How should artificial intelligence be used in Australian health care? Recommendations from a citizens’ jury
Publication Name
Medical Journal of Australia
Abstract
Objective: To support a diverse sample of Australians to make recommendations about the use of artificial intelligence (AI) technology in health care. Study design: Citizens’ jury, deliberating the question: “Under which circumstances, if any, should artificial intelligence be used in Australian health systems to detect or diagnose disease?”. Setting, participants: Thirty Australian adults recruited by Sortition Foundation using random invitation and stratified selection to reflect population proportions by gender, age, ancestry, highest level of education, and residential location (state/territory; urban, regional, rural). The jury process took 18 days (16 March – 2 April 2023): fifteen days online and three days face-to-face in Sydney, where the jurors, both in small groups and together, were informed about and discussed the question, and developed recommendations with reasons. Jurors received extensive information: a printed handbook, online documents, and recorded presentations by four expert speakers. Jurors asked questions and received answers from the experts during the online period of the process, and during the first day of the face-to-face meeting. Main outcome measures: Jury recommendations, with reasons. Results: The jurors recommended an overarching, independently governed charter and framework for health care AI. The other nine recommendation categories concerned balancing benefits and harms; fairness and bias; patients’ rights and choices; clinical governance and training; technical governance and standards; data governance and use; open source software; AI evaluation and assessment; and education and communication. Conclusions: The deliberative process supported a nationally representative sample of citizens to construct recommendations about how AI in health care should be developed, used, and governed. Recommendations derived using such methods could guide clinicians, policy makers, AI researchers and developers, and health service users to develop approaches that ensure trustworthy and responsible use of this technology.
Open Access Status
This publication may be available as open access
Funding Number
1181960
Funding Sponsor
National Health and Medical Research Council