If you’ve been paying careful attention to YouTube recently, you may have noticed the rising trend of so-called “faceless YouTube channels” that never feature a visible human talking in the video frame. While some of these channels are simply authored by camera-shy humans, many more are fully automated through AI-powered tools to craft everything from the scripts and voiceovers to the imagery and music. Unsurprisingly, this is often sold as a way to make a quick buck off the YouTube algorithm with minimal human effort.
It’s not hard to find YouTubers complaining about a flood of these faceless channels stealing their embedded transcript files and running them through AI summarizers to generate their own instant knock-offs. But one YouTuber is trying to fight back, seeding her transcripts with junk data that is invisible to humans but poisonous to any AI that dares to try to work from a poached transcript file.
The power of the .ass
YouTuber F4mi, who creates some excellent deep dives on obscure technology, recently detailed her efforts “to poison any AI summarizers that were trying to steal my content to make slop.” The key to F4mi’s method is the .ass subtitle format, created decades ago as part of fansubbing software Advanced SubStation Alpha. Unlike simpler and more popular subtitle formats, .ass supports fancy features like fonts, colors, positioning, bold, italic, underline, and more.
It’s these fancy features that let F4mi hide AI-confounding garbage in her YouTube transcripts without impacting the subtitle experience for her human viewers. For each chunk of actual text in her subtitle file, she also inserted “two chunks of text out of bounds using the positioning feature of the .ass format, with their size and transparency set to zero so they are completely invisible.”
In those “invisible” subtitle boxes, F4mi added text from public domain works (with certain words replaced with synonyms to avoid detection) or her own LLM-generated scripts full of completely made-up facts. When those transcript files were fed into popular AI summarizer sites, that junk text ended up overwhelming the actual content, creating a totally unrelated script that would be useless to any faceless channel trying to exploit it.
F4mi says that advanced models like ChatGPT o1 were sometimes able to filter out the junk and generate an accurate summary of her videos despite this. With a little scripting work, though, an .ass file can be subdivided into individual timestamped letters, whose order can be scrambled in the file itself while still showing up correctly in the final video. That should create a difficult (though not impossible) puzzle for even advanced AIs to make sense of.
The fight continues
While YouTube doesn’t support .ass natively, there are tools that let creators convert their .ass subtitles to YouTube’s preferred .ytt format. Unfortunately, these subtitles don’t display correctly on the mobile version of YouTube, where the repositioned .ass subtitles simply show up as black boxes covering the video itself.
F4mi said she was able to get around this wrinkle by writing a Python script to hide her junk captions as black-on-black text, which can fill the screen whenever the scene fades to black. But in the video description, F4mi notes that “some people were having their phone crash due to the subtitles being too heavy,” showing there is a bit of overhead cost to this kind of mischief.
F4mi also notes in her video that this method is far from foolproof. For one, tools like OpenAI’s Whisper that actually listen to the audio track can still generate usable transcripts without access to a caption file. And an AI-powered screen reader could still likely extract the human-readable subtitles from any video quite easily.
Still, F4mi’s small effort here is part of a larger movement that’s fighting back against the AI scrapers looking to soak up and repurpose everything on the public Internet. We doubt this is the last effort we’ll see from YouTube creators trying to protect their content from this kind of AI “summarizing.”