Warmth and Competence in Human-AI Agent Interactions
Warmth and Competence in Human-AI Agent Interactions
StatusPre-print
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Authors
Zaleśkiewicz, Tomasz
Samson, Katarzyna
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Date
2025-12-17
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Polish Psychological Bulletin
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Pages
1-39
ISSN
0079-2993
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Weblink
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2026-01-01
Abstract PL
Abstract EN
As artificial intelligence (AI) technologies increasingly integrate into daily life, understanding how people perceive AI agents in trust-related interactions is critical for fostering effective human-AI collaboration. Drawing on social cognition theory, this research examines the fundamental dimensions of warmth and competence in shaping impressions and trust towards AI agents compared to humans. Across two studies, using trust-related vignettes, we investigated how warmth and competence are attributed to AI agents, human experts, and friends in various social contexts and performance outcomes. The results indicated that although both warmth and competence impact trust judgments, these traits are generally considered less important and are attributed to AI agents to a lesser extent than to humans. Moreover, AI agents were perceived as equally warm and competent, whereas humans were rated higher on both traits—especially on warmth. The findings highlight the nuanced role of social cognitive dimensions in human-AI trust, suggesting that perceptions of AI are contextdependent and affected by implicit biases. This work advances understanding of human-AI social dynamics and underscores the importance of designing AI systems that effectively balance warmth and competence to enhance trust and cooperation.
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Keywords PL
Keywords EN
social cognition
trust
competence
warmth
artificial intelligence
trust
competence
warmth
artificial intelligence
Keywords other
Sustainable Development Goals
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