Trust and medical AI: the challenges we face and the expertise needed to overcome them. (19th December 2020)

• Record Type: Journal Article
• Authors: Quinn, Thomas P; Senadeera, Manisha; Jacobs, Stephan; Coghlan, Simon; Le, Vuong
• Is Part Of: Journal of the American Medical Informatics Association. Volume 28:Number 4(2021)
• Page Start: 890
• Page End: 894
• Publication Date: 2020-12-19
• Subjects: AI -- machine learning -- challenges -- ethics; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocaa268
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: Artificial intelligence (AI) is increasingly of tremendous interest in the medical field. How-ever, failures of medical AI could have serious consequences for both clinical outcomes and the patient experience. These consequences could erode public trust in AI, which could in turn undermine trust in our healthcare institutions. This article makes 2 contributions. First, it describes the major conceptual, technical, and humanistic challenges in medical AI. Second, it proposes a solution that hinges on the education and accreditation of new expert groups who specialize in the development, verification, and operation of medical AI technologies. These groups will be required to maintain trust in our healthcare institutions.