新闻编辑室引入AI后面临信任危机，这篇论文用实验数据戳破了“越透明越信任”的迷思，做AI产品设计或新闻业的朋友值得看看，避免好心办坏事。
一项针对34名新闻读者的对照实验发现，新闻中详细标注AI参与程度（如人工审核、编辑责任等）反而会降低读者信任，而简短的一行标注虽不引发此问题，却导致读者主动搜寻AI迹象以填补信息缺口。读者并未拒绝透明度，而是提出按需详情、AI比例可视化、媒体级别信号及明确“无AI”标签等用户主导的设计。研究指出，从业者认为负责任的披露方式与用户实际需求之间存在脱节，这是人机交互领域的设计问题。
Designed by Journalists, but Is It for Readers? Rethinking AI Disclosures and Transparency in News
As newsrooms integrate generative AI, journalists face a disclosure challenge: how to communicate AI involvement in ways that maintain reader trust. Current practice offers two approaches: brief one-line labels or detailed disclosures specifying human oversight, editorial accountability, and error reporting mechanisms. Neither achieves journalists' goal of building trust through transparency. An existing controlled experiment with 34 news readers show that detailed disclosures trigger a \textit{transparency dilemma}, reducing trust rather than increasing it, and risk introducing dark patterns that readers scroll past with the illusion of transparency. One-line disclosures avoid this effect but can create an information gap, prompting readers to expend cognitive effort searching for signs of AI involvement that the disclosure indicates but does not explain. Yet readers are not rejecting transparency, they proposed disclosure designs centered on user agency: detail-on-demand interactions, proportional AI-ratio visualizations, outlet-level signals, and explicit "no AI" labels. I argue that this disconnect between what practitioners believe is responsible disclosure and what users actually need is a design problem for the HCI community.