Substack contributors are rejecting the company’s decision to flag AI generated writing on the newsletter publishing platform, with several creators saying the new AI detection features are a “witch hunt.” Some Substack users who use AI to help them write or edit articles say the new policy unfairly discriminates against them, while other users who don’t use AI in their writing at all are worried that Substack will mistakenly flag their writing as being AI generated and tarnish their reputation. 

“I’m not going to apologize for using AI in the creation process. I wrote for 20 years without AI, I could do it again if I wanted to,” Mack Collier, who has a small Substack called Backstage Pass, wrote. “My output would fall, my posts would be less structured, and it would be more obvious that they needed a good editor. Using AI improves the overall quality of my writing. That’s why I use it.”

“These detectors are notoriously, wildly inaccurate,” Alice Lemee, a ghostwriter and digital writing coach, said in a video she made about Substack’s new AI detection features. “All it takes is one false accusation for a writer to have their reputation almost irreversibly tarnished.”

Substack announced the AI detection features on Tuesday in a post from CEO Christ Best, who said that “It’s getting harder to tell what’s real on the internet” and that “when content made by no one takes over parts of the internet that are supposed to be human, it pollutes the commons and makes it hard to discover and hear human voices.”

Best explained that Substack has partnered with the AI detection tool Pangram, which is now built in to Substack and allows any user to scan a piece of writing. Pangram then produces a percentage-based score determining how much of the writing was AI or human generated. (Disclosure: Pangram previously bought an ad on 404 Media). We’ve covered research from Pangram, or research that relies on its AI detector before, showing how AI generated writing is flooding every corner of the internet. 

As we’ve previously reported, AI detectors are not perfect, and Pangram itself is not immune to labeling human content as being AI, and labeling AI as human. Max Spero, the CEO of Pangram, recently told us that the company is constantly working on minimizing errors, and that it estimates its false positive rate at roughly one in 10,000.  

“We have now built the mirror image. Pangram is a real machine, trained on vast amounts of text to make a probabilistic guess, and we have pointed it at your writing to work out whether a person is hidden inside,” Sam Illingworth, a professor and the author of Slow AI, said on his Substack in a post titled “Substack’s AI Detector and the Return of the Witch Hunt.” “To decide if there is a human on the other end, Substack asks a machine.”

Substack also added a way for users to add a “How I make this” statement, where they can explain their writing process and disclose if they use AI. 

“We’re not against people using AI to assist their work, and we think people should be free to choose which tools they use to express themselves,” Best said. “Some on the platform are human-writing maximalists, others are publicly exploring the frontier of using AI tools while sweating the details to make work they stand behind. We use AI all the time at Substack to write software, do research, and build product features like clipping, translations, and more. But people should know what they’re getting.”

“I think the best way for Substack to address this is to invite further dialogue,” Illingworth told me. “I actually really like the new feature that lets authors tell their readers how they construct their newsletters using AI, and this is the kind of dialogue they should encourage rather than ascribing a score that we know to be incorrect. My worry is that not only do these AI detectors generate false flags for non-native English speakers and neurodiverse writers, but they also remove any opportunity for dialogue because they start from a position of suspicion. Whereas what we need to be doing is developing opportunities for trust between readers and authors.”

"The tools we've introduced today are intended to increase transparency and give readers more context, not to prohibit or penalize AI-assisted writing. They do not impact discovery on the platform,” a Substack spokesperson told me. “We're also encouraging Substack publishers to add a ‘How I make this’ statement, where they can explain their process directly, including how they use (or don't use) AI, and set expectations for readers. Creators can disable detection on their posts pre- and post-publication, as well as report and remove scans on their own work that they believe are mistaken. Find more information on how the features work here.”

Substack’s attempt to detect and label AI generated content was also celebrated by many readers who are exhausted by AI slop and other internet platforms that can’t or don’t want to label it. I just published story about how there is so much unlabeled AI slop on Spotify that people are now creating their own sites to detect and label it without the company’s help.  

But the backlash from some Substack users shows that companies can’t just flip a switch if they want to ban or give users the ability to filter out AI content from their feeds. As the flood of AI writing and images we see online and the real world every day makes clear, generating slop is easy. What we’re going to do about it is still an unsolved problem.

