Gender similarity effects in human-AI interaction
Development and validation of the Behavioral AI Anthropomorphism Scale (BAAS) and implications for trust and gender attribution
Publication date
2026-03-24
Document type
Forschungsartikel
Author
Publisher
Elsevier Ltd.
Series or journal
Computers in Human Behavior Reports
ISSN
Periodical volume
22
Article ID
101003
Peer-reviewed
✅
Part of the university bibliography
✅
Funding(s)
Language
English
Keyword
Behavioral anthropomorphism
Trust in AI
Gender attribution
Conversational agents
ChatGPT
Scale development
Abstract
As conversational artificial intelligence becomes increasingly embedded in everyday life, users routinely apply human social norms to chatbot-based systems. Yet most existing instruments capture anthropomorphism as self-reported attributions or perceptions of human-likeness, whereas enacted interactional behaviors in dialogue remain undermeasured. Across a large and diverse English sample (N = 933), we introduce and validate the Behavioral AI Anthropomorphism Scale (BAAS), the first behavioral self-report instrument assessing enacted reciprocity and socioemotional alignment with AI chatbots. Using a random-split sample approach, exploratory and confirmatory factor analyses supported a robust two-factor structure and a hierarchical higher-order model (CFI = .966, TLI = .949, RMSEA = .079, SRMR = .044), yielding strong reliability (α = .83 - .91; ω = .85 - .92) and discriminant validity (HTMT = .85) relative to psychological anthropomorphism. Behavioral anthropomorphism emerged as a central mechanism shaping trust: it explained incremental variance beyond self-reported psychological anthropomorphism (ΔR²= .06–.07) and mediated associations between AI use frequency, gender attribution, and trust. Gender similarity effects further revealed that men anthropomorphized AI more when perceiving it as male, whereas women did so when perceiving it as female, with parallel patterns for trust. These findings suggest that trust in AI is more closely linked to self-reported interaction behaviors than to attribution- and perception-based anthropomorphism. By identifying behavioral anthropomorphism as a key relational process in AI chatbot interaction, this work provides a validated tool and a theoretical foundation for designing socially calibrated and user-sensitive conversational AI systems.
Description
This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Version
Published version
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Metadata only access