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This study investigates why transparency signals on hospitality platforms backfire amid perceived bias, proposing a “reverse signaling” framework to explain how AI-based verification cues (versus community moderation) erode travelers’ confidence in online hotel reviews. Using a multi-study design, Study 1 (N=157) applied surveys and structural equation modeling to map psychological pathways, while Study 2 (N=406) experimentally manipulated signal types and cognitive moderators. Results show perceived bias indirectly undermines transparency by reducing confidence and review authenticity, with stronger effects for AI signals; traits like illusion of transparency intensify erosion. Advancing signaling theory, it introduces “metacognitive rupture” as a novel trust degradation mechanism in digital hospitality. Limitations call for longitudinal and cross-cultural studies. Practically, managers should favor human-centric signals and adapt cues to cognitive styles to maintain credibility.