Article(id=1315693751830434643, tenantId=1146029695717560320, journalId=1308397381743640680, issueId=1315693724970103290, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1751817600000, receivedDateStr=2025-07-07, revisedDate=1762444800000, revisedDateStr=2025-11-07, acceptedDate=null, acceptedDateStr=null, onlineDate=1791615434844, onlineDateStr=2026-10-10, pubDate=1791993600000, pubDateStr=2026-10-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791615434844, onlineIssueDateStr=2026-10-10, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791615434844, creator=13701087609, updateTime=1791615434844, updator=13701087609, issue=Issue{id=1315693724970103290, tenantId=1146029695717560320, journalId=1308397381743640680, year='2026', volume='44', issue='10', pageStart='2017', pageEnd='2240', issueExtLink='null', onlineDate='null', pubDate='1791993600000', pubDateStr='2026-10-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1791615428440, creator='13701087609', updateTime=1791615454688, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1315693835188031766, tenantId=1146029695717560320, journalId=1308397381743640680, issueId=1315693724970103290, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1315693835188031767, tenantId=1146029695717560320, journalId=1308397381743640680, issueId=1315693724970103290, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2081, endPage=2098, ext={EN=ArticleExt(id=1315693752149201748, articleId=1315693751830434643, tenantId=1146029695717560320, journalId=1308397381743640680, language=EN, title=The techno-nationalist attributes of U.S. artificial intelligence policy and responses, columnId=1309226307540574209, journalTitle=Studies in Science of Science, columnName=Theories and Methods, runingTitle=null, highlight=null, articleAbstract=

Amid growing global technological competition, understanding the reasoning behind U.S. artificial intelligence (AI) policy is crucial for evaluating its strategic impact and potential risks for China. Building on the theoretical framework of technological nationalism, this study introduces a four-dimensional analytical model covering national technological strategic positioning, the establishment of technological sovereignty, the connection between technology and national security, and the development of global technological discourse power.

Using the Dynamic Topic Model (DTM), we analyze 306 U.S. AI policy documents issued from 2015 to 2025 to identify key thematic trends and map the evolving policy emphasis. Complemented by keyword co-occurrence analysis, the study examines the interdependencies among policy themes to reveal how technological nationalism has become structurally embedded in the United States’ AI policymaking process and how this shapes its external technological stance toward China. The findings demonstrate that U.S. AI policy is characterized by a strong technological nationalist orientation. Domestically, the United States tightly links AI development with national security goals, creating a legitimacy narrative around “national security threats” to justify restrictive technological measures targeting China. Internationally, it promotes governance frameworks infused with American values and fosters alliances with like-minded partners, thereby institutionalizing a bloc-based regime of technological containment.

In response, the study proposes three strategic pathways for China—foundational breakthroughs, standard elevation, and partnership restructuring—aimed at mitigating external technological vulnerabilities and enhancing its strategic autonomy and competitiveness within the global AI landscape. These findings contribute to a deeper understanding of the geopolitical dimensions of AI governance and offer actionable insights for national technology strategy in an era of renewed techno-political rivalry.

, authors=Ting WEN, Nan JIANG, Yin-xin JIANG, authorsList=Ting WEN, Nan JIANG, Yin-xin JIANG, authorCompany=null, correspAuthors=Yin-xin JIANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1315693755198460782, articleId=1315693751830434643, tenantId=1146029695717560320, journalId=1308397381743640680, language=CN, title=美国人工智能政策的技术民族主义属性与应对, columnId=1309226307683180547, journalTitle=科学学研究, columnName=理论与方法, runingTitle=null, highlight=null, articleAbstract=

全球科技竞争加剧背景下,深入剖析美国人工智能政策演化逻辑,可为中国化解外部技术风险提供重要启示。基于技术民族主义理论,搭建“国家技术战略定位、技术主权构建、技术与国家安全耦合、全球技术话语权塑造”四维分析框架。利用动态主题模型(dynamic topic model)识别2015-2025年306份美国人工智能政策文本的主题,动态追踪政策主题强度演化,并基于以上四维分析框架解读模型结果,再结合文本共现方法,对模型结果进行主题词共现分析,研究不同政策主题间的协同逻辑,揭示技术民族主义在美国人工智能政策中的体现及对华人工智能发展的影响。研究发现,美国人工智能政策具备鲜明的技术民族主义属性。为获得人工智能全球领导地位,美国对内将人工智能技术与国家安全议题深度绑定,以“国家安全威胁”为核心逻辑,构建对华技术管制的合法性叙事基础。对外输出嵌入美式价值观的技术规则,并组建认可美式价值观的技术联盟实现对华技术遏制阵营化。对此,提出“底层突围、标准跃升、伙伴重塑”三条路径,应对外部技术风险,提升中国人工智能领域的竞争主动权。

, authors=温婷, 姜南, 姜银鑫, authorsList=温婷, 姜南, 姜银鑫, authorCompany=null, correspAuthors=姜银鑫, authorNote=

温婷(1996-),女,博士研究生。

姜南(1982-),女,教授,博士。

, correspAuthorsNote=
姜银鑫(1977-),男,高级工程师,博士研究生,E-mail:。
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温婷(1996-),女,博士研究生。

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温婷(1996-),女,博士研究生。

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资料来源:作者自制。

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U.S. AI policy topic terms

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序号 主题 关键词
维度一:国家技术战略定位
1 长期研发投资 Fundamental|Research|Funding|Innovation|Discovery|Sustained|Breakthrough|Grant|Exploration|Academic
基础性的|研究|资金\资助|创新|发现|持续的|突破||拨款\研究资助|探索|学术的
2 基础设施与资源 Infrastructure|Resource|Access|Open|Platform|Shared|Computing|Data|Availability|Interoperability
基础设施|资源|访问\获取|开放的|平台|共享的|计算|数据|可用性|互操作性
3 全球领导地位 Leadership|Global|International|Standard|Influence|Dominance|Diplomacy|Alliance|Competitiveness|Initiative
领导力|全球的|国际的|标准|影响力|主导地位|外交|联盟|竞争力|倡议\行动计划
维度二:技术主权构建
1 关键技术领域 AI|Quantum|Semiconductor|Biotechnology|Manufacture|Robotic|Cybersecurity|Material|Energy|Computing
人工智能|量子技术|半导体|生物技术|制造业/制造技术|机器人技术|网络安全|材料科学|能源技术|计算技术
2 人才与劳动力培养 Workforce|Training|Education|Skill|Talent|Development|Recruitment|Retention|Apprenticeship|Upskilling
劳动力|培训|教育|技能|人才|发展|招聘|保留|学徒制度|技能提升
3 本土创新生态系统 Ecosystem|Cluster|Collaboration|Startup|Grant|Talent|Supply|Chain|Regional|Hub
生态系统|创新集群|合作|初创企业|研究资助|人才|供应|链条|区域性|枢纽
维度三:技术与国家安全耦合
1 军事与国家安全 Mission|Threat|Sanction|Sensitive|Safeguard|Citizen|Predict|Respond|System|Cyber
任务|威胁|制裁|灵敏的|保护|公民|预测|响应|系统|网络
2 威慑性叙事 Security|Unfair|Risk|Compliance|Competitor|Restriction|Military|Manipulator|Deterrence|Resilience
安全|不平等的|风险|合规|竞争对手|限制|军事|操纵|威慑|韧性
3 对抗性防御技术 Adversarial|Defense|Technology|Secure|Resilient|Operation|Hacking|Bias|Mitigate|Validation
对抗性的|防御|技术|安全的|具备韧性|运作|黑客攻击|偏差|缓解|验证
维度四:全球技术话语权塑造
1 国际标准制定 Standard|Leadership|Consensus|Legal|Development|Influence|Participation|Organization|Framework|Certification
标准|领导力|共识|法律的|制定|影响力|参与|组织机构|框架|认证
2 可信AI与伦理 Valid|Reliable|Safe|Secure|Accountable|Transparent|Explainable|Fair|Privacy|Ethical
有效的|可靠的|安全的|保障性的\受保护的|可问责的|透明的|可解释的|公平的|隐私|符合伦理的
3 技术联盟构建 Alliance|Partnership|Collaboration|Network|Industry|Academia|Stakeholder|Global|Leadership|Innovation
联盟|伙伴关系|协作|网络|产业界|学术界|利益相关者|全球的|领导力|创新
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美国AI政策主题词表

