Regulation of Health-Related Artificial Intelligence in Medical Devices: The Canadian Story
Regulation of Health-Related Artificial Intelligence in Medical Devices: The Canadian Story
Artificial Intelligence (AI) may transform Canadian healthcare. The hope is that AI will enable more accurate and efficient care, thereby solving many access, quality, and safety problems. Despite this tantalizing prospect, there are risks of unsafe AI harming patients, algorithmic bias, and threats to privacy. This work begins analysis of whether applicable laws are up to the task of ensuring Canadians can benefit from effective health-related AI while minimizing AI-related risks. It focuses on Health Canada’s regulation of medical devices, a ‘first line of defence’ that decides which devices are safe, effective, and thus permitted for trade in Canadian markets. After highlighting the regulatory challenge, we provide the first detailed explanation of Canadian medical device regulations and how they apply to AI-enabled devices. We then discuss a still-developing “alternative pathway” for licencing devices with AI and the regulatory gaps left open. We conclude with recommendations that a recent emphasis on post-market surveillance should not be at the expense of robust pre-market review and that safety and efficacy review embrace bias- and privacy-related risks. Further, while post-market surveillance holds potential for ensuring the safety of adaptive machine-learning medical devices over time, much will depend on regulatory capacity and competency and investments therein.
Artificial Intelligence, Medical Devices, Health Law, Canadian Law
635-682
Da Silva, Michael
05ad649f-8409-4012-8edc-88709b1a3182
Flood, Colleen
a3853c9e-6bd3-400e-b908-140559d871a0
Herder, Matthew
ff7ef826-4f56-43d5-97dc-9e36608b1dfc
21 March 2023
Da Silva, Michael
05ad649f-8409-4012-8edc-88709b1a3182
Flood, Colleen
a3853c9e-6bd3-400e-b908-140559d871a0
Herder, Matthew
ff7ef826-4f56-43d5-97dc-9e36608b1dfc
Da Silva, Michael, Flood, Colleen and Herder, Matthew
(2023)
Regulation of Health-Related Artificial Intelligence in Medical Devices: The Canadian Story.
University of British Columbia Law Review, 55 (3), , [2].
Abstract
Artificial Intelligence (AI) may transform Canadian healthcare. The hope is that AI will enable more accurate and efficient care, thereby solving many access, quality, and safety problems. Despite this tantalizing prospect, there are risks of unsafe AI harming patients, algorithmic bias, and threats to privacy. This work begins analysis of whether applicable laws are up to the task of ensuring Canadians can benefit from effective health-related AI while minimizing AI-related risks. It focuses on Health Canada’s regulation of medical devices, a ‘first line of defence’ that decides which devices are safe, effective, and thus permitted for trade in Canadian markets. After highlighting the regulatory challenge, we provide the first detailed explanation of Canadian medical device regulations and how they apply to AI-enabled devices. We then discuss a still-developing “alternative pathway” for licencing devices with AI and the regulatory gaps left open. We conclude with recommendations that a recent emphasis on post-market surveillance should not be at the expense of robust pre-market review and that safety and efficacy review embrace bias- and privacy-related risks. Further, while post-market surveillance holds potential for ensuring the safety of adaptive machine-learning medical devices over time, much will depend on regulatory capacity and competency and investments therein.
Text
SSRN-id4027076
- Author's Original
Restricted to Repository staff only
Request a copy
Text
UBCLR Da Silva et al AM
- Accepted Manuscript
Restricted to Repository staff only
Request a copy
Text
Regulation of Health-Related Artificial Intelligence in Medical D
- Version of Record
Available under License Other.
More information
Accepted/In Press date: 27 January 2022
Published date: 21 March 2023
Keywords:
Artificial Intelligence, Medical Devices, Health Law, Canadian Law
Identifiers
Local EPrints ID: 457267
URI: http://eprints.soton.ac.uk/id/eprint/457267
PURE UUID: ac71568d-d7ad-4061-8dcd-08559eddf7d5
Catalogue record
Date deposited: 30 May 2022 16:45
Last modified: 17 Mar 2024 04:12
Export record
Contributors
Author:
Michael Da Silva
Author:
Colleen Flood
Author:
Matthew Herder
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics