Diachronic and synchronic variation in the performance of adaptive machine learning systems: the ethical challenges.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date:

Abstract

OBJECTIVES: Machine learning (ML) has the potential to facilitate "continual learning" in medicine, in which an ML system continues to evolve in response to exposure to new data over time, even after being deployed in a clinical setting. In this article, we provide a tutorial on the range of ethical issues raised by the use of such "adaptive" ML systems in medicine that have, thus far, been neglected in the literature.

Authors

  • Joshua Hatherley
    School of Philosophical, Historical, and International Studies, Monash University, Clayton, Victoria, Australia.
  • Robert Sparrow
    Philosophy, Monash University, Clayton, Victoria, Australia robert.sparrow@monash.edu.