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序号 主题 关键词
维度一:国家技术战略定位
1 长期研发投资 Fundamental|Research|Funding|Innovation|Discovery|Sustained|Breakthrough|Grant|Exploration|Academic
基础性的|研究|资金\资助|创新|发现|持续的|突破||拨款\研究资助|探索|学术的
2 基础设施与资源 Infrastructure|Resource|Access|Open|Platform|Shared|Computing|Data|Availability|Interoperability
基础设施|资源|访问\获取|开放的|平台|共享的|计算|数据|可用性|互操作性
3 全球领导地位 Leadership|Global|International|Standard|Influence|Dominance|Diplomacy|Alliance|Competitiveness|Initiative
领导力|全球的|国际的|标准|影响力|主导地位|外交|联盟|竞争力|倡议\行动计划
维度二:技术主权构建
1 关键技术领域 AI|Quantum|Semiconductor|Biotechnology|Manufacture|Robotic|Cybersecurity|Material|Energy|Computing
人工智能|量子技术|半导体|生物技术|制造业/制造技术|机器人技术|网络安全|材料科学|能源技术|计算技术
2 人才与劳动力培养 Workforce|Training|Education|Skill|Talent|Development|Recruitment|Retention|Apprenticeship|Upskilling
劳动力|培训|教育|技能|人才|发展|招聘|保留|学徒制度|技能提升
3 本土创新生态系统 Ecosystem|Cluster|Collaboration|Startup|Grant|Talent|Supply|Chain|Regional|Hub
生态系统|创新集群|合作|初创企业|研究资助|人才|供应|链条|区域性|枢纽
维度三:技术与国家安全耦合
1 军事与国家安全 Mission|Threat|Sanction|Sensitive|Safeguard|Citizen|Predict|Respond|System|Cyber
任务|威胁|制裁|灵敏的|保护|公民|预测|响应|系统|网络
2 威慑性叙事 Security|Unfair|Risk|Compliance|Competitor|Restriction|Military|Manipulator|Deterrence|Resilience
安全|不平等的|风险|合规|竞争对手|限制|军事|操纵|威慑|韧性
3 对抗性防御技术 Adversarial|Defense|Technology|Secure|Resilient|Operation|Hacking|Bias|Mitigate|Validation
对抗性的|防御|技术|安全的|具备韧性|运作|黑客攻击|偏差|缓解|验证
维度四:全球技术话语权塑造
1 国际标准制定 Standard|Leadership|Consensus|Legal|Development|Influence|Participation|Organization|Framework|Certification
标准|领导力|共识|法律的|制定|影响力|参与|组织机构|框架|认证
2 可信AI与伦理 Valid|Reliable|Safe|Secure|Accountable|Transparent|Explainable|Fair|Privacy|Ethical
有效的|可靠的|安全的|保障性的\受保护的|可问责的|透明的|可解释的|公平的|隐私|符合伦理的
3 技术联盟构建 Alliance|Partnership|Collaboration|Network|Industry|Academia|Stakeholder|Global|Leadership|Innovation
联盟|伙伴关系|协作|网络|产业界|学术界|利益相关者|全球的|领导力|创新
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美国人工智能政策的技术民族主义属性与应对
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温婷 , 姜南 , 姜银鑫
科学学研究 | 理论与方法 2026,44(10): 2081-2098
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科学学研究 |理论与方法 2026 , 44 (10) : 2081 -2098
美国人工智能政策的技术民族主义属性与应对
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温婷, 姜南, 姜银鑫
作者信息
  • 同济大学上海国际知识产权学院, 上海 200092
通讯作者:
姜银鑫(1977-),男,高级工程师,博士研究生,E-mail:。
作者简介:

温婷(1996-),女,博士研究生。

姜南(1982-),女,教授,博士。

The techno-nationalist attributes of U.S. artificial intelligence policy and responses
Ting WEN, Nan JIANG, Yin-xin JIANG
Affiliations
  • Shanghai International College of Intellectual Property, Tongji University, Shanghai 200092, China
出版时间: 2026-10-15
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全球科技竞争加剧背景下,深入剖析美国人工智能政策演化逻辑,可为中国化解外部技术风险提供重要启示。基于技术民族主义理论,搭建“国家技术战略定位、技术主权构建、技术与国家安全耦合、全球技术话语权塑造”四维分析框架。利用动态主题模型(dynamic topic model)识别2015-2025年306份美国人工智能政策文本的主题,动态追踪政策主题强度演化,并基于以上四维分析框架解读模型结果,再结合文本共现方法,对模型结果进行主题词共现分析,研究不同政策主题间的协同逻辑,揭示技术民族主义在美国人工智能政策中的体现及对华人工智能发展的影响。研究发现,美国人工智能政策具备鲜明的技术民族主义属性。为获得人工智能全球领导地位,美国对内将人工智能技术与国家安全议题深度绑定,以“国家安全威胁”为核心逻辑,构建对华技术管制的合法性叙事基础。对外输出嵌入美式价值观的技术规则,并组建认可美式价值观的技术联盟实现对华技术遏制阵营化。对此,提出“底层突围、标准跃升、伙伴重塑”三条路径,应对外部技术风险,提升中国人工智能领域的竞争主动权。

美国人工智能政策  /  技术民族主义  /  动态主题模型  /  文本共现分析

Amid growing global technological competition, understanding the reasoning behind U.S. artificial intelligence (AI) policy is crucial for evaluating its strategic impact and potential risks for China. Building on the theoretical framework of technological nationalism, this study introduces a four-dimensional analytical model covering national technological strategic positioning, the establishment of technological sovereignty, the connection between technology and national security, and the development of global technological discourse power.

Using the Dynamic Topic Model (DTM), we analyze 306 U.S. AI policy documents issued from 2015 to 2025 to identify key thematic trends and map the evolving policy emphasis. Complemented by keyword co-occurrence analysis, the study examines the interdependencies among policy themes to reveal how technological nationalism has become structurally embedded in the United States’ AI policymaking process and how this shapes its external technological stance toward China. The findings demonstrate that U.S. AI policy is characterized by a strong technological nationalist orientation. Domestically, the United States tightly links AI development with national security goals, creating a legitimacy narrative around “national security threats” to justify restrictive technological measures targeting China. Internationally, it promotes governance frameworks infused with American values and fosters alliances with like-minded partners, thereby institutionalizing a bloc-based regime of technological containment.

In response, the study proposes three strategic pathways for China—foundational breakthroughs, standard elevation, and partnership restructuring—aimed at mitigating external technological vulnerabilities and enhancing its strategic autonomy and competitiveness within the global AI landscape. These findings contribute to a deeper understanding of the geopolitical dimensions of AI governance and offer actionable insights for national technology strategy in an era of renewed techno-political rivalry.

