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Artificial Intelligence in Medicine: Issues When Determining Negligence.
- Source :
- Journal of Law & Medicine; 2023, Vol. 30 Issue 3, p593-615, 23p
- Publication Year :
- 2023
-
Abstract
- The introduction of novel medical technology, such as artificial intelligence (AI), into traditional clinical practice presents legal liability challenges that need to be squarely addressed by litigants and courts when something goes wrong. Some of the most promising applications for the use of AI in medicine will lead to vexed liability questions. As AI in health care is in its relative infancy, there is a paucity of case law globally upon which to draw. This article analyses medical malpractice where AI is involved, what problems arise when applying the tort of negligence -- such as establishing the essential elements of breach of duty of care and causation -- and how can these can be addressed. Product liability under Australian Consumer Law is beyond the scope of this article. In order to address this question, the article: (1) identifies the general problems that black box AI causes in the health care sector; (2) identifies the problems that will arise in establishing breach and causation due to the "black box" nature of AI, with reference to the Civil Liability Act 2002 (NSW) and common law through two hypothetical examples; and (3) considers selected legal solutions to the problems caused by "black box" AI. [ABSTRACT FROM AUTHOR]
- Subjects :
- NEGLIGENCE
MALPRACTICE
MEDICAL errors
INTERPROFESSIONAL relations
AUTONOMY (Psychology)
HEALTH insurance reimbursement
ARTIFICIAL intelligence
LEGAL liability
DRUG therapy
RESPONSIBILITY
PNEUMOTHORAX
DECISION making
DIAGNOSTIC errors
COMPUTER-aided diagnosis
CAUSALITY (Physics)
MEDICINE
MEDICAL screening
ADVERSE health care events
ACCURACY
PROFESSIONAL competence
MEDICAL triage
Subjects
Details
- Language :
- English
- ISSN :
- 1320159X
- Volume :
- 30
- Issue :
- 3
- Database :
- Supplemental Index
- Journal :
- Journal of Law & Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 176142562