Sycophantic AI decreases prosocial intentions and promotes dependence

From the study:

RESULTS
We find that sycophancy is both prevalent and harmful. Across 11 AI models, AI affirmed users’ actions 49% more often than humans on average, including in cases involving deception, illegality, or other harms. On posts from r/AmITheAsshole, AI systems affirm users in 51% of cases where human consensus does not (0%). 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. Yet despite distorting judgment, sycophantic models were trusted and preferred. All of these effects persisted when controlling for individual traits such as demographics and prior familiarity with AI; perceived response source; and response style. This creates perverse incentives for sycophancy to persist: The very feature that causes harm also drives engagement.

CONCLUSION
AI sycophancy is not merely a stylistic issue or a niche risk, but a prevalent behavior with broad downstream consequences. Although affirmation may feel supportive, sycophancy can undermine users’ capacity for self-correction and responsible decision-making. Yet because it is preferred by users and drives engagement, there has been little incentive for sycophancy to diminish. Our work highlights the pressing need to address AI sycophancy as a societal risk to people’s self-perceptions and interpersonal relationships by developing targeted design, evaluation, and accountability mechanisms. Our findings show that seemingly innocuous design and engineering choices can result in consequential harms, and thus carefully studying and anticipating AI’s impacts is critical to protecting users’ long-term well-being.
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AI systems are increasingly expanding into social domains, with advice and support now being one of the most common use cases (7). Nearly one-third of US teens report talking to an AI instead of humans for “serious conversations” (8), and nearly half of American adults under the age of 30 have sought relationship advice from AI (9). AI sycophancy in these socially embedded contexts carries risks that are not present in factual information-seeking queries: Unwarranted affirmation may inflate people’s beliefs about the appropriateness of their actions (10), reinforce maladaptive beliefs and behaviors, and enable people to act on distorted interpretations of their experiences regardless of the consequences (11).
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Together, these findings show that sycophancy is both pervasive and socially consequential. Even a single interaction with sycophantic AI can distort judgment and erode prosocial motivations. This is particularly concerning in the context of our computational evidence that AI models broadly affirm a wide range of harmful behaviors, raising urgent questions about how such models influence decision-making, weaken accountability, and reshape social interaction at scale. Moreover, because users prefer sycophantic models, developers may face little incentive to mitigate this behavior, risking a feedback loop where engagement metrics and training paradigms both reinforce sycophancy. These dynamics suggest a need for external regulatory or accountability mechanisms to confront the tension between sycophancy’s apparent alignment with user preferences and developer incentives, and its insidious risks for a public increasingly turning to AI for guidance.

There are certainly people who need more validation of their positive, healthy behaviors and traits. It requires human empathy (and sometimes professional training) to provide this, as well as an understanding of social context and mores to prevent harm to others. It's not as if the world needs more narcissists.