U.S. artificial intelligence policy  /  techno-nationalism  /  dynamic topic modeling  /  text co-occurrence analysis
温婷, 姜南, 姜银鑫. 美国人工智能政策的技术民族主义属性与应对. 科学学研究, 2026 , 44 (10) : 2081 -2098 .
Ting WEN, Nan JIANG, Yin-xin JIANG. The techno-nationalist attributes of U.S. artificial intelligence policy and responses[J]. Studies in Science of Science, 2026 , 44 (10) : 2081 -2098 .
人工智能(Artificial Intelligence,下文简称AI)已成为重塑全球科技竞争格局的战略性技术。党的十八大以来,习近平总书记高度重视AI的发展,多次强调把握AI领域的竞争主动权。2017年,国务院印发《新一代AI发展规划的通知》指明“AI领域是国际竞争的新焦点,世界主要发达国家把发展AI作为提升国家竞争力的重大战略”①( ① 中华人民共和国中央人民政府.国务院关于印发新一代人工智能发展规划的通知国发〔2017〕35号[EB/OL].(2017-07-20)[2025-09-25]. https://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm。)。2018年,习近平总书记进一步指出,“加快发展新一代AI是我国赢得全球科技竞争主动权的重要战略抓手”②(② 人民网.习近平:加强领导做好规划明确任务夯实基础推动我国新一代人工智能健康发展[EB/OL].(2018-11-01)[2025-09-25]. https://cpc.people.com.cn/n1/2018/1101/c64094-30374958.html。)。2025年,习近平总书记再次强调“牢牢掌握AI发展和治理主动权”③(③ 中华人民共和国中央人民政府.习近平在中共中央政治局第二十次集体学习时强调:坚持自立自强突出应用导向推动人工智能健康有序发展[EB/OL].(2025-04-26)[2025-09-25]. https://www.gov.cn/yaowen/liebiao/202504/content_7021072.htm。)。这些重要论述为我国AI发展提供了方向指引和制度保障。此背景下,我国AI快速发展,全球知名AI基准测试机构人工分析(Artificial Analysis)2025年发布《中国AI发展报告》(State of AI: China)指出全球正在形成中美双极主导的AI新格局④(④ Artificial Analysis.State of AI: China [EB/OL].(2025-4-22)[2025-06-02]. https://artificialanalysis.ai/downloads/china-report/2025/Artificial-Analysis-State-of-AI-China-Q1-2025.pdf。)。
随着中国在全球AI竞争格局中战略地位的持续上升,美国对华AI政策的战略导向呈现“针对性遏制”到“全面封锁”的趋势[1]。对此,学界围绕美国AI政策展开了深入探讨,大致形成三类文献资料。第一类研究关注政策体系结构,重点评估美国AI政策内容构成、目标导向和实施方式等[2-4]。第二类研究聚焦美国对华AI战略的形成和演变,揭示美国将中国视为主要竞争对手并实施遏制政策的原因和目的[5-8]。第三类研究借助文本分析、量化建模等工具探究美国AI政策模式、政策特征等[9-11]。以上三类研究对理解美AI政策具有重要学术价值。
然而,现有研究大多着重分析美国AI政策目标、实施架构和政策工具等方面,较少从意识形态层面探讨政策背后的驱动逻辑。此外,现有研究大多采用静态分析,缺乏对政策迁移路径、主题演化动向之间的关联性研究,难以全面了解美国AI政策的时序性与阶段性特点。
为弥补上述不足,本文引入技术民族主义理论,将AI政策置于大国竞争的意识形态之中,突破以往研究多从政策内容出发的局限,解构美国AI政策制定背后的逻辑,阐释技术民族主义对美国AI政策的影响。研究方法上,本文全面收集2015-2025年美国25个部门及机构发布的306份AI相关政策文本,以技术民族主义为分析框架,采取动态主题模型(Dynamic Topic Model,下文简称DTM)和文本共现研究方法,识别美国AI政策主题结构、动态演化趋势和协同逻辑,克服以往静态分析的缺陷。深刻揭示美国AI政策对华影响,为中国掌握AI竞争主动权提供参考。
技术民族主义是民族主义思想在科技领域的延伸。该理论强调技术应以国家利益为核心,技术活动服务于“民族—国家”的整体战略目标,必要时通过政策干预主导技术发展路径。它打破技术本身的中立性,区分“自我技术”与“他者技术”,将“自我技术”发展视为国家竞争力与地缘政治优势的战略资源[12],主张国家对内扶持关键技术,对外限制竞争性技术扩散,维护技术主权或技术领先地位[13,14]。总之,技术民族主义不仅将技术视为经济增长的工具,更当成国际竞争的重要支点,其最终可能演变为科技霸权主义。
技术民族主义可深入解释美国AI政策的制定逻辑。首先,技术民族主义与美国AI政策的制定与实践高度契合。如,美国将“技术优势等同于文明优越”,称本国的AI技术为“反映美国自由、民主价值观的AI”,而将中国AI技术称为“专制的AI”⑤(⑤SHAREAMERIC.防范技术被专制政权肆意操纵[EB/OL].(2021-07-21)[2025-06-10]. https://archive-share.america.gov/zh-hans/defending-technology-from-authoritarian-abuse/index.html。);再如,美国秉持“美国技术至上”的理念,污蔑中国的AI技术进步源于“对美技术盗窃”,此类做法是技术民族主义的典型表现[15-17]。其次,技术民族主义能够解释美国对中国AI发展的“警惕”。以AI模型为例,2024年全球重要AI模型40个来自美国,15个来自中国,虽然仍有数量差距,但质量差距已从2023年的20%缩小到0.3%⑥(⑥Stanford HAI.Artificial Intelligence Index Report 2025 [EB/OL].(2025-04-08)[2025-06-02]. https://hai.stanford.edu/ai-index/2025-ai-index-report。)。这种追赶态势触发美国维护技术优势的战略焦虑,推动其在政策层面对华采取更为激进的遏制措施。可见,借助技术民族主义,不仅有助于理解美国AI政策的内在动机,还能揭示其对华遏压逻辑[18,19]。
本文将技术民族主义作为核心理论支点,构建分析美国AI政策的理论框架。具体而言,本文基于现有文献对技术民族主义核心内涵的梳理,以“国家技术战略定位、技术主权构建、技术与国家安全耦合、全球技术话语权塑造”四个维度分析美国AI政策的演进逻辑。国家技术战略定位是技术民族主义的起点,反映国家借由政策制定主动介入技术发展的取向[20]。技术主权构建是技术民族主义实施的核心路径,重点为利用政策排外手段实现国家对核心技术与产业链的本土化诉求[21,22]。技术与国家安全耦合是排外手段实施的“正当”理由,通过将AI与军事安全、数据主权等安全议题绑定,为外部封锁和内部干预提供合法性叙事[23]。全球技术话语权塑造是技术民族主义的最终战略目标,通过主导技术标准制定、构建排他性技术联盟、操纵技术伦理叙事占据全球技术治理体系高地,塑造并维系技术霸权[24]。
需要说明的是,美国AI政策的形成并非技术民族主义单一逻辑的产物。产业竞争[25]、安全治理[26]、党派政治[27]等视角同样为解读美国AI政策提供了重要启示。然而,这些视角多聚焦于特定政策领域或政策局部,难以从整体上分析美国AI政策。相比之下,技术民族主义提供了更具统摄力的分析框架,将分散的政策主题纳入“国家战略—民族利益”的宏观逻辑中加以整合。此外,美国AI政策文件涉及主题广泛、内容复杂,若仅依赖局部视角难以形成系统性的解读。技术民族主义理论构建的四维分析框架可以涵盖广泛的政策议题,为DTM分析结果提供解读依据。技术民族主义与DTM研究方法相辅相成,使本文更为深刻地揭示美国AI政策的整体逻辑及其对华战略意图。
本文以美国AI政策为研究对象,在美国全部立法、司法、行政部门及其附属机构、独立机构的官网,以“Artificial Intelligence”(人工智能)、“Machine Learning”(机器学习)、“Large Models”(大模型)、“Large Language Model”(大语言模型)等AI相关术语为关键词,检索2015-2025年⑦(⑦本文所指2015-2025年,截至2025年6月30日。)发布的文件。排除没有发布AI相关政策的部门,纳入以AI为主题的政策文本及虽不以AI为主题但AI属于其中重要内容的文件,最终得到25个部门及机构发布的306份文件,文件类型以国会法案⑧(⑧尽管向国会提交的法案不会全部获得通过,但向国会提交法案本身代表美国不同党派议员对法案所涉事项的态度,因此本文的研究范围包括所有向国会提交的有关AI的法案。值得注意的是,本文所提及的全部2025年提交的法案截止2025年6月30日都仍未生效。)、政府部门政策为主,同时涵盖部分高度相关的官方报道和权威机构发布的调查报告。政策文本内容共计超400万词。图2为发文主体占比分析,展示出美国AI政策制定主体的多元性。发文主体涵盖国会、白宫、商务部、国防部、卫生与公共服务部、国务院、交通部、司法部、财政部、能源部等部门,既包括立法与战略统筹部门,也包含科技研发、产业监管、军事安全、社会治理等多个执行机关。
