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Substack Launches AI Detection Feature To Scan Posts And Comments For Machine-Generated Text

aiai-products 7 posts · 7 accounts

Substack launched a new artificial intelligence detection feature on its publishing platform following a partnership with Pangram. The tool allows users to scan posts, replies, and comments within the app to receive an estimate of how much text was written by a human versus machine-generated.

The platform will initially deploy a click-to-reveal mechanism that provides transparency without automatically filtering content flagged as AI-written. Pangram’s data indicates that 40% of long-form text on LinkedIn is generated by AI, a metric that contextualizes Substack’s effort to protect human authorship from machine-generated content saturation.

From the sources (7 posts)

@stefanfschubert

RT @Substack: Today, Substack is launching an AI detection feature, via an integration with @pangram. Going forward, you’ll be able to scan…

@emollick

This is an interesting experiment (and I am glad that I have always written my own posts!)

@mtslive

SITUATION DETECTED: Substack is partnering with Pangram to add AI detection to all posts.

@lulumeservey

Bravo. Chris & team have really created a refuge for people who think in public, warding off threats to independent writing from censorship to, now, the slopocalypse “The problem is not people using AI, it’s Claudefishing; the deception w

@thezachmueller

RT @Substack: Today, Substack is launching an AI detection feature, via an integration with @pangram. Going forward, you’ll be able to scan…

@andy_l_jones

substack's adding pangram integration, and i really like both the initial intervention - click-to-reveal - and the described (uncertain!) path to future interventions, like filtering out anything that scores highly. seems thoughtful & m

@substack

Today, Substack is launching an AI detection feature, via an integration with @pangram. Going forward, you’ll be able to scan posts, replies, and comments on the Substack app to see an estimate of how much of it was written by a human, or w

Preview built on a synthetic news corpus (16 weeks, Apr–Jul 2026). Impact calls are model reads, not price data.

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