Interpretive capture
Interpretive capture designates the phenomenon by which an actor (or set of signals) manages to impose a framing in AI systems, to the point where the produced interpretation becomes oriented, stable, and dominant, even if it is not the most legitimate with respect to the canon.
Interpretive capture does not necessarily require explicit falsification. It can result from saturation (volume), lexical hegemony (dominant vocabulary), aggressive semantic neighborhood, or invisibilization of the competing canon.
Definition
Interpretive capture is the situation where:
- a particular framing of a subject becomes the default reading of an AI system;
- this framing results from a signal advantage (density, repetition, coherence, distribution);
- and it reduces the system’s capacity to activate an alternative canon, even if it is more authoritative.
In other words: interpretive capture occurs when AI “learns” a truth by signal domination rather than by declarative legitimacy.
