Spontaneous Theory of Mind for Artificial Intelligence
This addresses the problem of developing more general and effective social AI, but it is incremental as it builds on existing ToM research without presenting new empirical results.
The paper argues that current AI approaches to Theory of Mind (ToM) focus too much on prompted reasoning, limiting Artificial Social Intelligence (ASI), and proposes shifting to spontaneous ToM for more robust AI.
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.