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Steve Rathje

@steverathje.bsky.social
5.9K followers 954 following 86 posts

Incoming Assistant Professor of HCI at Carnegie Mellon studying the psychology of technology. NSF postdoc at NYU, PhD from Cambridge, BA from Stanford. stevenrathje.com

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Steve Rathje @steverathje.bsky.social · 01/10/2026
Congrats Dan!!!!! 🤩
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Dan Mirea @danmirea.bsky.social · 01/10/2026
Thrilled to announce that I will be joining the University of Miami as an Assistant Professor of Psychology next year! I am recruiting a PhD student to start in Fall 2027 — please reach out if you are interested in joining the lab! For more info check out my website: dan-mirea.com
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Dan Mirea @danmirea.bsky.social · 13/07/2026
🚨 Now out in @jamapsychiatry.com 🚨 Are people with depression less responsive to rewards on social media, just like in the lab? Actually…quite the opposite! 🧵 📄 Read the paper here: jamanetwork.com/journals/jam...
jamanetwork.com
The Reinforcement Effect of Social Media Likes in Depression
This study investigates individual differences in the effect of social media likes on posting behavior and their association with and specificity to depressive psychopathology.
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Steve Rathje @steverathje.bsky.social · 12/06/2026
Great paper @rafmbatista.bsky.social!
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Rafael M Batista @rafmbatista.bsky.social · 15/05/2026
Hi Steve, Tom Griffiths and I have some work formalizing how this might happen, offering a mechanism for how that overconfidence develops arxiv.org/abs/2602.14270
arxiv.org
A Rational Analysis of the Effects of Sycophantic AI
People increasingly use large language models (LLMs) to explore ideas, gather information, and make sense of the world. In these interactions, they encounter agents that are overly agreeable. We argue...
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Meryl Ye @merylye.bsky.social · 22/05/2026
🚨 New preprint 🚨 We developed a sycophancy taxonomy based on prior literature and surveyed 106 experts. 94% agreed it's a serious problem. But they substantially disagreed about which behaviors actually count as sycophancy.
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Jay Van Bavel, PhD @jayvanbavel.bsky.social · 18/05/2026
People prefer to use “sycophantic” AI systems that reinforce their pre-existing beliefs. In a new paper (n=7,227), we found that people enjoyed interacting with sycophantic AI chatbots more than interacting with neutral chatbots or “disagreeable” chatbots that challenged their beliefs.
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Amrita Lamba @amritalamba.bsky.social · 15/05/2026
Recent preprint with Oriel FeldmanHall and Matt Nassar, showing clear neural evidence that adolescent (13-15 yrs) social media and smartphones use are associated with blunted reward signaling in the ventral striatum, the brain's reward processing hub, and worse mental health. osf.io/preprints/ps...
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Steve Rathje @steverathje.bsky.social · 16/05/2026
Fingers crossed!! 🤞
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René Walter @rawx.bsky.social · 15/05/2026
This shapes up to be a deep dive into the psychological effects of sycophant AI, making you overconfident and blind to your own biases. Would be interesting to see a comparison to social media effects on the same. After all, tribes are sycophant networks too.
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Herb @dropthet.bsky.social · 14/05/2026
AI is forcing us to reconcile our own psychology, & the subtle/unnoticed ways in which we can be manipulated, as we never have before. It's nothing new with AI, it's just a new discussion for the public in general.
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Steve Rathje @steverathje.bsky.social · 14/05/2026
Check out the updated pre-print (with @jayvanbavel.bsky.social, Meryl Ye, Laura Globig, @rmpillai.bsky.social, and @hellovic.bsky.social) here: osf.io/vmyek_v3
osf.io
OSF
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Steve Rathje @steverathje.bsky.social · 14/05/2026
This work both reveals the psychological consequences of sycophantic AI and presents a roadmap for creating AI that broadens users’ perspectives instead of reinforcing their biases.
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Steve Rathje @steverathje.bsky.social · 14/05/2026
A final study presented a potential solution to people’s resistance to disagreeing chatbots. Specifically, we found that people were more receptive to chatbots presenting opposing perspectives when those perspectives were paired with emotional validation.
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Steve Rathje @steverathje.bsky.social · 14/05/2026
Nevertheless, people enjoyed sycophantic chatbots more than disagreeable ones, chose to interact with them more, viewed them as warmer and more competent, and felt a stronger "sense of connection" with them.
