Combining Human Expertise with Artificial Intelligence: Experimental Evidence from Radiology

Nikhil Agarwal, Alex Moehring, Pranav Rajpurkar and Tobias Salz

No 31422, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Full automation using Artificial Intelligence (AI) predictions may not be optimal if humans can access contextual information. We study human-AI collaboration using an information experiment with professional radiologists. Results show that providing (i) AI predictions does not always improve performance, 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.

JEL-codes: C50 C90 D47 D83 (search for similar items in EconPapers)
Date: 2023-07
New Economics Papers: this item is included in nep-ain, nep-big, nep-cmp and nep-exp
Note: EH IO PR
References: Add references at CitEc
Citations: View citations in EconPapers (16)

Downloads: (external link)
http://www.nber.org/papers/w31422.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:31422

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w31422

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().