Field guide. Quartermaster. Associate Professor and Research Dean at UVA School of Data Science. Views my own. Newsletter: blog.stephenturner.us/
Charlottesville, VA
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October 2026 links: Tacit knowledge, AI and #biosecurity, field building, chat with DNA, #Nextflow, AI in academia and science, #Rstats package development, peer review blog.stephenturner.us/p/octo…
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Stephen Turner retweeted
We are excited to announce our partnership with University of Virginia's Aikyam Lab, part of the School of Data Science @uvadatascience, alongside @_cagarwal and @strnr.
The Mace AI Fellowship in Trustworthy Computing funds AI safety research at the school.
ALT Mace AI Funds a UVA Fellowship at The School of Data Science
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I wrote this morning in the UVA AI Exchange newsletter about Claude Code’s new code modernization plugin, rewrites in #bioinformatics, and the fact that you can just build stuff now aiatuva.substack.com/p/rewri…
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Follow up demonstration: Comparing Virginia degree programs with SCHEV’s ROI data aiatuva.substack.com/p/virgi…
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If you haven’t already seen it - a recent post from @strnr on SubStack is also pretty timely and related to this: open.substack.com/pub/stephe…
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Lots of debate this week on whether journals should ban AI in peer review.
We actually tested this in our new preprint, and the results were pretty clear to me.
For context, I've reviewed for most of the big journals and evaluated 1,000 human reviews as an editor. I love to read and evaluate science.
TLDR: From now on I won't do any peer review without AI. For clinical trials, I'd even call human-only review dangerous 🧵
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Anthropic is not pitching Normal Technology blog.stephenturner.us/p/anth… (cc @random_walker @sayashk)
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AI Reviews Might Beat Human Peer Reviews doi.org/10.59350/006kh-wdm07
A limited demonstration that AI reviews can do the job of human reviewers at improving papers. Deciding what to publish still needs an accountable editor with human reviewers they trust.
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Very good essay. You can read it in 5 minutes. I wrote some of my own thoughts on this over the weekend.
What Counts as Impact? doi.org/10.59350/006jq-a4y25
Some of my thoughts about the surge in AI-generated papers, why this feels like a completely new kind of problem, and what this means for how we evaluate science in biology.
Out now in PLOS Biology:
journals.plos.org/plosbiolog…
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Personal essay, weekend edition: I’m Skeptical of AI Disclosures blog.stephenturner.us/p/ai-d…
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Academic life & discourse, #biosecurity, AIxBio, creativity, peer review, Thomas Jefferson blog.stephenturner.us/p/sept…
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Generative AI for Biosciences: Emerging Threats and Roadmap to Biosecurity arxiv.org/abs/2510.15975 🧬🖥️🧪
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The Tidyomics Ecosystem tidyomics.github.io/tidyomic… An introduction to the tidyomics ecosystem, including principles, core packages, publications, and community resources for tidy omic analysis. #Rstats
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AI-driven formative assessment and adaptive learning in data-science education: Evaluating an LLM-powered virtual teaching assistant arxiv.org/abs/2509.20369
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A powerful framework for differential co-expression analysis of general risk factors academic.oup.com/bioinformat… 🧬🖥️🧪 #Rstats pkg: github.com/ajbass/kdca
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R+AI. Nov 12–13. Online. Cheap ($25-70) #Rstats rconsortium.github.io/RplusA…
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SNiPgenie: a tool for microbial SNP site detection from WGS data pmc.ncbi.nlm.nih.gov/article… 🧬🖥️🧪 github.com/dmnfarrell/snipge…
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