Beyond the code: The impact of AI algorithm transparency signaling on user trust and relational satisfaction

Abstract

This study investigates the effectiveness of AI-algorithm transparency signaling as a strategy to enhance organization-public relationships (OPRs) in AI-assisted communications. Building upon signaling theory and trust transfer theory, the study examines whether the AI algorithm transparency influences trust in AI systems by users and this trust can be transferred into trust in AI systems’ parent company, which in turn, influences the relational satisfaction with the company. An online experiment with 537 participants demonstrated that transparency signaling significantly improves users’ relational satisfaction with the AI parent company. However, this effect is mediated by trust in both the AI system and the parent company, rather than a direct relationship. Our findings offer practical guidelines for AI domain experts and public relations practitioners to deliberately convey the true essence of transparency in AI-mediated communication and ensure accountability in AI adoption, thereby improving public relations outcomes.