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#human-computer interaction Preprint Open access

A Scale For Value Alignment In Human-AI Interaction

Lena Hegemann Steeven Villa Hyemin Bang Mitchell L. Gordon Antti Oulasvirta Robin Welsch Patrick Ebel
Oct 2026
Human-computer Interaction

Abstract

Value alignment is a central objective in AI and HCI research, yet no validated instrument measures how users perceive it. This gap hampers the comparison and accumulation of findings and limits the effectiveness of applications, where understanding users' viewpoints is critical. We construct and evaluate a 13-item psychometric scale that measures perceived value alignment across two components: value understanding and value manifestation. It is based on a large item pool drawn from prior empirical studies, filtered by experts, and finally assessed by users (N=607) across diverse AI scenarios. Confirmatory factor analysis on an independent sample (N=259) confirmed the two-factor structure and high internal consistency for both subscales. Using optimization, we also derived a 6-item short form for quick administration. The scale is a reliable measure, providing HCI researchers with a common evaluation metric across contexts.

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