Your browser doesn't support javascript.
loading
Artificial Intelligence and Liability in Medicine: Balancing Safety and Innovation.
Maliha, George; Gerke, Sara; Cohen, I Glenn; Parikh, Ravi B.
  • Maliha G; Perelman School of Medicine, University of Pennsylvania.
  • Gerke S; Department of Internal Medicine, University of Pennsylvania.
  • Cohen IG; Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics, Harvard Law School, Harvard University.
  • Parikh RB; Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics, Harvard Law School, Harvard University.
Milbank Q ; 99(3): 629-647, 2021 09.
Article en En | MEDLINE | ID: mdl-33822422
ABSTRACT
Policy Points With increasing integration of artificial intelligence and machine learning in medicine, there are concerns that algorithm inaccuracy could lead to patient injury and medical liability. While prior work has focused on medical malpractice, the artificial intelligence ecosystem consists of multiple stakeholders beyond clinicians. Current liability frameworks are inadequate to encourage both safe clinical implementation and disruptive innovation of artificial intelligence. Several policy options could ensure a more balanced liability system, including altering the standard of care, insurance, indemnification, special/no-fault adjudication systems, and regulation. Such liability frameworks could facilitate safe and expedient implementation of artificial intelligence and machine learning in clinical care.
Asunto(s)
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Responsabilidad Legal / Atención a la Salud / Política de Salud Límite: Humans Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Responsabilidad Legal / Atención a la Salud / Política de Salud Límite: Humans Idioma: En Año: 2021 Tipo del documento: Article