.
    • Handle: RePEc:spr:joevec:v:33:y:2023:i:5:d:10.1007_s00191-023-00845-3
    DOI: 10.1007/s00191-023-00845-3
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    More about this item

    Keywords

    Artificial intelligence; Innovation; R&D prioritization;
    All these keywords.

    JEL classification:

    • D20 - Microeconomics - - Production and Organizations - - - General

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