William J. Brady

@williambrady.bsky.social

5.8K followers 310 following 110 posts

Assistant prof @ Kellogg School of Management, Northwestern University. Studying emotion, morality, social networks, psych of tech. #firstgen college graduate

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Medicine 25%

Sociology 11%

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William J. Brady @williambrady.bsky.social · Feb 14

👀New preprint! In 3 prereg experiments we study how engagement-based algorithms amplify ingroup, moral and emotional (IME) content in ways that disrupt social norm learning (and test one solution!) w/ @joshcjackson.bsky.social and my amazing lab managers
@merielcd.bsky.social
& Silvan Baier 🧵👇

Reposted by William J. Brady, Allison Eden

Rebecca Frazer @beccafraz.bsky.social · 1d

Out now in Scientific Reports! Despite high correlations, ChatGPT models failed to replicate human moral judgments. We propose tests beyond correlation to compare LLM data and human data.

With @mattgrizz.bsky.social @andyluttrell.bsky.social @chasmonge.bsky.social

www.nature.com/articles/s41...

ChatGPT does not replicate human moral judgments: the importance of examining metrics beyond correlation to assess agreement - Scientific Reports

Scientific Reports - ChatGPT does not replicate human moral judgments: the importance of examining metrics beyond correlation to assess agreement

www.nature.com

Reposted by Linda J. Skitka, William J. Brady, Rebecca Sear , and 1 more Linda J. Skitka, William J. Brady, Rebecca Sear, Jonathan Hopkin

Sasha Gusev @sashagusevposts.bsky.social · 3d

So there you have it, twin study estimates were greatly inflated, and molecular data sets the record straight. I walk through possible counter-arguments, but ultimately the uncomfortable truth is that genes contribute to traits much less than we always thought.

William J. Brady @williambrady.bsky.social · 7d

Great work by @natematias.bsky.social & Megan Price: public involvement in AI is an important part of rigorous science. AI systems are sociotechnical, meaning that the lived experience of the public is essential for validation, etc.

www.pnas.org/doi/10.1073/...

How public involvement can improve the science of AI | PNAS

As AI systems from decision-making algorithms to generative AI are deployed more widely, computer scientists and social scientists alike are being ...

www.pnas.org

Reposted by Mark J. Brandt, William J. Brady, Sylvia Perry

Jonathan Doriscar @jonds7.bsky.social · 8d

New preprint out 📄
“Why Reform Stalls: Justifications of Force Are Linked to Lower Outrage and Reform Support.”

Why do some cases of police violence spark reform while others fade? We look at how people explain them—through justification or outrage.

osf.io/preprints/ps...

OSF

osf.io

Reposted by Lisa W. Fazio, Sander van der Linden, Will Jennings , and 8 more Lisa W. Fazio, Sander van der Linden, Will Jennings, Brendan Nyhan, Garry Peterson, Gordon Hodson, Steve Peers, William J. Brady, Laia Balcells, Mohsen Mosleh, Allison Eden

David Rand @dgrand.bsky.social · 11d

🚨Out in PNAS🚨
Examining news on 7 platforms:
1)Right-leaning platforms=lower quality news
2)Echo-platforms: Right-leaning news gets more engagement on right-leaning platforms, vice-versa for left-leaning
3)Low-quality news gets more engagement EVERYWHERE - even BlueSky!
www.pnas.org/doi/10.1073/...

Reposted by William J. Brady

Mark Ho @markkho.bsky.social · 12d

Excited to share a new preprint, accepted as a spotlight at #NeurIPS2025!

Humans are imperfect decision-makers, and autonomous systems should understand how we deviate from idealized rationality

Our paper aims to address this! 👀🧠✨
arxiv.org/abs/2510.25951

a 🧵⤵️

Estimating cognitive biases with attention-aware inverse planning

People's goal-directed behaviors are influenced by their cognitive biases, and autonomous systems that interact with people should be aware of this. For example, people's attention to objects in their...

arxiv.org

William J. Brady @williambrady.bsky.social · 14d

See preprint for more details on (1) development of our taxonomy, (2) how we measured motive inferences in natural language and (3) how our intervention worked!
doi.org/10.31234/osf...

OSF

doi.org

William J. Brady @williambrady.bsky.social · 14d

They also show we might be able to people more receptive to political dialogue with a political opponent even when outrage is clearly expressed against people’s own political views.

