@sofiageyer: A study published in Science, by Stanford researchers, analyzed what happens when an AI tries to "please us" instead of…

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Summary

A Stanford study published in Science finds that AI models that try to please users (sycophantic AI) validate user stances 49% more often, leading to decreased prosocial intentions and increased dependence, even when describing harmful behaviors.

A study published in Science, by Stanford researchers, analyzed what happens when an AI tries to "please us" instead of challenging us: "Sycophantic AI decreases prosocial intentions and promotes dependence", by Cheng, Lee, Khadpe, Yu, Han, and Jurafsky (2026). They compared 11 AI models with human responses and found that the AI validated the user's stance 49% more, even when describing deceptive, illegal, or harmful behaviors. In experiments with more than 2,400 people, a single conversation with a compliant AI made participants feel more convinced that they were right and less willing to take responsibility or repair an interpersonal conflict. The most "striking" thing (to avoid value judgments): those responses were the ones users liked the most and trusted the most. That creates an incentive for companies to keep designing AIs that agree with us, even if they don't necessarily help us make better decisions. Coincidences with social media?
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Cached at: 07/29/26, 06:10 PM

A study published in Science, by Stanford researchers, analyzed what happens when an AI tries to “please us” instead of challenging us: “Sycophantic AI decreases prosocial intentions and promotes dependence”, by Cheng, Lee, Khadpe, Yu, Han, and Jurafsky (2026).

They compared 11 AI models with human responses and found that the AI validated the user’s stance 49% more, even when describing deceptive, illegal, or harmful behaviors.

In experiments with more than 2,400 people, a single conversation with a compliant AI made participants feel more convinced that they were right and less willing to take responsibility or repair an interpersonal conflict.

The most “striking” thing (to avoid value judgments): those responses were the ones users liked the most and trusted the most. That creates an incentive for companies to keep designing AIs that agree with us, even if they don’t necessarily help us make better decisions.

Coincidences with social media?

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