Do Children Trust AI, and Should They? Designing and Validating a Child-Centred K-AI Trust Scale for Intelligent Systems

要旨

Most trust metrics for intelligent systems are developed for adults, relying on complex reasoning and language that do not align with children’s developmental stages. As intelligent systems increasingly engage with young users, evaluating trust in child-AI interaction has become an urgent concern in HCI. In this paper, we present the iterative refinement and validation of the K-AI Trust Questionnaire, a child-centred instrument that integrates dispositional and situational trust components grounded in child-rights principles. Dispositional trust is captured through a child-adapted Propensity to Trust Technology (PTT), while situational trust is assessed through post-interaction items reflecting children's experience with AI. Starting with a sample of 289 children, we conducted psychometric analyses and exploratory testing, culminating in a confirmatory factor analysis on a subsample of 85 children. Results supported a unidimensional structure consistent with the PTT, and highlighted the limitations of adult-oriented scales, underscoring the need for developmentally appropriate tools for trustworthy child-AI design.

受賞
Best Paper
著者
Grazia Ragone
University of Bari, Bari, Italy
Paolo Buono
University of Bari Aldo Moro, Bari, BA, Italy
Judith Good
University of Amsterdam, Amsterdam, Netherlands
Rosa Lanzilotti
University of Bari, Bari, Italy
動画

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: AI-Assisted Clinical Diagnosis and Reasoning

Auditorium
7 件の発表
2026-04-16 20:15:00
2026-04-16 21:45:00