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Everything that could go wrong with X’s new AI-written community notes

By Advanced AI EditorJuly 2, 2025No Comments2 Mins Read
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If AI note writers “generate initial drafts that represent a wider range of perspectives than a single human writer typically could, the quality of community deliberation is improved from the start,” the paper said.

Future of AI notes

Researchers imagine that once X’s testing is completed, AI note writers could not just aid in researching problematic posts flagged by human users, but also one day select posts predicted to go viral and stop misinformation from spreading faster than human reviewers could.

Additional perks from this automated system, they suggested, would include X note raters quickly accessing more thorough research and evidence synthesis, as well as clearer note composition, which could speed up the rating process.

And perhaps one day, AI agents could even learn to predict rating scores to speed things up even more, researchers speculated. However, more research would be needed to ensure that wouldn’t homogenize community notes, buffing them out to the point that no one reads them.

Perhaps the most Musk-ian of ideas proposed in the paper, is a notion of training AI note writers with clashing views to “adversarially debate the merits of a note.” Supposedly, that “could help instantly surface potential flaws, hidden biases, or fabricated evidence, empowering the human rater to make a more informed judgment.”

“Instead of starting from scratch, the rater now plays the role of an adjudicator—evaluating a structured clash of arguments,” the paper said.

While X may be moving to reduce the workload for X users writing community notes, it’s clear that AI could never replace humans, researchers said. Those humans are necessary for more than just rubber-stamping AI-written notes.

Human notes that are “written from scratch” are valuable to train the AI agents and some raters’ niche expertise cannot easily be replicated, the paper said. And perhaps most obviously, humans “are uniquely positioned to identify deficits or biases” and therefore more likely to be compelled to write notes “on topics the automated writers overlook,” such as spam or scams.



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