Jay Baxter
Founding ML Engineer & Researcher, Community Notes at X (formerly Twitter)
Jay Baxter is the Founding ML Engineer and Researcher for Community Notes at X (formerly Twitter). He designed the bridging-based algorithm that powers Community Notes, which finds agreement among people who normally disagree to surface accurate, neutral corrections to misleading posts.
Dimension Profile
Key Themes
Episode Summary
Jay Baxter, alongside Keith Coleman, reveals the inside story of Community Notes — the crowdsourced fact-checking system on X that finds consensus among people who normally disagree. He explains the bridging-based algorithm he designed, why all of humanity should participate including leadership and advertisers, and how external studies have validated that Community Notes actually changes people's agreement with misleading claims. The system has since been adopted by Meta as their main fact-checking approach.
Leadership Principles
- → Look for agreement from people who have disagreed in the past — surprising consensus signals accuracy and neutrality
- → All of humanity should participate — don't exempt anyone, including leadership and advertisers
- → Open source your algorithm and data so people can verify your system is working as intended
Notable Quotes
"We actually look for agreement from people who have disagreed in the past. And what we see is when people actually have that sort of surprising agreement, that's what makes the notes so neutral and accurate and well-written."
— On the core algorithm principle behind Community Notes
"There have been external studies run by people totally independent of us who have found that if you take a post with or without a Community Note, that actually people's agreement with the core claims in the post does change if they see it with a note versus without."
— On external validation that Community Notes actually changes people's beliefs
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