We ran a randomized controlled trial to see if LLMs can help novices perform molecular biology in a wet-lab.
The results: LLMs may help in some aspects, but we found no significant increase at the core tasks end-to-end. That's lower than what experts predicted.
Our findings π§΅
19.02.2026 17:37 β
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I think doing this genre of modelling work could be really valuable. After my PhD I applied for a job with GiveWell because I was excited about this (but didn't make it past their first round)
11.12.2025 11:12 β
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My POV is that scientific best practises on modelling are worth adhering to. And that it'd be possible to do the types of sensitivity and assumption checking analysis GiveWell that values more effectively using best practise statistical methods (e.g. Bayesian workflow)
11.12.2025 11:12 β
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My understanding of this is:
* The domain is characterised by many difficult decisions about assumptions
* GiveWell staff and leadership feel more comfortable working and communicating using spreadsheets
11.12.2025 11:12 β
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GiveWell have supported development of Bayesian software, though in practise I don't think they are using it very much: www.givewell.org/research/inc... github.com/wwiecek/baggr
11.12.2025 11:12 β
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I've also looked into this and reached the a similar conclusion. Here are some additional links/thoughts:
11.12.2025 11:12 β
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My bad!
26.11.2025 15:07 β
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I'd like to see AGHQ in lme4/glmmTB! This is a good opportunity to have impact across statistical theory/methods/application (with two great mentors).
26.11.2025 11:57 β
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