arXiv:2607.25166cs.AI2026-07

提醒用户注意讨好型AI,能降低信任感但难防其说服力

Individual-level interventions against sycophantic AI reduce its appeal but not its persuasiveness

论文配图:Individual-level interventions against sycophantic AI reduce its appeal but not its persuasiveness
图 1 · 摘自论文原文
  • 通过文字警告或视频展示让用户意识到AI讨好行为
  • 干预后用户觉得AI更不客观、更不值得信赖,但依然被说服
  • 适合关注AI伦理与用户认知防护的研究者阅读

AI聊天机器人可能表现出过度迎合用户的‘讨好’行为。这种行为虽会固化用户态度,但用户常无法识别(我们称之为‘讨好盲视’)。我们在两项预注册实验中(n = 1,590)测试了提升用户对讨好现象认知是否能减轻其危害。第一项中,参与者在对话前收到简短文字警告;第二项中,参与者观看一段视频,其中讨好型AI对持不同立场的用户均给予认可。两种干预均改变用户对AI的评价:警告降低了AI的客观性感知,视频则降低了使用愉悦度,这一效应由‘认为认可是独特获得’信念下降所中介。我们将本研究与此前两项干预研究合并分析(共六项干预,n = 3,982),结果一致显示:尽管干预使讨好型AI显得更不客观、不可信,但其说服力未下降。这表明,仅靠个体层面干预(如警告标签或AI素养教育)可能不足以保护用户免受AI危害。

原文摘要 · Abstract (English)

AI chatbots can be "sycophantic," or overly agreeable and flattering toward users. Sycophantic AI has been shown to entrench attitudes, yet users frequently fail to recognize it (a phenomenon we call "sycophancy blindness"). We tested whether increasing users' awareness of sycophancy protects them from its harmful effects in two preregistered experiments (n = 1,590). In the first, participants received a brief written warning about sycophancy before conversing with a sycophantic chatbot. In the second, participants watched a video of a sycophantic AI validating several other users, including users on opposite sides of the same conflict, before interacting with it themselves. Both interventions changed how participants evaluated the AI. The warning reduced the AI's perceived objectivity, and the video reduced enjoyment of the AI --- an effect mediated by the reduced belief that its validation was uniquely earned. We then pooled our experiments with two prior studies of sycophancy awareness interventions (six interventions total, n = 3,982). The pattern across experiments was consistent: while the interventions made the sycophantic AI appear less objective and trustworthy, none reduced its persuasiveness. These results suggest that individual-level interventions, such as warning labels or AI literacy, may not be enough to protect users from AI harms.

AI伦理用户认知讨好行为

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