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Interpretive governance, semantic architecture, and machine readability.

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Glossary

Glossary: sustainability, debt, correction

Interpretive debt, interpretive sustainability, canonical fragility, version power, correction budget, and resorption: structuring the maintenance of a canonical truth over time, despite drift and inertia in AI systems.

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CollectionGlossary
TypeGlossary
Domainsustainability-debt-correction
Published2026-02-20
Updated2026-03-11

Glossary: sustainability, debt, correction

This family groups the notions that describe the real cost and discipline needed to maintain a canonical truth over time, in a web interpreted by AI systems. The issue is not merely to “correct” a response: it is to prevent regression, avoid inertia, and make correction sustainable.

Each entry links to: a canonical definition (if it exists), a framework (if applicable), and related pages for moving from diagnosis to execution.

Quick access

Terms in the “sustainability, debt, correction” family

Interpretive debt

Accumulation of gaps between a canon (declared truth) and the interpretation returned by AI systems, until correction becomes costly, slow, or unstable.

Interpretive sustainability

Capacity of a system (and a corpus) to maintain a canonical truth without letting correction and maintenance costs explode.

Correction budget

Recurring effort required to prevent regressions, correct drifts, and stabilize outputs over time (rather than a one-time effort).

Interpretive correction (resorption)

Process of resorbing canon-output gaps, with evidence discipline, prioritization, and anti-regression mechanisms.

Canonical fragility

Vulnerability of a canon when its truth depends on too few surfaces, formats, or artifacts: a local break suffices to cause global interpretation drift.

Version power

Principle that interpretive correction must be maintained and versioned like software: without version discipline, corrections regress and ambiguities reappear.

Previous page: Glossary: agentic, RAG, environments

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Glossary: drifts and interpretive inertia

Interpretive hallucination, smoothing, inertia, remanence, and state drift: understanding meaning drifts in generative AI systems and linking them to canonical definitions and frameworks.

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Glossary: agentic, RAG, environments

Agentic, non-agentic systems, RAG, open web vs closed environments, response conditions, risk matrix: mapping the application surfaces of interpretive governance and linking canonical frameworks.

Glossary
Glossary: canon, authority, non-response

Authority boundary, interpretability perimeter, canonical silence, legitimate non-response, authority conflict, and governed negation: clarifying what AI can infer, and what it must refuse.

Glossary
Glossary: capture, contamination, collisions

Interpretive capture, neighborhood contamination, interpretive collision, and invisibilization: understanding the signal warfare that distorts an entity truth in AI responses, and linking these phenomena to canonical definitions and frameworks.

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Glossary of interpretive governance

Glossary of interpretive governance. Glossary entry within interpretive governance, semantic architecture, and AI systems.

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Glossary: proof, audit, and observability

Proof of fidelity, interpretation trace, canon-output gap, interpretive observability, and version power: a family of concepts for audit and proof in an AI-interpreted web.

Glossary