Alex Imas

Workshops - Society For Neuroeconomics

ONE WEEK! The Society for Neuroecon conference is in Cambridge, MA in 1 week!

We are thrilled to have @amberalhadeff.bsky.social and @aleximas.bsky.social as the speakers for our neuroscience and social/decision science workshops

neuroeconomics.org/workshops/

‼️Event Alert‼️ Join @angeladuckworth.bsky.social & @katymilkman.bsky.social for a conversation with Nobel Prize winning economist @rthaler.bsky.social and Professor @aleximas.bsky.social about their new book, The Winner’s Curse.

📅 Thurs, Oct 23 | 4-5PM
📍 Huntsman Hall G06
📩RSVP: bit.ly/4nbI9EG

Probably longer than you need, but Richard Thaler and I have a book coming out trying to do just that. The chapters on Risk and Utility are especially pertinent: a.co/d/4HpJfEt

Why Students Lie About Using AI Chicago Booth’s Alex Imas talks about perceptions of AI use in the classroom.

Why do students lie about using AI?

Chicago Booth's @aleximas.bsky.social talks about perceptions of AI use in the classroom.

www.chicagobooth.edu/review/podca... #econsky

Systemic Discrimination: Theory and Measurement* Abstract. Economists often measure discrimination as disparities arising from the direct effects of group identity. We develop new tools to model and measu

#QJE Aug 2025, #2, “Systemic Discrimination: Theory and Measurement,” by Bohren, Hull (@instrumenthull.bsky.social), and Imas (@aleximas.bsky.social): doi.org/10.1093/qje/...

Twenty-six UChicago faculty members receive named, distinguished service professorships in July 2025

Congrats to all faculty who have been recognized for their stellar contributions!

We're especially thrilled to celebrate the eleven Chicago Booth faculty on this list, among them CAAI Faculty Affiliate @aleximas.bsky.social!

news.uchicago.edu/story/twenty...?

Systemic Discrimination: Theory and Measurement* Abstract. Economists often measure discrimination as disparities arising from the direct effects of group identity. We develop new tools to model and measu

Paper by @aislinnbohren.bsky.social @instrumenthull.bsky.social and @aleximas.bsky.social on Systemic Discrimination now published in QJE
academic.oup.com/qje/article/...

How AI Can Make Smarter Predictions Researchers gave AI a way to evaluate and calibrate its own uncertainty.

AI can be overconfident.

So a team of researchers came up with a solution: Give AI a way to evaluate and calibrate its own uncertainty, allowing a user to decide how much to trust a prediction. www.chicagobooth.edu/review/how-a...

The gutting of US biomedical research with loss of ~2,500 grants affecting research for cancer, Alzheimer’s, infectious disease, global health and much more
www.nytimes.com/interactive/...

In Its Expectations for the Economy, AI Is Surprisingly Human AI, designed to mimic the appearance of human reasoning, also forms predictions about the economy in human-like ways.

"You need some way of actually measuring people’s beliefs or their preferences if you wanna test these behavioral stories around bubbles," says Chicago Booth’s Leland Bybee. www.chicagobooth.edu/review/in-it... #econsky #ai

Our work now published showing how better AI can improve both accuracy and diversity in hiring relative to supervised learning tools and status-quo human hiring.

The interesting thing about people dragging the folks in that NYT piece who said that they didn’t vote for moms to get deported is that the article is about how these women are organizing for a member of their community, aggressively and openly, and actually, that’s good.

MIT Says It No Longer Stands Behind Student’s AI Research Paper The university said it has no confidence in a widely circulated paper by an economics graduate student.

Update on the paper: www.wsj.com/tech/ai/mit-...

Introspection has gotten a bad rap over the years. Here we show that people have more insight into the algorithms behind their decisions than we tend to assume. Thrilled to see this work out at Nature Comms with the always brilliant @thatadammorris.bsky.social!

Sorry, fixed!

bsky.app/profile/alex...

LINK: papers.ssrn.com/sol3/papers....

Yeah that’d be nice but it’s hard for me to think about an environment like that. I think in coding it’s likely smaller but not opposite direction.

This is cool for, like, other people who have actually used AI... not me, nope.

These results suggest that social desirability may bias estimates of AI use downwards, depending on the setting.

But that tools such as the indirect questioning technique can help.

Follow up surveys using both free response and direct questions revealed social desirability bias as the main reason given for the own-other gap. Specifically, the gap was attributed to a reluctance to report one's own AI use rather than an inflation of others' use.

On extent of use, majority of students reported using AI 0-1 days a week, while the majority of their friends used AI 4-5 days a week.

Results were striking, while ~60% of people reported using AI at all themselves, they reported that ~90% of their friends used AI.

The most common response for own use was "not at all", while the most common response for others' use was "a moderate amount" followed by "a lot".

We employed standard indirect questioning technique from psych to overcome social desirability bias:

Instead of asking about one's own AI use, ask about AI use of friends in one's social circle...

We ran large survey in educational setting--undergraduates at a mid-sized, selective university--where social desirability bias may be particularly prevalent...

One reason for difference in estimates: People may be embarrassed/worried to reveal their own AI use due to either social norms or fear of repercussions.

Such social desirability bias--tendency to answer surveys in ways others view favorably--could bias estimates downwards...

Survey of AI use typically rely on self-reports: people are asked whether they use AI and the extent to which they do.

Estimates of AI use vary wildly both between and within the same setting, making it hard to pin down true prevalence of AI use...

🚨New paper (link in reply)🚨

Are we underestimating AI use in self-report surveys?

Yes, by as much as 30 percentage pts. We find 60% self-reported vs. truth closer to ~90% (!!)

Why? Social desirability bias, people embarrassed/worried to admit AI use, so they underreport 🧵

Yes, Bluesky is full of ill-informed AI takes. But that doesn’t have to matter at all. The news you need is out there.

In addition to the filters recommended here, I recommend … +

Encourage your students to submit posters and register! Limited free housing is provided for student participants only, on a first-come (i.e., request)-first-serve basis.

We are also actively looking for sponsors. Reach out if you are interested!

Please repost! Help spread the words!

That’s a “hell yeah”. Take me to the best gym in Durham.