Jessica Silbey

@jessicasilbey.bsky.social

Frank R. Kenison Distinguished Scholar in Law, Associate Dean, Boston University School of Law https://www.bu.edu/law/profile/jessica-silbey/

🚨New preprint and our results are rather concerning.. We find the "boiling frog" equivalent of AI use. Using large-scale RCTs, we provide *casual* evidence that AI assistance reduces persistence and hurts independent performance. And these effects emerge after just 10–15 minutes of AI use! 1/

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A new paper shows that less than 2 months of exposure to Twitter’s algorithmic feed significantly shifts people’s political views to the right. Moving from chronological feed to the algorithmic feed also increases engagement. This is one of the most concerning papers I’ve read in awhile.

The political effects of X's feed algorithm
https://doi.org/10.1038/s41586-026-10098-2
Received: 16 December 2024
Accepted: 4 January 2026
Published online: 18 February 2026
Open access
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Germain Gauthier,5, Roland Hodler?5, Philine Widmer35 & Ekaterina Zhuravskaya3,4,5 m
Feed algorithms are widely suspected to influence political attitudes. However, previous evidence from switching off the algorithm on Meta platforms found no political effects'. Here we present results from a 2023 field experiment on Elon Musk's platform X shedding light on this puzzle. We assigned active US-based users randomly to either an algorithmic or a chronological feed for 7 weeks, measuring political attitudes and online behaviour. Switching from a chronological to an algorithmic feed increased engagement and shifted political opinion towards more conservative positions, particularly regarding policy priorities, perceptions of criminal investigations into Donald Trump and views on the war in Ukraine. In contrast, switching from the algorithmic to the chronological feed had no comparable effects.
Neither switching the algorithm on nor switching it off significantly affected affective polarization or self-reported partisanship. To investigate the mechanism, we analysed users' feed content and behaviour. We found that the algorithm promotes conservative content and demotes posts by traditional media. Exposure to algorithmic content leads users to follow conservative political activist accounts, which they continue to follow even after switching off the algorithm, helping explain the asymmetry in effects. These results suggest that initial exposure to X's algorithm has persistent effects on users' current political attitudes and account-following behaviour, even in the absence of a detectable effect on partisanship.

Walz: Minnesotans are witnessing, and we're creating a log of evidence for the future prosecution of ice agents and officials responsible for this.

As someone who has been on the business end of nationwide injunctions that I thought were improper, I find the question of what rules we should adopt for them to be genuinely hard. But yesterday's decision deserves massive criticism, for at least two reasons. (Thread.)

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