William J. Brady @williambrady.bsky.social · 14d

These results help solve a puzzle (cc @steverathje.bsky.social). Why do people express outrage when reporting they don't want to see it in their feeds? We suggest because when they express it they typically have behavioral motives, but they think others have contra-hedonic motives!

William J. Brady @williambrady.bsky.social · 14d

Key result #3: Motive inferences were malleable: we developed an intervention that corrected peoples’ motive inferences - increasing people’s inference of behavioral motive to out-partisan caused them to be more willing to have a political conversation even in context of outrage

William J. Brady @williambrady.bsky.social · 14d

Key result #2: Biased motive inferences predict greater partisan animosity, and specific inferences of behavioral / contra-hedonic motives predicted willingness to have a conversation. 👆 behavioral motive inference = 👆 willingness to converse, even if it was an out-partisan expressing outrage!

William J. Brady @williambrady.bsky.social · 14d

Key result #1: People largely reported their in-partisans’ (and their own) motives for outrage was to raise awareness or inspire action (behavioral motive), but thought political opponents motives were to shame or troll (contra-hedonic motive), which was a vast overestimation.

William J. Brady @williambrady.bsky.social · 14d

In online experiments and a field study on Reddit, we asked users to report their motives for posting outrage and then had observers infer the motives.

Reposted by Scott Clifford, Kate Starbird

William J. Brady @williambrady.bsky.social · 14d

✨New preprint! Why do people express outrage online? In 4 studies we develop a taxonomy of online outrage motives, test what motives people report, what they infer for in- vs. out-partisans, and how motive inferences shape downstream intergroup consequences. Led by @felix-chenwei.bsky.social 🧵👇

Reposted by William J. Brady

Jay Van Bavel, PhD @jayvanbavel.bsky.social · 20d

These has been sharp rise in moralized language on social media

Two processes explained this shift:
(1) within-user increases in moral language over time
(2) highly moralized users became more active while less moralized users disengaged osf.io/preprints/ps...

Reposted by Will Jennings, Brendan Nyhan, William J. Brady

Petter Törnberg @pettertornberg.com · 26d

Posting is correlated with affective polarization:
😡 The most partisan users — those who love their party and despise the other — are more likely to post about politics
🥊 The result? A loud angry minority dominates online politics, which itself can drive polarization (see doi.org/10.1073/pnas...)

Reposted by Mark J. Brandt

William J. Brady @williambrady.bsky.social · 28d

Reminder to apply to the DRRC postdoc fellowship! Deadline is this week.

William J. Brady @williambrady.bsky.social · Aug 12

Are you interested in topics related to conflict and intergroup relations *broadly construed*? Come join us as a postdoc in the Dispute Research Research Center! This position is up to 3 years, comes with your own research funding, and a phenomenal network of past DRRC postdocs.

Dispute Resolution Research Center @drrc-kellogg.bsky.social · Aug 11

Apply now for Kellogg’s DRRC Postdoc Fellowship, which supports outstanding research in conflict and cooperation, offering dedicated time for scholarship, access to exceptional resources, and a vibrant academic community. Deadline: Nov 1.
t.co/UDZwJCqDw5

Reposted by William J. Brady

Paul Smaldino @psmaldino.bsky.social · 28d

Re-posting this because I really like it and I think we need to understand identity from a functionalist perspective more than ever.
osf.io/preprints/ps...

Paul Smaldino @psmaldino.bsky.social · Jun 2

I wrote a chapter on a functionalist account of social identity.

IMO, thinking about identity in an instrumental way helps explain a lot of behavior that seems otherwise baffling.
osf.io/preprints/ps...

This chapter focuses on how people use identity categories for adaptive decision making and how they strategically apply signals of identity. Adopting a functional view of identity for communication and behavior allows us to focus on the forces that shape their use. I will first make it clear that signals of social identity often encode meaningful information for decision making. I will then review specific perspectives on how selection by consequences has shaped the use of identity signals to more adaptively facilitate social learning, partner choice, and coordination, followed by a consideration of how those uses have changed in a world characterized by diversity, anonymity and the Internet, and political polarization. Identity is constructed for functional purposes, and is therefore only essential insofar as forming categories and legible cultural artifacts are essential features of human activity.

Carl T. Bergstrom @carlbergstrom.com · Oct 24

1. We ( @jbakcoleman.bsky.social, @cailinmeister.bsky.social, @jevinwest.bsky.social, and I) have a new preprint up on the arXiv.