In a video my friend’s dog is laying on her back, her little paws in the air, while my friend rubs the dog’s chest. You can see most of the dog — who I’m not naming for very important privacy reasons — from her head to her belly. On closer inspection, you’ll notice the picture includes some dog nipples. 

Apple’s iMessage thought this video was so inappropriate that it flagged the video as potentially containing nudity and blurred it. When someone else received the video over iMessage, the app displayed the message “This may be sensitive.” They had to purposefully tap to reveal the video of a dog laying on her back being petted.

This, obviously, is not the intended use case for iMessage’s nudity detection features. They are designed to let people protect themselves against receiving unwanted or unsolicited nude photos and videos. But the case of my friend’s dog shows how this feature can sometimes misclassify videos.

“Sensitive Content Warning lets you receive warnings about photos or videos that might contain nudity before viewing them,” Apple’s website reads. Apple introduced the feature in iOS 17 a few years ago. Obviously, scanning the content of messages and content is controversial, but Apple says it performs the scan on the device. Users can also turn the feature off in the settings. “Sensitive Content Warning uses on-device machine learning to analyze photos and videos. Because they're analyzed on your device, Apple doesn't receive an indication that nudity was detected and doesn't get access to the photos or videos as a result,” its website adds.

The dog video isn’t an isolated incident either. Here’s another I found on an Apple forum from May 2025: “Why did a photo of my dog trigger a sensitive content warning on iMessage?” the title reads.

“So I was going to send 3 photos to a group chat I had on iMessage. After I pressed the send button, I got a sensitive content warning… the photo was one of my dog’s body, the other two were fine though. I’m confused and I wanted to report this problem. Just so you all know I’m just looking to report this problem. I think it was just a false and mistaken sensitive content warning,” the poster wrote.

There is also this one from October 2024: “A picture of a deer was flagged as sensetive [sic].”

“This was flagged as possibly sensitive, and a pop-up appeared asking me If I wanted to send it. That is a picture of a deer from a trail camera,” the poster wrote.

Apple did not respond to a request for comment.

Police arrested a high school physics teacher for clapping during a city council meeting last Wednesday. Teacher Lux Claridge went to a meeting of the Emporia, Kansas City Commission on July 22 with their spouse and brother. All three were there to speak out against a proposed hyperscale data center that would sit on 1,000 acres of rural land in Emporia. They left the meeting in handcuffs, dragged out by police on the orders of a city commissioner.

Emporia PD denied 404 Media’s request for a copy of Claridge’s arrest report. “The requested record is part of an active criminal investigation. As such, it is considered a criminal investigative record,” Emporia PD told 404 Media. “At this time, the Emporia Police Department is denying your request, as disclosure of the requested report could interfere with ongoing investigative efforts. Therefore, the record will not be released.” 404 Media has formally appealed this decision.

The Emporia City Council met on July 22 and planned to vote on zoning ordinances that would pave the way for the massive Flint Hills Digital Campus data center. Dozens of people from Emporia showed up to speak out against the project. The meeting went on almost five hours — much of it over community concerns about the data center. The small room where the council met could only fit around 30 people. Others waited to speak in a hallway outside or in two nearby overflow rooms.

The overwhelming majority of Emporia’s residents did not want it. There was a strict two minute time limit on public comments and the commissioners repeatedly warned people in the room not to clap or make noise. Attendees clapped anyway, though usually quickly and politely. Again, there were not many people in the room and it was not a rowdy meeting.

But the clapping upset the commissioners. “It was very clear at the beginning that everyone was given their two minutes and we’re trying to be respectful of that. Snapping, clapping, rude comments or anything, and we’ll ask you to leave. You’ve been finally warned and we’re done,” city commissioner Monica Duncan said about 50 minutes into the meeting.

Claridge clapped a few minutes later as a speaker finished and their spouse—Jessica Danford—took the podium. 

“Chief, will you take the next person out who claps or anything? Please.” Duncan said. “Sorry, I’m done.”

Emporia’s police chief approached Claridge and asked them to leave. “I have a right to speak,” they said. 

