研究AI在实验室和野外物理任务中的应用障碍与未来可能。
Beyond the Desk: Barriers and Future Opportunities for AI to Assist Scientists in Embodied Physical Tasks
- 通过访谈12位科学家，发现三类使用AI的现实障碍。
- 高风险实验、环境限制和人类隐性知识使AI难替代人力。
- 未来AI可作后台支持，如监测状态、组织知识、保障健康。
越来越多科学家开始使用AI，但现有研究仅关注其在办公桌前的计算机工作。而科学实践常发生在实验室和野外现场，因此我们开展了首个关于科学家在具身物理任务中使用AI的研究。通过对12位从事核聚变、灵长类认知、生物化学等领域的科研人员进行访谈，发现三大障碍：1）实验设置高风险，无法承受AI错误；2）环境受限，难以部署AI；3）AI无法匹配人类的隐性知识。参与者进一步提出未来AI助手的五种设想：监测任务状态、整合全实验室知识、监控科研人员健康、开展野外勘查、完成实际操作任务。研究指出，AI应作为支持物理工作的背景基础设施，而非取代人类专家。
原文摘要 · Abstract (English)
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.
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