作为狼群的到来：AI代理能否取代或增强社会科学家？
Vibe Researching as Wolf Coming: Can AI Agents with Skills Replace or Augment Social Scientists?
AI总结：
本文探讨AI代理在社会科学研究中的潜力，提出vibe研究概念，分析其在速度、覆盖和方法论上的优势及理论原创性的局限，并提出五条负责任的研究原则。
摘要：
AI代理——能够执行多步骤推理工作流、具有持久状态、工具访问和专业技能的系统——代表了社会科学研究中以往自动化技术的质变。不同于仅响应孤立查询的聊天机器人，AI代理现在可以阅读文件、运行代码、查询数据库、搜索网络并调用领域特定技能，以执行完整的研究流程。本文引入了“vibe研究”这一概念——AI时代与“vibe编程”相对应的概念，并以涵盖从想法到提交的18个有序阶段和53个质量门的scholar-skill插件作为示例。我开发了一个认知任务框架，将研究活动沿两个维度进行分类——可编程性和隐性知识需求，以确定一个认知边界，而非顺序边界：它贯穿研究流程的每一个阶段，而非在阶段之间。我主张AI代理在速度、覆盖范围和方法论支架方面表现优异，但在理论原创性和隐性领域知识方面存在困难。本文最后分析了三个对专业领域的影响——增强与脆弱条件、分层风险和教学危机，并提出了五条负责任的vibe研究原则。
英文摘要：
AI agents -- systems that execute multi-step reasoning workflows with persistent state, tool access, and specialist skills -- represent a qualitative shift from prior automation technologies in social science. Unlike chatbots that respond to isolated queries, AI agents can now read files, run code, query databases, search the web, and invoke domain-specific skills to execute entire research pipelines autonomously. This paper introduces the concept of vibe researching -- the AI-era parallel to vibe coding -- and uses scholar-skill, a 26-skill plugin for Claude Code covering the full research pipeline from idea to submission across 18 orchestrated phases with 53 quality gates, as an illustrative case. I develop a cognitive task framework that classifies research activities along two dimensions -- codifiability and tacit knowledge requirement -- to identify a delegation boundary that is cognitive, not sequential: it cuts through every stage of the research pipeline, not between stages. I argue that AI agents excel at speed, coverage, and methodological scaffolding but struggle with theoretical originality and tacit field knowledge. The paper concludes with an analysis of three implications for the profession -- augmentation with fragile conditions, stratification risk, and a pedagogical crisis -- and proposes five principles for responsible vibe researching.
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。
