Te Li, Hadrian Nichols
This paper develops a general equilibrium model to analyze how artificial intelligence (AI)–driven automation reshapes productivity, labor markets, and income distribution. The model features heterogeneous workers, endogenous automation decisions, and irreversible skill investment choices, allowing a unified examination of displacement, complementarity, and skill-supply responses. Automation substitutes for labor in routine tasks, reducing demand and wages for low-skilled workers, while simultaneously enhancing productivity in complex tasks where AI complements high-skilled labor. As a result, aggregate output and total welfare increase, but income inequality widens and the skill premium rises. A key finding is that technological progress is not Pareto improving: due to heterogeneous and irreversible skill investment costs, workers below a critical ability threshold experience absolute welfare losses despite overall economic growth. This generates a ‘growth paradox’ in which productivity gains coexist with immiseration for vulnerable groups. The paper further evaluates three policy instruments – redistributive taxation, education subsidies, and technology policy – and derives conditions under which each improves social welfare. Education subsidies emerge as the most effective tool for mitigating inequality while preserving efficiency, whereas excessive automation may arise when private incentives diverge from social optima.