Temporal Decay and Information Entropy

Entropy—the natural tendency of all systems toward disorder and information loss—governs both physics and attention. In natural attention ecology, information decays as it ages; we remember vivid recent events more clearly than distant ones. Algorithmic systems that counteract this natural entropy by continuously recycling past content create what might be called political time-sickness: citizens trapped in perpetual controversy rather than experiencing history's natural forgetting. Laozi embraces natural processes rather than fighting them; temporal decay is nature's way of clearing space for new information. Platforms that work with entropy rather than against it allow old stories to naturally fade while preserving them in archives for those who seek historical context. Search functions serve better than algorithmic resurrection for accessing past events. This principle matters profoundly for political psychology: humans require the ability to move past conflict, to experience genuine turning points. Algorithms that enforce eternal recurrence of past controversies prevent healing and growth. Taoist algorithmic politics recognizes that information entropy is not a bug but a feature—it creates the temporal distance necessary for wisdom, reflection, and forgiveness.