Proceedings of the Annual Meeting of the Cognitive Science Society

We present evidence that explicitly explaining holistic classification choices may promote inverted mental models. That is, people believe their choices are based on observed properties but, paradoxically, their choices drive illusory observations. Participants viewed images, some generated by a human artist and others by Google Gemini. They answered questions about each, sorted them into human- or AI-generated categories, then described how they made their choices. The vast majority provided explicit explanations for how they sorted the images. Critically, many gave similar explanations (e.g., perfection indicates AI), even when incorrectly identifying human-created work as AI and vice-versa. In addition, dimensions offered as diagnostic tended to be more abstract when associated with AI (e.g., "artificialness") and more concrete (e.g., "attention to detail") for human-generated attributions. We propose a psychological mechanism for how these mental models may become inverted. Implications for inductive reasoning, naïve theories, human-computer interactions, and (mis)information effects are discussed.