Impression transference from AI to human: The impact of AI's fairness on interpersonal perception in AI-Mediated communication

Abstract

Artificial Intelligence-mediated communication (AI-MC) is a new form of communication where AI algorithms modify, augment, or generate messages for its human principal. However, little is known about how AI-MC influences impression formation and interpersonal dynamics in the literature. This study examines how AI mediation affects impression formation in AI-MC using a moderated mediation model. We conducted an experiment with 66 participants who played the Alternated Repeated Ultimatum Game with a human-agent group. We manipulated the fairness of the AI agent and the entitativity of the human-agent group. The results show that the fairness of the AI agent influenced the participants’ impressions of both the AI agent and the human. This effect was mediated by the impression of AI and moderated by the entitativity of the group. The quantitative evidence shows that AI can influence impressions in AI-MC and suggests that modifying AI behavior can enhance social perceptions and relations.