Adaptive Governance for Health AI: A Policy and Regulatory Control Framework to Balance Innovation, Human Values, and Societal Well-Being

Rapid advancements of artificial intelligence (AI) call for a robust governance approach that keeps pace with technological progression and addresses the needs of society, institutions, and innovators. Emerging AI methods have demonstrated various successes, as well as concerning error patterns ranging from discrimination to hallucinations. Nonetheless, there is substantial momentum in the direction of broad and rapid deployment in critical use cases, including strategic decision support tools for healthcare, raising significant ethical concerns for responsible adoption. We propose an adaptive governance framework that views governance as a dynamic, human-centred control policy that explicitly integrates theories of change about technology acceptance, adoption, and rejection as part of a feedback loop to ensure ethical, secure, and effective implementation of the health AI (HAI) environment. The goal is to inform how policies and regulations can be optimised to balance responsible deployment for the greater good of society without stifling technological innovation.

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Publication Details

Journal
ACM Journal on Responsible Computing
Published
2026-03-20
DOI
https://doi.org/10.1145/3793925
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Adaptive Governance for Health AI: A Policy and Regulatory Control Framework to Balance Innovation, Human Values, and Societal Well-Being

Natalie Leesakul, Richard Hyde, Matt Kammer-Kerwick, Yang Lu et al.
ACM Journal on Responsible Computing
Artificial Intelligence in Healthcare and Education
article

Adaptive Governance for Health AI: A Policy and Regulatory Control Framework to Balance Innovation, Human Values, and Societal Well-Being

Natalie Leesakul, Richard Hyde, Matt Kammer-Kerwick, Yang Lu, Pepita Barnard
article en

Abstract

Rapid advancements of artificial intelligence (AI) call for a robust governance approach that keeps pace with technological progression and addresses the needs of society, institutions, and innovators. Emerging AI methods have demonstrated various successes, as well as concerning error patterns ranging from discrimination to hallucinations. Nonetheless, there is substantial momentum in the direction of broad and rapid deployment in critical use cases, including strategic decision support tools for healthcare, raising significant ethical concerns for responsible adoption. We propose an adaptive governance framework that views governance as a dynamic, human-centred control policy that explicitly integrates theories of change about technology acceptance, adoption, and rejection as part of a feedback loop to ensure ethical, secure, and effective implementation of the health AI (HAI) environment. The goal is to inform how policies and regulations can be optimised to balance responsible deployment for the greater good of society without stifling technological innovation.

ACM Journal on Responsible Computing
University of Nottingham (GB), Loughborough University (GB), The University of Texas at Austin (US)
Openalex Percentile: Top 15%
Artificial Intelligence in Healthcare and Education
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