Johan Ugander

@jugander.bsky.social

Associate Professor, Yale Statistics & Data Science. Social networks, social and behavioral data, causal inference, mountains. https://jugander.github.io/

I will be visiting Yale SOM for AY 2026/2027 The visit includes me teaching an interdisciplinary PhD methods course. If you often experience New Havenness, ask your Dr (advisor) whether "Methods Stumblers" may be right for you.

We are very excited to announce our first workshop on From Theory to Practice: behind the scenes on research deployments at EC’26 (July 6 in Rome)! Call for posters and submissions now open! Organized by myself, @ericachiang.bsky.social , Bailey Flanigan, @brwilder.bsky.social

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About This workshop will focus on the practical realities of deploying algorithmic and economic systems from academic research, especially with government and non-profit partners. While economics and ...

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Lots of provocations here, looking forward to reading. Its a brave new world for social science! I'm optimisic about automating the "boring parts" of research, but pessimistic about implications of the deluge of slop (its bad enough already). Two threads I find interesting re agentic research:

Per Engzell@pengzell.bsky.social · 3mo ago

What can we learn from automating an entire quantitative social science paper, from prompt to finished product? Thread about ongoing work with @natewilmers.bsky.social 1/12 Paper: osf.io/preprints/so...

I'm at MIT tomorrow, Monday, giving the Sloan OM Seminar, 11:45a–1p. Talking about recent work on causal inference under "structured" interference w/ Kevin Han and Shuangning Li. MIT folks, come say hi!

“We have many years of experience picking apart the work of the world’s best security researchers, and Mythos Preview is every bit as capable. So far we’ve found no category or complexity of vulnerability that humans can find that this model can’t.”

conputer dipshit@davidcrespo.bsky.social · 4mo ago

271 vulns fixed. but: "Encouragingly, we also haven’t seen any bugs that couldn’t have been found by an elite human researcher." — now that's interesting

🚨New preprint and our results are rather concerning.. We find the "boiling frog" equivalent of AI use. Using large-scale RCTs, we provide *casual* evidence that AI assistance reduces persistence and hurts independent performance. And these effects emerge after just 10–15 minutes of AI use! 1/

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Nature meta-research project puts claims in social-science paper to the test. Refs in last post I'm interested in Econ and Psych so I focused on that: Econ had about the same rate of "not reproducible" analyses as Psych and a worse rate then Political Science.

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