Check out "The persuasive potential of AI-paraphrased information at scale," an open-access article exploring "AIPasta," written by a team of @cip.uw.edu researchers led by @dashsaloni.bsky.social with co-authors @yiweixu.bsky.social, @maddyjalbert.bsky.social and @emmaspiro.bsky.social ‡οΈ
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#StopTheSteal AIPasta Stimuli: Profile images, usernames, and handles constructed by Jalbert et al. 2025. Profiles do not represent real users and were created from stock images and with handles that are not currently in use.
Repeating duplicated messagesβknown as CopyPastaβover and over online is a common misinformation strategy. Using AI to paraphrase the message, what the authors call βAIPasta,β could be even more effective at creating a false consensus. In PNAS Nexus: academic.oup.com/pnasnexus/ar...
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Key Takeaway: As AI-driven information operations become increasingly common, we expect traditional CopyPasta to be replaced by AIPasta, which is harder to detect and mitigate.
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AIPasta (vs. Control) also increases belief in the exact false claim of the campaign, depending on political orientation. Current state-of-the-art AI-text detectors fail to detect AIPasta, enabling these operations to scale successfully.
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In a preregistered experiment with 1200 U.S. participants, we find that AIPasta (but not CopyPasta) is effective at increasing perceptions of consensus in false claims. Exposure to AIPasta does not change levels of sharing intent compared to a control condition (CopyPasta reduces this).
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In this paper, we study how AI-paraphrased messages can enhance information campaigns. We look at how CopyPasta - a single message crafted by adversarial actors & shared repeatedly at scale --- can be paraphrased using LLMs to generate repetitive, non-identical messages i.e., AIPasta.
24.07.2025 18:24 β π 4 π 0 π¬ 1 π 0
The persuasive potential of AI-paraphrased information at scale
Abstract. In this article, we study how AI-paraphrased messages have the potential to amplify the persuasive impact and scale of information campaigns. Bui
Excited to announce that my paper "The persuasive potential of AI-paraphrased information at scale" with my wonderful collaborators @yiweixu.bsky.social, @maddyjalbert.bsky.social, and @emmaspiro.bsky.social has been published at PNAS Nexus!
Link: academic.oup.com/pnasnexus/ar...
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Inspired by @wimlds.bsky.social , I looked for a "Women in Machine Learning" starter pack and couldn't find one.
So I created one! May have some mistakes. I'll try to do an AI ethics one next. π€
go.bsky.app/LT6CwNN
11.12.2024 04:02 β π 408 π 136 π¬ 55 π 8
Great news! CIP now has a starter pack that showcases our current and past team members! Give them a follow!
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YouTube video by vlogbrothers
Populism, Media Revolutions, and Our Terrible Moment
This is one of those videos that you could work on forever, but suddenly it felt very important to make it, so I finally did: www.youtube.com/watch?v=d8Pn...
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Research Scientist at the Center for an Informed Public at the University of Washington. Social Psych PhD at USC. I study misinformation correction and how people make judgments of truth. Otherwise probably in the mountains. She/her
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UMass Amherst, Initiative for Digital Public Infrastructure, Global Voices, Berkman Klein Center. Formerly Center for Civic Media, MIT Media Lab.
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Founder: The Distributed AI Research Institute @dairinstitute.bsky.social.
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A multidisciplinary research center at the University of Washington in Seattle with a mission to resist strategic misinformation, promote an informed society, and strengthen democratic discourse.
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seattle
uw phd student working on scientific software
Asst Prof @ University of Washington Information School // PhD in English from WashU in St. Louis
Iβm interested in books, data, social media, and digital humanities.
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Computer scientist β’ Prof @UWischool & @UWcse
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AI & Societal Impacts: Ethics in NLP β’ Multimodal ML β’ CV β’ Human-AI Collaboration