Beyond the Desk: Barriers and Future Opportunities for AI to Assist Scientists in Embodied Physical Tasks

TL;DR

This study explores how AI can assist scientists in physical lab and field tasks, identifying barriers and proposing future AI roles to support embodied scientific work beyond traditional desk-based applications.

Contribution

It is the first to investigate AI use in embodied scientific tasks and proposes future AI assistant designs tailored for lab and field environments.

Findings

Three main barriers to AI adoption in physical science work

Designs for AI to monitor, organize, and support physical scientific tasks

AI viewed as infrastructure support rather than replacement of human expertise

Abstract

More scientists are now using AI, but prior studies have examined only how they use it 'at the desk' for computer-based work. However, given that scientific work often happens 'beyond the desk' at lab and field sites, we conducted the first study of how scientific practitioners use AI for embodied physical tasks. We interviewed 12 scientific practitioners doing hands-on lab and fieldwork in domains like nuclear fusion, primate cognition, and biochemistry, and found three barriers to AI adoption in these settings: 1) experimental setups are too high-stakes to risk AI errors, 2) constrained environments make it hard to use AI, and 3) AI cannot match the tacit knowledge of humans. Participants then developed speculative designs for future AI assistants to 1) monitor task status, 2) organize lab-wide knowledge, 3) monitor scientists' health, 4) do field scouting, 5) do hands-on chores. Our findings point toward AI as background infrastructure to support physical work rather than replacing human expertise.