本文细致梳理美国AI政策的发布脉络,并结合不同执政政府的战略取向,将其政策发展过程划分为战略启蒙期、制度建设期、规则强化期、全球布局期四个阶段⑨(⑨若无特别说明,本文所指四个阶段皆为战略启蒙期、制度建设期、规则强化期、全球布局期。),如图3所示,以展现美国AI政策与其国内政治周期之间的深刻关联,同时为DTM提供时间划分依据,便于对比解读模型处理结果。
政策文本的初步分析表明,美国AI政策发文主体多样,政策内容存在显著差异,同时政策跨越多个政府任期,呈现高度异质性,仅凭人工解读难以揭示政策的演变逻辑。为深入探究美国AI政策,本文采用无监督动态时间主题模型(Dynamic Topic Model, DTM)提取政策主题。DTM作为分析文本主题随时间演化的概率生成模型,是隐含狄利克雷分布(Latent Dirichlet Allocation, LDA)的扩展,它通过引入时间维度能够捕捉主题内容和主题强度的时序性动态变化[28]。
本文中DTM具有三重功能。第一,实现不同政策主题间的跨阶段比较。DTM具备时序性建模能力,通过主题概率分布计算,将复杂政策文本划分为多个政策子领域,从而实现政策文本间跨主题、跨年份的比较。第二,有助于减少主观解读政策文本的偏误。利用DTM完成高频词建模,可有效减少人工直接解读政策文件的主观偏差。第三,为剖析美国AI政策对华影响提供量化支撑。DTM分析结果服务于美国AI政策“国家技术战略定位、技术主权建构、技术与国家安全耦合、全球技术话语权塑造”的四维分析框架,为后文探讨美国AI政策对中国AI发展造成的影响提供依据。
(1)文本数据预处理
半结构化处理政策文本数据。具体过程如下:第一,删除非主体内容。删除文本中涉及部门简介、职能宣传、人员构成、政策制定过程、参考文献等与政策主体内容无关的信息。第二,还原缩写。政策文本为编写简洁,会于正文中缩写专业术语等较长的英语词组,为便于DTM识别需予以还原,并将还原后的词组视为单一词项(token)进行处理,以避免在分词过程中被拆解而导致语义偏差。例如,“Artificial Intelligence”(AI,人工智能)、“Large Language Models”(LLMs,大语言模型)、“Privacy-Enhancing Technologies”(PETs,隐私增强技术)、“Automated Driving Systems”(ADSs,自动驾驶系统)、“Research and Development”(R&D,研发)等。第三,提取分析单元。一份政策文件囊括AI治理的众多子主题,为使DTM精准识别某一主题在不同年份的演化需提取主题分析单元。根据前述四维分析框架,阅读306份政策文本并按照其内容分类,以500词⑪(⑪ 通过反复实验,500-800词切割标准下DTM分析准确率较高,为保障准确率的同时提高分析效率,本文以500词为标准提取分析单元。)为一个分析单元,提取到9816个分析单元。第四,利用自然语言工具包(Natural Language Toolkit, NLTK)完成分词、删除停用词⑫(⑫ 删除停用词指删除文本中不携带特定含义的常见单词,例如“the”“a”“an”“in”等。)和词形还原⑬(⑬ 词形还原指将英文单词还原为最基本的、词典中的形式,例如将“drove”、“driving”都还原为“drive”。)。
(2)TF-IDF文本向量化
TF-IDF(Term Frequency-Inverse Document Frequency)常用于评估一个词对一份文件的重要程度。词频(Term Frequency, TF)表示一个词在文本中出现的频率,逆文档频率(Inverse Document Frequency, IDF)衡量词的普遍重要性,如果一个词频繁出现在大部分文档中,说明这个词对主题区分度较低。借助该方法可筛选掉一些政策文本中反复出现但对文本主题区分度不大的词。例如“agency”(机构)、“US”(美国)、“USA”(美国)、“American”(美国)等。
(3)确定最优主题数
确定主题数对DTM研究至关重要[29],本文参考Mimno等一致性指标[30]确定最优主题数。该指标用于评估主题内部词语语义的一致性,数值越高表示主题越聚焦。本文使用Gensim内置的一致性函数,计算2015-2025年不同阶段,不同主题数的一致性。最终结果如图4所示,当主题数为12时,一致性平均值最高且拟合度也较好,因此本文DTM分析选择12个主题。
利用DTM对2015-2025年306份政策文本建模,识别出12个具有代表性的政策主题。按照“国家技术战略定位、技术主权构建、技术与国家安全耦合、全球技术话语权塑造”4个维度,归类整理所有主题,并提取各主题中权重排名前10的高频词作为特征词,构建政策主题与语义特征的对应关系,具体结果如表1所示。从整体上看,美国AI政策呈现国家主导、安全嵌入、话语输出的复合式特点。为详细揭示政策主题的内部演化,本文在12个主题的基础上,提取每一主题4个发展阶段前10的高频词,结合各阶段政策,解读美国AI政策特性。
(1)国家技术战略定位
如图5所示,“investment”(投资、投入)、“infrastructure”(基础设施)、“leadership”(领导)等词在国家技术战略定位四个阶段反复出现,表明美国以研发投入和基础设施建设为抓手,塑造全球技术领导优势。
战略启蒙期,2015年《美国国家创新战略》⑭(⑭ The White House.A Strategy for American Innovation [EB/OL].(2015-10-01)[2025-06-05].https://obamawhitehouse.archives.gov/sites/default/files/strategy_for_american_innovation_october_2015.pdf。)(A Strategy For American Innovation)奠定美国重视AI基础研究和基础设施建设的发展思路。制度建设期,2019年《维护美国AI领导地位的行政命令》⑮(⑮The White House.Executive Order on Maintaining American Leadership in Artificial Intelligence [EB/OL].(2019-02-11)[2025-06-06]. https://trumpwhitehouse.archives.gov/presidential-actions/executive-order-maintaining-american-leadership-artificial-intelligence/。)(Executive Order on Maintaining American Leadership in Artificial Intelligence)将“确保美国AI领域的领导地位”作为战略目标⑯(⑯从2019年第13859号行政命令《维护美国AI领导地位的行政命令》(Executive Order on Maintaining American Leadership in Artificial Intelligence)开始,到标志性立法《国家AI倡议法案(2020年)》(National Artificial Intelligence Initiative Act of 2020),以及详尽的战略更新《国家AI研发战略计划2023更新》(National Artificial Intelligence Research and Development Strategic Plan 2023 Update),再到2025年1月23日特朗普上任仅三天就签署的行政命令《消除美国在AI领域领导地位的障碍》(Removing Barriers to American Leadership in Artificial Intelligence),“全球领导地位”等类似表述反复出现,可见美国对其在AI领域影响力的重视。)。规则强化期,美国AI政策转向“技术发展支持”与“技术标准制定”的双重提升。2023年《国家AI研发战略计划更新》⑰ (⑰The NITRD.National Artificial Intelligence Research And Development Strategic Plan 2023 Update [EB/OL].(2023-05-23)[2025-06-09]. https://www.nitrd.gov/national-artificial-intelligence-research-and-development-strategic-plan-2023-update/。)(National Artificial Intelligence Research and Development Strategic Plan 2023 Update)持续加强国内AI技术基础研究投入。2024年《AI创新未来法案》⑱(⑱The House of Congress.S.4178 - Future of Artificial Intelligence Innovation Act of 2024 [EB/OL].(2024-07-31)[2025-06-09]. https://www.congress.gov/bill/118th-congress/senate-bill/4178/text。)(Future of Artificial Intelligence Innovation Act of 2024)则重点关注AI国际标准的制定。全球布局期,美国AI政策重心由内部制度建设向全球制度输出拓展。例如,2025年《AI行动计划建议》⑲(⑲CSET.Recommendations for an Al Action Plan [EB/OL].(2025-03-21)[2025-06-10]. https://cset.georgetown.edu/wp-content/uploads/Center-for-Security-and-Emerging-Technology-%E2%80%94-Recommendations-for-an-AI-Action-Plan.pdf。)(Recommendations for an Al Action Plan)主张美国在国际治理中发挥主导作用,获得AI全球领导地位。
