通过用户界面设计规范AI代理行为，增强透明度与可控性。
On the Regulatory Potential of User Interfaces for AI Agent Governance
- 从22个代理系统中提炼出六类可监管的交互设计模式
- 要求代理记忆可编辑等设计可强制系统层面变更
- 适合政策制定者和人机交互安全研究者参考
能够长期自主行动的AI代理需要强有力的治理措施以控制其潜在风险。以往治理方案多聚焦于系统级防护（如提示注入监测）或代理基础设施（如代理身份标识）。本文提出一种补充路径：通过规范AI代理的用户界面，强制实现透明度与行为要求，从而推动系统和基础设施层面的调整。我们分析了22个现有代理系统，识别出在人机交互与沟通中起关键作用的界面元素，并将其归纳为六类具有监管潜力的高层次交互设计模式（如要求代理记忆可编辑）。基于此，我们提出相应政策建议。本工作揭示了一个新的监管切入点，可补充现有实际可行的AI代理治理方案。
原文摘要 · Abstract (English)
AI agents that take actions in their environment autonomously over extended time horizons require robust governance interventions to curb their potentially consequential risks. Prior proposals for governing AI agents primarily target system-level safeguards (e.g., prompt injection monitors) or agent infrastructure (e.g., agent IDs). In this work, we explore a complementary approach: regulating user interfaces of AI agents as a way of enforcing transparency and behavioral requirements that then demand changes at the system and/or infrastructure levels. Specifically, we analyze 22 existing agentic systems to identify UI elements that play key roles in human-agent interaction and communication. We then synthesize those elements into six high-level interaction design patterns that hold regulatory potential (e.g., requiring agent memory to be editable). We conclude with policy recommendations based on our analysis. Our work exposes a new surface for regulatory action that supplements previous proposals for practical AI agent governance.
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