Intuitive psychology is a pillar of common-sense reasoning. The replication of this reasoning in machine intelligence is an important stepping-stone on the way to human-like artificial intelligence. Several recent tasks and benchmarks for examining this reasoning in Large-Large Models have focused in particular on belief attribution in Theory-of-Mind tasks. These tasks have shown both successes and failures. We consider in particular a recent purported success case, and show that small variations that maintain the principles of ToM turn the results on their head. We argue that in general, the zero-hypothesis for model evaluation in intuitive psychology should be skeptical, and that outlying failure cases should outweigh average success rates. We also consider what possible future successes on Theory-of-Mind tasks by more powerful LLMs would mean for ToM tasks with people.

翻译：直觉心理学是常识推理的支柱之一。在机器智能中复现这种推理，是迈向类人人工智能的重要基石。近期针对大型语言模型（LLMs）进行此类推理检验的数项任务与基准，尤其聚焦于心理理论任务中的信念归因。这些任务既显示了成功案例，也暴露了失败情形。我们特别考察了一个近期所谓的成功案例，并表明那些保持心理理论原则的细微变动完全颠覆了原有结果。我们认为，总体而言，在直觉心理学领域，模型评估的零假设应持怀疑态度，离群失败案例的权重应高于平均成功率。同时，我们还探讨了未来更强大的LLMs在心理理论任务上可能的成功，对人类心理理论任务意味着什么。