Interpretive inertia
Interpretive inertia designates an AI system’s resistance to modifying an already stabilized interpretation, even after correction or clarification of the canon. The more an interpretation has spread and been repeated, the more costly it becomes to displace.
In an interpreted web, interpretive inertia explains why “correcting a page” does not necessarily correct responses. A representation can persist through synthesis habits, dominant neighborhood, or residual traces, producing durable interpretive debt.
Definition
Interpretive inertia is the phenomenon where:
- an interpretation becomes default in responses;
- canonical corrections exist;
- but the system continues producing the old representation, or a hybrid version.
Interpretive inertia can be caused by competing signal dominance, remanence, selection mechanisms, or the absence of enforceable evidence (trace, fidelity) making the correction activatable.
