人工智能建议抑制人们说“我不知道”的意愿，即使建议错误且鼓励准确性
AI advice suppresses people's willingness to say "I don't know", even when the advice is wrong and accuracy is incentivized
AI总结：
研究探讨人工智能建议对人回答问题及判断的影响，通过五项实验发现即便建议错误，有建议时人们说“我不知道”意愿降低，回答增多但正确率降，鼓励准确虽有改善但仍受影响，还可能改变元认知阈值。
AI中文摘要：
知道何时说“我不知道”对人类判断至关重要，但人工智能助手几乎能回答任何问题。在五项实验（N = 3132；四项预注册，一项直接复制）中，参与者回答难题且可选择不回应。设计错误的人工智能建议，将其使用与准确性分离。仅能使用人工智能就几乎消除了参与者暂缓判断的意愿，无论建议是主动请求还是仅展示。结果是参与者回答更多问题，但正确率仅为无人工智能时的三分之一，不过信心几乎翻倍。鼓励准确性和惩罚不准确性使参与者寻求和遵循人工智能建议减少，回答更准确，暂缓判断更频繁，但仍远低于无人工智能时。随着人工智能建议变得无处不在且不请自来，它们可能不仅影响答案准确性，还可能改变人们决定是否有足够知识回答的元认知阈值。
英文摘要：
Knowing when to say "I don't know" is fundamental to human judgment, yet AI assistants offer a fluent answer to almost any question. In five experiments (N = 3,132; four preregistered, one direct replication), participants answered difficult questions and could always decline to respond. We engineered the questions so that AI advice was wrong, separating AI use from its accuracy. Merely having access to AI nearly eliminated participants' willingness to suspend judgment, and this held whether the advice was actively requested or simply displayed. Consequently, participants answered more questions but were correct about a third as often as when AI was unavailable-yet their confidence nearly doubled. Incentivizing accuracy and penalizing inaccuracy led participants to seek and follow AI advice less, answer more accurately, and suspend judgment more often, though still far less than when AI was unavailable. As AI suggestions grow ubiquitous and unsolicited, they may not simply affect answer accuracy; they may even alter the metacognitive threshold at which people decide whether they know enough to answer.
