TY - JOUR
T1 - FROM 'AI TO LAW' IN HEALTHCARE
T2 - THE PROLIFERATION OF GLOBAL GUIDELINES IN A VOID OF LEGAL UNCERTAINTY
AU - Solaiman, Barry
N1 - Publisher Copyright:
© 2023, William S. Hein & Co., Inc. All rights reserved.
PY - 2023/8/24
Y1 - 2023/8/24
N2 - Artificial intelligence (AI) in healthcare raises significant legal and ethical concerns. Al has been deployed rapidly in healthcare systems despite a lack of legal oversight, leaving policymakers and lawmakers scrambling to catch up. This article develops a four-stage framework for multidisciplinary audiences to understand more clearly the path that has emerged from 'Al to law' using healthcare as a case study. First, Al is introduced into the healthcare system, posing unique legal challenges surrounding algorithmic autonomy, explainability and data biases. Second, legal research interprets current regulations and mainly tort law to determine whether the law can be adapted to these unique challenges, but the law can only be adapted to a point which will then require new legislation. Third, from the absence of legal oversight, policies and guidelines are created as a stopgap measure from governments and bodies such as the World Health Organization (WHO), the Food and Drug Administration (FDA), and the National Health Service (NHS). The policies and guidelines form part of a growing body of research that considers what new laws should be created-research that informs high-level governmental and intergovernmental consultations on developing such new laws. Fourth, following consultations, new laws are devised to address the unique challenges posed by Al, such as the European Union's Artificial Intelligence Act (AIA). While this process is slow, multifaceted, and highly complex, it is argued that it is necessary owing to the unique challenge posed by Al technology.
AB - Artificial intelligence (AI) in healthcare raises significant legal and ethical concerns. Al has been deployed rapidly in healthcare systems despite a lack of legal oversight, leaving policymakers and lawmakers scrambling to catch up. This article develops a four-stage framework for multidisciplinary audiences to understand more clearly the path that has emerged from 'Al to law' using healthcare as a case study. First, Al is introduced into the healthcare system, posing unique legal challenges surrounding algorithmic autonomy, explainability and data biases. Second, legal research interprets current regulations and mainly tort law to determine whether the law can be adapted to these unique challenges, but the law can only be adapted to a point which will then require new legislation. Third, from the absence of legal oversight, policies and guidelines are created as a stopgap measure from governments and bodies such as the World Health Organization (WHO), the Food and Drug Administration (FDA), and the National Health Service (NHS). The policies and guidelines form part of a growing body of research that considers what new laws should be created-research that informs high-level governmental and intergovernmental consultations on developing such new laws. Fourth, following consultations, new laws are devised to address the unique challenges posed by Al, such as the European Union's Artificial Intelligence Act (AIA). While this process is slow, multifaceted, and highly complex, it is argued that it is necessary owing to the unique challenge posed by Al technology.
KW - AIA
KW - Al Act
KW - Artificial Intelligence
KW - Artificial Intelligence Act
KW - Guidelines
KW - Healthcare
KW - Medicine
KW - Soft Law
KW - Technology
UR - https://www.scopus.com/pages/publications/85167416165
M3 - Article
AN - SCOPUS:85167416165
SN - 0723-1393
VL - 42
SP - 391
EP - 406
JO - Medicine and Law
JF - Medicine and Law
IS - 2
ER -