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Legal AI System Design

Structural reliability

A research system is structurally reliable for a class of error when the information needed to catch that error is recorded in its stored representation and consulted by a defined, repeatable check, so that the error is impossible or reliably detectable.

First used in The Promise Fulfilled

The claim is deliberately modest. Structural reliability does not mean a tool never errs. It means the error class is handled by a procedure someone could inspect, rerun and audit.

Its counterpart is opportunistic reliability. The pair converts an unanswerable evaluation question (is this tool accurate?) into an answerable one: for which classes of error does the tool have a defined detection procedure, and for which is it relying on what retrieval happens to surface? Vendors can answer that question, and a refusal to answer is itself information.

Institute papers derive five minimum representation requirements for structural reliability in legal research: proposition-level extraction, typed adversarial metadata, authority-health composites, jurisdiction-hierarchy modeling, and rejected-argument indexing.

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