Trading off accuracy and explainability in AI decision-making: findings from 2 citizens' juries.

Sabine N van der VeerLisa RisteSudeh Cheraghi-SohiDenham L PhippsMary P TullyKyle BozentkoSarah AtwoodAlex HubbardCarl WiperMalcolm OswaldNiels Peek

Published in: Journal of the American Medical Informatics Association : JAMIA (2021)

Citizens may value explainability of AI systems in healthcare less than in non-healthcare domains and less than often assumed by professionals, especially when weighed against system accuracy. The public should therefore be actively consulted when developing policy on AI explainability.

Keyphrases

healthcare
artificial intelligence
decision making
machine learning
mental health
deep learning
public health
emergency department
health information
drug induced
electronic health record