The scars of the Iraq War run deep in Europe. At the time, France, led by President Jacques Chirac, could not countenance supporting an attack on Saddam Hussein, given the weak evidence for either weapons of mass destruction or a link to the horrors of 9/11. When the Spanish prime minister, Jose Maria Aznar, agreed to back President George W. Bush there was a popular backlash. Tony Blair, the then U.K. leader, still suffers under the “Bliar” tag.
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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对于无人配送车这一前沿赛道而言，真正的护城河，从来不是单一的技术参数，而是一整套能够应对政治波动、网络攻击、数据合规、供应链中断等复合风险的系统能力。，推荐阅读PDF资料获取更多信息
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