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<p>AI systems are becoming increasingly complex and human-like, and we interact with them more and more frequently. How does perceived human-likeness affect trust in AI systems? And what makes AI systems appear human in the first place? In a&#xa0;scoping review, we first examined the relationship between anthropomorphism and trust, although the operationalisation of anthropomorphism was very inconsistent. To address this gap, two conjoint analyses were conducted online focusing on four anthropomorphic characteristics identified in the review: name, appearance, voice, and communication style. The studies found that voice and communication style significantly influenced perceptions of human-likeness, while voice had a&#xa0;slightly stronger effect on trustworthiness. Overall, more human-like systems were perceived as more trustworthy across all attributes.</p><p><i>Practical Relevance:</i> The findings highlight the need for a&#xa0;comprehensive, integrated approach to AI design that considers how design elements shape user perceptions and trust. Importantly, the context in which AI is used, particularly in the workplace, must always be considered.</p>

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To trust or not to trust a human(-like) AI—A scoping review and conjoint analyses on factors influencing anthropomorphism and trust

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月23日

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  • Muriel Reuter,
  • Britta Marleen Kirchhoff,
  • Thomas Franke,
  • Thea Radüntz,
  • Corinna Peifer

摘要

AI systems are becoming increasingly complex and human-like, and we interact with them more and more frequently. How does perceived human-likeness affect trust in AI systems? And what makes AI systems appear human in the first place? In a scoping review, we first examined the relationship between anthropomorphism and trust, although the operationalisation of anthropomorphism was very inconsistent. To address this gap, two conjoint analyses were conducted online focusing on four anthropomorphic characteristics identified in the review: name, appearance, voice, and communication style. The studies found that voice and communication style significantly influenced perceptions of human-likeness, while voice had a slightly stronger effect on trustworthiness. Overall, more human-like systems were perceived as more trustworthy across all attributes.

Practical Relevance: The findings highlight the need for a comprehensive, integrated approach to AI design that considers how design elements shape user perceptions and trust. Importantly, the context in which AI is used, particularly in the workplace, must always be considered.