“Come on,” the police said.

“Drag me out,” Claridge said. “Drag me out.”Then the police physically raised Claridge up, handcuffed them, and dragged them out. They were later charged with disorderly conduct and interference with police.

Danford panicked as she watched police arrest Claridge. “Take a breath,” Emporia mayor Becky Smith said.“That’s my spouse down there,” Danford said.

“I know. I know. Take a breath,” Smith said.“Please don’t hurt them,” Danford said.

“Let him stay!” People begin to shout in the room.“They can all leave,” commissioner Duncan said, pointing her finger at the room. Then the commissioners shut down the camera feed for the meeting. It resumed about 10 minutes later. Danford was back at the podium and delivered her prepared remarks speaking out against the data center.

A few minutes later, Claridge’s brother David — who is running for state representative — took the podium. “I really look forward to making life hard for you when I get to the statehouse,” he said. “Because you removed my older sibling against their constitutional first amendment rights. This is ridiculous. I have never seen politicians so abundantly terrible at their PR. It is insane. You had someone from the opposition removed for clapping because they enjoyed a speech another member made.”

David told 404 Media that they were angry when police removed his brother. “I was enraged and had to consistently remind myself that a felony battery charge would disqualify me from office,” David told 404 Media. “I don't understand how the commission could think it was a good idea when they are already being so heavily scrutinized. I'm running for office obviously, and I cannot imagine how they thought this political theater would paint them as anything other than a mustache twirling fascist.”

At the end of the evening the commissioners voted 5 - 0 to approve the data center zoning measure.

Emporia, Kansas is like many other towns and cities that are fighting against data centers. It’s small, with a population of around 20,000, and the details around the data center development are shrouded in mystery. The Flint Hills Digital Campus is supposedly the brainchild of developer Gary Pinkston. He penned an op-ed published in the local paper the Emporia Gazette about the importance of the data center for the future of the area. The op-ed was also posted on the website for the Flint HIlls Digital Campus.

Pinkston has also recently declared federal bankruptcy and in public testimony revealed by related to that, he told his creditors that he wasn't involved with the Flint Hills Digital Campus at all. It was, he said, his daughter’s project. “I did not write this,” Pinkston told his creditors when questioned about the op-ed. The Flint HIlls Digital Campus website is now offline. The Emporia Gazette published recordings from Pinkston’s bankruptcy hearing on July 20, two days before an Emporia City Commission meeting where police arrested Claridge.

The police posted a comment about the incident on Facebook. “During the course of the meeting, several individuals in attendance were issued verbal warnings by the City Commission regarding disruptive conduct that was interrupting the proceedings,” the Emporia Police Department said in a statement on Facebook. “One individual, Lux Claridge [...] continued this behavior and was directed to leave the meeting. Claridge did not comply with law enforcement's efforts to remove [them] from the premises, requiring officers to physically carry [them] out of the meeting.”

According to Emporia PD, Claridge was booked at the Lyon County Jail on charges of interference with law enforcement and disorderly conduct. “The Emporia Police Department remains committed to ensuring public meetings are conducted safely and in an orderly manner, while also respecting the rights of all citizens to participate in the civic process,” it said in its Facebook statement.

Claude is exposing a wealth of users’ chats and creations in Google search results, meaning anyone can dig through conversations or other material that people used Claude to make but may not have realized were publicly available for strangers to see.

Slime Dot, a young R&B artist from Las Vegas, currently has over 100,000 monthly listeners on Spotify. In an interview with GQ in May, after sharing an image of herself posing with Drake on Instagram, Slime Dot directly denied accusations that she was an “AI artist,” saying “The truth doesn’t matter these days. People are always gonna try to explain something they don’t fully understand and believe what they want.” GQ originally credulously published the interview and said it was “debunking the AI rumors.” Eventually, GQ added a note to the end of the article conceding Slime Dot was an AI avatar, but said the “talent behind the music remains undeniable.”

This confusion could have been avoided if Spotify had done what many of its users and critics have been begging it to do since AI music generators like Suno and Udio made it trivial to flood the internet with AI music. Spotify could flag Slime Dot and other AI-generated music on its platform as such. Other platforms, like YouTube, already do this. 

