We propose sycophancy leads to less discovery and overconfidence through a simple mechanism: When AI systems generate responses that tend toward agreement, they sample examples that coincide with users’ stated hypotheses rather than from the true distribution of possibilities. If users treat this biased sample as new evidence, each subsequent example increases confidence, even though the examples provide no new information about reality. Critically, this account requires no confirmation bias or motivated reasoning on the user’s part. A rational Bayesian reasoner will be misled if they assume the AI is sampling from the true distribution when it is not. This insight distinguishes our mechanism from the existing literature on humans’ tendency to seek confirming evidence; sycophantic AI can distort belief through its sampling strategy, independent of users’ bias. We formalize this mechanism and test it experimentally using a rule discovery task.
中共中央政治局委员、外交部长王毅3月4日同沙特外交大臣费萨尔通电话。
，详情可参考搜狗输入法
村民卢森说：“我们夫妻在工地上干活，工作送上门，一年能挣六七万！”
没什么用，但就是好玩：盘点或恶搞或无聊的「神经病」应用。看看都有啥
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