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Appropriate Trust in Artificial Intelligence (AI) systems has rapidly becomean important area of focus for both researchers and practitioners. Variousapproaches have been used to achieve it, such as confidence scores,explanations, trustworthiness cues, or uncertainty communication. However, acomprehensive understanding of the field is lacking due to the diversity ofperspectives arising from various backgrounds that influence it and the lack ofa single definition for appropriate trust. To investigate this topic, thispaper presents a systematic review to identify current practices in buildingappropriate trust, different ways to measure it, types of tasks used, andpotential challenges associated with it. We also propose a Belief, Intentions,and Actions (BIA) mapping to study commonalities and differences in theconcepts related to appropriate trust by (a) describing the existingdisagreements on defining appropriate trust, and (b) providing an overview ofthe concepts and definitions related to appropriate trust in AI from theexisting literature. Finally, the challenges identified in studying appropriatetrust are discussed, and observations are summarized as current trends,potential gaps, and research opportunities for future work. Overall, the paperprovides insights into the complex concept of appropriate trust in human-AIinteraction and presents research opportunities to advance our understanding onthis topic.

A Systematic Review on Fostering Appropriate Trust in Human-AI Interaction