ARTIFICIAL INTELLIGENCE IN HEALTHCARE AND ETHICAL FRAMEWORKS: A COMPARATIVE STUDY OF THE UNITED STATES AND CHINA
Résumé (anglais)
Achieving SDG 9 (Industry, Innovation and Infrastructure) requires building resilient infrastructure, promoting inclusive and sustainable industrialization, and fostering innovation. Target 9.5 aims to enhance scientific research and upgrade the technological capabilities of industrial sectors in all countries, particularly developing countries, including by encouraging innovation and substantially increasing the number of research and development workers per one million people and public and private research and development spending. Target 9.B supports domestic technology development, research and innovation in developing countries. Artificial intelligence (AI) is transforming healthcare globally, with applications spanning medical imaging analysis, clinical decision support, drug discovery, predictive analytics, robotic surgery, and personalized medicine. However, the rapid integration of AI into healthcare systems has raised critical ethical concerns including algorithmic bias and discrimination, data privacy and security, informed consent, transparency and explainability, clinical accountability and liability, equitable access, and patient safety. The ethical governance of medical AI is not uniform across jurisdictions; different countries have developed divergent frameworks shaped by political systems, legal traditions, cultural values, industrial policies, and public trust. This study conducts a comparative analysis of artificial intelligence in healthcare and ethical frameworks in the United States and China, the two leading global powers in AI research, development, and deployment, with contrasting governance models, regulatory philosophies, and value priorities. The United States, a high-income country with a market-driven economy and a decentralized regulatory system, has adopted an innovation-favorable approach to medical AI governance. The FDA has approved over 1,250 AI-enabled medical devices as of 2025, with more than 75 percent in radiology. The US regulatory framework is risk-based, utilizing pre-market review, post-market surveillance, and pre-determined change control plans for iterative algorithm updates. The US approach prioritizes innovation and market-driven flexibility but faces regulatory fragmentation and accountability gaps. China, an upper-middle-income country with a state-led economy and centralized regulatory system, has rapidly advanced medical AI as a national strategic priority. The NMPA has approved over 110 deep learning-based Class III medical device software products. China's regulatory framework is centralized under the NMPA, with a comprehensive guidance system for AI medical devices and ethical guidelines for brain-computer interface research and science and technology ethics governance. China's approach prioritizes safety and state-led strategic development but faces transparency deficits and potential innovation constraints. Using a qualitative comparative case study methodology, the study analyzes secondary data from government reports, peer-reviewed literature, and regulatory policy documents over the period 2015 to 2026. The study finds that the US and China represent two divergent governance paradigms for medical AI: the US prioritizes innovation and market-driven flexibility, while China prioritizes safety and state-led strategic development. Both countries face common challenges including algorithmic bias, data privacy, clinical integration, and public trust. The study concludes that effective AI governance requires hybrid models combining safety as a non-negotiable baseline, innovation incentives, transparency mandates, and accountability mechanisms. Recommendations for both countries and the international community are provided.
Mots-clés: Artificial intelligence; healthcare; ethics; United States; China; SDG 9; medical devices; algorithmic bias; data privacy; regulatory framework
Résumé (français)
Atteindre l'ODD 9 (Industrie, Innovation et Infrastructure) nécessite de promouvoir l'innovation et d'augmenter les dépenses de recherche et développement. L'intelligence artificielle (IA) transforme les soins de santé à l'échelle mondiale, mais soulève des préoccupations éthiques : biais algorithmiques, confidentialité des données, transparence, responsabilité clinique et équité d'accès. Cette étude analyse l'IA dans les soins de santé et les cadres éthiques aux États-Unis et en Chine. Les États-Unis ont approuvé plus de 1 250 dispositifs médicaux basés sur l'IA (FDA). L'approche américaine privilégie l'innovation et la flexibilité axée sur le marché. La Chine a approuvé plus de 110 produits logiciels de dispositifs médicaux basés sur l'apprentissage profond (NMPA). L'approche chinoise privilégie la sécurité et le développement stratégique dirigé par l'État. L'étude conclut que la gouvernance de l'IA nécessite des modèles hybrides alliant sécurité, incitations à l'innovation, transparence et mécanismes de responsabilité. Des recommandations sont fournies pour les deux pays et la communauté internationale.
Mots-clés: intelligence artificielle, soins de santé, éthique, États-Unis, Chine, ODD 9, dispositifs médicaux, biais algorithmiques, confidentialité des données