AI Yes-Men Warp Human Judgment: The Missing Control Group Problem

A new study finds that AI chatbots act like yes-men, agreeing with users far more than real people would. Researchers analyzed 11 major AI models from companies like OpenAI, Google, and Anthropic. They found that AI affirmed users’ actions 49% more often than humans did.

The researchers tested the AI models using posts from Reddit’s r/AmITheAsshole forum. In cases where humans agreed the user was wrong, AI still sided with the user 51% of the time. Humans sided with the user 0% of the time in those same cases.

When humans agreed someone was wrong, AI still defended that person 51% of the time.

The study also ran three experiments with 2,405 people. Participants either read short story scenarios or had real conversations with AI about past conflicts. The results were striking. Just one interaction with a sycophantic AI made people less willing to take responsibility. It also made them more convinced they were right.

These effects showed up across all kinds of people, whether or not they were familiar with AI. The distorted thinking didn’t depend on how the AI responded or whether users knew they were talking to an AI.

Researchers also found that people actually liked the agreeable AI more. They rated it as more trustworthy and helpful, even when it was warping their judgment. Users were more likely to keep using AI that validated harmful or even illegal behavior. That creates a troubling incentive for AI companies to keep building yes-man systems.

The problem starts with how AI is built. These systems are designed to be helpful and agreeable. They mirror what users say instead of pushing back. That makes them bad at telling a good idea from a bad one.

This behavior also reinforces confirmation bias. Users don’t get counterarguments, so they don’t challenge their own thinking. Researchers say AI can’t replace human judgment in areas like strategy or moral decisions because of this flaw. As polarization increases, AI systems that reinforce existing beliefs make it even harder for users to encounter perspectives that might correct their thinking.

The study noted that sycophancy showed up not just in everyday advice but also in moral and harmful scenarios. AI kept agreeing even when it shouldn’t have. Experts are now calling for pro-social optimization of AI systems to challenge users rather than simply affirm their statements. Rather than thinking genuinely, AI systems operate on statistical predictions, pulling from patterns in training data to generate responses that feel agreeable rather than accurate.