China IGF

1.Results-oriented: Focus on practical effectiveness, and uphold a result-oriented approach to ensure practical and tangible outcomes. It is recommended to produce meeting summary reports, research findings, or conclusive outputs; and to compile a list of key and challenging issues to clarify where the divergences lie. 2.Case Sharing: Establish a collection of best-practice cases to facilitate knowledge exchange and drive global AI governance from fragmented exploration to collaborative cooperation. 3.Regularized Exchange: Emphasize the continuity of the dialogue by setting fixed agenda items following the initial session, and establish a regular exchange mechanism involving multi-stakeholders. 4.Participation Support: Provision of financial and access support for youth representatives including university students, to ensure inclusive and meaningful youth participation in the Dialogue. 5.Open Participation: Support remote online engagement.

• AI capacity-building
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Interoperability of governance approaches
• Open-source software, open data and open AI models

1.AI Capacity-building: This serves as the cornerstone for achieving equitable global development. The advancement of AI is extremely uneven worldwide. Promoting AI capacity building, including talent development and computing power support, is essential to ensure that all countries, including developing nations, can participate equally and benefit from this technological revolution. 2.Social, economic, ethical, cultural, linguistic, and technical implications of AI: This is the core embodiment of a "people-centered" approach. AI is not only a technical issue, but a profound social matter affecting employment, privacy, cultural diversity, ethical norms, as well as natural environmental protection and energy sustainability. AI can empower carbon emission monitoring, renewable energy scheduling and ecological conservation, while its high computing demand also brings challenges for energy consumption and environmental governance, which should be addressed through holistic governance. 3.Interoperability of governance approaches: This is key to preventing fragmentation of global AI market. Divergent national and regional AI governance frameworks risk creating technical barriers and trade frictions. Prioritizing interoperability aims to build bridges and common benchmarks between governance systems, prevent the formation of exclusive blocs and "small circle" culture, and uphold an open global AI ecosystem. 4.Open-source software, open data and open AI models: These are critical accelerators for inclusive innovation, while open systems must be paired with robust risk prevention. Open-source tools can lower technical barriers foster global collaborative innovation, and enable broader participation from SMEs and researchers. These are the most efficient path to break down technical barriers and achieve inclusive technology, but we must also guard against risks including data security breaches, intellectual property disputes, algorithmic vulnerabilities and malicious code implantation, to balance open innovation and security governance.

1.Inclusiveness and Equity: Bridge the "AI divide" by focusing on vulnerable groups such as the elderly and children, as well as populations in remote areas. Strengthen the equitable dissemination of technology, knowledge, and skills to prevent the "Matthew Effect". 2.Risk and Ethical Governance: Address specific risks such as algorithmic bias, privacy breaches, AI fraud, and "AI slop" (AI-generated information pollution and low-quality content), and advocate for risk tracking mechanisms and collaborative governance strategies. 3.Additional recommendations include: These include exploring how AI can foster the development of new industries, employment opportunities, and professions, as well as leveraging AI to assist in scientific research management. 4.Key missing issues include national digital sovereignty in AI governance, AI application in Internet infrastructure, and AI governance for small and medium-sized Internet entities. These are critical for balanced and inclusive global AI governance.

1.Law and Responsibility: Amid the rapid iteration of AI technology, it is necessary to continuously optimizing and refining legal and liability framework to adapt to emerging governance challenges, while upholding a balanced approach to development and security. 2.Open-source Applications: International adoption of open-source AI large models still faces challenges, requiring efforts to address stakeholders' concerns. 3.Systemic Risks: False information, privacy breaches, employment structure instability, and widening the digital divide pose major challenges. 4.Uncoordinated standards and insufficient capacity widen the AI gap in Asia-Pacific. Developing economies lack technical and talent support. Opportunities lie in AI-driven digital infrastructure upgrading and industrial innovation.

1.The role of AI: In addressing cross-domain systemic challenges posed by AI—including misinformation, privacy breaches, and employment disruptions—no single entity can cope alone. With its non-binding nature and flexibility, "AI Dialogue" enables participation from diverse stakeholders and adapts to rapid technological iterations, offering a more resilient approach to global governance. 2.Key contributions include advancing the establishment of unified international standards and fostering international collaboration. Through direct communication, it builds trust among key stakeholders, thereby promoting cooperation—particularly in alleviating concerns about the international application of open-source AI large models—and facilitating consensus-building within the global community. 3.The Dialogue can act as a multilateral platform to coordinate governance positions, share technical standards, promote South-South cooperation on AI capacity-building, and advance interoperable and inclusive global AI governance.

Building on the UN IGF, ITU AI standards, and the UNESCO Recommendation on the Ethicsof Artificial Intelligence, the Dialogue can provide unique value in inclusive multilateral coordination, integrating technical and policy governance, to avoid fragmentation.

It is recommended to prioritize offline, open discussions, as this format proves superior to presentations only. A hybrid approach combining online and offline formats, such as organizing sub-forums or side events, can be adopted. Open discussions should be emphasized over standalone presentations, and the arrangement of "side events" should be increased.

1.Enhance the participation of developing countries, SMEs, small economies, technical communities, general users, and rural users. Specific measures include providing financial support to those willing to participate (e.g., university students, young scholars) and offering free online attendance opportunities. 2.Expansion of diversified perspectives. It is recommended to provide channels for general users to voice their opinions and feedback, emphasizing that Dialogue should be "people-centered".

Technical workshops, multilingual live sessions, and online consultation portals.

1.The Chinese Government: China has put forward the Global Initiative on AI Governance, which proposes core principles and action directions for global AI governance, upholding multilateralism, people-centered development, and balance between development and security. China has also issued the New Generation Artificial Intelligence Development Plan to guide high-quality AI development, and the Interim Measures for the Management of Generative Artificial Intelligence Services, which establishes a risk-classified, multi-stakeholder governance framework for AI services. China has also carried out AI capacity-building training programs for developing countries under the South-South cooperation framework, to support inclusive global AI development. 2.China Mobile: Shared its initiatives in fostering a transparent and trustworthy environment (e.g., employing AI detection technologies to identify misinformation) and promoting inclusive participation (e.g., AI products for the elderly and the "Smart Village Doctor" system for rural areas). 3.Zhuanzhuan Group: It showcased its practices of leveraging AI-powered quality inspection to facilitate the circulation of second-hand goods, thereby enhancing transparency and user trust.