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William J. Brady

@williambrady.bsky.social
5.9K followers 370 following 170 posts

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

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Reposted by William J. Brady
Kevin Elliott @kjephd.bsky.social · 23/09/2026
AI is the Gyges' ring of student work: it offers perfect concealment of wrongdoing. If Glaucon is right, then everyone will use it to do injustice (cheat), & will be wise to do so. If Socrates/Plato is right, then doing so also harms the wrong-doer, whose soul will be malformed into misery by it.
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William J. Brady @williambrady.bsky.social · 09/09/2026
Glad to see a revised version of this out now at Current Opinion in Psychology! www.sciencedirect.com/science/arti...
sciencedirect.com
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William J. Brady @williambrady.bsky.social · 04/09/2026
Thanks to 2027 co-organizers @ashwinia.bsky.social @baixuechunzi.bsky.social Tessa Charlesworth
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William J. Brady @williambrady.bsky.social · 04/09/2026
Featuring @ylelkes.bsky.social @jatucker.bsky.social @dianatamir.bsky.social @angelinawang.bsky.social @dcameron.bsky.social Natala Velez, Adam Waytz, Nathan Matias
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William J. Brady @williambrady.bsky.social · 04/09/2026
Register / submit by Oct 8: spsp.org/events/annua...
spsp.org
Preconferences | SPSP
Explore SPSP Annual Convention preconferences—specialized sessions offering in-depth insights, networking, and collaboration in personality and social psychology.
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William J. Brady @williambrady.bsky.social · 04/09/2026
📣 Students & postdocs: submit your research! We're selecting 2–3 data blitz talks per keynote theme, + posters. 🏆 New this year: committee will pick one data blitz speaker for the inaugural Computational Psychology Early Career Research Award, judged on rigor + novelty.
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William J. Brady @williambrady.bsky.social · 04/09/2026
Registration is open for the 4th annual Computational Psychology preconference at @spspnews.bsky.social Annual conference in Philly 🎊 We are on for a full day on Thursday, Feb 11. 3 keynote themes + a debate that couldn't be more timely 🧵👇
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William J. Brady @williambrady.bsky.social · 02/09/2026
www.kellogg.northwestern.edu/academics-re... I'm also happy to answer any questions about working in a business school for social psychologists and computational social scientists - feel free to reach out!
kellogg.northwestern.edu
Faculty Recruiting
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William J. Brady @williambrady.bsky.social · 02/09/2026
Come join me @kelloggschoolnu.bsky.social. The management department is hiring for position of Assistant Professor. We are a fun cross-disciplinary group, so if your training is in psychology, sociology, OB or computational social science, etc you should check out the position! Apps due in 2 weeks!
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William J. Brady @williambrady.bsky.social · 27/08/2026
Excited to work on this with a great team ✨ Stay tuned for some hiring announcements if you're interested in these topics!
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William J. Brady @williambrady.bsky.social · 15/08/2026
Rockaway Beach can get some nice waves!
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William J. Brady @williambrady.bsky.social · 13/08/2026
Are you hooked yet?
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William J. Brady @williambrady.bsky.social · 13/08/2026
🤙
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William J. Brady @williambrady.bsky.social · 29/07/2026
Wait until you hear about zwischenzug
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Reposted by William J. Brady
Mohammad Atari @mohammadatari.bsky.social · 20/07/2026
New paper out today in Social and Personality Psychology Compass! What happens when our moral values come into conflict? Our new paper explores "metamorality": the second-order principles we use to navigate conflicting moral choices. W/ Jesse Graham
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William J. Brady @williambrady.bsky.social · 20/07/2026
awesome paper! I think about these conflicts a lot so looking forward to checking it more closely.
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William J. Brady @williambrady.bsky.social · 29/06/2026
Our 2023 paper for reference: www.cell.com/trends/cogni...
cell.com
Algorithm-mediated social learning in online social networks
Human social learning is increasingly occurring on online social platforms, such as Twitter, Facebook, and TikTok. On these platforms, algorithms exploit existing social-learning biases (i.e., towards...
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William J. Brady @williambrady.bsky.social · 29/06/2026
Paper here! osf.io/preprints/ps...
osf.io
OSF
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William J. Brady @williambrady.bsky.social · 29/06/2026
The result: pluralistic ignorance and false consensus. The upside: if the problem is upstream, the fixes can be too. As engagement algorithms keep their dominance and generative AI proliferates, we discuss two solutions worth taking seriously.
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William J. Brady @williambrady.bsky.social · 29/06/2026
Generative AI distorts differently. Predicting the most probable next token and tuned toward annotator-preferred text, LLMs converge hard on the modal answer — in some forced-choice tests placing 99%+ probability on a single response to questions people are split on. Both routes corrupt learning.
