Cognitive Debt: AI as Intellectual Leverage and the Dynamics of Systemic Fragility
For AI researchers and policymakers, it provides a theoretical framework to understand systemic risks from AI substitution, though the analysis is purely formal without empirical validation.
The paper develops a formal theory of cognitive debt, showing that rational agents over-adopt substitutive AI due to deferred costs and externalities, leading to systemic fragility and a potential 'cognitive Minsky moment' where subjective risk decreases while true fragility increases.
We develop a formal theory of cognitive debt: the stock of unverified reasoning obligations that accumulates when individuals use AI as a substitute rather than a complement for first-principles cognition. The model features two state variables per agent, cognitive capital and cognitive debt, and a multiplicative production technology in which cognitive capital functions as collateral that determines the return to AI adoption. We establish six propositions. Rational agents incur positive cognitive debt because the costs are deferred, partially external, and masked by short-run productivity gains. Tranquil periods lower subjective risk assessments, raise AI substitution intensity, and compound leverage, generating a cognitive Minsky moment in which subjective risk falls while true systemic fragility rises. Expected crisis losses are convex in aggregate leverage. Post-crisis, output-target pressure can produce a false-correction loop in which agents patch AI failures with more AI. The decentralised equilibrium over-adopts substitutive AI relative to the social optimum because of systemic risk, cognitive public goods, and arms-race externalities. In a two-type heterogeneous-agent economy, high-cognitive-capital agents adopt AI more intensively and may eventually erode their unaided cognitive capital below that of initially lower-skilled agents.