与AI合作：衡量生成式AI对职业的适用性
Working with AI: Measuring the Applicability of Generative AI to Occupations
AI总结：
本文通过分析微软Bing Copilot的对话数据，研究生成式AI对职业适用性的影响，发现信息工作是最常见的AI应用领域，并预测哪些职业更可能使用AI辅助工作。
摘要：
随着生成式AI作为一种通用技术的出现，理解其经济影响已成为社会最紧迫的问题之一。现有对AI影响的研究大多依赖于对AI能力的预测，或局限于单个企业。相反，我们利用真实世界中的AI使用情况，分析了一个包含20万条匿名与微软Bing Copilot对话的数据集，以衡量AI对职业的适用性。我们使用基于大型语言模型的流程来分类每条对话中由AI协助或执行的O*NET工作活动。我们发现，最常见且成功的AI协助工作活动涉及信息工作——信息的创建、处理和交流。在职业层面，我们发现AI的适用性广泛存在于各个行业，因为大多数职业都有信息工作成分。我们的方法还允许我们预测哪些职业更可能将任务委托给AI，哪些职业更可能使用AI协助现有工作流程。
英文摘要：
With generative AI emerging as a general-purpose technology, understanding its economic effects is among society's most pressing questions. Existing studies of AI impact have largely relied on predictions of AI capabilities or focused narrowly on individual firms. Drawing instead on real-world AI usage, we analyze a dataset of 200k anonymized conversations with Microsoft Bing Copilot to measure AI applicability to occupations. We use an LLM-based pipeline to classify the O*NET work activities assisted or performed by AI in each conversation. We find that the most common and successful AI-assisted work activities involve information work--the creation, processing, and communication of information. At the occupation level, we find widespread AI applicability cutting across sectors, as most occupations have information work components. Our methodology also allows us to predict which occupations are more likely to delegate tasks to AI and which are more likely to use AI to assist existing workflows.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
