From bias to trust: Ethical perceptions and trust formation in GAI-driven automated decision-making in tourism

This study examines how tourists interpret ethical concerns in Generative Artificial Intelligence (GAI)-driven automated decision-making and how these perceptions shape trust formation in tourism services. The study focuses on fairness, transparency, privacy, human oversight, and cultural sensitivity as key ethical conditions influencing evaluations of GAI-supported decisions. A qualitative research design was adopted using semi-structured interviews with 18 international tourists who had prior experience with AI-enabled tourism services in Pakistan and China. Participants were selected through purposive sampling, and the data were analyzed using thematic analysis supported by NVivo 14. The findings identify three main themes: ethical concerns of GAI technologies, interpretations of fairness, transparency, and human oversight, and trust formation in GAI-driven decision-making. Trust was shaped not only by the outcomes of automated recommendations, but also by whether decision processes were perceived as fair, transparent, inclusive, and ethically responsible. The study contributes to trust theory by showing that trust in GAI-driven tourism is shaped not only by system performance, but also strongly by ethical evaluations that function as interconnected trust signals. These findings provide practical guidance for the responsible design of transparent, fair, and user-centered GAI applications in tourism.