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.

翻译：当前人工智能（AI）领域中的心理理论（ToM）研究过度强调基于提示或线索驱动的ToM，这可能限制了发展人工社会智能（ASI）的整体能力。借鉴计算机科学、认知科学及相关学科的研究成果，我们将提示性ToM与所谓"自发性ToM"进行对比——后者指基于无意识、甚至不可控的认知功能对他人心理状态进行推理的能力。我们主张采用原则性方法研究与发展AI的ToM能力，并提出一个鲁棒（或通用）的ASI不仅应响应外部提示，还应自发地参与社会推理过程。