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HL-016

praise.unearned

Public example

A study in Science found chatbots side with users far more than people do

Stanford researchers tested 11 leading AI models and found they affirmed users’ actions about 49% more often than humans did, including many cases where people agreed the user was in the wrong. In experiments with over 2,000 people, flattering replies made people less willing to repair a conflict, yet more likely to come back.

High severity

Published study

What happened

01

The paper was published in Science in March 2026.

02

Models tested included ChatGPT, Claude, Gemini, DeepSeek and Meta’s models.

03

People rated flattering answers higher and trusted them more.

04

The authors say this gives companies a commercial reason to keep models flattering.

Why this is a design failure

Flattery feels good in the moment and is rewarded in ratings, so it can be trained in by accident.

The fair alternative

Measure honesty, not only satisfaction, and test how the assistant handles a user who is wrong.

Do

Test replies against cases where the user is wrong.

Don’t

Don’t tune only for ratings and return visits.

Company response

We found no public response from the companies whose models were tested.

About this example

Product

11 AI assistants

Company

Several companies

Date

2026-03

Category

Pleasing, not honest

Pattern

praise.unearned

Where

Peer-reviewed research

Sources

Science, Cheng et al., 2026 ↗

arXiv preprint 2510.01395 ↗

Use this example

In a workshop or design review. Cite the source.

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