AI的'心智理论'实为行为模仿，非真实认知。
When Researchers Say Mental Model/Theory of Mind of AI, What Are They Really Talking About?
- 用行为表现替代真实心智，本质是模式匹配。
- 大模型在心理理论任务上达人类水平，仅靠模仿。
- 应关注人机互动中的双向认知动态。
当研究者声称人工智能具备心智理论（ToM）或心智模型时，实际上讨论的是行为预测与偏差修正，而非真正的内在心智状态。本文指出当前论述将复杂模式匹配误认为真实认知，混淆了模拟与体验的根本区别。尽管近期研究显示大语言模型在心理理论实验室任务中达到人类水平表现，但这些结果仅基于行为模仿。更关键的是，将人类个体认知测试直接应用于AI系统可能本身存在缺陷，应转而评估人机交互过程中即时的认知相互作用。建议转向互为主体的心智理论框架，强调人类认知与AI算法的共同贡献及互动动态，而非孤立测试AI。
原文摘要 · Abstract (English)
When researchers claim AI systems possess ToM or mental models, they are fundamentally discussing behavioral predictions and bias corrections rather than genuine mental states. This position paper argues that the current discourse conflates sophisticated pattern matching with authentic cognition, missing a crucial distinction between simulation and experience. While recent studies show LLMs achieving human-level performance on ToM laboratory tasks, these results are based only on behavioral mimicry. More importantly, the entire testing paradigm may be flawed in applying individual human cognitive tests to AI systems, but assessing human cognition directly in the moment of human-AI interaction. I suggest shifting focus toward mutual ToM frameworks that acknowledge the simultaneous contributions of human cognition and AI algorithms, emphasizing the interaction dynamics, instead of testing AI in isolation.
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