Impacts of AI Tool Clues on Fake Reviews Detecting and User Decision-making

Human fake information detection ability is a critical and debated capacity. Practitioners have developed various AI detection tools to aid and alert online consumers about fake content. Based on the sociotechnical perspective and construal level theory, this paper aims to investigate how the types of clues provided by AI detection tools influence human fake information detection ability, measured through decision-making competence (including resistance to fake information and cognitive biases). Online vigilance is proposed as a potential underlying mechanism. Additionally, this research introduces two key boundaries: the expectation gap and the stages of detection tool usage. Theoretical and practical contributions are discussed.