| 凌胜利,董笑宇.美国人工智能领域联盟管理方式缘何不同[J].国际安全研究,2025,(5):3-26 |
| 美国人工智能领域联盟管理方式缘何不同 |
| Why the United States Adopts Different Approaches to Alliance Management in the Field of Artificial Intelligence |
| 修订日期：2025-06-13 |
| DOI：10.14093/j.cnki.cn10-1132/d.2025.05.001 |
| 中文关键词: 人工智能 联盟管理 技术安全 中美安全关系 |
| 英文关键词: artificial intelligence, alliance management, technological security, China-U.S. security relations |
| 基金项目: |
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| 中文摘要: |
| 随着人工智能时代的来临，大国都将人工智能视为国家实力的重要基础，由此也引发人工智能博弈的加剧。为争夺人工智能领域的霸权，美国既需要依靠联盟体系来获取在人工智能技术、规则等方面的优势，也需要加强联盟管理，协调联盟内部各方利益，谋求聚合人工智能优势。然而，美国在不同人工智能议题领域却采取了不尽相同的联盟管理方式。既有研究主要探讨了人工智能对联盟关系的影响、美国与盟国之间的人工智能合作、人工智能领域的大国竞争等，但对于美国在人工智能领域的联盟管理机制分析还有待加强。本文基于技术依赖和利益分歧两个变量，分析美国在人工智能领域的联盟管理机制。美国根据其与盟国人工智能技术依赖和利益分歧程度的不同，分别采取权力强制、利益交换、制度约束和权威引导四种不同的联盟管理方式。美国在半导体、无人机、人工智能基础设施等议题领域的联盟管理案例，基本验证了本文的理论假设。展望未来，人工智能将持续影响美国联盟管理和联盟体系，对于大国博弈也会产生复杂且深远的影响，中国对此需要加强研判与应对。 |
| 英文摘要: |
| With the advent of the artificial intelligence (AI) era, major countries increasingly regard AI as a fundamental source of national strength, leading to intensified strategic competition in this domain. In its pursuit of hegemony in AI, the United States not only leverages its alliance system to gain an advantage in technology and rule-making, but also strengthens its alliance management to coordinate internal interests and aggregate AI resources. However, the U.S. adopts varying approaches to alliance management for different AI issues. Existing research has primarily focused on the impact of AI on alliance relations, U.S. cooperation with its allies, and major-country competition in the AI field. However, analysis of the mechanisms behind U.S. alliance management in AI remains insufficient. This paper, based on two key variables—technological dependence and interest divergence—analyzes the mechanisms behind U.S. alliance management in the AI field. Depending on the degree of technological reliance and the extent of conflicting interests between the U.S. and its allies, the United States employs four distinct management approaches: coercive power, interest-based exchange, institutional constraints, and authoritative guidance. Case studies of U.S. alliance management in areas such as semiconductors, drones, and AI infrastructure largely support the theoretical assumptions of this research. Looking ahead, AI will continue to shape U.S. alliance management and its alliance system, exerting complex and far-reaching impacts on major-country competition. China, therefore, needs to strengthen its strategic assessment and preparedness in this regard. |
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