No Last Mile: A Theory of the Human Data Market

TL;DR

This paper models structured human-data work as a persistent, essential input in AI development, showing that maintenance and improvement demand continue indefinitely even as models improve, leading to a steady-state labor share.

Contribution

It introduces a novel theory of the human data market, emphasizing the ongoing role of human data work as a durable, productive input in AI systems.

Findings

Steady-state labor share of 5-7% in long run

Persistent maintenance demand despite model improvements

Reallocation towards low-maturity task families

Abstract

The standard framing treats structured human-data work as transitional, a bridge between today's imperfect models and a future state where automation is complete. We challenge this view by modeling structured human data as a persistent production input: evaluation, rubric-based judgment, auditing, exception handling, and continual updates that convert raw model capability into dependable, deployable performance. These activities accumulate into a reusable AI capability stock that raises productivity by improving reliability on existing tasks and by expanding the frontier of task families for which AI can be used at high confidence. Crucially, this capability stock depreciates as tasks and contexts drift, standards evolve, and new edge cases emerge. In a tractable baseline model, an interior steady state implies a closed-form, strictly positive long-run labor share devoted to structured human-data work whenever depreciation is positive, a "no last mile" result in which maintenance demand persists even as models improve. We then microfound aggregate capability with a portfolio of task families featuring diminishing returns, frontier entry, and complementarity, generating reallocation toward low-maturity and bottleneck families and a Roy-style mechanism for within-structured wage dispersion. Finally, we map model objects to observable proxies using standard data layers, and provide a conservative calibration suggesting a 5-7% steady-state structured labor share in the long run.