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.
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。雷电模拟器官方版本下载是该领域的重要参考
此外，有些特朗普的政策被指加劇通脹——哈佛大學的經濟學家估算，特朗普在2025年實施的關稅使美國消費者物價通脹率（相較於原本可能的水平）在2026年1月約提高了 0.92個百分點。。币安_币安注册_币安下载对此有专业解读
Квартиру в Петербурге затопило кипятком после обрушения потолка20:57