Impact of artificial intelligence on pathologists' decisions: an experiment

Julien Meyer, April Khademi, Bernard Têtu, Wencui Han, Pria Nippak, David Remisch

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: The accuracy of artificial intelligence (AI) in medicine and in pathology in particular has made major progress but little is known on how much these algorithms will influence pathologists' decisions in practice. The objective of this paper is to determine the reliance of pathologists on AI and to investigate whether providing information on AI impacts this reliance. Materials and Methods: The experiment using an online survey design. Under 3 conditions, 116 pathologists and pathology students were tasked with assessing the Gleason grade for a series of 12 prostate biopsies: (1) without AI recommendations, (2) with AI recommendations, and (3) with AI recommendations accompanied by information about the algorithm itself, specifically algorithm accuracy rate and algorithm decision-making process. Results: Participant responses were significantly more accurate with the AI decision aids than without (92% vs 87%, odds ratio 13.30, P <. 01). Unexpectedly, the provision of information on the algorithm made no significant difference compared to AI without information. The reliance on AI correlated with general beliefs on AI's usefulness but not with particular assessments of the AI tool offered. Decisions were made faster when AI was provided. Discussion: These results suggest that pathologists are willing to rely on AI regardless of accuracy or explanations. Generalization beyond the specific tasks and explanations provided will require further studies. Conclusion: This study suggests that the factors that influence the reliance on AI differ in practice from beliefs expressed by clinicians in surveys. Implementation of AI in prospective settings should take individual behaviors into account.

Original languageEnglish (US)
Pages (from-to)1688-1695
Number of pages8
JournalJournal of the American Medical Informatics Association
Volume29
Issue number10
DOIs
StatePublished - Oct 1 2022
Externally publishedYes

Keywords

  • artificial intelligence
  • pathology
  • reliance

ASJC Scopus subject areas

  • Health Informatics

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