AI代理需兼顾技术与法律，解决忠诚度和披露问题。
AI Agents and the Law
- 对比计算机科学与法律对代理权的理解差异
- 指出当前AI缺乏对第三方互动中忠诚度的考量
- 为负责任的AI代理开发提供法律融合路径
随着AI变得更具自主性，其在技术和法律层面均面临挑战，若要实现提升经济生产力与效率的潜力，必须加以应对。本文从技术和法律双重视角分析，当AI系统开始代表用户直接执行任务时，情况如何变化。我们发现，计算机科学与法律虽都关注代理行为的不明确性，并有相应机制确保代理行为符合设计者或委托人意图且不越界，但计算机科学尚未充分理论化法律中的忠诚与披露等核心概念。首先，探讨了代理法中的默示权限与AI中价值对齐原则的关联，后者要求在目标不完整时仍能正确执行；其次，揭示了现有计算机科学对代理理解在披露与忠诚方面的缺失，忽视这些可能引发AI电商代理的意外后果。通过暴露这些差距，本文指明了负责任的AI代理发展的前进方向。
原文摘要 · Abstract (English)
As AI becomes more "agentic," it faces technical and socio-legal issues it must address if it is to fulfill its promise of increased economic productivity and efficiency. This paper uses technical and legal perspectives to explain how things change when AI systems start being able to directly execute tasks on behalf of a user. We show how technical conceptions of agents track some, but not all, socio-legal conceptions of agency. That is, both computer science and the law recognize the problems of under-specification for an agent, and both disciplines have robust conceptions of how to address ensuring an agent does what the programmer, or in the law, the principal desires and no more. However, to date, computer science has under-theorized issues related to questions of loyalty and to third parties that interact with an agent, both of which are central parts of the law of agency. First, we examine the correlations between implied authority in agency law and the principle of value-alignment in AI, wherein AI systems must operate under imperfect objective specification. Second, we reveal gaps in the current computer science view of agents pertaining to the legal concepts of disclosure and loyalty, and how failure to account for them can result in unintended effects in AI ecommerce agents. In surfacing these gaps, we show a path forward for responsible AI agent development and deployment.
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