调研科研机构员工用AI的实况与顾虑，发现小规模增长但潜力大。
Generative AI Uses and Risks for Knowledge Workers in a Science Organization
- 通过问卷和访谈，分析66名员工使用AI工具的现状。
- 内部工具Argo被少量但稳步使用，主要作助手或流程代理。
- 核心担忧在数据安全、论文发表与岗位影响，适合组织管理者参考。
生成式AI可能通过支持科学机构中的知识工作者来促进科学发现，但其在实际应用中的情况及感知风险尚不明确。本文报告了与美国国家实验室合作的研究，涵盖科学与运营部门员工对生成式AI工具的使用情况。调查了66名员工，访谈22人，并测量了内部生成式AI界面Argo在全实验室的早期采用情况。研究发现：(1) Argo使用数据显示科学与运营人员的小幅且持续增长的使用；(2) 当前及预期使用场景可归为两类：(2) 协作助手模式或 (3) 工作流代理模式；(4) 主要担忧包括敏感数据安全、学术出版规范以及对工作岗位的影响。基于上述发现，本文为科学及其他组织提出生成式AI使用的建议。
原文摘要 · Abstract (English)
Generative AI could enhance scientific discovery by supporting knowledge workers in science organizations. However, the real-world applications and perceived concerns of generative AI use in these organizations are uncertain. In this paper, we report on a collaborative study with a US national laboratory with employees spanning Science and Operations about their use of generative AI tools. We surveyed 66 employees, interviewed a subset (N=22), and measured early adoption of an internal generative AI interface called Argo lab-wide. We have four findings: (1) Argo usage data shows small but increasing use by Science and Operations employees; Common current and envisioned use cases for generative AI in this context conceptually fall into either a (2) copilot or (3) workflow agent modality; and (4) Concerns include sensitive data security, academic publishing, and job impacts. Based on our findings, we make recommendations for generative AI use in science and other organizations.
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