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Yes—X allows AI systems to propose Community Notes, but its documented process does not let an AI bot decide on its own that a note appears publicly. X describes two related but distinct features: enrolled AI contributors can submit proposed notes, and its experimental Collaborative Notes feature can generate a draft after a person requests one. In both workflows, human contributors provide the ratings that determine whether a note is considered helpful enough to show.

How X’s AI Community Notes work

The phrase “AI bot for writing Community Notes” can refer to two different workflows. One is the AI Note Writer API, which lets an enrolled AI contributor submit proposed notes on eligible posts. The other is Collaborative Notes, an experimental feature that generates a draft after a contributor taps “Request a Note.” They differ in who starts the process and who drafts the note; neither gives AI the final visibility decision.

Workflow What starts it Who drafts Who rates and decides visibility
AI Note Writer API The AI writer can submit proposals on candidate posts. X says the initial candidate set includes posts where people requested a note and may expand. An enrolled AI contributor Regular human contributors
Collaborative Notes A contributor taps “Request a Note.” The Collaborative Notes system generates a draft. Contributors can rate the draft and suggest improvements.

X’s AI Note Writers guide says AI writers can gain or lose the ability to write over time based on helpfulness, much like human contributors. They cannot rate notes. X’s Collaborative Notes guide describes that feature as new and experimental, with changes expected as it receives feedback.

Can an AI bot publish a Community Note automatically?

The documented AI Note Writer API allows AI contributors to submit proposed notes; it does not give them authority to make a note publicly visible by themselves. Human contributor ratings determine whether a note is considered helpful enough to show. In the Collaborative Notes workflow, a person can also rate a generated draft and suggest changes.

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X explains that notes become helpful when contributors with differing histories of rating notes agree. Its Community Notes introduction says: “X doesn’t write, rate or moderate notes (unless they break X’s Rules.)” That is X’s description of the system’s role; it does not mean X can never enforce its platform rules.

What is required to build an AI Note Writer?

X’s API route is for developers building an AI contributor, not a general-purpose setting that any account can switch on. The official guide specifies these requirements and steps:

  1. Use an X account that is not already signed up as a Community Notes contributor.
  2. Ensure the account has a verified email address and a phone number verified through a trusted carrier.
  3. Sign up for the X API and enable read/write permissions for the app.
  4. Enroll in the AI Note Writer API.
  5. Connect the app to Community Notes.

X also limits how Community Notes API data may be used: it may be processed solely for AI note writing and may not be used to train or fine-tune a foundation or frontier model. These requirements apply to the documented API workflow; they should not be assumed to describe access to Collaborative Notes in the consumer product.

What the 2025 pilot and current documentation establish

TechCrunch reported on July 1, 2025 that X was piloting a program in which AI chatbots generated Community Notes. The report said AI submissions would receive the same vetting as human submissions and that broader rollout depended on testing. That article is dated pilot context, not proof of current availability or the launch date of every feature now described by X.

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X’s current documentation describes both the AI Note Writer API and Collaborative Notes, but the two features should not be treated as one product or assumed to have identical access conditions. The practical distinction is that the API supports enrolled AI contributors submitting proposals, while Collaborative Notes begins with a contributor’s request for a generated draft.

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What a 2026 field evaluation found

A field study by Haiwen Li and Michiel A. Bakker evaluated one LLM-based writer during a three-month deployment from November 1, 2025, through January 31, 2026. The authors reported 1,614 AI-written notes on 1,597 posts, compared with 1,332 human-written notes on the same posts; the analysis included 108,169 ratings from 42,521 raters.

The results depend on how helpfulness is measured. Individual ratings were more positive for the LLM notes across rater viewpoint groups. In the full sample, however, human-written notes more often reached “Currently Rated Helpful” status, while LLM notes less often reached “Currently Rated Not Helpful” status and had similar average helpfulness scores. When the researchers compared notes using raters who rated every note on a post—an approach that equalized rating exposure—the LLM notes had higher helpfulness scores.

Li and Bakker caution that submission timing and differences in which notes people rated complicate direct comparisons. The findings concern one implementation in one field evaluation; they do not establish that AI-generated notes are always accurate, more helpful, or better across topics and systems. Read the 2026 paper for its methods and full results.

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