Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Global AI Governance in Healthcare: A Cross-Jurisdictional Regulatory Analysis

Attrayee Chakraborty, Mandar Karhade

TL;DR

This paper examines the global regulatory landscape for AI in healthcare by analyzing 25 laws, guidance, and regulations from 14 jurisdictions and mapping them to the WHO principles for ethical AI use in healthcare. It identifies common themes—documentation, risk management, data quality, intended use and validation, and privacy—and notes broad alignment with WHO guidance, while healthcare-specific rules remain unevenly developed and largely embedded within SaMD frameworks. The authors also explore GenAI governance, contrasting generic approaches with China and Singapore’s GenAI-specific policies, and argue for a three-pronged path toward international harmonization, risk-based regulation, and stakeholder collaboration. The study highlights the dynamic, rapidly evolving nature of AI regulation and aims to inform policymakers and industry on how to balance innovation with safety and ethics in a global context. Overall, the work provides a global, WHO-aligned perspective to guide future harmonization efforts and policy development in AI-based healthcare.

Abstract

Artificial Intelligence (AI) is being adopted across the world and promises a new revolution in healthcare. While AI-enabled medical devices in North America dominate 42.3% of the global market, the use of AI-enabled medical devices in other countries is still a story waiting to be unfolded. We aim to delve deeper into global regulatory approaches towards AI use in healthcare, with a focus on how common themes are emerging globally. We compare these themes to the World Health Organization's (WHO) regulatory considerations and principles on ethical use of AI for healthcare applications. Our work seeks to take a global perspective on AI policy by analyzing 14 legal jurisdictions including countries representative of various regions in the world (North America, South America, South East Asia, Middle East, Africa, Australia, and the Asia-Pacific). Our eventual goal is to foster a global conversation on the ethical use of AI in healthcare and the regulations that will guide it. We propose solutions to promote international harmonization of AI regulations and examine the requirements for regulating generative AI, using China and Singapore as examples of countries with well-developed policies in this area.

Global AI Governance in Healthcare: A Cross-Jurisdictional Regulatory Analysis

TL;DR

This paper examines the global regulatory landscape for AI in healthcare by analyzing 25 laws, guidance, and regulations from 14 jurisdictions and mapping them to the WHO principles for ethical AI use in healthcare. It identifies common themes—documentation, risk management, data quality, intended use and validation, and privacy—and notes broad alignment with WHO guidance, while healthcare-specific rules remain unevenly developed and largely embedded within SaMD frameworks. The authors also explore GenAI governance, contrasting generic approaches with China and Singapore’s GenAI-specific policies, and argue for a three-pronged path toward international harmonization, risk-based regulation, and stakeholder collaboration. The study highlights the dynamic, rapidly evolving nature of AI regulation and aims to inform policymakers and industry on how to balance innovation with safety and ethics in a global context. Overall, the work provides a global, WHO-aligned perspective to guide future harmonization efforts and policy development in AI-based healthcare.

Abstract

Artificial Intelligence (AI) is being adopted across the world and promises a new revolution in healthcare. While AI-enabled medical devices in North America dominate 42.3% of the global market, the use of AI-enabled medical devices in other countries is still a story waiting to be unfolded. We aim to delve deeper into global regulatory approaches towards AI use in healthcare, with a focus on how common themes are emerging globally. We compare these themes to the World Health Organization's (WHO) regulatory considerations and principles on ethical use of AI for healthcare applications. Our work seeks to take a global perspective on AI policy by analyzing 14 legal jurisdictions including countries representative of various regions in the world (North America, South America, South East Asia, Middle East, Africa, Australia, and the Asia-Pacific). Our eventual goal is to foster a global conversation on the ethical use of AI in healthcare and the regulations that will guide it. We propose solutions to promote international harmonization of AI regulations and examine the requirements for regulating generative AI, using China and Singapore as examples of countries with well-developed policies in this area.
Paper Structure (20 sections, 8 figures)

This paper contains 20 sections, 8 figures.

Table of Contents

  1. Introduction
  2. Related Work
  3. Material and Methods
  4. Global Regulatory Landscape of AI
  5. Definitions
  6. Common themes in global regulations
  7. Documentation and Transparency
  8. Risk Management
  9. Data Quality
  10. Intended Use, Analytical and Clinical Validation
  11. Privacy and Data Protection
  12. Regulations on AI in Healthcare
  13. Generative AI: The New Frontier
  14. GenAI Regulation: Why Do We Need To Regulate It Differently?
  15. Current Legislation on GenAI
  16. ...and 5 more sections

Figures (8)

  • Figure 1: Map depicting areas of legal jurisprudence covered in the scope of this paper (indicated in green)
  • Figure 2: Table representing definitions of AI across nations
  • Figure 3: Key regulatory considerations as outlined by the WHO for ethical use of AI in healthcare
  • Figure 4: Visual representation of the current AI regulatory landscape in healthcare across 14 jurisdictions
  • Figure 5: Depiction of laws illustrating WHO’s core principles on ethical AI use in healthcare
  • ...and 3 more figures