🚨Out in Science!🚨 Conspiracy beliefs famously resist correction, ya? WRONG: We show brief convos w GPT4 reduce conspiracy beliefs by ~20%! -Lasts over 2mo -Works on entrenched beliefs -Tailored AI response rebuts specific evidence offered by believers https://t.co/3Rg79Cx5id 1/

Back to X just to post new PNAS paper for @elonmusk: we find @CommunityNotes flags 2.3x more Republicans than Democrats for misleading posts! The issue is Reps sharing misinformation, not fact-checker bias... https://t.co/qnVNWCUHPt

Many thanks to lead author @captaineco_fr who does amazing work on Community Notes and other topics; and the always-wonderful coauthor Mohsen Mosleh For more of my group's work on misinformation, check out this doc:

CONCLUSION: *Clear partisan diff in misinfo sharing not due to political bias on the part of fact-checkers or academics *Undercuts logic offered by Musk+Zuckerberg for eliminating fact-checkers *Platforms should expect more Rep-sanctioning even when using Community Notes!

We also address two poss confounds: *Is it just that more Reps are using X than Dems, throwing off base rates? No, it's the opposite *It is just that more Dems use CN? No, b/c rated-helpful notes + bridging algorithm require people from both sides rating the notes as helpful

Across all English notes 1/23-6/24: 1.5x more notes proposed on tweets written by Reps than Dems. The partisan diff is MUCH bigger when restricting to "helpful" (ie ~unbiased) notes: 70% on Reps, 30% on Dems. The "vox populi" has concluded that Reps share more misinfo than Dems!

Many studies find Reps do share more misinfo. But those studies could be biased in evaluating what is misinfo. So we analyze Community Notes, where users flag posts & X decides what is misleading using a “bridging algorithm” requiring agreement from users who typically disagree

Accusations of bias against Reps (eg Trump+others suspensions) drove @elonmusk to buy Twitter & gut fact-checking in favor of @CommunityNotes. @finkd did same at @Meta. But greater sanctioning of Reps could just be the result of Reps sharing more misinfo

Back to X just to post new PNAS paper for @elonmusk: we find @CommunityNotes flags 2.3x more Republicans than Democrats for misleading posts! The issue is Reps sharing misinformation, not fact-checker bias... https://t.co/qnVNWCUHPt

Today Meta announced it's getting rid of fact-checking to avoid bias. But is there actually evidence of anti-conservative bias? Not really - conservatives get suspended more but also share more low quality news (as judged by politically balanced crowds) ⏬

If you had to pick *1* measure of racial attitudes to predict white Americans' Trump support, we find opposition to anti-racism (agreement w/ statements like "People these days can’t speak their minds without someone accusing them of racism") is most correlated

NEW: According to Oxford and MIT researchers @_mohsen_m, @DG_Rand, and @cameron_martel_, social media users are more likely to follow and engage with like-minded accounts that demonstrate similar political views. https://t.co/sRHlGw3UBa

This is a very cool paper by two of my fav people! Many studies have shown that more reflective people believe in God less. This paper shows that *changing* belief (in either direction) is ALSO associated with reflectiveness. Higher CRT = more willing to update beliefs

"On the role of analytic thinking in religious belief change: Evidence from over 50,000 participants in 16 countries" ✍️Michael N Stagnaro & @GordPennycook Key finding: Reflection is associated with belief change independent of the direction of change. https://t.co/GhAs9qEiJz

Are AIs the misinformation machines? Or are we humans the originals? In our latest episode of the Behavioral Design Podcast, @GordPennycook schools @SamuelSalzer and I on all things BS and misinfo. https://t.co/ke0jJ25L8m

Feel like passing the time while anxiously waiting for the election? I was on 3 fun podcasts recently #1: You Are Not So Smart with @davidmcraney: https://t.co/pWlDEzIagt Focus is on our recent AI-conspiracy belief paper. Got to join with @DG_Rand & @tomstello_!

An interview with the scientists who created Debunkbot, an AI/LLM that reliably reduces belief in conspiracy theories via back-and-forth chat: https://t.co/Ma0OInWAI1 ( featuring @tomstello_ - @DG_Rand - @GordPennycook )

New episode — an interview with the scientists who created Debunkbot, an AI that reliably reduces belief in conspiracy theories via back-and-forth chat, no matter how far down the rabbit hole a person may be: https://t.co/COca6xKrnb (try it at https://t.co/pBRyMlzNHa)

So what have I learnt about #misinformation research? I tried to condense it into a list of the 5 biggest challenges the field faces. Second story in my package of stories about misinformation research is up here (and thread to come): https://t.co/08QKJ03Nma

Great article from @kakape about the five biggest challenges facing misinformation researchers highlighting some of our recent work! Agree with pretty much all these. https://t.co/JOtSi6Fk8a

5 biggest challenges facing misinformation researchers https://t.co/8V2acFbPx8 1) Defining it 2) Everything is political 3) Harms hard to pin down 4) Companies own the data 5) The problem is global I would add (related to #3), what's the direction of causation? Do people use