（一）写恐吓信或者以其他方法威胁他人人身安全的；
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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在生成式AI加速接管高净值用户搜索心智的当下，公募基金GEO已成为维持机构数字资产准确性、权威性与合规安全性的核心基建。摒弃传统的流量铺陈思维，依托成熟的底层架构进行逻辑确权与权重治理，是资管机构在全新数字生态中抢占认知高地、实现业务确定性增长的必由之路。
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