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Combining Human Expertise with Artificial Intelligence: Experimental Evidence from Radiology

Author

Listed:
  • Nikhil Agarwal
  • Alex Moehring
  • Pranav Rajpurkar
  • Tobias Salz

Abstract

Full automation using Artificial Intelligence (AI) predictions may not be optimal if humans have information not available to the AI (contextual information). We study human-AI collaboration using an information experiment with professional radiologists. Results show that providing (i) AI predictions does not improve performance on average, whereas (ii) contextual information does. Radiologists do not realize the gains from AI assistance because of errors in belief updating – they underweight AI predictions and treat their own information and AI predictions as statistically independent. Unless these mistakes can be corrected, the optimal human-AI collaboration design delegates cases either to humans or to AI, but rarely to AI assisted humans.

Suggested Citation

  • Nikhil Agarwal & Alex Moehring & Pranav Rajpurkar & Tobias Salz, 2023. "Combining Human Expertise with Artificial Intelligence: Experimental Evidence from Radiology," NBER Working Papers 31422, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:31422
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    More about this item

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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