Generative AI Uses and Risks for Knowledge Workers in a Science Organization
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.
Code (0)
등록된 구현이 없습니다.
Tasks
scientific discoverySimilar Papers 제목 키워드 기반
ErgoChat: a Visual Query System for the Ergonomic Risk Assessment of Construction Workers
In the construction sector, workers often endure prolonged periods of high-intensity physical work and prolonged use of tools, resulting in injuries and illnesses primarily linked to postural ergonomic risks, a longstand…
Image CaptioningQuestion AnsweringVisual Question AnsweringVisual Question Answering (VQA)A data science axiology: the nature, value, and risks of data science
Data science is not a science. It is a research paradigm with an unfathomed scope, scale, complexity, and power for knowledge discovery that is not otherwise possible and can be beyond human reasoning. It is changing our…
Redefining Research Crowdsourcing: Incorporating Human Feedback with LLM-Powered Digital Twins
Crowd work platforms like Amazon Mechanical Turk and Prolific are vital for research, yet workers' growing use of generative AI tools poses challenges. Researchers face compromised data validity as AI responses replace a…
Shifting Work Patterns with Generative AI
We present evidence on how generative AI changes the work patterns of knowledge workers using data from a 6-month-long, cross-industry, randomized field experiment. Half of the 7,137 workers in the study received access …
How do Data Science Workers Collaborate? Roles, Workflows, and Tools
Today, the prominence of data science within organizations has given rise to teams of data science workers collaborating on extracting insights from data, as opposed to individual data scientists working alone. However, …