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Too Good to Be Real? Diagnosing and Reducing the Gap Between AI Preference and Real User Engagement

arXiv · AI, language, vision and robotics · article · Sep 16, 2026 · UTC

Large language models are increasingly used to generate and evaluate online content, yet it remains unclear whether the qualities they associate with higher engagement match what real users respond to. We study this question using 1.17 million answers to 25,978 questions from Zhihu, Quora, and Reddit, comparing real platform answers and AI-generated answers across four within-question engagement levels. We introduce Ontological Preference Measurement, which represents answers along three dimensions: logic, affect, and expression. We find a systematic gap between AI preference and real user eng

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