China Releases White Paper on International AI Application and Governance Cooperation, Emphasizing People-Centered Development

China has released a white paper detailing its principles and approaches to international cooperation in AI application and governance. The document, unveiled at the 2026 AI+ Conference in Beijing, advocates for a people-centered approach to AI development, stressing the importance of AI for positive societal good. Key tenets include openness, win-win cooperation, ensuring AI is secure and controllable, promoting inclusiveness, and fostering solidarity. The white paper also highlights the establishment of a shared technological foundation that integrates models, computing power, and corpus data. It traces the evolution of China's international AI application from single-technology exports to comprehensive industry solutions and the sharing of open-source models and governance experience. This development is significant for several reasons. For practitioners, it provides a clear articulation of China's stance on AI ethics and regulation, which will undoubtedly influence how AI is developed, deployed, and governed globally. As China is a major player in AI research and development, its policy frameworks have far-reaching implications for international standards and collaborations. Companies and researchers engaging with Chinese entities or operating in markets influenced by Chinese policies will need to align their AI governance strategies accordingly. The emphasis on a "people-centered" approach and "secure and controllable" AI suggests a focus on mitigating risks and ensuring beneficial outcomes, which resonates with broader global discussions on responsible AI. This white paper fits into a broader, well-established trend of nations and supranational bodies developing their own AI governance frameworks. The European Union's AI Act, for instance, is nearing its implementation phase in early 2027, focusing on risk-based regulation. Similarly, the United States has been advocating for a lighter touch, emphasizing innovation and reserving new regulations for genuinely novel risks. These differing approaches create a complex global landscape for AI governance, where interoperability and mutual understanding of principles become paramount. China's white paper adds another critical layer to this evolving international dialogue, underscoring the geopolitical dimensions of AI development. In practice, this means that organizations involved in AI should actively monitor and understand these diverse national and regional AI governance strategies. For those looking to collaborate with Chinese partners or expand into Chinese markets, a thorough understanding of the white paper's principles will be essential for compliance and successful engagement. It also implies a need for robust internal AI governance frameworks that are adaptable enough to navigate varying international requirements. Practitioners should watch for how these principles translate into concrete policies and technical standards, particularly concerning data sharing, model transparency, and accountability mechanisms. The call for a shared technological foundation also suggests potential opportunities for collaborative development, but also raises questions about data sovereignty and technological dependencies.