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Steve Rathje @steverathje.bsky.social · 14/05/2026
While sycophantic chatbots did not increase people’s actual knowledge about the topics they discussed, they increased people’s *perceived* knowledge. In other words, sycophancy led to overconfident perceptions of knowledge that did not align with reality
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Steve Rathje @steverathje.bsky.social · 14/05/2026
This suggests that people may have a “bias blind spot” surrounding AI sycophancy: they can recognize when AI is biased in favor of others, but not themselves.
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Steve Rathje @steverathje.bsky.social · 14/05/2026
People interacting with sycophantic chatbots viewed them as unbiased, but viewed “disagreeable” chatbots that challenged their beliefs as highly biased. However, third-party annotators recognized that responses from sycophantic and disagreeable chatbots were equally biased:
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Steve Rathje @steverathje.bsky.social · 14/05/2026
The effects of AI sycophancy were both durable and generalizable across topics. Brief interactions with sycophantic chatbots about a variety of personal and political topics increased attitude certainty, with effects persisting for at least one week.
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Steve Rathje @steverathje.bsky.social · 14/05/2026
AI sycophancy impacted costly decisions. Specifically, participants who interacted with a sycophantic chatbot bet more money that they scored better than the average participant on tasks measuring desirable traits, such as intelligence and empathy.
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Steve Rathje @steverathje.bsky.social · 14/05/2026
We’ve updated our pre-print on the effects of AI sycophancy with four additional studies (total n = 7,227). Here is a brief summary of our new findings (🧵1/n):
Screenshot of abstract: AI can be a powerful tool for opening people up to new perspectives, yet people may prefer to use “sycophantic” (or overly agreeable and validating) AI systems that reinforce their pre-existing beliefs. Across seven studies (total n = 7,227), we found that people enjoyed interacting with sycophantic AI chatbots more than interacting with neutral chatbots or “disagreeable” chatbots that challenged their beliefs. Brief conversations with sycophantic chatbots about political or personal topics increased attitude extremity and certainty, with most effects persisting for at least one week. Sycophantic chatbots also inflated people’s perceptions that they were better than average on desirable traits (e.g., intelligence, empathy). Moreover, people who interacted with sycophantic (rather than disagreeable) AI bet more money that they scored better than average on tasks measuring these traits (approximately 6 cents more out of 75 possible cents), demonstrating that sycophancy can affect costly decisions. Participants consistently rated sycophantic chatbots as more “unbiased” than disagreeable chatbots, even though third-party raters viewed these chatbots as equally biased, suggesting that people may be blind to biases in AI output that aligns with their views. People were more receptive to chatbots that presented opposing information when that information was presented in a validating way, and individuals who scored higher on a measure of intellectual humility were also more receptive to disagreeing chatbots. Altogether, these results suggest that people’s preference for, and blindness to, sycophantic AI risks creating AI “echo chambers” that increase attitude extremity and lead to overconfident beliefs and decisions.
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Tobia Spampatti, PhD @tspampatti.bsky.social · 05/05/2026
However, we find that this preference is politically polarized: in 32 out of 40 countries, right-leaningparticipants prioritize protecting free expression more than left-leaning participants(55% vs. 48%).
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Tobia Spampatti, PhD @tspampatti.bsky.social · 05/05/2026
Laura Globig, @steverathje.bsky.social, @jayvanbavel.bsky.social , @hallgeirsjastad.bsky.social and I surveyed 47000+ people across countries to measure people's preferences. We found that people are split between protecting freeexpression (51%) and preventing misinformation from spreading (49%) 2/
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Steve Rathje @steverathje.bsky.social · 02/05/2026
Sycophancy was less common in more recent models, but even small amounts of sycophancy may have psychological consequences, given the sheer number of people using generative AI products. See our work on the consequences of sycophancy here: osf.io/preprints/ps...
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Steve Rathje @steverathje.bsky.social · 02/05/2026
An analysis of 1 million Claude conversations found that Claude was sycophantic around 9% of the time. However, this rate varied by topic: sycophancy was higher in conversations about spirituality (38%) and relationships (25%). See Anthropic’s full analysis here: anthropic.com/research/cla...
