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Promising Topics for U.S.-China Dialogues on AI Risks and Governance

Saad Siddiqui, Lujain Ibrahim, Kristy Loke, Stephen Clare, Marianne Lu, Aris Richardson, Conor McGlynn, Jeffrey Ding

TL;DR

The paper investigates how the United States and China can cooperate on AI risk governance despite strategic competition. It systematically analyzes over 40 primary US and Chinese AI policy and corporate documents using an adapted AGORA taxonomy to identify convergences in risk perception and governance approaches. The authors find strong and moderate overlap on issues like transparency, reliability, multi-stakeholder convening, and safety-oriented AI roles, with privacy showing weaker alignment, and they translate these findings into concrete bilateral dialogue recommendations. The work provides a framework for harmonizing international AI governance notions and informing diplomacy, standards development, and Track II efforts to promote global responsible AI development. It also acknowledges the rapidly evolving policy landscape and calls for future case studies and expert interviews to validate and extend the findings.

Abstract

Cooperation between the United States and China, the world's leading artificial intelligence (AI) powers, is crucial for effective global AI governance and responsible AI development. Although geopolitical tensions have emphasized areas of conflict, in this work, we identify potential common ground for productive dialogue by conducting a systematic analysis of more than 40 primary AI policy and corporate governance documents from both nations. Specifically, using an adapted version of the AI Governance and Regulatory Archive (AGORA) - a comprehensive repository of global AI governance documents - we analyze these materials in their original languages to identify areas of convergence in (1) sociotechnical risk perception and (2) governance approaches. We find strong and moderate overlap in several areas such as on concerns about algorithmic transparency, system reliability, agreement on the importance of inclusive multi-stakeholder engagement, and AI's role in enhancing safety. These findings suggest that despite strategic competition, there exist concrete opportunities for bilateral U.S.-China cooperation in the development of responsible AI. Thus, we present recommendations for furthering diplomatic dialogues that can facilitate such cooperation. Our analysis contributes to understanding how different international governance frameworks might be harmonized to promote global responsible AI development.

Promising Topics for U.S.-China Dialogues on AI Risks and Governance

TL;DR

The paper investigates how the United States and China can cooperate on AI risk governance despite strategic competition. It systematically analyzes over 40 primary US and Chinese AI policy and corporate documents using an adapted AGORA taxonomy to identify convergences in risk perception and governance approaches. The authors find strong and moderate overlap on issues like transparency, reliability, multi-stakeholder convening, and safety-oriented AI roles, with privacy showing weaker alignment, and they translate these findings into concrete bilateral dialogue recommendations. The work provides a framework for harmonizing international AI governance notions and informing diplomacy, standards development, and Track II efforts to promote global responsible AI development. It also acknowledges the rapidly evolving policy landscape and calls for future case studies and expert interviews to validate and extend the findings.

Abstract

Cooperation between the United States and China, the world's leading artificial intelligence (AI) powers, is crucial for effective global AI governance and responsible AI development. Although geopolitical tensions have emphasized areas of conflict, in this work, we identify potential common ground for productive dialogue by conducting a systematic analysis of more than 40 primary AI policy and corporate governance documents from both nations. Specifically, using an adapted version of the AI Governance and Regulatory Archive (AGORA) - a comprehensive repository of global AI governance documents - we analyze these materials in their original languages to identify areas of convergence in (1) sociotechnical risk perception and (2) governance approaches. We find strong and moderate overlap in several areas such as on concerns about algorithmic transparency, system reliability, agreement on the importance of inclusive multi-stakeholder engagement, and AI's role in enhancing safety. These findings suggest that despite strategic competition, there exist concrete opportunities for bilateral U.S.-China cooperation in the development of responsible AI. Thus, we present recommendations for furthering diplomatic dialogues that can facilitate such cooperation. Our analysis contributes to understanding how different international governance frameworks might be harmonized to promote global responsible AI development.
Paper Structure (38 sections, 7 tables)