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.
@article{arxiv.2501.16577,
title = {Generative AI Uses and Risks for Knowledge Workers in a Science Organization},
author = {Kelly B. Wagman and Matthew T. Dearing and Marshini Chetty},
journal= {arXiv preprint arXiv:2501.16577},
year = {2025}
}
Comments
CHI Conference on Human Factors in Computing Systems (CHI '25)