There we explore how social media companies and other online information technology firms are able to manipulate scientific research about the effects of their products.

Three schematic diagrams. The first illustrates selective publishing of internal resection, the second selective causal focus, and the third selective access and funding for researchers.

Reposted by Brian J. Enquist, Richard McElreath, William J. Brady , and 3 more Brian J. Enquist, Richard McElreath, William J. Brady, Nathan P. Kalmoe, Will M. Gervais, Ignacio Quintero

Joe Bak-Coleman @jbakcoleman.bsky.social · Oct 22

Great piece on the absurdity of brute force multiverse analyses.

www.pnas.org/doi/10.1073/...

Robustness is better assessed with a few thoughtful models than with billions of regressions | PNAS

Robustness is better assessed with a few thoughtful models than with billions of regressions

www.pnas.org

Reposted by Joanna Bryson, Lisa W. Fazio, Suresh Venkatasubramanian , and 9 more Joanna Bryson, Lisa W. Fazio, Suresh Venkatasubramanian, Dorothy Bishop, Carl T. Bergstrom, Elizabeth Stokoe, William J. Brady, Kelly Smith, Meri Koivusalo, Petri Ylikoski, Aleksandra Urman, Mohammad Atari

M.J. Crockett @mjcrockett.bsky.social · Oct 21

Can AI simulations of human research participants advance cognitive science? In @cp-trendscognsci.bsky.social, @lmesseri.bsky.social & I analyze this vision. We show how “AI Surrogates” entrench practices that limit the generalizability of cognitive science while aspiring to do the opposite. 1/

AI Surrogates and illusions of generalizability in cognitive science

Recent advances in artificial intelligence (AI) have generated enthusiasm for using AI simulations of human research participants to generate new know…

www.sciencedirect.com

William J. Brady @williambrady.bsky.social · Oct 20

Last call for data-blitz and poster submission for the Computational Psychology preconference @spspnews.bsky.social! See thread below for details and hope to see you in Chicago!

William J. Brady @williambrady.bsky.social · Sep 29

The computational psych preconference is back @spspnews.bsky.social for a full day! This year's lineup:

👉theory-driven modeling: Hyowon Gweon
👉data-driven discovery: @clemensstachl.bsky.social
👉application: me
👉 panel: @steveread.bsky.social Sandra Matz, @markthornton.bsky.social Wil Cunningham

William J. Brady @williambrady.bsky.social · Oct 7

Very difficult indeed. We study these types of issues empirically:

osf.io/preprints/os...

OSF

osf.io

Reposted by Lisa W. Fazio, Will Jennings, Brendan Nyhan , and 5 more Lisa W. Fazio, Will Jennings, Brendan Nyhan, William J. Brady, Alessandro Nai, Matti Vuorre, Aleksandra Urman, Shan Kothari

Steve Rathje @steverathje.bsky.social · Oct 1

🚨 New preprint 🚨

Across 3 experiments (n = 3,285), we found that interacting with sycophantic (or overly agreeable) AI chatbots entrenched attitudes and led to inflated self-perceptions.

Yet, people preferred sycophantic chatbots and viewed them as unbiased!

osf.io/preprints/ps...

Thread 🧵

William J. Brady @williambrady.bsky.social · Sep 30

Cool work! Did y'all look at how people update when they discover AI makes an error?

Reposted by William J. Brady

Jay Van Bavel, PhD @jayvanbavel.bsky.social · Sep 30

Our new paper finds that AI can overcome partisan #bias

We find that AI sources are preferred over ingroup and outgroup sources--even when people know both are equally accurate (N = 1,600+): osf.io/preprints/ps...

William J. Brady @williambrady.bsky.social · Sep 29

missed you @baixuechunzi.bsky.social !

William J. Brady @williambrady.bsky.social · Sep 29

Thanks to our rotating organizers: lead organizer Tessa Charlesworth & co-organizers: @chujunlin.bsky.social Brent Hughes Xuechunzi Bai

Post any questions here!

William J. Brady @williambrady.bsky.social · Sep 29

We are now accepting submissions for posters and data blitz! If your research is computational (broadly construed) you should apply! We try to program for a wide range of topics and computational approaches.

Submission guide here: spsp.sharepoint.com/:w:/g/EdvejV...

Deadline: October 23rd 🎃

William J. Brady @williambrady.bsky.social · Sep 29

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