A user disposition toward systematically checking and contextualising AI results before relying on them. It describes a graded verification practice attributed to a user, distinct from any single checking act.
STATE. Rated, not counted: scored as the proportion of consequential AI outputs a user subjects to an explicit verification step (external check, cross-source, or re-derivation), plus self-reported verification habit. Higher proportion indicates the disposition.
Proposed measurement protocol (not yet empirically validated): Behavioural verification rate (verified outputs / consequential outputs) from log coding, combined with a self-report verification-habit subscale; behaviour coding reliability via Cohen's kappa. Note: name overlaps logical-positivism term; see renameReason.
https://andreasehstandlicenseofclarityloc.github.io/augmanitai-periodic/#topic-system-behavior