AI 中文总结
通过对1174名成年人的随机实验发现，生成式AI缩小了不同教育背景劳动者的任务执行生产力差距，且提升效果并非完全源于任务委托。
AI 中文摘要
生成式人工智能（AI）是扩大还是缩小了不同劳动者之间的生产力差距？我们通过一项包含1174名年龄在25至45岁之间的成年人的随机在线实验研究这一问题，这些参与者完成了一项工作场所风格的问题解决任务，过程中部分人使用生成式AI助手，另一部分人不使用，之后所有人完成一个无AI辅助的模块。AI提升了所有参与者的表现，但受教育程度较低者的提升幅度更大：无AI时，高教育水平参与者的表现比低教育水平参与者高出0.548个标准差；有AI时，这一差距降至0.139，约缩小了初始差距的四分之三。聊天记录显示，低教育水平参与者获得了大量帮助，而高教育水平参与者能更有效地使用AI。这种提升并非完全源于任务委托：接受AI处理的参与者在移除AI后表现并未变差，且低教育水平参与者保留了部分提升，尽管会重新出现较大差距。无论参与者自身努力如何，频繁使用AI都会提升辅助下的表现，但后续表现的提升仅在频繁使用AI与持续努力相结合时才会出现。生成式AI缩小了任务执行中的有效生产力差异，而人力资本差异仍会影响无辅助表现和工具使用。
英文摘要
Does generative artificial intelligence (AI) widen or narrow productivity gaps across workers? We study this in a randomized online experiment with 1,174 adults aged 25-45 who completed a workplace-style problem-solving task with or without a generative AI assistant, followed by an unassisted module. AI improves performance for all participants, but gains are larger among those with less education. Without AI, higher-education participants outperform lower-education participants by 0.548 standard deviations; with AI, the gap falls to 0.139, closing about three-quarters of the initial difference. Chat logs show that lower-education participants obtain substantial assistance, while higher-education participants use AI more effectively. Gains are not purely due to delegation: treated participants do not perform worse once AI is removed, and lower-education participants retain part of their improvement, although a sizable gap re-emerges. Intensive AI use raises assisted performance regardless of participants' own effort, but follow-up performance improves only when intensive use is combined with sustained effort. Generative AI narrows effective productivity differences in task execution, while human-capital differences continue to shape unassisted performance and tool use.
