Increased levels of user control in learning systems is commonly cited as good AI development practice. However, the evidence as to the effect of perceived control over trust in these systems is mixed. This study investigated the relationship between different trust dimensions and perceived control in postgraduate student burnout support chatbots, and modelled the moderating factors therein. We present an in-between subject controlled experiment using simulated therapy-goal learning to study the effect of perceived control (as manipulated by feedback incorporation) on perceived agent benevolence, competence, and trust. Our results showed that perceived control was moderately correlated with benevolence (r = 0.448, BF10 = 7.150), and weakly correlated with competence and trust.@en

Appropriate trust, trust which aligns with system trustworthiness, in Artificial Intelligence (AI) systems has become an important area of research. However, there remains debate in the community about how to design for appropriate trust. This debate is a result of the complex nature of trust in AI, which can be difficult to understand and evaluate, as well as the lack of holistic approaches to trust. In this paper, we aim to clarify some of this debate by operationalising appropriate trust within the context of the Human-Centred AI Design (HCD) process. To do so, we organised three workshops with 13 participants total from design and development backgrounds. We carried out design activities to stimulate discussion on appropriate trust in the HCD process. This paper aims to help researchers and practitioners understand appropriate trust in AI through a design lens by illustrating how it interacts with the HCD process.@en

Appropriate trust, trust which aligns with system trustworthiness, in Artificial Intelligence (AI) systems has become an important area of research. However, there remains debate in the community about how to design for appropriate trust. This debate is a result of the complex nature of trust in AI, which can be difficult to understand and evaluate, as well as the lack of holistic approaches to trust. In this paper, we aim to clarify some of this debate by operationalising appropriate trust within the context of the Human-Centred AI Design (HCD) process. To do so, we organised three workshops with 13 participants total from design and development backgrounds. We carried out design activities to stimulate discussion on appropriate trust in the HCD process. This paper aims to help researchers and practitioners understand appropriate trust in AI through a design lens by illustrating how it interacts with the HCD process.@en