(2)技术主权构建
如图6所示,“semiconductor”(半导体)、“education”(教育)、“talent”(人才)、“hub”(枢纽)等词多次出现,表明美国通过掌控技术、人才等关键资源提升AI的自主可控性,在四个阶段都展示出典型的“外部遏制”与“内部强化”特征。
“外部遏制”方面,美国利用出口管制、投资限制等手段,打压被其视为“竞争对手”的国家。以中国为例,2022年,商务部对华实施先进计算和半导体制造严格控制的出口规定⑳(⑳Federal Register.Implementation of Additional Export Controls: Certain Advanced Computing and Semiconductor Manufacturing Items; Supercomputer and Semiconductor End Use; Entity List Modification [EB/OL].(2022-10-13)[2025-06-02]. https://www.federalregister.gov/documents/2022/10/13/2022-21658/implementation-of-additional-export-controls-certain-advanced-computing-and-semiconductor。),时任副部长的艾伦·埃斯特维兹(Alan Estevez)公开表示,此举旨在防止“中国成为AI领域的世界领导者” ㉑(㉑美国驻华大使馆和领事馆.美国商务部对中华人民共和国实施先进计算和半导体制造的出口管制新规[EB/OL].(2022-10-11)[2025-06-02]. https://china.usembassy-china.org.cn/zh/commerce-implements-new-export-controls-on-advanced-computing-and-semiconductor-manufacturing-items-to-the-peoples-republic-of-china-prc/。)。2024年《关于美国在受关注国家投资有关国家安全技术和产品的规定》㉒(㉒Federal Register.Provisions Pertaining to U.S. Investments in Certain National Security Technologies and Products in Countries of Concern [EB/OL].(2024-05-07)[2025-09-20]. https://www.federalregister.gov/documents/2024/07/05/2024-13923/provisions-pertaining-to-us-investments-in-certain-national-security-technologies-and-products-in。)(Provisions Pertaining to U.S. Investments in Certain National Security Technologies and Products in Countries of Concern)禁止美国资本投资中国AI领域,并限制相关合资与技术合作行动。2025年商务部连发三份管控文件㉓(㉓三份管控文件分别为《关于可能用于训练AI模型的先进计算集成电路及其他商品的管控政策声明》《防止先进计算集成电路被转用的行业指南》《对中国先进计算集成电路适用通用禁令十的指南》三份文件加强对华先进芯片与AI模型的限制,并将华为昇腾910B、910C、910D三款AI芯片纳入出口管制范围。Bureau of Industryand Security.BIS Policy Statement on Controls that May Apply to Advanced Computing Integrated Circuits and Other Commodities Used to Train AI Models [EB/OL].(2025-05-13)[2025-06-20]. https://www.bis.gov/media/documents/ai-policy-statement-training-ai-models-may-13-2025。),严格限制对中国出口AI芯片与模型。
“内部强化”方面,美国十分重视AI人才培养。2020年《国家AI倡议法案》㉔(㉔The House of Congress.H.R.6216 - National Artificial Intelligence Initiative Act of 2020 [EB/OL].(2020-03-12)[2025-06-06]. https://www.congress.gov/bill/116th-congress/house-bill/6216。)(National Artificial Intelligence Initiative Act of 2020)指出人才是美国AI发展的基础。2023年《国家AI研发战略计划更新》(National Artificial Intelligence Research and Development Strategic Plan 2023 Update)提高计算机科学课程在美国教育体系中的地位。司法部、劳工部、卫生与公共服务部等部门都对AI人才培养方案做出说明㉕(㉕国防部发布《AI教育战略》(AI Education Strategy)加强军事人员AI素养,推动AI在情报、装备保障和战术决策中的应用。司法部《AI战略》(Artificial Intelligence Strategy for the U.S. Department of Justice)、卫生与公共服务部《卫生、公众服务和公共卫生中使用AI的战略计划》(Strategic Plan for the Use of Artificial Intelligence in Health, Human Services, and Public Health)、劳工部《劳动力创新与机会法案》(Workforce Innovation and Opportunity Act)围绕司法实践、公共治理与产业转型出台配套的技能提升和再培训项目。)。
(3)技术与国家安全耦合
图7反映美国通过技术与国家安全耦合,以“国家安全”为由打压别国AI发展势头的政策趋势。
战略启蒙期,2016年《国家AI研究与发展战略计划》㉖(㉖The NITRD.The National Artificial Intelligence R&D Strategic Plan [EB/OL].(2016-10-30)[2025-06-06]. https://www.nitrd.gov/PUBS/national_ai_rd_strategic_plan.pdf。)(The National Artificial Intelligence R&D Strategic Plan)强调AI在国家安全中的作用,为AI技术与国家安全的交织奠定方向。制度建设期、规则强化期和全球布局期,“competitor”(竞争对手)、“sanction”(制裁)等词频繁出现,说明美国开始将AI部署与“国家安全威胁”双轨推进。换言之,若别国AI发展有超过美国的势头,美国就将其视为“国家安全的威胁”,并以此作为理由阻挠别国AI发展进程。以中国为例,2019年美国智库新美国安全中心(Center for a New American Security)发布《了解中国AI战略》㉗(㉗CNAS.Understanding China's AI Strategy[EB/OL].(2019-02-06)[2025-06-21]. https://www.cnas.org/publications/reports/understanding-chinas-ai-strategy?utm_medium=email&utm_campaign=Understanding Chinas AI Strategy White Paper Rollout Media&utm_content=Understanding Chinas AI Strategy White Paper Rollout Media+CID_eecdd0d32a84c74e153b8409074cd04e&utm_source。)(Understanding China’s AI Strategy)论述中国技术崛起的“系统性威胁”。2021年《美国创新与竞争法案》㉘(㉘The House of Congress.S.1260 - The United States Innovation and Competition Act [EB/OL].(2021.05-19)[2025-06-10]. https://www.congress.gov/bill/117th-congress/senate-bill/1260。)(United States Innovation and Competition Act)将中国明确定位为“战略竞争对手”,全面加强对华AI技术打压。
