论文概要
研究领域: NLP 作者: Christopher Potts, Moritz Sudhof 发布时间: 2026-04-29 arXiv: 2504.21111
中文摘要
用户对AI的熟练程度在多大程度上塑造了AI实际为他们提供的价值？这个问题对用户、AI产品构建者和社会整体都至关重要，但尚未得到充分探索。通过对WildChat-4.8M中27K段丰富标注的对话样本分析，我们发现熟练用户比新手承担更复杂的任务，并采用根本不同的交互模式：他们与AI协作迭代，精炼目标并批判性评估输出，而新手则采取被动姿态。这些差异导致了AI熟练度悖论：熟练用户比新手经历更多失败——但他们的失败往往是可见的（是其积极参与的直接后果），更可能导致部分恢复，并且伴随着在复杂任务上的更大成功。相比之下，新手更常经历隐形失败：对话看似成功结束，实则偏离目标。这些结果重新界定了AI成功的依赖因素。个人应采取主动参与而非被动接受的姿态。AI产品构建者应认识到，他们设计的不仅是模型行为，还有用户行为；鼓励深度参与而非无摩擦体验，将带来整体更大的成功。
原文摘要
How much does a user's skill with AI shape what AI actually delivers for them? This question is critical for users, AI product builders, and society at large, but it remains underexplored. Using a richly annotated sample of 27K transcripts from WildChat-4.8M, we show that fluent users take on more complex tasks than novices and adopt a fundamentally different interactional mode: they iterate collaboratively with the AI, refining goals and critically assessing outputs, whereas novices take a passive stance. These differences lead to a paradox of AI fluency: fluent users experience more failures than novices -- but their failures tend to be visible (a direct consequence of their engagement), they are more likely to lead to partial recovery, and they occur alongside greater success on complex...
--- *自动采集于 2026-04-30*
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