Between Rivalry and Risks: AI and the Future of U.S.-China Relations

Artificial intelligence is becoming an increasingly important issue in China-U.S. relations. As frontier models and AI agents advance rapidly, emerging risks such as loss of control, cyberattacks, and threats to critical infrastructure are becoming more pronounced. At the same time, competition between China and the United States over technological capabilities, national security, and global rules continues to deepen. Yet shared concerns over AI-related risks do not necessarily translate into cooperation. How will technological competition, export controls, and national security considerations shape China-U.S. dialogue on AI safety? If concrete agreements remain difficult to reach in the near term, what should be the priority? Faced with emerging AI-related security challenges, where can China and the U.S. find practical areas for cooperation? On issues including cyber threats, malicious use by non-state actors, and risks from frontier models, which mechanisms for risk management and crisis communication are most workable? Can Track II dialogue help build consensus for government-to-government engagement while reducing the risks of misperception and unintended escalation? More fundamentally, as AI becomes increasingly embedded in national security and strategic decision-making, does the traditional concept of strategic stability also need to evolve? In this episode of SinoAI Insights, we are joined by LU Chuanying, Professor and Vice Dean of the School of Political Science and International Relations at Tongji University, and JIANG Tianjiao, Associate Professor at the Fudan Development Institute and Research Fellow at the Center for Global AI Innovative Governance. Together, we discussed U.S.-China competition and AI security governance, dialogue mechanisms, risk management, and the evolving challenges to strategic stability in the age of AI. 【Host】 ·XIAO Qian, Deputy Director, Center for International Security and Strategy, Tsinghua University 【Guests】 ·JIANG Tianjiao, Associate Professor, Development Institute of Fudan University; Research Fellow, Center for Global AI Innovative Governance ·LU Chuanying, Professor, Vice Dean, School of Political Science and International Relations, Tongji University 【Shownotes】 02:40 Will AI Become a Key Issue at the Summit? 06:56 Calls to Slow Frontier AI Development: Implications and Prospects 13:51 What Should Be the Primary Objective of China-U.S. Intergovernmental AI Dialogue? 18:46 New Developments in Track II Dialogue 21:17 A Priority for Cooperation: Establishing an AI Crisis Communication Mechanism 23:30 Can China and the U.S. Share Information on AI-Enabled Cyber Threats? 25:44 How Can China and the U.S. Cooperate to Prevent the Malicious Use of AI by Non-State Actors? 31:37 Strategic Stability in the AI Age 34:30 Understanding a Constructive China-U.S. Relationship of Strategic Stability 36:13 Prospects for China-U.S. Intergovernmental AI Dialogue and the Leaders’ Summit 【Team】 Executive Producer: XIAO Qian Producers: WANG Yexu, LIU Yuan Content Assistant: LIU Zhi Podcast Editor: ZHENG Ruirui Graphics Designer: ZHANG Yue

As generative AI enters a new phase of abundant foundation‑model supply, access to general‑purpose models and compute resources has become widely accessible for enterprises and government bodies. Real‑world experience nonetheless demonstrates that model access does not automatically translate into tangible productivity gains. Identical foundation models can yield vastly different outcomes when deployed by different organizations. The key to success lies in an organization’s “AI absorptive capacity”. What exactly constitutes “AI absorptive capacity”? What institutional, talent and data gaps need to be addressed for general-purpose models to deliver real-world business value? Does sovereign AI boil down to domestically-trained foundation models? How can developing countries break free from the pitfall of “prioritizing model procurement over systemic capacity-building”? Endowed with rich real-world industrial scenarios, how can China translate its scenario advantages into sustainable AI competitiveness? In this episode of SinoAI Insights, we are joined by Dr. Ning Ning, Vice President of International Business & AI Consulting at 01.AI. Centered on the core thesis that “access is not absorption”, we explore how AI can align with an organization’s real-world business contexts, refine supporting rules and authority and governance mechanisms, build business systems with swappable underlying foundation models architectures, and foster human-in-the-loop capabilities. The conversation also focuses on talent development and organizational transformation, mapping out actionable pathways for enterprise-level, industrial scale and sovereign-AI implementation. 【Host】 ·XIAO Qian, Deputy Director, Center for International Security and Strategy, Tsinghua University 【Guest】 ·Ning Ning, Vice President, International Business & AI Consulting, 01.AI 【Shownotes】 02:50 The Shifting AI Divide: From Model Access to Absorptive Capacity 10:00 Dissecting Five Core Pillars of AI Absorptive Capacity 21:25 Governance Framework and Human‑in‑the‑Loop Learning Mechanism 24:00 Moving Beyond Foundation Models Toward Institutional Intelligence 26:28 Enterprise AI Transformation: Top‑Level Sponsorship, Organizational Memory and Durable Competitive Advantages 42:15 TrueNorth Decision Hub: Real‑World AI Practice for Executives 45:08 Sovereign AI and Capacity Building for Developing Countries 50:42 Opportunities and Constraints for China’s AI Deployment and the Core of Next‑Round AI Competition 52:54 Fresh Perspectives on International AI Cooperation 【Team】 Executive Producer: XIAO Qian Producers: LIU Yuan, WANG Yexu Content Assistant: ZHONG Junwen Podcast Editor: GAO Meilin Graphics Designer: GAO Meilin

