The Division of Understanding: Specialization and Democratic Accountability

I develop a model in which occupational knowledge links the organization of production to democratic performance. In production, specialized knowledge allows workers to perform narrow tasks efficiently, while cross-field knowledge allows coordinators to keep the system coherent. In politics, voters bring their occupational knowledge to the ballot. Voters lacking the relevant knowledge have difficulty distinguishing good policies from bad ones, relaxing the electoral pressure towards high-quality policymaking. I show that productive efficiency can sacrifice knowledge needed to understand cross-domain policies. Competitive markets reward knowledge for its productive contribution while leaving its political value unpriced; I identify when this externality creates over-specialization and show that its welfare cost can grow with policy complexity. When policies are in the common interest, I show that expanding coordinators' responsibilities can maximize welfare by increasing their employment share and voters' average policy understanding. When policies have redistributive consequences, broadening specialists' knowledge can instead be preferable: reducing inequality in policy understanding improves the allocation of public spending. I use the framework to study the political effects of technology shocks, showing how AI adoption at different layers of the organizational hierarchy affects welfare and when firms' incentives conflict with social efficiency.