White Paper on AI Healthcare Governance

As Artificial Intelligence (AI) integrates deeply into the healthcare sector, a profound industrial transformation is accelerating. While AI healthcare significantly enhances clinical efficiency and diagnostic precision, it also introduces unprecedented complexities. Consequently, constructing a scientific, prudent, and forward-looking governance system has become an urgent task for the current era. This white paper aims to systematically review global AI healthcare governance trends, conduct an in-depth analysis of China’s current governance landscape, and propose a framework and policy recommendations that blend international perspectives with local characteristics.

First, after clarifying the developmental background and the urgency of governance, this report conducts a comparative study of the governance models of developed economies—including the United States, the European Union, the United Kingdom, and Singapore. It extracts their core characteristics, categorized as "Market-Driven," "Rule-Driven," "Value-Oriented," and "Agile Governance." Building on this, the report establishes a comprehensive evaluation index system for governance levels across four dimensions: Governance System, Governance Capability, Governance Effectiveness, and Continuous Improvement.

Second, the report systematically outlines China’s significant achievements in policies, regulations, and regulatory practices driven by top-level strategies. Utilizing the aforementioned evaluation framework, it objectively analyzes deep-seated challenges such as insufficient institutional granularity, an incomplete multi-stakeholder governance mechanism, and the lack of a closed-loop value feedback system. The report then performs a horizontal comparative analysis of the governance status of five major economies to clarify their respective strengths, weaknesses, and evolutionary paths. To address these challenges, the report adopts a risk-based perspective to map out an AI healthcare life-cycle risk profile covering four dimensions: technology, data, law, and ethics. Based on this, it proposes a "Troika" path to build a core regulatory system: Multi-stakeholder Governance to define subjects, Differentiated Regulation to clarify objects, and Full-Process Coverage to provide necessary tools.

Finally, the report puts forward specific policy recommendations and action initiatives across multiple levels—improving top-level design, strengthening technical support, optimizing regulatory sandboxes, and building feedback mechanisms. These aim to provide a decision-making reference for a new paradigm of safe, credible, efficient, and equitable AI healthcare governance, contributing Chinese wisdom and solutions to the global arena.