However, a critical gap exists in the lack of generalizable and accurate specialized measurement tools Trust plays a crucial role not only in fostering cooperation, for assessing affective trust in the context of AI, especially efficiency, and productivity in human relationships (Brainov with the enhanced and nuanced capabilities of LLMs. This and Sandholm 1999) but also is essential for the effective highlights a need for a better measurement scale for affective use and acceptance of computing and automated systems, trust to gain a deeper understanding of how trust dynamics including computers (Madsen and Gregor 2000), automation function, particularly in the context of emotionally intelligent (Lee and See 2004), robots (Hancock et al. 2011), and AI. AI technologies (Kumar 2021), with a deficit in trust potentially In this paper, we introduce a 27-item semantic differential causing rejection of these technologies (Glikson and scale for assessing cognitive and affective trust in AI, Woolley 2020). The two-dimensional model of trust, encompassing aiding researchers and designers in understanding and improving both cognitive and affective dimensions proposed human-AI interactions. Our motivation and scale and studied in interpersonal relationship studies (McAllister development process is based on a long strand of prior research 1995; Johnson and Grayson 2005; Parayitam and Dooley on the cognitive-affective construct of trust that has 2009; Morrow Jr, Hansen, and Pearson 2004), have been shown to be important in interpersonal trust in organizations, been adopted in studying trust in human-computer interactions, human trust in conventional technology and automation, particularly with human-like technologies (Hu, Lu and more recently in trust towards AI.

Handling trust is one of the core requirements for facilitating effective interaction between the human and the AI agent. Thus, any decision-making framework designed to work with humans must possess the ability to estimate and leverage human trust. In this paper, we propose a mental model based theory of trust that not only can be used to infer trust, thus providing an alternative to psychological or behavioral trust inference methods, but also can be used as a foundation for any trust-aware decision-making frameworks. First, we introduce what trust means according to our theory and then use the theory to define trust evolution, human reliance and decision making, and a formalization of the appropriate level of trust in the agent. Using human subject studies, we compare our theory against one of the most common trust scales (Muir scale) to evaluate 1) whether the observations from the human studies match our proposed theory and 2) what aspects of trust are more aligned with our proposed theory.