How Are Canadians Regulating Artificial Intelligence for Healthcare? A Brief Analysis of the Current Legal Directions, Challenges and Deficiencies.

Sian Hsiang-Te Tsuei
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Abstract

Effective regulations can ensure a minimum level of performance from artificial intelligence (AI) systems. Canadian regulators face two major categories of challenges. First, the AI-specific challenges stem from the unpredictable developments, use, evidence, and acceptable ethical trade-offs around AI systems. These uncertainties can drive the need for flexible definitions of risk, evidentiary threshold, change plan, and post hoc determination of ethical trade-off. These regulatory flexibilities could neglect impactful AI systems, allow regulatory capture, and undermine public oversight. Second, the jurisdictional challenges obfuscate the scope of products, regulatory boundaries, and division of power across regulations. Clarifying regulatory definitions, the responsibilities of professional bodies, and the need for provincial and territorial legislations may help. However, the lack of reason to believe that regulators have clear motivation and capacity to meaningfully protect patient health is worrisome.

加拿大人如何监管医疗保健领域的人工智能?浅析当前的法律方向、挑战与不足。
有效的法规可以确保人工智能(AI)系统的最低性能水平。加拿大监管机构面临两大挑战。首先,人工智能特有的挑战源于人工智能系统不可预测的发展、使用、证据和可接受的道德权衡。这些不确定性可以推动对风险、证据阈值、变更计划和事后道德权衡的灵活定义的需求。这些监管灵活性可能会忽视有影响力的人工智能系统,允许监管捕获,并破坏公众监督。其次,管辖权的挑战模糊了产品的范围、监管边界和跨法规的权力划分。澄清监管定义、专业机构的责任以及省和地区立法的必要性可能会有所帮助。然而,缺乏理由相信监管机构有明确的动机和能力来有意地保护患者的健康,这令人担忧。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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