Existing approaches to Theory of Mind (ToM) in Artificial Intelligence (AI)
overemphasize prompted, or cue-based, ToM, which may limit our collective
ability to develop Artificial Social Intelligence (ASI). Drawing from research
in computer science, cognitive science, and related disciplines, we contrast
prompted ToM with what we call spontaneous ToM -- reasoning about others'
mental states that is grounded in unintentional, possibly uncontrollable
cognitive functions. We argue for a principled approach to studying and
developing AI ToM and suggest that a robust, or general, ASI will respond to
prompts \textit{and} spontaneously engage in social reasoning.

现有的人工智能（AI）的心灵理论（ToM）方法过多地强调受到提示或刺激的 ToM，这可能限制我们共同发展人工社会智能（ASI）。通过对计算机科学、认知科学及相关学科的研究，我们将受到提示的 ToM 与我们所称的自发的 ToM 进行对比，即在无意识、可能无法控制的认知功能基础上进行他人心灵状态的推理。我们主张在研究和发展 AI ToM 时采用有原则的方法，并建议在应对提示的同时，积极进行社会推理的强大，或通用的 ASI。