When Researchers Say Mental Model/Theory of Mind of AI, What Are They Really Talking About?

• URL: http://arxiv.org/abs/2510.02660v1
• Date: Fri, 03 Oct 2025 01:37:32 GMT
• Title: When Researchers Say Mental Model/Theory of Mind of AI, What Are They Really Talking About?
• Authors: Xiaoyun Yin, Elmira Zahmat Doost, Shiwen Zhou, Garima Arya Yadav, Jamie C. Gorman,
• Abstract summary: This position paper argues that the current discourse conflates sophisticated pattern matching with authentic cog- nition.<n>I suggest shifting focus toward mutual ToM frameworks that acknowledge the simultaneous contributions of human cognition and AI algorithms.
• Score: 0.9786690381850356
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: When researchers claim AI systems possess ToM or mental models, they are fundamentally dis- cussing behavioral predictions and bias corrections rather than genuine mental states. This position paper argues that the current discourse conflates sophisticated pattern matching with authentic cog- nition, 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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