What AI pretends to be?

Abstract Recent research shows that anthropomorphizing of artificial intelligence (AI) technologies, such as virtual assistants or chatbots, affects users’ trust. This paper explores what an AI technology should look like at the interface to facilitate appropriate trust. It proposes an integrated framework based on related work, including Lee and See’s (2004) trust in automation model, Mollerup’s (2019) pretense design, as well as Clark and Fischer’s (2023) notion of depictions, for analysis and design of appearances of AI applications that pretend to be something different. Following the proposed framework, cases of AI applications are analyzed. They span a spectrum of appearances, from humans with open or specifc identities, through talking animals, to plants. Analyses suggest that appearances of AI applications should faithfully reflect the actual ability, characteristics, and design intent, in order to facilitate users’ trustworthiness assessments of the applications. Lastly, design implications and future research are discussed.