Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We develop a tractable model of Artificial Intelligence (AI) as self-learning capital that improves through application. An AI sector and an applied research (AR) sector produce inputs for a final goods firm and compete for high-skilled labor, benefiting from mutual spillovers. The economy undergoes four tipping points, with initial AI growth driven by entrepreneurs and skilled workers, before reversing direction. In the steady state, AI advances autonomously via spillovers from AR. We show that well-designed subsidies and taxes — such as an AI tax once learning becomes self-sustaining — can guide labor allocation toward socially optimal outcomes.