Beyond Rational Choice: AI–Quantum Probability for Adaptive Policy Design in Korea's Demographic Crisis

Abstract South Korea faces an unprecedented demographic crisis, with fertility now at a record low despite the government's substantial pronatalist spending. Traditional cash incentives have yielded marginal results, and this study introduces a quantum probability (QP)-based artificial intelligence framework to model dynamic public sentiment toward South Korea's population policy. Drawing on a rich dataset of 5,430 citizen comments from government-managed platforms, it applies KoBERT for semantic embedding, clusters belief states using k-means, and simulates preference shifts with QP dynamics. The model not only outperforms classical baselines in predicting preference reversals (72% accuracy) but also reduces cross-entropy loss and improves F1 scores, capturing nonlinear, emotionally ambivalent opinion patterns that rational models often miss. These findings make a significant contribution to the advancement of the field, offering practical implications for informed public policy decision-making.