arXiv cs.CY· Giuseppe Soda, Alessandro Iorio, Leonardo Rizzo·· 12 小时前AI 评分48
生成式 AI 如何影响知识工作者的协作与社会网络：基于 Microsoft Copilot 的研究
The Effects of Generative AI on Collaboration and Social Networks Among Knowledge Workers
AI 导读
一项基于 12,000 余名知识工作者 13 个月行为数据的研究发现，Microsoft Copilot 的使用增加了跨沟通渠道的协作时间，使用者与更多同事互动、网络聚类度下降，协作结构趋于拓宽。同时，协作更多集中在有较强合作历史的既有关系上，加深了对已信任同事的依赖。研究采用交错双重差分与固定效应工具变量两种准实验设计，认为生成式 AI 改变工作方式但未必取代人际互动。
正文 · 原文
Abstract:The rapid diffusion of generative artificial intelligence has raised concerns that knowledge work may become less dependent on human-to-human interaction. Yet because AI-generated outputs require interpretation, verification, and social legitimation, generative AI may instead increase collaboration among workers. We test these competing predictions using passively collected behavioral data from more than 12,000 knowledge workers observed over 13 months during the staged organizational rollout of an AI-powered assistant (Microsoft Copilot). Using two complementary quasi-experimental designs -- a staggered difference-in-differences model and a fixed-effects instrumental-variable approach -- we estimate the effects of generative AI on workers' collaboration behavior and social network structure. We estimate that generative AI increased collaboration time across communication channels and reshaped individual networks. Those using generative AI interacted with more colleagues and their networks became less clustered, indicating broadening in collaboration structures. At the same time, they also concentrated more of their collaboration on ties with stronger prior histories, deepening reliance on already trusted colleagues. Together, these findings suggest that, while generative AI changes how people work, it may not displace human-to-human interactions.
| Subjects: | Physics and Society (physics.soc-ph); Computers and Society (cs.CY) |
| Cite as: | arXiv:2610.32461 [physics.soc-ph] |
| (or arXiv:2610.32461v1 [physics.soc-ph] for this version) | |
| https://doi.org/10.48550/arXiv.2610.32461 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Leonardo Rizzo [view email]
[v1]
Fri, 23 Oct 2026 10:27:08 UTC (542 KB)
来源：arXiv cs.CY · arxiv.org