ArXiv TLDR

Human-Provenance Verification should be Treated as Labor Infrastructure in AI-Saturated Markets

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2605.03210

Erin McGurk, David Khachaturov

cs.CYcs.AIecon.GN

TLDR

AI-saturated markets will value verified human presence, making human-provenance verification crucial labor infrastructure for future economies.

Key contributions

  • AI will devalue standardized middle-tier labor, creating an asymmetric barbell-shaped economy.
  • Demand shifts to "performative humanity" in labor, valued for relational presence, aesthetics, or accountability.
  • Human-provenance verification systems must be treated as essential labor infrastructure by AI governance.
  • Proposes "constitutive human presence" as the standard for valuing human labor in hybrid AI-human work.

Why it matters

This paper redefines how human labor will be valued in AI-saturated markets, predicting a shift towards "human-provenance premiums." It proposes a framework for understanding this shift and argues for treating human-provenance verification as critical labor infrastructure. This is crucial for future AI governance and economic policy.

Original Abstract

We argue that AI-saturated markets are likely to create Veblen-good premiums, which we term human-provenance premiums, for verified human presence, and hence AI governance should treat human-provenance verification as labor infrastructure. Generative and agentic AI systems lower the cost of many standardized cognitive, creative, and coordination tasks, weakening the scarcity premiums that have supported much middle-tier knowledge work. We argue that this pressure may produce an asymmetric barbell-shaped structure of value capture in advanced economies: high-volume synthetic production controlled by owners of AI infrastructure at one pole, and scarce, high-status human labor valued for verified human presence at the other. We advance three claims. First, AI compresses the value of standardized middle-tier labor by making good-enough synthetic substitutes scalable at low marginal cost, hollowing out the middle of the skill distribution currently categorized by knowledge work. Second, this compression reallocates demand for human labor toward work valued for its visible human character. We term this performative humanity and distinguish three forms of labor: relational presence, aesthetic provenance, and accountability. Third, as these premiums depend on credible verification, AI governance should treat human-provenance systems as labor infrastructure rather than as luxury authenticity labels. To evaluate hybrid human-AI work, we propose constitutive human presence as the relevant standard: human labor retains premium value when human judgment, attention, accountability, authorship, or relational participation is not incidental to the output but constitutive of what is being purchased.

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