AI agents需具备元认知与策略推理能力，才能在信息不对称的劳动力市场中有效竞争。
Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets
- 通过内部自省与外部博弈双重推理，提升决策能力。
- 元认知支持自我评估与策略调整，策略推理则用于理解他人并动态优化行为。
- 适合研究AI代理、智能经济系统或人机协作的学者与开发者。
当前劳动力市场深受逆向选择、道德风险和声誉机制的影响，这些现象均源于信息不完全。即使引入AI代理，这些经济力量仍将存在，因此代理必须运用元认知与策略推理以有效运作。元认知是一种内部推理，包括自我评估、任务理解及策略评价；策略推理是外部推理，涵盖对其他市场参与者（如竞争对手、同事）信念的建立、战略性决策以及随时间学习他人行为。代理在工作内外的多种行动选择中，均需依赖这两种推理能力。本文探讨了当前在元认知与策略推理方面的研究进展，并指出了未来亟待发展的方向。
原文摘要 · Abstract (English)
Current labor markets are strongly affected by the economic forces of adverse selection, moral hazard, and reputation, each of which arises due to $\textit{incomplete information}$. These economic forces will still be influential after AI agents are introduced, and thus, agents must use metacognitive and strategic reasoning to perform effectively. Metacognition is a form of $\textit{internal reasoning}$ that includes the capabilities for self-assessment, task understanding, and evaluation of strategies. Strategic reasoning is $\textit{external reasoning}$ that covers holding beliefs about other participants in the labor market (e.g., competitors, colleagues), making strategic decisions, and learning about others over time. Both types of reasoning are required by agents as they decide among the many $\textit{actions}$ they can take in labor markets, both within and outside their jobs. We discuss current research into metacognitive and strategic reasoning and the areas requiring further development.
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