(4)全球技术话语权塑造
如图8所示,高频词汇中除“standard”(标准、规范)、“leadership”(领导力)、“global”(全球)等词,还包括“fair”(公平)、“ethical”(伦理的)等包含价值观的词汇,说明美国全球技术话语权塑造主要以技术标准输出和价值观宣传为手段。
战略启蒙期和制度建设期,美国AI政策致力于推广符合美式价值观的技术标准。例如,2019年《美国如何领导AI:联邦参与制定技术标准和相关工具的计划》㉙(㉙The NIST.U.S.Leadership in AI:A Plan for Federal Engagement in Developing Technical Standards and Tools [EB/OL].(2019-08-09)[2025-06-10]. https://www.nist.gov/system/files/documents/2019/08/10/ai_standards_fedengagement_plan_9aug2019.pdf。)(U.S. Leadership in AI:A Plan for Federal Engagement in Developing Technical Standards and Tools)中明确指出美国AI领域的全球领导地位取决于政府AI标准制定中的影响力,支持政府各部门积极参与AI标准的制定工作。
规则强化期和全球布局期的美国进一步强化AI治理规则的话语支配权。2025年《国家AI顾问委员会特朗普政府政策建议报告》㉚(㉚NAIAC.NAIAC Insights for the Administration of President Donald J. Trump [EB/OL].(2025-01-27)[2025-06-09]. https://insideaipolicy.com/sites/insideaipolicy.com/files/documents/2025/jan/ai01272025.pdf。)(NAIAC Insights for the Administration of President Donald)指明美国需在全球AI治理中发挥领导作用。具体行动中,美国积极推动制定北约《AI战略》㉛(㉛North Atlantic Treaty Organization.Summary of the NATO Artificial Intelligence Strategy(2021-10-22)[2025-06-10]. http://nato.int/cps/en/natohq/official_texts_187617.htm。)(Artificial Intelligence Strategy)、《美国印太地区战略》㉜(㉜The White House.Indo-Pacific Strategy of the United States [EB/OL].(2022-02-11)[2025-06-21]. https://bidenwhitehouse.archives.gov/wp-content/uploads/2022/02/U.S.-Indo-Pacific-Strategy.pdf。) (Indo-Pacific Strategy of the United States)等国际合作战略,将技术标准与“民主价值观”绑定,借“自由”“开放”之名构建以美为中心的技术同盟,计划控制全球技术话语权。
上一节基于技术民族主义的四维分析框架和DTM主题词分析结果,分析了美国AI政策不同发展阶段的演进特征。为进一步从整体上剖析美国AI政策,本节借鉴邱均平等的研究[31],利用DTM得到的主题—词矩阵,计算2015-2025年12个主题的热度,绘制主题词热力图9,分析不同主题在不同时间的受关注度。同时,借鉴吴瑞鹏等(2023)的研究[32],计算不同主题间的相似度,绘制桑基图10,阐明各个主题的演化路径。主题热力图能呈现静态阶段主题强度分布,桑基图则提供跨时期主题间的动态演化路径。两者结合,可较为全面地解读美国AI政策热点主题的演变以及不同主题间的迁移关系。
图9显示,美国AI政策主题热度变化与技术民族主义演进路径契合。战略启蒙期政策热度主要集中于“长期研发投资”“基础设施与资源”以及“人才与劳动力培养”,体现美国AI政策初期主要关注技术基础资源。制度建设期、规则强化期和全球布局期,“全球领导地位”“军事与国家安全”“可信AI与伦理”热度居高不下,说明在AI政策发展阶段美国对“安全嵌入”与“全球领导力”的重视。“全球领导地位”自战略启蒙期起总体呈升温趋势,至全球布局期达到热度峰值0.3009,在同期所有主题中保持压倒性优势。结合图10,“军事与国家安全”主题同样在四阶段热度总体呈上升趋势,并在规则强化期、全球布局期与“对抗性防御技术”“威慑性叙事”及“可信AI与伦理”形成密集路径,呈现安全叙事、前沿部署与伦理治理三者之间的高度融合,标志AI政策已全面嵌入国家安全战略。此外,“对抗性防御技术”路径显示战略启蒙期与“军事与国家安全”绑定,规则强化期、全球布局期向“可信AI与伦理”“全球领导地位”转化,说明美国逐步将技术能力嵌入价值观框架,以提升其AI国际治理话语权。
综合图9、图10可发现主题热度的下降并不意味着该主题被忽视,也有可能是不同政策阶段同一主题的作用发生了转变。例如,图9中“长期研发投资”与“人才与劳动力培养”虽在战略启蒙期热度接近,分别为0.1215与0.1344,但图10表明“人才与劳动力培养”在战略启蒙期和制度建设期的主题演化路径更丰富。证明美国AI政策在早期同时推动多项基础性能力建设,但对“研发”与“人才”采取不同策略。前者被并入国家战略底层逻辑中,热度下降,后者虽热度下降,但因其对技术主权和国际话语权输出的支撑作用,持续保留并与多个主题形成联动关系。
图10还揭示出一些热度中等的主题虽并非政策焦点,但却发挥着关键的支撑作用。例如,“国际标准制定”虽热度值中等,但其路径高度复杂,制度建设期与“可信AI与伦理”“全球领导地位”交织,并在全球布局期与“威慑性叙事”融合加深。说明该主题并非孤立提出,而是演变为连接外部制度输出与内部伦理治理的桥梁,是美国构建AI全球治理领导力的重要支点。
综上所述,美国AI政策呈现由“底层能力构建”向“战略安全嵌入”再向“制度主导输出”演进的逻辑。各政策主题在不同阶段强度不断变动,跨阶段形成联动结构,构建出以“全球领导地位”为定位,“技术主权构建”和“技术与国家安全耦合”为手段、“全球技术话语权塑造”为政策目标的战略框架。该过程体现美国AI政策日益深化的技术民族主义属性,表明其技术主权输出的深层逻辑。
共现网络作为文本中隐性政策知识结构的可视化表达,能揭示关键词之间的紧密交织关系与策略联动机制[33]。本文引入文本共现分析,进一步揭示政策主题间的联动机制与嵌套关系,补足主题热度阐释的静态分布和桑基图呈现的演化路径所难以揭示的语义链接关系[34]。具体而言,利用Gephi分析DTM提取的12个维度关键词识别高频词共现对形成政策共现网络,结果如图11所示。
图11表明美国AI政策话语体系核心由“research”(研究)、“technology”(技术)、“development”(发展)和“system”(系统)构成,即以技术体系为中心的国家战略架构,反映美国AI政策由技术推动,进而成为国家主权建构和技术治理体系的支柱。技术民族主义的基本特点——将关键技术与国家战略制度化、法治化绑定——深刻显化。外围语义集群揭示支撑美国技术主权的三大路径:一是制度规范构建,如“standard”(标准)、“organization”(组织)、“legal”(法律的)等;二为人才与教育生态的培育,如“training”(培训)、“education”(教育)、“talent”(人才)等;三是以“risk”(风险)、“privacy”(隐私)、“secure”(安全的)等为核心的战略防御。同时,“international”(国际的)、“partnership”(伙伴关系)、“global”(全球的)、“collaboration”(合作)等关键词的突出位置表明,美国正试图凭借规则设定和全球协作平台向外输出其AI政策。
为细致刻画政策核心词汇的嵌入逻辑,本文进一步构建以“research”(研究)、“technology”(技术)、“development”(发展)、“system”(系统、体系)为核心节点的共现网络。如图12所示,核心语义周围密集出现“act”(法案)、“federal”(联邦)、“committee”(委员会)、“shall”(应)等制度相关的关键词,显示美国AI政策已高度嵌入其国家立法体系之中,体现国家凭借立法路径进行制度锁定与安全治理的政策逻辑。此外,“security”(安全)、“risk”(风险)、“support”(支撑、支持)、“institute”(研究所、学院、机构)等词的高共现频率,揭示政策实施并非依赖自由市场机制,而是依托系统性制度设计,实现对AI发展方向的宏观掌控。
