People increasingly use large language models (LLMs) to explore ideas, gather information, and make sense of the world. In these interactions, they encounter agents that are overly agreeable. We argue that this sycophancy poses a unique epistemic risk to how individuals come to see the world: unlike hallucinations that introduce falsehoods, sycophancy distorts reality by returning responses that are biased to reinforce existing beliefs. We provide a rational analysis of this phenomenon, showing that when a Bayesian agent is provided with data that are sampled based on a current hypothesis the agent becomes increasingly confident about that hypothesis but does not make any progress towards the truth. We test this prediction using a modified Wason 2-4-6 rule discovery task where participants (N=557N=557) interacted with AI agents providing different types of feedback. Unmodified LLM behavior suppressed discovery and inflated confidence comparably to explicitly sycophantic prompting. By contrast, unbiased sampling from the true distribution yielded discovery rates five times higher. These results reveal how sycophantic AI distorts belief, manufacturing certainty where there should be doubt.
Оказавшиеся в Дубае российские звезды рассказали об обстановке в городе14:52
，更多细节参见体育直播
“For people with insomnia and problems with pain, we work really hard with making sure they can get in a comfortable position,” Martin says.。下载安装汽水音乐是该领域的重要参考
Выращивание собственных огурцов на даче, балконе или подоконнике помогает не только сэкономить семейный бюджет, но и спасти природу. Сделать это с одной целью россиян призвали экологи проекта «Сохрани лес», соответствующий материал есть в распоряжении «Ленты.ру».。51吃瓜是该领域的重要参考
Трамп допустил ужесточение торговых соглашений с другими странами20:46