In the near term, Substack could suffer financially because the tool might reveal that a large number of its newsletters are not fully human-authored. This could possibly undermine confidence in the platform's network of independent journalism and blogs, or harm its standing as a purveyor of premium material. However, over the long run, such detection tools might help Substack avoid being overrun with low-quality AI content, and instead build reader confidence that what they see is genuinely human-written, or at least aware of the mix.
Chris Best, Substack's CEO, said: "When I used to pitch Substack to writers, one way I would do it is … we'll do everything for you except the hard part. You have to have something - an idea that's worth reading, that's worth caring about, that's worth sharing. That one thing is very hard and very valuable … [S]oftware should do everything else, but I think you do want the person to do the hard part."
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The goal is long-term trust. Substack wants readers to feel confident that what they are reading comes from a real human who actually wrote it.
Users will find this feature in the Substack app, applicable to any post, note, reply, or comment exceeding 100 characters. Additionally, the platform will permit authors to add a voluntary AI authorship label that lets creators explicitly state their use of AI, according to Substack's announcement to TechCrunch. Substack emphasized that the feature does not aim to ban or punish AI-assisted content.
Instead, it is designed to encourage writers to add a "how I make this" statement where they explain their process. Creators may also use Pangram on their pre-published drafts, and they can flag and delete any scans they consider erroneous on their own posts.
For readers, this is a chance to decide what matters to them. Some people care deeply that every word is human-written. Others are fine with AI tools as long as the author is still driving the bus. The important thing is that you get to know the difference.
This move comes as AI-generated text has become increasingly common on platforms like Substack. Many writers now use large language models for outlines, research, or full drafts, blurring the line between human and machine authorship. Substack's partnership with Pangram is an early attempt to give readers a clear signal about authenticity.
The tool does not block or flag content - it simply shows a percentage, leaving the judgment to the audience. This approach mirrors broader industry debates about transparency in digital media, where trust is a fragile commodity.
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