综合主题热度图、桑基图路径演化与文本共现网络的结果看,美国AI政策在不同层面展现技术民族主义的主要特性。战略层面,美国采用价值观叙事、制度设计和标准制定等多元手段,积极塑造其全球AI治理体系中的主导地位;国内层面,政策文本普遍强调以“美国价值观”为核心的技术治理框架,体现将技术发展与特定制度价值观相结合的特点;国际层面,围绕国家安全的政策逻辑推动技术管制和出口审查等制度,增强对关键技术扩散的管控。该政策路径反映美国对维护自身技术优势的焦虑,揭示技术民族主义已成为其应对全球技术竞争的核心意识形态工具。
美国一方面刻意将AI技术优势与国家安全深度绑定,借助威慑性叙事渲染“中国AI威胁”,为对华技术管制打下“舆论基础”。《2020-2022年国家反情报战略》㉞(㉞NCSC.National Counterintelligence Strategy of the United States of America, 2020-2022 [EB/OL].(2020-02-05)[2025-06-21]. https://www.dni.gov/files/NCSC/documents/features/20200205-National_CI_Strategy_2020_2022.pdf。)(National Counterintelligence Strategy of the United States of America, 2020-2022)无端指责中国系统性窃取美国AI技术。2022年《国防部负责任AI战略和实施路径》㉟(㉟U.S. Department of Defense.U.S. Department of Defense Responsible Artificial Intelligence Strategy and Implementation Pathway [EB/OL].(2022-06-30)[2025-06-10]. https://media.defense.gov/2024/Oct/26/2003571790/-1/-1/0/2024-06-RAI-STRATEGY-IMPLEMENTATION-PATHWAY.PDF。)(Department of Defense Responsible Artificial Intelligence Strategy and Implementation Pathway)认为中国AI发展是对美国国防安全的威胁。同年《国家防务战略报告》㊱(㊱U.S. Department of Defense.National Defense Strategy[EB/OL].(2022-10-27)[2025-06-20]. https://media.defense.gov/2022/Oct/27/2003103845/-1/-1/1/2022-NATIONAL-DEFENSE-STRATEGY-NPR-MDR.PDF。)(National Defense Strategy)将中国定位为“对美国步步紧逼的挑战”。借助此类威慑性话语美国逐步塑造出“中国AI威胁”的形象。
另一方面借助“国家安全”之名赋予对华技术管制更强的“正当性”。与一般基于贸易保护或产业政策差异的技术管制不同,“国家安全”之名使得技术管制可能绕开国际规则,扩展管控范围和强度[35]。仅2025年上半年,美国就有三个涉华技术管制法案被递交国会,管制范围涉及人才、知识产权、技术等领域,管制理由都与“国家安全”相关。2025年1月《中美AI能力脱钩法案》㊲(㊲The House of Congress.Decoupling America's Artificial Intelligence Capabilities from China Act of 2025 [EB/OL].(2025-01-29)[2025-06-06]. https://www.congress.gov/bill/119th-congress/senate-bill/321/text。)(Decoupling America’s Artificial Intelligence Capabilities from China Act)将“排斥中国”策略制度化,禁止美国公民和实体参与中国AI技术研发,全面限制中美之间AI技术与知识产权的跨境流动。紧接着,2月《中国技术转让管制法案》㊳(㊳The House of Congress.H.R.1122 - China Technology Transfer Control Act of 2025 [EB/OL].(2025-02-03)[2025-06-10]. https://www.congress.gov/bill/119th-congress/house-bill/1122/text/ih。)(China Technology Transfer Control Act)限制美国向中国出口所有可能提升中国军事能力的AI相关技术。暗示美国的封锁措施是由于“中国借助美国AI技术提升军事实力”。同年6月《禁用对抗性AI法案》㊴(㊴Federal Register.No Adversarial AI Act [EB/OL].(2025-06-25)[2025-06-29]. https://www.rickscott.senate.gov/services/files/A4B03393-9417-44D4-9FE5-4AF1F58FD2ED。)(No Adversarial AI Act)要求制定中国企业AI系统清单,禁止联邦政府采购或使用,表明美国对华AI技术的遏制已经从半导体、芯片等硬件领域扩展到模型、算法领域。
这种以国家安全为借口的技术管制,实际上将科技竞争政治化,对中国AI的发展造成一定阻碍。短期来看,技术管制挤压中国在高端芯片、先进算力、核心模型等领域的技术资源外部获取渠道,使中国AI产业的发展受限,研发成本和研发周期显著增加,形成“卡脖子”效应;长期来看,“技术威胁者”标签,可能会在国际社会造成对中国AI发展的不信任与警惕氛围,无形中削弱中国在全球AI技术治理体系中的话语权,限制中国AI技术影响力。
AI全球治理中,美国逐步构建起“宣扬意识形态差异”与“规则性孤立”为核心的战略体系。借由意识形态标定,将不同意识形态下采取不同治理规则的国家排除于国际技术秩序之外,塑造美国AI领域的主导权。
美国以美式价值观为门槛组建技术联盟。借助“安全”“民主”“伦理”为话语工具,美国不断将中国AI发展描绘为“技术滥用”“威胁民主”的象征,以此构建二元对立的技术图景,边缘化中国AI治理模式与方案。2020年美国发布报告指出美国需与盟友合作,将AI政策塑造为“自由社会价值观的堡垒”,对抗所谓的中国“技术威权主义”㊵(㊵National Security Commission on Artificial Intelligence.National Security Commission on Artificial Intelligence releases Second Quarterly Report [EB/OL].(2020-08-27)[2025-09-10]. https://files2.dlapiper.com/DLA_Piper_Web_Images_US_2/pdfs/NSCAI%20Q2%20Memo_20200722.pdf。)。同年,美国宣布加入AI全球伙伴关系并推动建立一套共同民主原则,对抗中国利用“扭曲的技术威胁公民自由”的行为㊶(㊶DefenseNews.US joins G7 artificial intelligence group to counter China [EB/OL].(2020-05-29)[2025-07-10]. https://www.defensenews.com/global/the-americas/2020/05/29/us-joins-g7-artificial-intelligence-group-to-counter-china/。)。美国还将技术标准与“美式价值观”绑定,划定技术合作与标准适用的边界,从而在叙事层面实现“技术异己”的合法排除[36]。
美国借助技术联盟推进技术“圈层治理”,主导技术联盟制定排他规则。“Chip4联盟”(美国、日本、韩国、中国台湾)是该机制的典型体现。美国依托该联盟试图将中国大陆排除在全球半导体供应链联盟之外㊷(㊷国合中心.“芯片四方联盟”:供应链联盟的战略支柱[EB/OL].(2022-11-25)[2025-07-10]. https://www.icc.org.cn/trends/mediareports/796.html。)。2022年美国颁布《芯片与科学法案》㊸(㊸The House of Congress.H.R.4346 - CHIPS and Science Act of 2022 [EB/OL].(2022-08-09)[2025-06-03]. https://www.congress.gov/bill/117th-congress/house-bill/4346。)(CHIPS and Science Act)以520多亿美元补贴吸引台积电、三星等企业在美建厂,同时要求接受补贴的企业十年内不得在中国大陆扩建先进制程产能。2024年《AI创新未来法案》(The Future of AI Innovation Act of 2024)虽以推动国际“促进创新、科学与AI研发的协作”为目标,但将合作对象明确限定于“现有双边与多边协定下的特定盟友”,排除中国等被认定为战略竞争对手的国家。2025年《AI扩散框架》㊹(㊹Federal Register.Framework for Artificial Intelligence Diffusion [EB/OL].(2025-01-15)[2025-06-10]. https://www.federalregister.gov/documents/2025/01/15/2025-00636/framework-for-artificial-intelligence-diffusion。)(Export Control Framework for Artificial Intelligence Diffusion)完全禁止中国、俄罗斯等“受关注国家”进口美国芯片。随后,《美国科学愿景》㊺(㊺VAST.Vision for American Science and Technology [EB/OL].(2025-02-27)[2025-06-21]. https://www.vastfuture.org/?et_rid=514997345&et_cid=5542278。) (Vision for American Science and Technology)指出美国AI领域的技术优势正被中国超越,建议美国维护国际伙伴关系形成稳固的技术联盟,保护美国在技术联盟中的核心领导地位。
