Substack’s new tool tells you who’s been writing their newsletters with AI
Quick Answer
Substack has introduced a feature integrating Pangram's AI writing detection, allowing users to assess the human versus AI content ratio in newsletters.
Quick Take
While this may initially undermine trust in some newsletters, it aims to enhance transparency and maintain content quality in the long run.
Key Points
- Users can scan posts to see AI content estimates using Pangram integration.
- Feature available for any content over 100 characters in Substack's app.
- Writers can disclose AI usage with an optional author’s note.
- Publishers can check drafts with Pangram before publication.
- Substack aims to improve trust in human-generated content.
DeepSignal Analysis
What happened
Substack has launched a feature that integrates Pangram's AI writing detection, allowing users to see the ratio of human versus AI-generated content in newsletters. This tool aims to enhance transparency regarding content creation on the platform. While it may initially undermine trust in some newsletters, it could ultimately improve content quality.
Key evidence
- Substack's new feature allows users to scan posts, comments, and replies to estimate the human versus AI content ratio in newsletters.
- The tool is designed to encourage writers to disclose their use of AI by adding an optional AI author’s note.
- Publishers can run Pangram on their drafts before publication and report any inaccuracies in the AI detection results.
Why it matters
The introduction of AI detection could reshape how users perceive content on Substack, potentially leading to a decline in trust for newsletters that rely heavily on AI. However, by promoting transparency, Substack may foster a more informed readership. This move aligns with broader industry trends where platforms are increasingly labeling AI-generated content.
What to watch
📖 Reader Mode
~3 min readSubstack has launched a new feature that can show you which of your favorite newsletters are being written using AI.
This week, the newsletter and writing platform announced an integration with the AI writing detection software Pangram that will allow users to scan posts, comments, and replies on Substack’s app to see an estimate of how much of the content was written by a human and how much was AI.
In the short term, the move might be bad for Substack’s business, as it could expose many of the newsletters on its platform that aren’t entirely written by people. That could potentially erode trust in the platform’s ecosystem of independent news and blogs, or even damage its reputation as a host of high-quality content.
But in the long term, AI-detection features could help keep Substack free of “AI slop” and encourage more users to trust what they’re reading was written by a person, or at least better understand when it’s not.
Substack joins several platforms that are leaning toward labeling AI content as such, especially now that AI is playing a greater role in the creation process. Photos and videos generated with AI are labeled on social media sites, while music streaming services have more recently begun labeling and, in some cases, penalizing AI-generated music.
“This is good use of AI,” Substack CEO Chris Best 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,” he explained in an online chat with Pangram’s founder, Max Spero. “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.”
The feature will be available in Substack’s app for any post, note, reply, or comment above 100 characters. Substack will also allow its writers to include an optional AI author’s note, using which creators can properly disclose their use of AI, the company told TechCrunch.
The company clarified that the tool is not meant to prohibit or penalize AI-assisted writing, but rather to encourage writers to add a “how I make this” statement, where they explain their process.
Publishers can also run Pangram on their own drafts before publication, and report and remove scans on their own work they believe are mistakes.
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Sarah has worked as a reporter for TechCrunch since August 2011. She joined the company after having previously spent over three years at ReadWriteWeb. Prior to her work as a reporter, Sarah worked in I.T. across a number of industries, including banking, retail and software.
You can contact or verify outreach from Sarah by emailing sarahp@techcrunch.com or via encrypted message at sarahperez.01 on Signal.
— Originally published at techcrunch.com
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