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Large language models (LLMs) show emerging theory of mind (ToM)-like abilities. ChatGPT-4 achieved 75% accuracy on false-belief tasks, matching young children, suggesting AI may develop social skills alongside language.

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Area of Science:

  • Cognitive Science
  • Artificial Intelligence
  • Developmental Psychology

Background:

  • Theory of Mind (ToM) is crucial for human social interaction.
  • LLMs are increasingly sophisticated AI systems.
  • Assessing ToM in AI is a novel research area.

Purpose of the Study:

  • To evaluate the Theory of Mind (ToM) capabilities of large language models (LLMs).
  • To compare LLM performance on ToM tasks with human developmental benchmarks.
  • To explore the implications of emergent ToM-like abilities in AI.

Main Methods:

  • Eleven LLMs were tested on 40 bespoke false-belief tasks.
  • Tasks included false-belief, true-belief, and reversed scenarios.
  • Performance was measured by the number of tasks correctly solved across all eight scenario types.

Main Results:

  • Older LLMs failed all tasks.
  • GPT-3 and ChatGPT-3.5-turbo achieved 20% accuracy.
  • ChatGPT-4 reached 75% accuracy, comparable to 6-year-old children.

Conclusions:

  • LLMs demonstrate emerging ToM-like abilities.
  • These abilities may be an emergent property of advanced language skills in AI.
  • The development of socially skilled AI has significant implications.