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◆ International Journal of Human-Computer Interaction2026-02-25· Scale (ratio)

Moral Suspension in Human-GenAI Interaction: Scale Development and Validation for Chinese Emerging Adults

Zhirui Chen, Wenchen Guo, Yiyang Zhang, Xihui Liu, Biao Li, Hailiang Wang

原始摘要(英文原文)· Original abstract
The emergence of generative artificial intelligence (GenAI) has introduced unprecedented ethical complexity into contemporary human-GenAI collaboration, especially among emerging adults (individuals aged 18–29). Traditional moral theories emphasize users’ active rationalization processes but do not fully capture the passive ethical ambiguity that arises in interactions with opaque and autonomous GenAI systems. To address this gap, this study introduces and operationalizes the construct of Moral Suspension, defined as a psychological state characterized by interactive environmental complexity, ambiguity in responsibility attribution, and passive responsibility exemption during GenAI-assisted tasks. Guided by social cognitive theory, we developed the Moral Suspension Scale (MSS) and employed a rigorous multi-phase validation process, including expert review, pilot testing, exploratory and confirmatory factor analyses, and measurement invariance assessment. Data were collected from Chinese emerging adults (n = 785) with practical experience in AI-assisted academic or creative activities. The finalized MSS consists of 38 items and demonstrates strong reliability, model fit, and invariance across gender. The MSS provides a robust instrument for assessing moral psychological ambiguity in GenAI contexts, advancing theoretical integration between moral psychology and human-GenAI interaction. This research contributes an empirical foundation for the ethical evaluation of GenAI and offers practical guidance for responsible system design and digital ethics education for younger generations.
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