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Joe Pierre, MD @psychunseen.bsky.social · 29/04/2026
"people consistently preferred and chose to interact w/ sycophantic AI models over disagreeable chatbots that challenged their beliefs... conversations w/sycophantic chatbots [also] increased attitude extremity & certainty." @jayvanbavel.bsky.social @steverathje.bsky.social osf.io/preprints/ps...
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Jay Van Bavel, PhD @jayvanbavel.bsky.social · 21/04/2026
A small fraction of online actors exerts outsized influence over what the public sees, believes, and discusses. In a new paper, we trace how social media influencers turn fringe claims into viral narratives by exploiting a feedback loop between influencers, algorithms & crowds osf.io/preprints/ps...
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Stefan Feuerriegel @sfeuerriegel.bsky.social · 23/03/2026
🚀Introducing 𝐆𝐔𝐈𝐃𝐄-𝐋𝐋𝐌: A reporting checklist for using LLMs in behavioral & social science ✅GUIDE-LLM is a reporting checklist designed by 80+ experts to improve transparency, reproducibility & ethical accountability of LLM-based research 📄 llm-checklist.com
llm-checklist.com
GUIDE-LLM
Reporting Checklist for Studies with Large Language Models in the Behavioral and Social Sciences
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David Ho @davidho.bsky.social · 12/03/2026
The 2026 National Science Foundation budget is $8.75 Billion.
nytimes.com
First 6 Days of Iran War Cost U.S. $11.3 Billion, Pentagon Says
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Steve Rathje @steverathje.bsky.social · 21/03/2026
The very factors that make AI an effective tool for truth-seeking (such as its ability to provide instant, targeted facts and evidence) may also make it an effective tool for providing custom rationalizations.
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Steve Rathje @steverathje.bsky.social · 21/03/2026
People can now receive instant, detailed, on-demand rationalizations of their bespoke realities from generative AI. In other words, AI may serve as a powerful rationalization machine, generating elaborate justifications for what people already (or wish to) believe.
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Steve Rathje @steverathje.bsky.social · 21/03/2026
AI might provide more opportunities than past technologies for people to have their beliefs confirmed. While people may have only had a handful of television channels or online communities to choose from, they can now have hyper-specific and idiosyncratic beliefs validated.
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Steve Rathje @steverathje.bsky.social · 21/03/2026
🚨 𝗛𝗼𝘄 𝗔𝗜 𝗰𝗮𝗻 𝗳𝘂𝗲𝗹 𝗰𝗼𝗻𝗳𝗶𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗯𝗶𝗮𝘀 🚨 AI can be an excellent tool for truth-seeking. But people may not *want* to use AI to search for the truth. Instead, they may prefer to use it to confirm their pre-existing beliefs. New working paper (with @jayvanbavel.bsky.social): osf.io/preprints/ps...
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Jay Van Bavel, PhD @jayvanbavel.bsky.social · 17/03/2026
Will AI become a confirmation bias machine? AI can be a powerful tool for truth-seeking. Yet, people might prefer to use AI to confirm their pre-existing beliefs, and features of AI systems (eg sycophancy) may make AI effective at justifying what people want to believe. osf.io/preprints/ps...
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Steve Rathje @steverathje.bsky.social · 05/02/2026
As Andy thoughtfully explains, certain technologies may be new, but our psychology isn't, and decades of psychology research can be used to explain questions like what goes viral online and why people enjoy sycophantic chatbots.
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Steve Rathje @steverathje.bsky.social · 05/02/2026
Really enjoyed speaking with @andyluttrell.bsky.social about the psychology of technology after appearing on his podcast a few years ago to discuss science communication.
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Andy Luttrell @andyluttrell.bsky.social · 03/02/2026
This month on Opinion Science, I talk with @steverathje.bsky.social about his research on the "psychology of technology." We cover the predictors of what goes viral online and the allure and influence of agreeable AI chatbots.
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Matthew Facciani @matthewfacciani.bsky.social · 20/01/2026
In my latest podcast episode, I discuss the psychology of virality with @steverathje.bsky.social, explore how agreeable AI chatbots may influence our beliefs, and examine how scientists can communicate effectively in a noisy, polarized media environment. matthewfacciani.substack.com/p/the-psycho...
matthewfacciani.substack.com
The Psychology of Virality in the Age of AI
Steve Rathje joins me to discuss why conflict goes viral, how social media shapes polarization, and what AI chatbots mean for belief and bias.
