Professor Robert Sparrow1, Mr Josh Hatherley1
1Monash University
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 even after being deployed in a clinical setting. In this paper, we draw attention to a range of ethical issues raised by the use of such ‘adaptive’ ML systems in medicine that have been neglected in the literature. Discussions of adaptive ML systems to date have over-looked the distinction between two sorts of variance that such systems may exhibit — diachronic evolution (change over time) and synchronic variation (difference between cotemporaneous instantiations of the algorithm at different sites) — and under-estimated the significance of the latter. Both diachronic and synchronic variation will complicate the hermeneutic task of clinicians in interpreting the outputs of ML systems and pose significant challenges to the process of securing informed consent to treatment. Equity issues may occur where synchronic variation is permitted, as the quality of care provided by the ‘same’ system may vary significantly across patients or between hospitals. However, the decision as to whether to allow synchronic variation involves complex trade-offs between accuracy and generalisability, as well as a number of other values, including justice and non-maleficence. In some contexts, preventing synchronic variation from emerging may only be possible at the expense of the wellbeing of, and quality of care available to, particular patients or classes of patients. These ethical issues require sustained attention if we are to realise the benefits of continuous learning in medicine.
Biography:
Rob Sparrow is a Professor in the Philosophy Program, and an Associate Investigator in the Australian Research Council Centre of Excellence for Automated Decision Making and Society, at Monash University, where he works on ethical issues raised by new technologies.
Joshua Hatherley is a PhD candidate in the Department of Philosophy at Monash University, where he is completing a thesis on the ethical issues associated with the use of AI in medicine.