誰為認知勞動定價？——代理時代的計算錨定工資

Who Prices Cognitive Labor in the Age of Agents? Compute-Anchored Wages

May 8, 2026

作者: Siqi Zhu

cs.AI

摘要

关于AI代理经济学的一个自然直觉是，由于代理能够以极低的边际成本复制，当其与人类劳动高度替代时，代理劳动可能以高度弹性的方式供给，从而对认知劳动工资施加下行压力。我们认为这一框架在机制上存在偏差，但结论部分正确，而这一纠正对理论与政策均具有意义。代理并非劳动本身；它们是能将计算资本K_c转化为有效认知劳动单位L_A的生产技术。一旦认识到这一点，决定均衡工资的弹性供给边界便从劳动市场转移至计算资本市场。基于经典的要素定价框架（mankiw2020），我们推导出基于计算的工资上限（CAW）约束：在人类劳动与代理生产的认知劳动可相互替代的任务中，竞争性人类工资的上限为λ·k·r_c，其中r_c为计算资本的租金率，k为生产一单位有效代理认知劳动所需的计算强度，λ为人类与代理的相对生产率。我们通过常数替代弹性（CES）聚合将该结果一般化，区分可替代任务与互补任务，并讨论要素份额影响。结论简明：认知劳动的价格制定者已不再是劳动市场。

English

A natural intuition about the economics of AI agents is that, because agents can be replicated at very low marginal cost, agent labor may be supplied highly elastically, placing downward pressure on cognitive-labor wages when it closely substitutes for human labor. We argue this framing is wrong in mechanism but partially correct in conclusion, and that the correction matters for both theory and policy. Agents are not labor; they are a production technology that converts compute capital K_c into effective units of cognitive labor L_A. Once this is recognized, the elastic-supply margin that anchors the equilibrium wage migrates from the labor market to the compute capital market. Building on the classic factor-pricing framework mankiw2020, we derive a Compute-Anchored Wage (CAW) bound stating that, on tasks where human and agent-produced cognitive labor are substitutes, the competitive human wage is bounded above by λcdot k cdot r_c, where r_c is the rental rate of compute capital, k is the compute intensity of one effective agent-produced cognitive labor unit, and λ is the relative human-to-agent productivity. We generalize the result through constant elasticity of substitution (CES) aggregation, separate substitutable from complementary tasks, and discuss factor-share consequences. The conclusion is concise: the price-setter for cognitive labor is no longer the labor market.