Of Regulating Healthcare AI and Robots

53 Pages Posted: 7 Feb 2019 Last revised: 12 Jun 2019

See all articles by Nicolas Terry

Nicolas Terry

Indiana University Robert H. McKinney School of Law

Date Written: January 23, 2019


This article argues that advances in healthcare artificial intelligence (AI) will seriously challenge the robustness and appropriateness of our current healthcare regulatory models. Initially healthcare AI will join other technologies such as big data and mobile health apps in highlighting the current deficiencies in our regulatory models (particularly data protection). In the near future they will challenge regulatory models that use binary formulations such as “safe” or “unsafe.” The regulation of AI will require some fresh thinking. Underpinned by broadly embraced ethical and moral values future AI regulation must be holistic, universal, contextually aware, and responsive to what will be major shifts in the man-machine relationship. The article seeks to provide context for these discussions by suggesting a typology for the healthcare AI technologies of our present and near future, a typology based in part on their substitutive effects. That is followed by a critical look at the existing healthcare regulatory structure as it would be applied to AI. The core of the article then then suggests the imperatives for a new regulatory structure, one that relies less on the senses that we know the “practice of medicine” or “device” when we see it, and more on generally accepted normative principles. Those imperatives include quality, safety, cost-effectiveness, improved data protection, protections against discrimination and in support of health equity.

Suggested Citation

Terry, Nicolas P., Of Regulating Healthcare AI and Robots (January 23, 2019). Available at SSRN: https://ssrn.com/abstract=3321379 or http://dx.doi.org/10.2139/ssrn.3321379

Nicolas P. Terry (Contact Author)

Indiana University Robert H. McKinney School of Law ( email )

530 W. New York St
Indianapolis, IN 46202
United States

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