The extent to which a user anchors decisions during AI interaction in their own explicit value system, using personal criteria as the reference point when appraising or accepting AI output. A graded reliance on internally held standards.
STATE. Rated from think-aloud or annotated decisions: the share of AI-output acceptance/rejection decisions the user justifies by reference to stated personal values or criteria, versus deferring without such reference. The construct is the degree of value-anchored appraisal.
Proposed measurement protocol (not yet empirically validated): Rater coding of decision rationales (think-aloud or written) for explicit value-criterion references; could be reported as proportion of value-anchored decisions; inter-rater agreement would be assessed via Cohen's kappa on the rationale-type code.
https://andreasehstandlicenseofclarityloc.github.io/augmanitai-periodic/#topic-meta-reflection