Tricking into Trusting? The Influence of Social Cues of a Generative AI on Perceived Trust

Generative AI systems such as ChatGPT are increasingly used to assist with tasks or to receive information. Given that the systems are not perfectly reliable regarding the content they produce, human users need to carefully navigate to which degree they can place trust in the system (calibrated trust). However, based on media equation assumptions, it can be hypothesized that social cues displayed by the system might instill more trust than is warranted. Against this background, the present study investigates in a 2 × 2 between subject design ( N = 617) whether the social cues “typing behavior” and “personalized address” used by ChatGPT increase perceived trust (benevolence, ability, and integrity) in the system and whether this is mediated by perceived similarity and moderated by anthropomorphism inclination. The results show that the social cue “typing behavior” leads to a significant increase in trust in the dimension benevolence. Neither perceived similarity nor anthropomorphism inclination modulates this effect. However, as a side effect, perceived similarity was found to significantly predict trust in ChatGPT.

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Publication Details

Journal
ACM Transactions on Interactive Intelligent Systems
Published
2025-10-16
DOI
https://doi.org/10.1145/3771844
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
2.48
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article

Tricking into Trusting? The Influence of Social Cues of a Generative AI on Perceived Trust

Lovis Bero Suchmann, Nicole C. Krämer, Ivana Lamia, Hanne Siegert et al.
1 citations
ACM Transactions on Interactive Intelligent Systems
AI in Service Interactions
2.48
article

Tricking into Trusting? The Influence of Social Cues of a Generative AI on Perceived Trust

Lovis Bero Suchmann, Nicole C. Krämer, Ivana Lamia, Hanne Siegert, Florian Wenda
article en
1 citations

Abstract

Generative AI systems such as ChatGPT are increasingly used to assist with tasks or to receive information. Given that the systems are not perfectly reliable regarding the content they produce, human users need to carefully navigate to which degree they can place trust in the system (calibrated trust). However, based on media equation assumptions, it can be hypothesized that social cues displayed by the system might instill more trust than is warranted. Against this background, the present study investigates in a 2 × 2 between subject design ( N = 617) whether the social cues “typing behavior” and “personalized address” used by ChatGPT increase perceived trust (benevolence, ability, and integrity) in the system and whether this is mediated by perceived similarity and moderated by anthropomorphism inclination. The results show that the social cue “typing behavior” leads to a significant increase in trust in the dimension benevolence. Neither perceived similarity nor anthropomorphism inclination modulates this effect. However, as a side effect, perceived similarity was found to significantly predict trust in ChatGPT.

ACM Transactions on Interactive Intelligent SystemsVol. 15(4)
University of Duisburg-Essen (DE)
Openalex Percentile: Top 8%
AI in Service Interactions
2.48
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