从自主性等四维度刻画AI智能体，助力治理与对齐
Characterizing AI Agents for Alignment and Governance
- 从自主性、效能、目标复杂度、通用性四维建模智能体
- 提出智能体画像框架，区分任务专用到通用系统的治理差异
- 为开发者与政策制定者提供对齐社会目标的治理参考
构建有效的人工智能代理治理机制需要深入理解其核心属性及其与部署和运行的相关性。本文聚焦自主性、效能、目标复杂度和通用性四个维度，为每个维度提出不同梯度，并指出各维度带来的独特设计、操作与治理问题。基于该框架，我们构建了不同类型智能体的‘代理画像’，揭示从特定任务助手到高度自主通用系统所面临的跨领域技术与非技术治理挑战。通过描绘关键变异轴线与连续性，该框架为开发者、政策制定者及公众提供了与集体社会目标更契合的治理方案制定机会。
原文摘要 · Abstract (English)
The creation of effective governance mechanisms for AI agents requires a deeper understanding of their core properties and how these properties relate to questions surrounding the deployment and operation of agents in the world. This paper provides a characterization of AI agents that focuses on four dimensions: autonomy, efficacy, goal complexity, and generality. We propose different gradations for each dimension, and argue that each dimension raises unique questions about the design, operation, and governance of these systems. Moreover, we draw upon this framework to construct "agentic profiles" for different kinds of AI agents. These profiles help to illuminate cross-cutting technical and non-technical governance challenges posed by different classes of AI agents, ranging from narrow task-specific assistants to highly autonomous general-purpose systems. By mapping out key axes of variation and continuity, this framework provides developers, policymakers, and members of the public with the opportunity to develop governance approaches that better align with collective societal goals.
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