GoKawiilSpace scientists propose four lab 'archetypes' to guide AI adoption policies
A team of astronomers, led by Sarah Burke-Spolaor at West Virginia University and Michelle Ntampaka at the Space Telescope Science Institute, posted an unreviewed white paper on arXiv outlining four archetypes for research groups to help them decide how to use AI tools like large language models. Rather than proposing a single universal policy, the framework maps each lab type against its research priorities using a radar-style diagram to suggest which AI applications, from code generation to writing assistance, best fit its values.
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As AI tools become embedded in everyday research tasks, from note-taking to coding, institutions are scrambling to set rules without a shared framework for what those rules should protect. This paper offers principal investigators a practical starting point for internal conversations with students and postdocs, framing AI adoption as a values question rather than a binary allow-or-ban decision.
- The white paper defines four lab archetypes to guide tailored AI adoption strategies.
- It has been posted on arXiv but has not yet undergone peer review.
- The authors argue AI policy should reflect a lab's specific research values rather than a blanket rule.
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Published there as: “What’s your lab’s archetype? The answer could inform how you use AI”
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