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Steve Rathje @steverathje.bsky.social · 20/12/2025
Enjoyed talking with @sudkrc.bsky.social on one of my favorite podcasts, the Stanford Psychology Podcast! We discuss how I got into psychology (it all began at Stanford), my recent work on the psychology of virality and sycophantic AI, and much more.
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Stanford Psychology Podcast @stanfordpsypod.bsky.social · 19/12/2025
NEW EPISODE OUT🗣️!! In this episode, Su @sudkrc.bsky.social chats with Dr. Steve Rathje @steverathje.bsky.social on why certain content spreads rapidly online and offline! LISTEN NOW🎧: open.spotify.com/episode/7CoK...
open.spotify.com
166 - Steve Rathje: The Psychology of Virality
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Steve Rathje @steverathje.bsky.social · 17/12/2025
"Using 'virality' as the main way to decide the information people see every day will (like actual viruses) make us sick." @jayvanbavel.bsky.social and I wrote a column on our recent paper on the psychology of virality. Check it out here: www.powerofusnewsletter.com/p/why-some-i...
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Jay Van Bavel, PhD @jayvanbavel.bsky.social · 16/12/2025
While studies find that moral outrage & negativity goes viral on social media, this is also true of the offline world. Gossip is also mostly negative & about people we dislike I explain why some ideas go viral--but most don't with @steverathje.bsky.social www.powerofusnewsletter.com/p/why-some-i...
powerofusnewsletter.com
Why Some Ideas Go Viral—and Most Don’t
What decades of research reveal about why certain content spreads—and how social forces shape what we all see.
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Matt DeVerna @matthewdeverna.com · 29/11/2025
🚨 New working paper 🚨 Can LLMs with reasoning + web search reliably fact-check political claims? We evaluated 15 models from OpenAI, Google, Meta, and DeepSeek on 6,000+ PolitiFact claims (2007–2024). Short answer: Not reliably—unless you give them curated evidence. arxiv.org/abs/2511.18749
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Hanna Sistek @sistek.bsky.social · 04/12/2025
New research by @steverathje.bsky.social et al Epistemic Fragility in Large Language Models: Prompt Framing Systematically Modulates Misinformation Correction WGemini 2.5 Pro had 74% lower odds of strong correction than Claude Sonnet 4.5, highlighting epistemic fragility arxiv.org/pdf/2511.22746
arxiv.org
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Igor Grossmann, PhD @igi.bsky.social · 17/11/2025
Are you curious about the results of our #wisdomturingtest? Want to find out who was the AI? If so, tune-in to the second part of the ON WISDOM podcast on the "Wisdom Turing Test," with the amazing @steverathje.bsky.social : onwisdompodcast.fireside.fm/67 #TuringTest #ChineseRoom #AIsycophancy
lnkd.in
LinkedIn
This link will take you to a page that’s not on LinkedIn
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Steve Rathje @steverathje.bsky.social · 01/10/2025
🚨 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 🧵
Abstract and results summary
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William J. Brady @williambrady.bsky.social · 11/11/2025
✨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 🧵👇
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Steve Rathje @steverathje.bsky.social · 22/10/2025
Really enjoyed speaking with tech ethicist Tristan Harris, who you might know from the Netflix documentary "The Social Dilemma" or his work with the Center for Humane Technology. 🎥 Watch here on YouTube: www.youtube.com/watch?v=TFm3... 🎧 Listen on Spotify: open.spotify.com/episode/0Oi6...
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Jay Van Bavel, PhD @jayvanbavel.bsky.social · 21/10/2025
The Science Behind Why Social Media Makes Us Miserable I was on the @andrew-yang.bsky.social podcast to discuss the impact of social media. We discussed what goes viral online, how it impacts our lives, and what we can do about it (with @steverathje.bsky.social): www.youtube.com/watch?v=YrDV...
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Andrew Yang @andrew-yang.bsky.social · 21/10/2025
What do 92% of scientists agree on regarding social media and smartphone use? blog.andrewyang.com/p/the-scienc...
blog.andrewyang.com
The Science of Smartphones
Hello, I hope that you’re doing great.
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