Since Spotify doesn’t do that, users can visit SoullessMusic.com, a database for “AI artists hiding on Spotify. No bands, no studios, no soul, just machines and melody.” There, Slime Dot is listed as “almost certainly AI” based on an analysis of three of the tracks and the fact that Slime Dot released such a large number of tracks in a short period of time. Alternatively, users could go to SlopTracker, where they can upload files or copy/paste links to Spotify tracks to run them through a tool which will tell them, with varying degrees of confidence, whether a song was AI-generated or not. SlopTracker found that Slime Dot’s track “Fully” was 95 percent likely to be AI generated by Suno. 

“I didn't know what's AI and what's not,” Graeme Fulton, who created SoullessMusic, told me. “And then I'm on Instagram Reels and I see loads of artists unhappy saying some artist has popped up with their song and just copied it. And there's loads of different cases where they [AI artists] would copy an artist's look and appearance […] sort of just stealing from artists.”

Last year, I wrote a story about an exceptionally bad example of what Fulton is talking about. A scammer used Spotify to publish AI-generated music under the name of a real, dead musician, seemingly in an attempt to syphon money from his popularity via streams. After I published that story I heard from several (living) artists who said the same thing happened to them. A similar case involving a Danish jazz musician was covered by Danish publications in April. 

Another reader recently told me about a popular Spotify artist that was publishing hours of Iranian jazz every week. The channel, Qajar Jazz, which popped up in December of last year, has 29,579 monthly listeners, gained more popularity after the start of the U.S. war with Iran and the channel making vague allusions to resilience and preserving culture in video descriptions and comments on YouTube. Unlike Spotify, Qajar Jazz videos on YouTube are labeled as being AI-generated in the fine print, though it’s unclear if the channel tagged itself as such or if YouTube did. Both SoullessMusic and SlopTracker detect it as being AI generated. 

Qajar Jazz did not respond to a request for comment. 

Many of the YouTube comments on Qajar Jazz videos indicate that people think the music is made by real people. In addition to creating a database of AI generated music on Spotify, SoullessMusic also collects social media posts from people who say they were similarly tricked by AI generated music. Some posts are from musicians who lament the fact that they are now competing with algorithms that can produce thousands of tracks with no effort, and others are from artists whose music was directly ripped off by AI artists. 

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Fulton said he started looking around on GitHub for open source AI music detection tools, and ended up building a new, open source detector that relies on open source models called SONICS, the lofcz vocoder fakeprint detector, and other open data sets. SoullessMusic also  scans a track’s metadata for any tags that might tie it back to a specific AI music generator, and Fulton says he also has a script that scans Wikipedia for existing entries on an artist. Users can submit tracks from Spotify to the site they suspect are AI generated, and Fulton reviews them manually before adding them to the database. Despite all of this, he admits the system is not perfect. 

Both Soulless Music and SlopTracker use AI and other automated tools to detect AI music. As we’ve written previously, using AI detectors to detect AI content is an inherently flawed process that can lead to false positives. When I asked him how he handles cases of false positives, Fulton said “it's not ideal when that happens, but it's going to happen because it's still quite tricky to check what's AI and what’s not.”

Spotify’s lack of transparency and unwillingness to label AI-generated music makes it impossible to track how much money its making on the platform. Last year, the company announced that it would it would AI disclosures on AI generated music, but I haven’t seen it on any of the dozens of tracks I reviewed for this story. Udio and Sudo both include inaudible digital watermarking in their generation, which in theory could make it easy for Spotify to tag these tracks. 

Spotify did not respond to a request for comment. 

Soulless music attempts to quantify that number based on publicly available streaming data. The small number of AI artists tracked on SoullessMusic generate an estimated $5.7 million a year, with the most popular AI artist, mikeeysmind, generating $1.5 million annually alone. In April, Deezer, a Spotify competitor that attempts to tag all AI-generated music on its platform, said 44 percent of all new music uploaded to its platform is now AI generated. SlopTracker, which attempts to track AI generated music on Spotify that is featured on official Spotify-curated playlists, that those artists are “draining” $0.1188 per second from real artists who could be making the music instead.