公共部门需重构监督机制以应对智能代理的持续运行挑战
Oversight Structures for Agentic AI in Public-Sector Organizations
- 提出五维治理框架：跨部门协作、全面评估、安全强化、操作可见性、系统审计
- 发现现有监督体系在持续监控、融合运营与协同上均面临加剧困境
- 为公共部门设计适配其约束的智能代理监督方案，兼顾可行性与责任
本文发现，智能代理系统的引入加剧了公共部门传统监督机制的固有挑战——这些机制依赖孤立的合规单元和周期性审批，而非持续集成的监管。我们识别出五个负责任部署智能代理的关键治理维度：跨部门实施、全面评估、增强的安全协议、操作可见性以及系统性审计。通过文献综述与对人工智能相关岗位公务员的访谈，采用混合方法评估现有监督结构应对这些挑战的能力。研究发现，代理监督放大了三大现有治理难题：持续监督、治理与运营能力的深度整合、跨部门协调。为此，我们提出既调整制度结构又设计契合公共部门限制的代理监督路径。
原文摘要 · Abstract (English)
This paper finds that the introduction of agentic AI systems intensifies existing challenges to traditional public sector oversight mechanisms -- which rely on siloed compliance units and episodic approvals rather than continuous, integrated supervision. We identify five governance dimensions essential for responsible agent deployment: cross-departmental implementation, comprehensive evaluation, enhanced security protocols, operational visibility, and systematic auditing. We evaluate the capacity of existing oversight structures to meet these challenges, via a mixed-methods approach consisting of a literature review and interviews with civil servants in AI-related roles. We find that agent oversight poses intensified versions of three existing governance challenges: continuous oversight, deeper integration of governance and operational capabilities, and interdepartmental coordination. We propose approaches that both adapt institutional structures and design agent oversight compatible with public sector constraints.
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