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
Source Excerpt
Substack is giving readers a way to estimate how much of a newsletter was written by AI, signaling a broader shift toward transparency around AI-assisted content.
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from TechCrunch
See more →
Why the first GPU financiers are turning to inference chips in a $400 million deal
General Compute secured a $400 million loan from Upper90, using inference-specific chips as collateral, signaling a shift towards cost-effective AI infrastructure. Their SN50 chips promise 16x faster inference than traditional GPU clouds, highlighting a growing market for open-source AI models and alternatives to Nvidia.
