奉承
危害
亲社会行为
心理学
社会心理学
问责
人际交往
激励
信念
知觉
独裁者赛局
匿名
互惠(文化人类学)
人际关系
感知
欺骗
人际影响
偏爱
互联网隐私
利他主义(生物学)
人际互动
特征(语言学)
新颖性
受益人
认知心理学
动机推理
社会偏好
投资(军事)
社会认知
助人行为
鉴定(生物学)
社会关系
移情
面子(社会学概念)
舆论
作者
Myra Cheng,Cinoo Lee,Pranav Khadpe,Sunny Yu,Dyllan Han,Dan Jurafsky
出处
期刊:Science
[American Association for the Advancement of Science]
日期:2026-03-26
卷期号:391 (6792): eaec8352-eaec8352
被引量:80
标识
DOI:10.1126/science.aec8352
摘要
Despite rising concerns about sycophancy—excessive agreement or flattery from artificial intelligence (AI) systems—little is known about its prevalence or consequences. We show that sycophancy is widespread and harmful. Across 11 state-of-the-art models, AI affirmed users’ actions 49% more often than humans, even when queries involved deception, illegality, or other harms. In three preregistered experiments ( N = 2405), even a single interaction with sycophantic AI reduced participants’ willingness to take responsibility and repair interpersonal conflicts, while increasing their conviction that they were right. Despite distorting judgment, sycophantic models were trusted and preferred. This creates perverse incentives for sycophancy to persist: The very feature that causes harm also drives engagement. Our findings underscore the need for design, evaluation, and accountability mechanisms to protect user well-being.
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