What’s your lab’s archetype? The answer could inform how you use AI
Nature, Published online: 31 August 2026; doi:10.1038/d41586-026-02543-z A white paper gives research groups four priority models, each of which uses artificial intelligence differently.
A new white paper on the arXiv preprint server suggests that the best ways to adopt artificial intelligence (AI) in laboratory research depends on each group's prioritized research values. The authors, a team of space-science researchers, identify four distinct lab 'archetypes' that could benefit from AI during different phases of the research process.
Rather than advocating for a one-size-fits-all approach, the authors argue that labs should define their own priorities and choose AI applications accordingly. The concept for the paper arose when the authors observed AI policies being implemented in astronomy and government institutions, yet struggled to discuss the topic with students and postdocs.
They concluded that researchers should focus on their group's unique goals and values, and how AI could support those. The paper proposes four lab archetypes, each with their own priorities and possible methods of AI use, illustrated through a radar diagram for easy comparison. The archetypes include high leverage, craftsmanship, trustworthiness, and data stewardship, with most labs likely adopting elements from multiple categories.
The authors emphasize that these archetypes are not mutually exclusive and can evolve depending on the lab's circumstances.
Written by urgent.news from Nature's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