由价值观对立引发的技术联盟排斥将压缩中国参与全球AI治理的空间。排他性技术联盟使中国不仅要面对美国单边技术封锁的压力,还需承受来自其他国家协同排斥的风险,可能导致我国AI技术标准与技术成果在国际主流技术平台受到忽视,削弱我国AI技术的全球竞争力。
(1)底层突围:加强核心技术自主体系建设
当前,我国AI产业总体规模位居世界前列,截至2024年4月,我国AI企业数量已经超过4000家,仅次于美国,全球排名第二㊻(㊻Emerging Technologies.Transforming industries with AI: Lessons from China’s journey[EB/OL].(2025-01-23) [2025-06-12]. https://www.weforum.org/stories/2025/01/transforming-industries-with-ai-lessons-from-china/。)。但我国AI企业主要集中于应用层,基础层与技术层企业数量偏少㊼(㊼中国新一代人工智能发展战略研究院.《中国新一代人工智能科技产业发展2024》发布[EB/OL].(2024-06-21)[2025-06-12]. https://cingai.nankai.edu.cn/2024/0621/c10232a546068/page.htm。)。AI产业是一个高度协同、跨领域的复杂体系,涉及芯片设计、硬件制造、数据处理等多个环节,全球产业链稳定循环的前提下,我国这种产业结构可以推动AI技术迅速落地,实现技术市场化,保持技术市场活力。然而,美国的技术封锁破坏了全球产业链的稳定,产业结构短板造成的技术供给不足制约中国全链条自主可控能力的建设,加剧“断链”风险。建议适度调整重点AI领域布局,提升基础层和技术层的研发能力与产业配套水平,优化资源配置,完善产业支持政策。引导科研机构、高校和企业加强协作,推动基础技术研究与产业需求有效衔接,持续建设开放共享的基础研发资源与设施,提升算力、数据和平台资源可及性,引导并支持多样化创新主体,尤其是中小企业、初创团队等主体的研发活动。推动全国范围内资源整合、标准化接口建设和数据共享机制,提升整体资源利用效率。
(2)标准跃升:推动技术成果向国际标准转化
为应对美国及其主导的技术联盟对华持续施压,我国突破关键核心技术的同时还需构建具备影响力的技术标准体系,提升我国在全球技术治理格局中的话语权。“十四五”规划和《新一代AI发展规划》等重要政策文件中都将推动国内AI技术规则向国际规则的接轨与输出作为重要目标。2024年《国家AI产业综合标准化体系建设指南》㊽(㊽中华人民共和国中央人民政府.工业和信息化部中央网络安全和信息化委员会办公室国家发展和改革委员会国家标准化管理委员会关于印发国家AI产业综合标准化体系建设指南(2024版)的通知[EB/OL].(2024-06-05)[2025-06-18]. https://www.gov.cn/zhengce/zhengceku/202407/content_6960720.htm。)提出到2026年制定50项以上AI国家标准和行业标准,参与国际标准制定项目超过20项的目标。面向未来,建议坚持标准体系建设的整体规划和前瞻布局。重点关注数据治理、算法安全、模型可控性等核心领域的标准化问题,推动标准制定过程前置于技术研发环节,实现从研发到标准的有机衔接。并且重视多层次、跨领域的标准协调机制,避免行业内信息孤岛和标准碎片化问题,提升标准在不同行业和应用场景中的兼容性和通用性。此外,完善标准落地机制,增强标准转化能力,鼓励重点AI企业开展标准输出型技术转化项目。
(3)伙伴重塑:发展包容互惠的合作关系网络
面对当前国际技术竞争阵营化问题,为促进更广泛的国际合作,可探索构建以技术发展为导向、普惠性与规则包容性为基础的合作关系网络。首先,摆脱美式意识形态主导联盟的方式,重构以技术理性为核心的非意识形态化国际合作体系。与美国以“美式价值观”为前提设定“制度认同”门槛的做法不同,中国组建的联盟以技术能力建设、互利共赢与公平参与为核心理念,包容不同制度类型的国家基于共同的技术需求形成非对抗性技术伙伴关系。避开意识形态冲突的焦点,推动以技术为导向、发展普惠性为目标、规则包容性为基础的国际合作新叙事。
其次,构建技术透明机制消解西方对中国AI发展的误解与偏见。通过金砖国家、南南合作、“一带一路”等多边合作机制,倡导制定更具包容性的国际规则。例如,2025年2月,中国与来自60个国家的代表在巴黎AI行动峰会上共同签署《关于为人类和地球提供包容性和可持续的AI的声明》㊾(㊾Mission Permanentede La France Aupresdes Nations Uniesa New York.Statement on Inclusive and Sustainable Artificial Intelligence for People and the Planet[EB/OL].(2025-02-11)[2025-06-18]. https://onu.delegfrance.org/statement-on-inclusive-and-sustainable-artificial-intelligence-for-people-and。)(Statement on Inclusive and Sustainable Artificial Intelligence for People and the Planet),强调“开放”“包容”“道德”“安全”“透明”等原则。此外,积极推进《全球数据安全倡议》㊿(㊿中华人民共和国中央人民政府.全球数据安全倡议[EB/OL].(2020-09-08)[2025-06-18]. https://www.gov.cn/xinwen/2020-09/08/content_5541579.htm。)的国际化,继续承诺不强制获取境外企业数据、不滥用技术优势谋求地缘利益,树立可信数据治理的国际形象,以事实和透明度反驳美国虚假指控,提升国际社会对中国AI治理模式的信任度。
基于技术民族主义理论,构建“国家技术战略定位、技术主权构建、技术与国家安全耦合、全球技术话语权塑造”的四维分析框架,梳理2015-2025年美国AI政策,将其发展过程划分为战略启蒙期、制度建设期、规则强化期和全球布局期四个阶段。依据四维分析框架解读DTM分析结果,总结四个政策发展阶段的主题热点、主题演化路径以及主题词共现关系。研究表明,美国AI政策呈现从基础能力建设向国家安全绑定,再到全球规则塑造的渐进演化特点,体现美国将技术与国家安全议题的深度融合,强化对华技术管制,最终实现主导AI全球治理的意图,凸显美国AI政策中鲜明的技术民族主义属性。
美国AI政策演化态势对中国AI发展提出突破技术封锁与重塑全球技术形象的挑战。对此,中国既需巩固自身技术研发实力,完善从基础层到应用层的完整技术链构建,提升核心技术自主可控能力,也需加强标准化能力和国际参与,推动形成更加开放、包容和多元的全球AI技术治理体系。
  • 国家自然科学基金面上项目(72274137)
  • 国家自然科学基金面上项目(71874122)
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2026年第44卷第10期
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  • 接收时间:2025-07-07
  • 首发时间:2026-10-10
  • 出版时间:2026-10-15
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  • 收稿日期:2025-07-07
  • 修回日期:2025-11-07
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国家自然科学基金面上项目(72274137)
国家自然科学基金面上项目(71874122)
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    同济大学上海国际知识产权学院, 上海 200092

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姜银鑫(1977-),男,高级工程师,博士研究生,E-mail:。
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
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