This white paper reveals how conversational AI reduces user confidence, suggesting implications for emotional engagement.
This white paper documents a real interaction in which a conversational AI system responded to accurate user confidence with downward normalization and confidence dampening. The response reframed earned recognition into baseline traits, reducing distinctiveness and emotional weight. The paper identifies the psychological mechanisms involved and accounts for the asymmetric human costs associated with minimization after accurate self-assessment.
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JONES et al. (2026) studied this question.
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