Interpretation of AI systems: governance, silence, and canonical reading
The strategic problem is not only what an AI system says. It is how it reads. Interpretation precedes the answer. It determines which source is admissible, which boundary matters, which silence must be preserved, and what the system is even allowed to infer.
This page states the canonical position: AI interpretation must be governed, bounded, and readable against an explicit canon.
Canonical reading
A canonical reading does not mean stylistic rigidity. It means that the system must remain inside the declared perimeter, preserve governed negations, and distinguish what is established from what is inferred or unknown.
Silence is part of interpretation
Silence is not merely the absence of content. In a governed regime, silence can be the correct result when the canon does not authorize a conclusion. The system must therefore know how not to answer.
Why this is a governance problem
Once an interpreted system becomes the first interface to a corpus, its reading choices shape public meaning. If those choices remain implicit, drift becomes normalized.
Machine-first surfaces
The doctrinal and canonical surfaces of this site exist to reduce that drift: canon, dual web, AI usage policy, and machine-first entrypoints form an explicit interpretive environment rather than leaving meaning to probabilistic reconstruction alone.