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AI, Output, and Inequality: Why Production Structure Trumps Profit Distribution

This article re‑frames the AI debate from a focus on who profits to an examination of how AI reshapes production. Using everyday analogies—washing machines versus luxury yachts—it shows that broadening output, such as installing household appliances and expanding housing supply, delivers more shared prosperity than redistributing the wealth generated by elite goods. The author advocates for progressive consumption taxes and supply‑side policies that increase aggregate output.

In recent conversations about artificial intelligence, the dominant narrative has been about the distribution of its profits. While the question of who will accumulate wealth is certainly important, a longer‑term and more inclusive metric is the quantity and type of output that AI will enable. A shift in the structure of production – more household appliances, higher‑quality housing, and scalable services – is a stronger driver of widespread living standards than any single taxation policy. ### The Washing Machine Analogy Consider the task of estimating how many washing machines exist in the United States. A rough calculation is straightforward: about 130‑million households, most of which own one washing machine. The number of appliances per household therefore mirrors the number of households, a ubiquitous good that raises average well‑being. In contrast, the number of private yachts larger than 200 feet is minuscule and concentrated in the hands of a tiny elite. The two goods illustrate a core economic principle: widespread ownership of a commodity that satisfies a basic human need leads to broad, diffuse improvements in quality of life, whereas rare, high‑value items amplify inequality. ### Production vs. Consumption Historically, the rise of output has been the most reliable engine of reduced poverty. In the 1950s, telephone operators—hundreds of thousands of jobs—were rapidly displaced by automated switching systems. The workforce displaced found new opportunities in a burgeoning restaurant industry, and the overall volume of output (and consumer choice) increased dramatically. Today, the same pattern can be seen in AI‑enabled manufacturing, autonomous logistics, and intelligent customer service. If AI substitutes for routine human labor while simultaneously creating new, higher‑productivity roles, the net effect is an expansion of output and a flattening of income distribution. ### Luxury Goods as a Mirror of Inequality Luxury yachts, high‑end cars, and other elite commodities are not merely signs of wealth; they are structural outputs that disproportionately benefit a very small segment of the population. A society that produces an excess of mega‑yachts relative to mass‑market goods is inherently less equitable than one that focuses on high‑volume consumer staples. Policies that tax luxury consumption can be more effective than broad corporate profit taxes, because they directly curb the production of items whose utility is limited to a minority. ### Progressive Consumption Taxes The author proposes a steeply progressive consumption tax scheme that targets high‑end goods while leaving average consumers largely untaxed. Such a system encourages the production of essential items—washing machines, efficient appliances, affordable housing—while still providing revenue for public services. Coupled with supply‑side reforms like up‑zoning and the removal of restrictive rent controls, this approach can substantially increase the total volume of goods and services available to the average citizen. ### Housing: The Next Frontier Even in a world where most households already own washing machines, the median American family still faces housing affordability challenges. Building an additional ten million homes—whether through up‑zoning, streamlined permitting, or public‑private partnerships—would dramatically shift the supply‑demand balance. Contrary to the rhetoric that new high‑rise construction drives up costs, evidence suggests that densifying city cores can free up existing single‑family homes for new occupants, thereby lowering overall housing prices. ### A Call to Action for Policymakers The prevailing discourse often conflates poverty reduction with redistributing already‑built wealth. A more strategic focus is on the structure of production. By emphasizing AI‑driven productivity gains and fostering an environment where essential goods can be produced at scale, governments can lift living standards without forcing a redistribution of existing assets. Tariffs, blanket subsidies, and heavy regulatory burdens should be replaced by incentives for innovation, investment in infrastructure, and targeted taxes on luxury consumption. ### Conclusion The narrative around AI should move beyond who will receive the profits and toward understanding how AI can reshape what society produces. A future rich in household appliances, affordable housing, and efficient services will naturally dilute inequality more effectively than any redistribution policy that merely shifts existing wealth. By focusing on output, we can harness AI’s promise to create a more prosperous and equitable society for all.