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William J. Brady @williambrady.bsky.social · 29/06/2026
They corrupt the upstream sample, so downstream biases act on bad input ("upstream selection problem"). Engagement algorithms optimize for attention, which is drawn to emotional, moral, conflict-heavy content from a small hostile minority. Feeds overrepresent extremes, bury the moderate majority.
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William J. Brady @williambrady.bsky.social · 29/06/2026
The key point: those biases are "smart shortcuts" — but only when the visible sample is representative. If what looks common really is common, conforming is rational. If who looks respected really is competent, deferring is rational. Both engagement algorithms and generative AI break that "if."
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William J. Brady @williambrady.bsky.social · 29/06/2026
How does social learning work? We see 2 stages: upstream selection (what becomes visible to us) and downstream selection (what we copy from that visible sample). Downstream is shaped by well-studied biases: conformity (copy what looks common) and prestige (copy whoever looks respected/competent).
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William J. Brady @williambrady.bsky.social · 29/06/2026
In this new paper w/ @joshcjackson.bsky.social , @nickornstein.bsky.social , @felix-chenwei.bsky.social , & Bolun Sun, we argue generative AI also distorts social learning, but because it optimizes for something different, it distorts in a different direction.
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William J. Brady @williambrady.bsky.social · 29/06/2026
In our new paper we ask: when probing LLMs for opinions, ideas, or a read on what a group thinks, does that fix the skew engagement algorithms introduced? We argue and review evidence that the answer is "no".
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William J. Brady @williambrady.bsky.social · 29/06/2026
In 2023 we showed how engagement-based algorithms exploit human social learning biases, distorting how we learn what's normal, common, or credible from each other ("Algorithm-mediated social learning," Trends in Cognitive Sciences). The obvious follow-up: where does generative AI fit in?
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William J. Brady @williambrady.bsky.social · 28/06/2026
Congrats!
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William J. Brady @williambrady.bsky.social · 16/06/2026
If we aren't careful in how we teach grad students to use AI, I don't think it's hyperbole to say a crisis is coming. From talking to many colleagues, I think we are past the "wait and see" stage.
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Reposted by William J. Brady
Jason Koebler @jasonkoebler.bsky.social · 15/06/2026
New: Researchers have quantified how easy AI search is to manipulate. Just 13 words buried in a random Reddit comment can poison AI search results. They suggest this is not easy to stop: "The way you can attack these systems is so much dumber than you think it is" www.404media.co/it-is-trivia...
404media.co
It Is Trivially Easy to Use Reddit to Manipulate AI Search, Research Suggests
"We show that a tiny snippet—just 13 words—of retrieved text on a UGC website like Reddit, Wikipedia, Quora, or Facebook can change AI agents to output spam / scam content pretty consistently."
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Reposted by William J. Brady
Matthew Facciani @matthewfacciani.bsky.social · 29/05/2026
Researchers looked at people’s positions on specific issues, rather than just whether they identified as conservative or liberal. They found 43% of self-identified conservatives supported mostly left-leaning policies on topics like spending, climate action, immigration, and vaccine mandates.
academic.oup.com
Thinking Ideologically: The Limited Role of Left and Right Labels as Policy Shortcuts
Abstract. How do voters use left-right ideological labels as shortcuts for policy positions in evaluating electoral candidates? We offer a distinction betw
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William J. Brady @williambrady.bsky.social · 27/05/2026
for a high-level write up of the findings, check out this insight.kellogg.northwestern.edu/article/can-...
insight.kellogg.northwestern.edu
Can We Take the Doom Out of Scrolling?
Today’s social-media feeds elevate toxicity and partisanship. A new algorithm offers hope for a less-hostile, more-enjoyable experience.
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William J. Brady @williambrady.bsky.social · 27/05/2026
open: www.nature.com/articles/s41...
nature.com
Redesigning algorithms to intervene on social norm misperceptions during a national election
Nature - Engagement-based feeds amplify intergroup, moralized, emotional (IME) and toxic content relative to reverse-chronological feeds, and a diversified extremity algorithm reduces exposure to...
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William J. Brady @williambrady.bsky.social · 27/05/2026
As I mentioned in the below thread, this project involved many feats of engineering, led by the fantastic @markptorres.bsky.social. If you're a CS or CSS person interested in the gory details, see his blog post: markptorres.com/research/202...
markptorres.com
How we built the infrastructure for a large-scale social media field experiment during the 2024 US election
What we built
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William J. Brady @williambrady.bsky.social · 27/05/2026
Link to paper: www.nature.com/articles/s41... Shoot me an email if you need help accessing
nature.com
Redesigning algorithms to intervene on social norm misperceptions during a national election - Nature
Engagement-based feeds amplify intergroup, moralized, emotional (IME) and toxic content relative to reverse-chronological feeds, and a diversified extremity algorithm reduces exposure to IME and toxic...
