Genai Advisory Systems: The Role of AI Advice Source Disclosure, Transparency, And Fairness in Trust-Building And Decision Aid, And The Moderating Effect Of Machine Heuristic

Abstract

Generative AI (GenAI) systems have become involved in various sectors such as healthcare, finance, education, and customer care provision, etc. However, the widespread adoption of GenAI advisory systems is still hindered by a lack of user trust, stemming from issues that need improvement. Therefore, the objective of this study is to identify the factors impacting trust and perceived threats of users in GenAI advisory systems. In particular, the research focuses on explaining the influence of AI advice disclosure, perceived fairness, and perceived transparency on user trust. Using a mixed-method approach, this study employs a qualitative method via expert advice and a quantitative method via a survey of 404 users of GenAI advisory systems in Ho Chi Minh City.Results indicate that significant trust is achieved through transparency and fairness, especially through source disclosure, which enhances transparency and directly impacts trust. Trust, in turn, influences adoption intentions in decision-making processes. AI advice source disclosure becomes crucial, striking a balance between users' suspicion of system outcomes and the system's accountability, trust, and especially transparency. This research provides insights into GenAI advisory systems consistent with user expectations regarding transparency, source disclosure, fairness, and accountability. This study aims to contribute to both theory and practice by offering influential factors to policymakers and developers on how to facilitate trust and reduce risks in AI deployment