Dan Goldstein
@dggoldst
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Senior Principal Research Manager at Microsoft Research NYC. Economics and Computation Group. Distinguished Scholar at Wharton.
New York
Joined October 2007
If you see a graph like this, I don't think you should conclude people are "really bad" at estimating something (like where they sit in the income distribution or the size of groups in America), unless you truly believe they're "really bad" at estimating everything. 1/4
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RT @szaszibarnabas: 🧵 Can you predict whether behavioral interventions will work in new contexts? . … probably not, right? . In our new….
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New paper just dropped:. Szaszi, Barnabas, Daniel G. Goldstein, Dilip Soman, Susan Michie. (2025). Generalizability of Choice Architecture Interventions. Nature Reviews Psychology. Thanks to @szaszibarnabas for doing the lion's share!.
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RT @JQ_Zhu: Centaur may have learned a shortcut that explains away psychological tasks. @PsychBoyH . Link to preprint: .
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Do you have strong programming skills but need research experience before heading off to grad school for computational social science / business / econ? Apply now to predoc with me and @DavMicRot and @jakehofman. DMs open .
microsoft.com
Are you a recent college graduate wishing to gain research experience prior to pursuing a Ph.D. in fields related to computational social science (CSS)? Do you have a deep love of “playing with...
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The Society for Judgment and Decision Making is pleased to announce that the latest newsletter is ready for download:. This issue contains announcements, conferences, jobs, and a new section entitled HotFresh Research News!.
decisionsciencenews.com
SOCIETY FOR JUDGMENT AND DECISION MAKING NEWSLETTER The Society for Judgment and Decision Making is pleased to announce that the latest newsletter is ready for download: This issue contains announc…
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RT @erikbryn: Check out the Stanford AI Index Report: @indexingai . It's the best one-stop-shop for credible, current data on AI trends. ht….
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New from @MSFTResearch and @HarvardHBS colleagues.
Great and intriguing paper out recently on how Generative AI is changing knowledge work. What a time to be doing ORG econ!
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A nice discussion of why it is so hard to outpredict models. References one of my favorite papers: . "Improving out-of-population prediction. The complementary effects of model assistance and judgmental bootstrapping".
Why is it so hard to show that people can be better decision-makers than statistical models? Some ways that common intuitions about the superiority of human judgment contradict statistical reality, and a few that don't.
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🚨 Predoc at Microsoft Research 🚨. Do you have strong front-end programming and statistics skills but need research experience before heading off to graduate school for a computational social science PhD? Apply now for this summer!.
microsoft.com
Are you a recent college graduate wishing to gain research experience prior to pursuing a Ph.D. in fields related to computational social science (CSS)? Do you have a deep love of “playing with...
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RT @serinachang5: What happens when a static benchmark comes to life? ✨Introducing ChatBench, a large-scale user study where we *converted*….
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UPDATE APRIL 2025. The best explanation of this has been published by Guay et al in PNAS:.
🚨Out today in PNAS @PNASNews🚨. Why do people overestimate the size of politically relevant groups (immigrant, LGBTQ, Jewish) and quantities (% of budget spent on foreign aid, % of refugees that are criminals)?. We analyze 100k estimates to find out🧵👇
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RT @BrianMGuay: 🚨Out today in PNAS @PNASNews🚨. Why do people overestimate the size of politically relevant groups….
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RT @SJDM_Tweets: The Society for Judgment and Decision Making is pleased to announce that the latest newsletter is ready for download:. htt….
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RT @jakehofman: Attention NYC undergrads: Applications are open for our 12th annual Data Science Summer school at Microsoft Research NYC! A….
microsoft.com
Microsoft Research New York City’s Data Science Summer School (DS3) is an intensive hands-on introduction to data science for NYC-area undergraduate students who are interested in attending graduate...
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While there are big crowds on the "AI hurts learning" train, let's realize that's like saying "computers hurt learning". Two papers where unaided learners do better after AI interaction:.
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It gets harder and harder to identify experts through tests because of cheating with AI. Forecasting performance will become the primary metric on which experts compete. Those who consistently outforecast AI are either psychic or possess valuable knowledge and judgment.
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