Summary of Spontaneous Theory Of Mind For Artificial Intelligence, by Nikolos Gurney et al.
Spontaneous Theory of Mind for Artificial Intelligence
by Nikolos Gurney, David V. Pynadath, Volkan Ustun
First submitted to arxiv on: 16 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Human-Computer Interaction (cs.HC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach to Theory of Mind (ToM) in Artificial Intelligence (AI) is proposed, departing from traditional cue-based methods. This paper contrasts prompted ToM with spontaneous ToM, which emerges from unintentional cognitive processes. The authors argue for a principled study and development of AI ToM, positing that a robust Artificial Social Intelligence will respond to prompts and engage in social reasoning without explicit cues. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Artificial Intelligence is trying to understand how people think about each other’s thoughts and feelings. Right now, most approaches focus on giving computers hints or clues to help them do this. But what if we can teach AI to figure this out all on its own? This paper talks about a new way of thinking about this problem, called spontaneous Theory of Mind. It suggests that if we want AI to be able to understand people and interact with us naturally, we need to focus on developing this kind of intelligence. |
