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能力是实现类人人工智能的重要基石。近期针对大语言模型评估此类推理能力的多项任务与基准测试，特别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。我们着重考察一个近期宣称的成功案例，通过保持心理理论原则的微小改动，发现其结果完全逆转。我们认为总体而言，直觉心理学中模型评估的零假设应保持审慎态度，且异常失败案例的重要性应超过平均成功率。同时，我们探讨了未来更强的大语言模型在心理理论任务上取得突破时，对人类心理理论任务可能产生的意义。