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，是迈向类人人工智能的重要基石。近期针对大型语言模型进行此类推理能力的若干任务与基准测试，尤其聚焦于心理理论任务中的信念归因。这些任务既展现了成功案例，也暴露了失败情形。我们重点考察了一项近期声称成功的案例，发现若在保持心理理论原则的前提下进行细微改动，结果便会截然相反。我们主张，在直觉心理学领域，模型评估的零假设应持怀疑态度，且异常失败案例的权重应高于平均成功率。此外，我们探讨了未来更强大的大型语言模型在心理理论任务上可能取得的成功，对涉及人类参与的心理理论任务意味着什么。