Writing with AI boosts trust-building efficiency
AI-mediated communication promises efficiency but raises concerns about diminished authenticity and interpersonal trust. We examined this potential trade-off across two preregistered online experiments (<i>N</i> = 1,637) in which participants engaged in incentivized two-player trust games with communication. Half of the participants could use state-of-the-art predictive text assistance when composing a message to encourage trust; the others wrote unaided. We measured both objective (behavioral) and subjective (stated) trust. Frequentist and Bayesian analyses showed that AI assistance had minimal impact on trust, regardless of disclosure. AI-assisted participants wrote more efficiently, producing equally trust-inducing messages but in less time. This advantage persisted even when AI use was disclosed. Linguistic analyses indicated that AI-assisted messages were slightly less authentic than those written alone but that they exhibited greater warmth, complexity, and clout-features commonly associated with trustworthiness. These findings challenge the view that AI-mediated communication necessarily undermines trust, particularly in one-shot, transactional interactions.
Authors
- Maurice Jakesch (ORCID: https://orcid.org/0000-0002-2642-3322)
- Zoe Alexandra Purcell (ORCID: https://orcid.org/0000-0002-3051-9191)
- Mengchen Dong (ORCID: https://orcid.org/0000-0001-8547-3808)
- Nils Köbis (ORCID: https://orcid.org/0000-0002-0608-7333)
- Anne-Marie Nußberger (ORCID: https://orcid.org/0000-0002-1805-9399)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université Paris Cité (FR)
- Sorbonne Paris Cité (FR)
- Max Planck Institute for Human Development (DE)
- Bauhaus-Universität Weimar (DE)
- University of Duisburg-Essen (DE)
Publication Details
- Journal
- iScience
- Published
- 2025-11-20
- DOI
- https://doi.org/10.1016/j.isci.2025.114092
- Citations
- 1
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 2.48