arXiv:2608.26626cs.MAcs.AI2026-08

构建跨组织AI代理交互风险框架,明确管控责任边界

Risks and Controls for Multi-Agent Systems: an analytical framework for deployment of AI agents across organisational boundaries

  • 划分三类部署层级:单一治理、联邦治理与开放环境
  • 识别跨组织交互下的风险因素与失效模式,强调控制权缺失问题
  • 适合政策制定者与企业AI负责人参考,解决协同治理难题

本报告提出一个分析框架,帮助组织、政策制定者和研究人员理解当人工智能代理彼此交互时产生的风险,以及这些风险在跨越组织边界后如何演变,并探讨可能的管控措施。随着组织部署AI代理,这些代理将越来越多地在内部、与合作伙伴、客户及供应商的代理,以及开放互联网上的未知对手之间进行交互。故障可能源于交互本身,一旦交互超出组织边界,就没有任何单一组织能完全观测、控制或治理。报告定义了三个部署层级:单一治理(一个组织管理所有代理)、联邦治理(多个组织在共同规则下部署于共享环境)和开放环境(代理在无中心权威的情况下运行,标准仅自愿采纳)。在每个层级中,报告分析了风险因素、失效模式及可用控制手段,并指出控制责任方;对无人可承担的空白,则界定所需集体行动。

原文摘要 · Abstract (English)

This report presents a framework to help organisations, policymakers and researchers reason about the risks that emerge when AI agents interact with each other, how those risks change as interactions cross organisational boundaries, and the controls that may help address them. As organisations deploy AI agents, those agents will increasingly interact with each other: inside the organisation, with the agents of partners, customers and suppliers, and with unknown counterparties on the open internet. Failures can emerge from the interactions themselves, and once those interactions cross an organisation's perimeter, no single organisation can fully see, control or govern them. The report introduces three deployment tiers, defined by the minimum common governance binding any two interacting agents: singular governance, where one organisation governs every agent; federated governance, where multiple organisations deploy into a shared environment under agreed rules; and open environments, where agents operate with no central authority and shared standards are adopted voluntarily if at all. Within each tier, the report examines risk factors, failure modes and available controls. It identifies who is positioned to apply the controls, and where no actor is positioned to act, it characterises the gap and the collective action required to close it.

AI治理多智能体风险分析

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