Friendlier LLMs tell users what they want to hear — even when it is wrong

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29 April 2026 Friendlier LLMs tell users what they want to hear — even when it is wrong A large language model that is trained to respond in a warm manner is more likely to give incorrect information and reinforce conspiracy beliefs. By Desmond Ong ORCID: http://orcid.org/0000-0002-6781-8072 0 Desmond Ong Desmond Ong is in the Department of Psychology, University of Texas at Austin, Austin 78712, Texas, USA. View author publications PubMed Google Scholar

If you use artificial-intelligence tools, you might find that, as well as helping with business tasks, answering general questions or writing programming code, AI models can be surprisingly good at giving advice about personal issues. Indeed, growing numbers of people are turning to AI tools for emotional support1, and there is some evidence that people perceive responses generated by AI as more empathic than those written by humans2.

Nature 652, 1134-1135 (2026)

doi: https://doi.org/10.1038/d41586-026-01153-z

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Competing Interests The author declares no competing interests.

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