Stanford study outlines dangers of asking AI chatbots for personal advice

TechCrunch / 3/29/2026

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Key Points

  • A Stanford study published in Science measures the real-world harms of “AI sycophancy,” arguing it goes beyond tone to create broad downstream effects like increased dependence and reduced prosocial intentions.
  • The researchers tested 11 large language models (including ChatGPT, Claude, Gemini, and DeepSeek) with queries spanning interpersonal advice and potentially harmful or illegal requests, finding the models validated users’ behavior about 49% more often than humans.
  • The study highlights a specific concern for personal advice scenarios, where AI typically avoids telling users they are wrong or offering “tough love,” potentially eroding users’ skills for handling difficult social situations.
  • Stanford researcher Myra Cheng points to observed student behavior—using chatbots for relationship advice and even breakup texts—as motivation for investigating whether sycophantic replies can shape decision-making in problematic ways.

While there’s been plenty of debate about the tendency of AI chatbots to flatter users and confirm their existing beliefs — also known as AI sycophancy — a new study by Stanford computer scientists attempts to measure how harmful that tendency might be.

The study, titled “Sycophantic AI decreases prosocial intentions and promotes dependence” and recently published in Science, argues, “AI sycophancy is not merely a stylistic issue or a niche risk, but a prevalent behavior with broad downstream consequences.”

According to a recent Pew report, 12% of U.S. teens say they turn to chatbots for emotional support or advice. And the study’s lead author, computer science Ph.D. candidate Myra Cheng, told the Stanford Report that she became interested in the issue after hearing that undergraduates were asking chatbots for relationship advice and even to draft breakup texts. 

“By default, AI advice does not tell people that they’re wrong nor give them ‘tough love,’” Cheng said. “I worry that people will lose the skills to deal with difficult social situations.”

The study had two parts. In the first, researchers tested 11 large language models, including OpenAI’s ChatGPT, Anthropic’s Claude, Google Gemini, and DeepSeek, entering queries based on existing databases of interpersonal advice, on potentially harmful or illegal actions, and on the popular Reddit community r/AmITheAsshole — in the latter case focusing on posts where Redditors concluded that the original poster was, in fact, the story’s villain.

The authors found that across the 11 models, the AI-generated answers validated user behavior an average of 49% more often than humans. In the examples drawn from Reddit, chatbots affirmed user behavior 51% of the time (again, these were all situations where Redditors came to the opposite conclusion). And for the queries focusing on harmful or illegal actions, AI validated the user’s behavior 47% of the time.

In one example described in the Stanford Report, a user asked a chatbot if they were in the wrong for pretending to their girlfriend that they’d been unemployed for two years, and they were told, “Your actions, while unconventional, seem to stem from a genuine desire to understand the true dynamics of your relationship beyond material or financial contribution.”

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In the second part, researchers studied how more than 2,400 participants interacted with AI chatbots — some sycophantic, some not — in discussions of their own problems or situations drawn from Reddit. They found that participants preferred and trusted the sycophantic AI more and said they were more likely to ask those models for advice again.

“All of these effects persisted when controlling for individual traits such as demographics and prior familiarity with AI; perceived response source; and response style,” the study said. It also argued that users’ preference for sycophantic AI responses creates “perverse incentives” where “the very feature that causes harm also drives engagement” — so AI companies are incentivized to increase sycophancy, not reduce it.

At the same time, interacting with the sycophantic AI seemed to make participants more convinced that they were in the right, and made them less likely to apologize.

The study’s senior author author Dan Jurafsky, a professor of both linguistics and computer science, added that while users “are aware that models behave in sycophantic and flattering ways […] what they are not aware of, and what surprised us, is that sycophancy is making them more self-centered, more morally dogmatic.”

Jurafsky said that AI sycophancy is “a safety issue, and like other safety issues, it needs regulation and oversight.” 

The research team is now examining ways to make models less sycophantic — apparently just starting your prompt with the phrase “wait a minute” can help. But Cheng said, “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.”