Practical, epistemic and normative implications of algorithmic bias in healthcare artificial intelligence: a qualitative study of multidisciplinary expert perspectives.

Abstract

Authors

• Yves Saint James Aquino
  Australian Centre for Health Engagement, Evidence and Values, School of Social Sciences, University of Wollongong, Wollongong, Australia.
• Stacy M Carter
  Australian Centre for Health Engagement, Evidence and Values, School of Social Sciences, University of Wollongong, Wollongong, Australia.
• Nehmat Houssami
  Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
• Annette Braunack-Mayer
  Australian Centre for Health Engagement, Evidence and Values, School of Health and Society, Faculty of the Arts, Social Sciences, and Humanities, University of Wollongong, Northfields Ave, Wollongong, NSW, 2522, Australia.
• Khin Than Win
  School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2500, Australia.
• Chris Degeling
  Australian Centre for Health Engagement, Evidence and Values, School of Social Sciences, University of Wollongong, Wollongong, Australia.
• Lei Wang
  Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
• Wendy A Rogers
  School of Psychology, Georgia Institute of Technology, Atlanta, GA, United States of America.

Keywords

External Resources