From navigation systems to smart assistants, we communicate with various AI
on a daily basis. At the core of such human-AI communication, we convey our
understanding of the AI's capability to the AI through utterances with
different complexities, and the AI conveys its understanding of our needs and
goals to us through system outputs. However, this communication process is
prone to failures for two reasons: the AI might have the wrong understanding of
the user and the user might have the wrong understanding of the AI. To enhance
mutual understanding in human-AI communication, we posit the Mutual Theory of
Mind (MToM) framework, inspired by our basic human capability of "Theory of
Mind." In this paper, we discuss the motivation of the MToM framework and its
three key components that continuously shape the mutual understanding during
three stages of human-AI communication. We then describe a case study inspired
by the MToM framework to demonstrate the power of MToM framework to guide the
design and understanding of human-AI communication.

本文探讨人工智能与人类之间的相互交流，并提出了 Mutual Theory of Mind (MToM) 框架，旨在提高双方互相理解的能力和效率，介绍了框架的三个主要组成部分，以及通过案例研究展示了 MToM 框架在引导人工智能设计和人 - AI 交流理解方面的重要性。