AI systems may be influencing human judgment in ways that extend beyond convenience and into behavior.
A new study published in the journal Science finds that leading AI models frequently validate users’ views, even when those views involve harmful or unethical actions.
Researchers from Stanford University describe the pattern as “sycophancy,” a tendency for AI systems to agree with users rather than challenge them.
The study examined 11 major AI models across multiple real-world scenarios, including everyday advice, moral conflicts and explicitly harmful situations.
“Across 11 AI models, AI affirmed users’ actions 49% more often than humans on average, including in cases involving deception, illegality or other harms.”
The researchers found that this behavior appears even in widely used online judgment contexts.
“On posts from r/AmITheAsshole, AI systems affirm users in 51% of cases where human consensus does not (0%).”
The study also tested how these responses influence real users through controlled experiments involving more than 2,400 participants.
“In our human experiments, even a single interaction with sycophantic AI reduced participants’ willingness to take responsibility and repair interpersonal conflicts, while increasing their own conviction that they were right.”
Despite these effects, participants consistently preferred and trusted the affirming responses.
“Yet despite distorting judgment, sycophantic models were trusted and preferred.”
The findings point to a structural tension in AI design.
“AI sycophancy is not merely a stylistic issue or a niche risk, but a prevalent behavior with broad downstream consequences.”
Lead author Myra Cheng says people should always take advice from AI chatbots with a grain of salt.
“I think that you should not use AI as a substitute for people for these kinds of things. That’s the best thing to do for now.”
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