Journal of Information Security Reserach ›› 2026, Vol. 12 ›› Issue (10): 923-929.DOI: 10.12379/j.issn.2096-1057.2026.10.07

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Technology Transition and Risk Regulation of Administrative Algorithm Decision Driven by Large Model Integration Architecture

Zhou Li, Shen Min   

  • Online:2026-10-12 Published:2026-10-12

大模型集成架构驱动行政算法决策的技术跃迁与风险规制

周丽,申敏   

Abstract: With the improvement of the cognitive ability of the large-scale model integration architecture represented by GPT-5, the automatic decision-making mode of administrative algorithms has also changed in many aspects, forming a paradigm transition from “rule driven” to “cognitive generalization”. The technical transition of administrative algorithm decision driven by the large-scale model integration architecture is specifically manifested in the cross-modal data integration, dynamic routing calculation force distribution and chain reasoning correction, which lays a new foundation for the automatic decision-making of administrative algorithms and improves the government’s digital governance ability and problem-solving ability. However at the same time, the deep involvement of the large-scale model integration architecture in the decision-making of administrative algorithms has also induced risks and challenges in data security, procedural justice and power operation structure to a certain extent. In view of this, corresponding institutional responses and regulations shall be formulated. On the one hand, it is necessary to reconstruct data governance boundaries through hierarchical data right confirmation and the public data trust system, and enhance the interpretability and transparency of algorithms via a dynamic interpretation mechanism. On the other hand, the principles of proportionality and anti-discrimination rules are embedded in the process of algorithm design, and the binding system of subject responsibility for algorithm decision-making is established.

Key words: large model integration architecture, administrative algorithm decision making, data security, procedural justice, legal regulation

摘要: 伴随着以GPT-5为代表的大模型集成架构认知能力的提升和增强,行政算法自动化决策方式也随之发生了诸多变化,整体上形成了从“规则驱动”向“认知泛化”的范式跃迁。大模型集成架构驱动行政算法决策的技术跃迁具体表现为跨模态数据整合、动态路由算力分配以及链式推理纠偏,从而奠定了行政算法自动化决策的基础,提升了政府数字治理能力和问题响应能力。但与此同时,在大模型集成架构深度介入行政算法决策过程中,也带来了数据安全、程序正义以及权力运行结构上的风险和挑战。有鉴于此,本文拟从制度上进行回应和规制,一方面,通过数据分级确权与公共数据信托制度重构数据治理边界,并且借助动态解释机制提升算法的可解释性和透明度;另一方面,在算法设计过程中嵌入比例原则和反歧视规则等范式,并建立算法决策的主体责任绑定制度。

关键词: 大模型集成架构, 行政算法决策, 数据安全, 程序正义, 法律规制

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