The Economics of AI

Catalog description

This course examines the economics of artificial intelligence and technological change. Rather than focusing on how to use AI directly, the course explores AI's likely economic impact by drawing on lessons from past periods of transformative technological change, including electrification, railroads, aviation, computers, and the Internet. The course addresses several core questions. First, it considers why even powerful new technologies historically took decades to achieve widespread adoption and measurable productivity gains, and what this implies for AI's trajectory. Second, it examines the distinction between value creation and value capture, asking which layers of the AI value chain — from chip makers to foundation models to enterprise applications — are likely to earn sustained returns. Third, the course analyzes AI's impact on labor markets, exploring whether AI will primarily augment or automate workers across different occupations and skill levels, and how to think about jobs in terms of tasks rather than roles. Fourth, it investigates the macroeconomic productivity puzzle: why firm-level efficiency gains from AI may take years to appear in aggregate data, and whether AI will ultimately prove inflationary or deflationary. Fifth, the course explores the intersection of AI with the broader electrification revolution and the global competition to lead in semiconductors, clean energy, and AI infrastructure. Finally, it examines the political and regulatory responses that technological revolutions inevitably provoke, from historical antitrust movements to contemporary debates over autonomous vehicles and AI governance. Students engage with academic research, policy analysis, and journalism, and develop their analytical skills through memo assignments, a group presentation, class discussion, and a final paper.