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arXiv 2607.23207cs.CYcs.CR

可问责且匿名的人工智能代理——中国国家代理身份层中的知识拆分绑定

Accountable yet Anonymous AI Agents - Split-Knowledge Binding in National Agent-Identity Layer in China

Yifan He, Zhiguang Shan, Le Luo, Wei Wang

AI总结:

研究中国国家人工智能代理身份系统,提出知识拆分绑定机制,实现可问责且匿名。贡献包括制度性分离、事后归因论点、问责表面概念、比例框架及反身管辖方法,证明国家规模可行性并提供评判部署的框架。

AI中文摘要:

新兴的人工智能代理身份基础设施在行业实践和研究提案中,都集中于解决问责与隐私之间的矛盾:使每个代理都可识别。本文记录了中国的一个国家系统,它作为国家基础设施构建,计划于2026年第三季度公开推出。该系统在同一设计空间中占据了一个不同且未被充分探索的点:一个代理与经过验证的合法主体相关联,但该主体不会向任何业务层参与者披露。只有通过正当程序行事的法定当局,通过分别强制两个不同的政府机构,才能进行重新识别,且任何一方都无法单独进行重新识别。我们将这种机制命名为知识拆分绑定,并坦率地指出它是有条件的:这种分离是结构性和程序性的,而非加密性的,并且有权强制两个机构的国家可以进行重新识别。本文做出了五项贡献:(1)知识拆分绑定,一种用于托管问责的制度性而非加密性分离;(2)事后归因论点,即认为只有基于归因的问责对具有法律后果的人工智能代理行为具有法律效力;(3)问责表面,一个设计概念,用于识别哪些代理行为会留下带有身份的痕迹;(4)身份托管的比例框架,一种在三种信任架构中进行选择的决策结构;(5)反身管辖方法,一种应用于本文自身部署的评估标准。该系统证明了在国家规模上的可行性;该框架是评判任何部署(包括此部署)的工具。

英文摘要:

The emerging infrastructure for AI-agent identity has converged, in industry practice and research proposals alike, on a single resolution of the tension between accountability and privacy: make every agent identifiable. We document a national system in China -- built as national infrastructure and scheduled for public launch in Q3 2026 -- that occupies a different and underexplored point in the same design space: an agent is associated with a verified legal principal without that principal being disclosed to any business-layer participant. Re-identification is possible only to a legal authority acting through due process, by separately compelling two distinct government agencies, neither of which can re-identify alone. We name the mechanism split-knowledge binding and are candid that it is conditional: the separation is structural and procedural, not cryptographic, and a state empowered to compel both agencies can re-identify. The paper makes five contributions: (1) split-knowledge binding, an institutional rather than cryptographic separation for escrowed accountability; (2) the ex-post attribution thesis, the argued claim that only attribution-based accountability carries legal force for AI agent actions with legal consequences; (3) the accountability surface, a design concept identifying which agent actions leave identity-bearing traces; (4) a proportionality framework for identity escrow, a decision structure selecting among three trust architectures; and (5) the reflexive jurisdiction method, an evaluative standard administered to the paper's own deployment. The system is evidence of feasibility at national scale; the framework is the instrument by which any deployment -- including this one -- should be judged.

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