Drift Phenomena

Drift phenomena are the ways that knowledge systems change over time, often invisibly, leading to errors that look like contradiction but are actually about temporal mismatch.

Semantic Drift

• Definition Drift — when a term's meaning shifts across time or communities
• Meaning Loss — when claims become obsolete because their terms no longer apply

Environmental Drift

• Nonstationarity — when the underlying process that produces data changes over time

System Drift

• Model Collapse — degradation from training on AI-generated data
• Correction vs Drift — what happens when fixing errors costs more than letting them propagate

Defense

The Dialectical Graph tracks drift explicitly by separating definitions from claims and recording when and where claims were intended to apply. This prevents false contradictions from temporal mismatch.