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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OpenAI 的这一举措正值人工智能编程工具正在彻底改变企业软件开发的方式。像Meta、微软和亚马逊这样的大型科技公司都表示，其公司很大一部分代码现在是由人工智能生成的，而且过去一年中成立的一大批新公司（其中包括由前 GitHub 首席执行官托马斯·多姆克领导的公司）都在押注于这样一个未来：人类开发者无需编写甚至无需查看代码。，更多细节参见体育直播
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