Abstract

This paper introduces the Curiosity Premium Theory, a conceptual framework proposing that artificial intelligence's compression of information access costs fundamentally restructures the determinants of economic productivity. Where classical human capital theory emphasizes accumulated knowledge stocks operationalized through educational attainment, skill certification, and experience this framework argues that AI-saturated economies increasingly reward a dispositional variable the intrinsic orientation toward continuous, unbounded epistemic expansion. I distinguish between instrumental learners, who acquire knowledge to satisfy immediate utility thresholds, and epistemically curious agents, who engage in open-ended knowledge acquisition as a behavioral disposition. The central claim is that this distinction, previously economically latent, becomes a first-order determinant of productivity differentials as AI democratizes access to information while simultaneously raising the premium on cognitive activities that transcend information retrieval. I develop the theoretical architecture for a Curiosity Capital Index and explore its implications for growth theory, labor economics, and human capital measurement in post-scarcity information environments.