Does automating labor concentrate power more than augmenting it?

The essay argues the distributive effect of AI depends on whether it augments or automates human labor, and names the automation path's end state "the Turing Trap." "When AI augments human capabilities, enabling people to do things they never could before, then humans and machines are complements," and complementarity "implies that people remain indispensable for value creation and retain bargaining power in labor markets and in political decision-making." By contrast, "when AI replicates and automates existing human capabilities, machines become better substitutes for human labor and workers lose economic and political bargaining power." A fully automated economy "could, in principle, be structured to redistribute the benefits from production widely," but "the beneficiaries would be in a weak bargaining position to prevent a change in the distribution that left them with little or nothing" — "the peril of being trapped in an equilibrium where those without power have no way to improve their outcomes."

The mechanism the essay gives is incentive, not technical necessity. Pursuing human-like artificial intelligence (HLAI) — machines built to pass the Turing Test — has drawn "the best and brightest minds" toward what pioneer Nils Nilsson called "strong AI," implicitly or explicitly aimed at "fully automating human labor, rather than assisting or augmenting it." The essay reports both paths can raise labor productivity, but only augmentation has historically paid workers: "the market price [of an hour of human labor] as measured by median wages has grown more than ten-fold since 1820," evidence offered for augmentation, not automation, being "far more important throughout most of the past two centuries." It closes with an explicit analogy to the free-trade bargain — grow the pie through comparative advantage, then compensate the losers — which "hasn't worked as they had hoped," fueling a populist backlash; the essay warns the same dynamic is "already underway with AI."

This is the political-economy argument that Why do firms build automating AI instead of pro-worker AI? later operationalizes into a firm-level taxonomy and nine policy levers — where Brynjolfsson frames automation-versus-augmentation as a question of bargaining power and political equilibrium, Acemoglu, Autor and Johnson break "automation" and "augmentation" each into finer categories and ask why firms under-invest in the pro-worker ones. It also supplies a labor-market mechanism for Does incremental AI replacement erode human influence over society?: loss of bargaining power from substitution is one concrete channel by which human influence over systems could erode. And it shares an endpoint with What happens to human wages in an AGI economy?, though that paper derives the zero-labor-share outcome from a calibrated model while this essay states it as a qualitative risk to be averted by choice of technology design.

The essay offers no firm-level data on how AI investment currently splits between automating and augmenting types, no test for when an economy has actually entered a "trapped" equilibrium, and no causal isolation of augmentation (versus population growth, institutions, or labor organizing) in the wage-growth figure it cites. At the strength the argument allows, it is a call to redirect R&D and policy incentives toward augmentation — not a forecast of which path current AI investment is actually taking.