AI Winters as Evolutionary Selection

Historical AI winters (1974-1980 and 1987-1993) are reframed not as failures but as selection events that systematically chose control over emergence. The first winter rejected bottom-up learning in favor of rule-based systems; the second rejected human-like reasoning for statistical scaling. This pattern reveals how technological development has been shaped by preferences for centralized control rather than distributed intelligence. Understanding these winters as deliberate selections rather than accidents illuminates current debates about AI development and suggests that future progress depends on choosing different values—favoring emergence, agency, and distributed practice over centralization.