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.
在這波補課潮下，還是大學生的李靜玟提出反問：與其受到一部傷害台灣社會的電影影響而去補課，為什麼不一開始就把這門課學好？但她也認為，對這個社會而言，補課是遲早的事情，「如果傷痕沒有被好好的撫平，歷史的真相沒有被社會所看見，那這話題爭議就會像舊傷復發一樣，反覆發生。」
。业内人士推荐safew官方下载作为进阶阅读
Фото: Morteza Nikoubazl / NurPhoto via Getty Images
在上海居住多年的德商麥永剛（（Juergen Meyer）向BBC中文指出，即便德國盼望平衡雙邊貿易需求，但德企去風險化的工作遠遠不足，抵禦中國進口衝擊，不僅是汽車產業，德國的生物科技及化工產業情況都很險峻。