Artificial intelligence is entering multiple stages of life sciences research. From protein-structure prediction, genomic analysis, and literature synthesis to molecular and sequence design, experimental planning, and automated laboratory execution, AI is evolving from a collection of point solutions into a new kind of research infrastructure connecting the entire “hypothesis–design–experiment” cycle. This convergence could accelerate drug discovery, biomanufacturing, and the transition to a more sustainable economy. But it also raises a series of new challenges: when AI models can translate biological knowledge into actionable designs and experimental pathways, are existing biosecurity safeguards still sufficient? How should we move beyond text-level refusal tests to measure the real capability uplift AI provides to users? And where should biosecurity safeguards be deployed at the model layer, tool application layer, DNA synthesis stage, or laboratory operation stage? In this episode of SinoAI Insights, we are joined by BAO Yuhan, Lecturer at the School of International Organizations at Beijing Foreign Studies University and Coordinator of the iGEM Human Practices Committee, and XU Jia, Researcher at the Shanghai Artificial Intelligence Laboratory. We explore the rapidly evolving intersection of AI and biology through the lens of China’s technological development and governance practices. 【Host】 ·XIAO Qian, Deputy Director, Center for International Security and Strategy, Tsinghua University 【Guests】 ·BAO Yuhan, Lecturer, School of International Organizations, Beijing Foreign Studies University; Coordinator, iGEM Human Practices Committee ·XU Jia, Researcher, Shanghai Artificial Intelligence Laboratory 【Shownotes】 02:51 From Task-Specific Tools to an Integrated Research Pipeline: How Is AI Transforming the Life Sciences? 05:49 The Public Value of AI × Bio: Biomanufacturing, Medicine, and the Transition to Sustainability 12:41 The State of AI × Bio Development in China 19:16 Does the Integration of AI into the Life Sciences Create New Governance Risks? 22:41 Frontier AI Risk Management and the “Yellow Line–Red Line” Dual-Threshold Framework 25:28 Beyond Model Refusal: What Intern-BioBreaker Reveals About AI Safety Evaluation 30:24 Can Existing Governance Systems Keep Pace with Technological Development? 38:45 From Models to Laboratories: Building End-to-End Safety across the AI × Bio Chain 46:05 The Evolution of China’s AI × Bio Governance Approaches and Policy Tools 55:45 Building Practical International Cooperation on AI × Bio 【Team】 Executive Producer: XIAO Qian Producers: WANG Yexu, LIU Yuan Podcast Editor: ZHONG Junwen Content Assistant: GAO Meilin Graphics Designer: DU Wanhong

