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独著作者的回归:生成式人工智能时代科学领域劳动分工的变化

Return of the solo author: The changing division of labor in science in the age of generative AI

Akira Matsui

arXiv 2607.10780首次发表:更新:

AI 中文总结

研究探讨生成式人工智能时代科学领域劳动分工变化,通过分析大量作品发现ChatGPT发布后独著率下降趋势逆转且不均匀,在特定领域明显,涉及作者类型多样,揭示了生成式人工智能对科学劳动替代及论文内认知劳动重新配置情况。

AI 中文摘要

现代科学经历了从个人工作到团队合作的长期转变。生成式人工智能似乎通过降低研究成本和实现更大规模的合作来延续这一趋势。然而,如果曾经由合著者执行的任务可以委托给人工智能,这项技术也可能削弱研究过程中部分环节对合作的需求。本文通过关注作者数量分布中的独著尾部,而非平均团队规模,来研究这种矛盾。分析26个领域的3亿多篇作品后发现,2022年末ChatGPT发布后,长达数十年的独著率下降趋势停止并部分逆转。这一现象并不均匀:在合著者工作更容易被替代的领域最为明显,而在依赖实地合作的领域则较弱或不存在。在个人层面,这种回升并非由新研究人员的加入或领域构成的变化所解释。相反,这种转变出现在那些只与他人合作过的作者中,包括那些之前没有独著发表过的作者,以及资深作者和新人。他们的独著论文与合著作品相近,但范围变窄并转向计算主题。由于独著论文没有署名的人类合著者,本研究提供了关于生成式人工智能如何替代科学劳动的实证探索,以及论文内部认知劳动重新配置而非团队规模变化的证据。

英文摘要

Modern science has experienced a long shift from individual work to team production. Generative artificial intelligence (AI) might appear to extend this trajectory by lowering research costs and enabling larger-scale collaboration. Yet if tasks once performed by coauthors can be delegated to AI, the same technology may also weaken the need for collaboration in parts of the research process. Here, we examine this tension by moving beyond average team size and focusing on the solo-authored tail of the author-count distribution. Analyzing over 300 million works across 26 fields, we find that the decades-long decline in solo authorship halted and partially reversed with ChatGPT's public release in late 2022. We also reveal that this is an uneven phenomenon: it is strongest in fields where coauthors' work is more readily replaceable, and weak or absent in fields that depend on physical collaboration. At the individual level, the recovery is not explained by the entry of new researchers or by changes in field composition. Instead, the break appears among authors who had written only with others, including those with no prior solo publications, and among long-established authors as well as newcomers. Their solo papers stay close to their own coauthored work while narrowing in scope and shifting toward computational topics. Because a solo paper is work without credited human coauthors, this study offers an empirical probe of how generative AI can substitute for scientific labor, and evidence of a reconfiguration of cognitive labor within papers rather than of team size.

Comments37 pages, 12 figures

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