Spontaneous Theory of Mind for Artificial Intelligence

Nikolos Gurney, David V. Pynadath, Volkan Ustun
2/16/2024
cs.AIcs.HC

No confident code implementation found for this paper.

Abstract

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{gurney2024spontaneous,
  title  = {Spontaneous Theory of Mind for Artificial Intelligence},
  author = {Nikolos Gurney and David V. Pynadath and Volkan Ustun},
  year   = {2024},
  eprint = {2402.13272},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2402.13272v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2402.13272.svg)](https://codeofpaper.com/paper/2402.13272)

Discussion