In July 2026, Moonshot AI released Kimi K3, an open-weight model that has become the world’s largest open-weight AI model to date. Kimi K3 has once again drawn global attention to the capabilities of China’s frontier AI models, while bringing the debate over open versus closed AI models into sharper focus. Previously, many in the industry believed that the future of advanced AI would belong almost entirely to closed models. However, in recent years, an increasing number of leading AI companies around the world have begun exploring open-weight approaches. What innovations and value do open models bring? To what extent can they be considered global public goods? What unique advantages does China’s open AI ecosystem possess? As models become increasingly powerful and develop agentic capabilities, what new security risks and governance challenges will emerge? And how can we establish more responsible evaluation mechanisms and governance frameworks? In this episode of SinoAI Insights, we invite two leading experts to examine these questions through the lens of Kimi K3. Together, they explore the driving forces behind the emerging shift toward open AI, examine the latest developments in AI safety evaluation, and discuss new governance frameworks for a future shaped by rapidly advancing frontier AI capabilities. 【Host】 ·XIAO Qian, Deputy Director, Center for International Security and Strategy, Tsinghua University 【Guests】 ·Tianhao CHEN, Tenured Associate Professor and Ph.D. Supervisor, School of Public Policy and Management and School of Law; Director of the Center for Law and Governance and Assistant Director of the Center for Science & Technology Development and Governance (THUSTDG), Tsinghua University ·Xiaojian (Luke) LI, Founder & CEO of Fangcun Leap; Ph.D. Candidate at the College of Artificial Intelligence, Tsinghua University 【Shownotes】 03:05 Starting from Kimi K3: Why Leading AI Companies Are Turning Toward Open Models? 05:17 The Value of Open Models: From Engineering Efficiency to Accelerated Innovation 06:45 Can Open Models Be Global Public Goods? 08:06 How China Became a Major Contributor to the Global Open-Source AI Ecosystem? 10:34 Governance Challenges Emerging from Increasingly Powerful Open Models 14:43 What 60 System Cards Reveal: Changing Trends in AI Safety Evaluation 19:45 The Value of Third-Party Evaluation and the Worrying Turn Toward Closed Benchmarks 22:17 Evaluating AI with AI: Automated Benchmark Repair and System Card Generation 24:41 Why Agentic Runtime Safety Is Becoming Increasingly Important? 26:56 Introducing Agent Safety Governance Framework 1.0 30:34 The Four Threat Layers and Seven Governance Pillars for AI Agents 34:47 How Abstract Governance Principles Can Be Translated into Actionable Implementation Mechanisms? 37:32 Global AI Safety Priorities for the Next Three Years 【Team】 Executive Producer: XIAO Qian Producers: WANG Yexu, LIU Yuan Podcast Editor: CAI Leyao Content Assistant: ZHANG Shuoning Graphics Designer: XU Ruijia

As global AI governance enters a new institutional-building phase, the 2026 World Artificial Intelligence Conference (WAIC) has delivered four landmark outcomes to foster a fair and rational global AI governance system. First, it advances global AI governance from conceptual initiatives to tangible implementation, focusing on building institutional cooperation platforms, expanding international collaboration channels, and translating governance concepts into practical measures. Second, it places AI safety at the heart of its agenda, coordinates development and security, balances innovation and regulation, and upholds human-centric, ethical principles to ensure AI development remains secure, reliable, and controllable. Third, the conference formally launches the World AI Cooperation Organization (WAICO), strengthening the representation and voice of Global South countries in global AI governance. Fourth, China will offer 5,000 specialized AI training slots for developing countries to advance inclusive and equitable global AI development. Is China shifting from a participant in global AI rule-setting to a builder of global AI governance mechanisms? What gaps in existing global frameworks will WAICO address? What global value does AI capacity building for the Global South hold? Amid U.S.-China strategic competition, are there avenues for bilateral engagement with the new organization? In this episode of SinoAI Insights, we take the major outcomes of WAIC 2026 as our starting point to interpret China’s AI governance approach, analyze WAICO’s global positioning, and explore pathways for global AI safety regulation and viable models of multilateral AI cooperation amid U.S.-China strategic competition. 【Host】 ·XIAO Qian, Deputy Director, Center for International Security and Strategy, Tsinghua University 【Guests】 ·YAO Xu, Secretary-General, Center for Global AI Innovative Governance; Associate Professor, Fudan Development Institute, Fudan University ·George CHEN, Distinguished Visiting Professor, Schwarzman College, Tsinghua University; Senior Fellow, Centre for Civil Society and Governance, The University of Hong Kong; Former Managing Director, Public Policy, Greater China at Meta 【Shownotes】 03:12 Core Shifts and Three Defining Keywords of WAIC 2026 06:40 WAIC: Evolving from a Tech Expo to a Multilateral Platform for Global AI Governance 10:15 Why AI Capacity Building for Developing Countries Matters Globally 19:30 The Genesis of WAICO and Its Distinction from Existing International AI Governance Regimes 24:15 Perspectives of Global Tech and Industrial Sectors, as well as Regional Governance Bodies on WAICO 28:50 The Internal Logic Behind China’s Elevated AI Safety Agenda and International Interpretations 33:10 U.S. Perceptions of WAICO: A Geopolitical Instrument or a Multilateral Public Good 38:45 Prospects for Practical U.S.-China Cooperation Under the WAICO Framework 43:20 How WAIC and WAICO Reshape China’s Role in Global AI Governance 47:10 Key Global AI Governance Issues to Watch in the Coming Year 【Team】 Executive Producer: XIAO Qian Producers: LIU Yuan, WANG Yexu Podcast Editor: XU Ruijia Content Assistant: ZHONG Junwen Graphics Designer: CAI Leyao