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Theory of Mind (ToM), humans' capability of attributing mental states such as intentions, goals, emotions, and beliefs to ourselves and others, has become a concept of great interest in human-AI interaction research. Given the fundamental role of ToM in human social interactions, many researchers have been working on methods and techniques to equip AI with an equivalent of human ToM capability to build highly socially intelligent AI. Another line of research on ToM in human-AI interaction seeks to understand people's tendency to attribute mental states such as blame, emotions, and intentions to AI, along with the role that AI should play in the interaction (e.g. as a tool, partner, teacher, facilitator, and more) to align with peoples' expectations and mental models. The goal of this line of work is to distill human-centered design implications to support the development of increasingly advanced AI systems. Together, these two research perspectives on ToM form an emerging paradigm of "Mutual Theory of Mind (MToM)" in human-AI interaction, where both the human and the AI each possess the ToM capability. This workshop aims to bring together different research perspectives on ToM in human-AI interaction by engaging with researchers from various disciplines including AI, HCI, Cognitive Science, Psychology, Robotics, and more to synthesize existing research perspectives, techniques, and knowledge on ToM in human-AI interaction, as well as envisioning and setting a research agenda for MToM in human-AI interaction.
Wang et al. (Sat,) studied this question.