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William J. Brady @williambrady.bsky.social · 27/05/2026
Special shoutout to @markptorres.bsky.social my senior lab engineer. It felt like we ran a start-up for a year...If you're a CS or CSS person interested in the gory details of engineering that went into this ambitious project, we are doing a separate thread for you! See my profile
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William J. Brady @williambrady.bsky.social · 27/05/2026
I'd like to thank my amazing team of collaborators @joshcjackson.bsky.social @nourkteily.bsky.social @elijfinkel.bsky.social @curtispuryear.bsky.social @merielcd.bsky.social @markptorres.bsky.social @abdoe.bsky.social @vaparker.bsky.social @trevorspelman.bsky.social Jake Teeny
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William J. Brady @williambrady.bsky.social · 27/05/2026
Many limitations, including the fact that Bluesky population changed dramatically(!) in the middle of our study. Our participants were earlier users, but users who joined later express more outrage! (see SI). How does this generalize to other platforms, etc? See discussion
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William J. Brady @williambrady.bsky.social · 27/05/2026
There are TONS of other interesting results, positive findings and nulls, that are in the paper. There are also 240(!) pages of SI material. If you have a question or analysis idea, we probably thought of it 😎
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William J. Brady @williambrady.bsky.social · 27/05/2026
Result 4: it's often assumed that dialing down divisive content hurts user experience. Our data suggest that tradeoff may be overstated—the diversified extremity feed reduced toxic/IME content while maintaining overall login freq and (even improving) overall platform enjoyment (see discussion)
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William J. Brady @williambrady.bsky.social · 27/05/2026
Result 3: Null finding: We found no evidence that algorithms changed people's own engagement behavior with IME/toxic content. Engagement was extremely rare & concentrated (top 5% of users = 75% of all toxic engagement). Exposure shifted; behavior, at least over 2 months, didn't.
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William J. Brady @williambrady.bsky.social · 27/05/2026
Our best explanation: amplified toxic posts often came wrapped in visible condemnation (critical replies, quote posts). Seeing others push back may have signaled that toxic posting was less acceptable—even as the overall vibe felt more hostile.
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William J. Brady @williambrady.bsky.social · 27/05/2026
Result 2: Engagement-based feeds raised perceived partisan animosity (esp. after the election) AND reduced norm perception accuracy. Unexpected: for norm-perception people underestimated how acceptable others found toxic political content.
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William J. Brady @williambrady.bsky.social · 27/05/2026
Another interesting tidbit: because we designed our own engagement algo, we could see separate influence of personalized vs community engagement signals. Turns out community signals are much more responsible for IME amplification (see SI)!
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William J. Brady @williambrady.bsky.social · 27/05/2026
One cool thing about our study is we estimated true base rate of content in English-speaking content across WHOLE study period. Thus, we can show that this amplification of IME content is an *overrepresentation* = misrepresents true base rate on platform (see methods)
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William J. Brady @williambrady.bsky.social · 27/05/2026
Result 1: engagement-based feeds amplified IME & toxic content vs. a chronological feed. The biggest jumps were in moral outrage (up to +79%) and political content (up to +57%) after the election. Our diversified extremity algorithm reduced this exposure (by aiming to reduce extreme users)
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William J. Brady @williambrady.bsky.social · 27/05/2026
Another goal we had: show one way to do an algo RCT independent of industry. We engineered our own ranking algorithms on @bsky.app, giving us full control & transparency over how they worked—less black box, no conflicts of interest, no concerns of changes during study. Ok, now results:
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William J. Brady @williambrady.bsky.social · 27/05/2026
Fun fact: This is @nature.com first published Stage 2 registered report! Everything you see was pre-registered and agreed upon BEFORE study was executed. After doing this I have many thoughts on pros and cons of RR's, maybe for another thread!
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William J. Brady @williambrady.bsky.social · 27/05/2026
We also built & tested an intervention: a "diversified extremity" algorithm. Instead of amplifying outgroup posts (which can backfire), it reduces the outsized influence of extreme users—who post most of the toxic political content—to make feeds more socially representative.
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William J. Brady @williambrady.bsky.social · 27/05/2026
✨New paper out @nature.com ✨ For 8 weeks around the 2024 US election, we randomly assigned 2,000 people to use social media algos we built ourselves. Do engagement-based algorithms amplify intergroup, moral & emotional (IME) content—and does that distort how we see political norms? 🧵🔗 👇
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Reposted by William J. Brady
Joshua Tucker @jatucker.bsky.social · 14/05/2026
This paper benefitted enormously from the very involved and insightful editorial team @nature.com, led by @meharpist.bsky.social.
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