AI代理的真相：自主与自动的边界
你听到的“AI代理”可能只是自动化，不是真正的自主。这篇论文从笛卡尔的“我思故我在”出发，划了一条线：真正的代理需要系统内部拥有目标、身份、决策、自我调节和学习这五个结构，而不是靠外部拼凑。研究者提出了一个通用代理架构GIC，让AI能像人一样分解目标、演化身份、用世界模型模拟推理，并从真实和模拟经验中自我学习。它不是你明天能用上的，但帮你分清哪些AI只是工具，哪些可能真正自主——这对理解AI风险和潜力很关键。
📄 原文摘要(英文)
What is an agent? What constitutes agency? With the rise of Large Language Model (LLM) systems marketed as ``coding agents'', ``AI co-scientists'', and other ``agentic" tools that promise to drive up productivity, and at the same time, ``existential" concerns such as AI escaping human control with destructive power under a speculative ``machine agency" against humans, it has become essential to clarify where automation ends and agency begins, both for building capable systems and for understanding whether and what to fear. Drawing on Descartes' grounding of agency in independent thought, and on portrayals of autonomous beings in science fiction, we survey the current landscape of AI agents, and analyze agent architectures along five dimensions: goal, identity, decision-making, self-regulation, and learning. Specifically, we argue that genuine agency requires these structures to be internalized within the system itself rather than assembled through external scaffolding. This distinction between agentic systems, whose competence resides in engineered workflows, and agentive systems, whose capabilities (including social interaction) arise endogenously, defines the boundary between systems designed for prescribed tasks, and those capable of operating in the open world with true autonomy. Building on this analysis, we propose the Goal-Identity-Configurator (GIC) architecture for a general-purpose agent model, combining hierarchical goal decomposition, identity evolution, simulative reasoning grounded in a separately trained world model, learned self-regulation, and self-directed learning from both real and simulated experience. Furthermore, we share insight on the auditability, controllability, and safety of agentive systems that possess greater autonomy and ``agency", but remain under human oversight.