How does a virtual human earn your trust?: guidelines to improve willingness to self-disclose to intelligent virtual agents

Abstract

Virtual humans demonstrate the ability to act as non-judgmental conversational partners, eliciting greater self-disclosure. However, it is unclear what virtual human and conversational characteristics are important when self-disclosing. To address this gap, we conducted a set of qualitative, semi-formal interviews (n = 17) among computer science students to investigate participant mental models of willingness to disclose to virtual humans and characteristics of virtual humans that affect their self-disclosure. Our findings indicate that participants' mental models of virtual humans are largely inconsistent with current literature. This inconsistency appears to eliciting hesitancy and discomfort with virtual humans. Furthermore, trust and listening were identified as two primary characteristics of a virtual human interaction that are valuable towards willingness to disclose. Additionally, these characteristics were also valued in different ways for virtual humans in comparison to real humans. From the interviews, we identify and provide guidelines of designing virtual human interactions and conversations to elicit greater willingness to disclose.