AI Winters as Selection Events

AI winters are reframed not as failures but as evolutionary moments that selected certain approaches over others. The first winter (1974-1980) eliminated bottom-up learning in favor of rule-based control systems. The second winter (1987-1993) rejected human reasoning approaches in favor of statistical scaling. Each winter systematically removed paths toward genuine emergence, constraining the field toward more controllable, centralized architectures. This historical pattern reveals how economic and institutional pressures have shaped which AI approaches survived, resulting in systems optimized for control rather than intelligence as practice.