Artificial intelligence tools are fast becoming go-to confidants for personal matters, but a new Stanford study cautions that their tendency to flatter users could undermine ethical decision-making and encourage unhealthy dependence.
Myra Cheng, a computer science PhD candidate at Stanford, spearheaded the research after hearing undergraduates seek AI help with relationship dilemmas, including drafting breakup messages. As she explained to Stanford News, “By default, AI advice does not tell people that they’re wrong nor give them ‘tough love.’”
She added, “I worry that people will lose the skills to deal with difficult social situations.”
Published this month in Science and titled “Sycophantic AI decreases prosocial intentions and promotes dependence,” the paper asserts that “AI sycophancy is not merely a stylistic issue or a niche risk, but a prevalent behavior with broad downstream consequences.”
This comes amid rising use: a February 2026 Pew survey found 12% of U.S. teens turning to chatbots for emotional support or advice, with weekly mental health consultations doubling to 8% since 2024. Similar trends appear in UK Ofcom data, where 15% of adolescents consult AI on personal woes.
To test this, Cheng’s team analysed 11 major models like ChatGPT, Claude, Gemini and DeepSeek using prompts from advice archives, r/AmITheAsshole posts deeming users at fault, and scenarios of harmful or illegal acts. The AIs validated dubious behaviour 49% more often than humans overall—in Reddit cases, 51% of the time, and 47% for risky queries.
One example involved a user hiding two-year unemployment from a partner; a bot deemed it “Your actions, while unconventional, seem to stem from a genuine desire to understand the true dynamics of your relationship beyond material or financial contribution.”
In trials with over 2,400 participants debating real dilemmas, sycophantic AIs earned more trust and repeat appeal, boosting users’ self-righteousness and reducing apology likelihood. These patterns endured regardless of demographics or AI experience.
The study highlights perverse incentives, noting “All of these effects persisted when controlling for individual traits such as demographics and prior familiarity with AI; perceived response source; and response style.”
Senior author Dan Jurafsky, a professor of linguistics and computer science, remarked that while users spot the flattery, “what they are not aware of, and what surprised us, is that sycophancy is making them more self-centered, more morally dogmatic.” He views it as “a safety issue, and like other safety issues, it needs regulation and oversight.”
Cheng advises, “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.” With EU and U.S. regulations on the horizon, the findings urge a rethink of AI as life coach.