Musk denied he was aware Grok ever produced ‘any naked underage images’
A survivor of child sexual abuse has sued Elon Musk’s artificial intelligence company, alleging that its chatbot used pictures of her abuse to generate new illegal pornographic images that depict her.
“Using real images of Plaintiff and class members, Grok generated child pornography depicting Plaintiff and class members,” states the complaint, which was filed last week in a US district court in California.
Attorneys for the plaintiff, who is listed as Jane Doe in the case to protect her identity, accuse xAI of both generating CSAM of their client and of ingesting child sexual abuse images depicting her into the company’s datasets after new images were publicly posted.
How does that work? Are there hashes of child sex abuse images somehow reproduced by LLM? Surely the new images don’t have the same hashes. Guardian is not really being clear here.
edit: Ars’ is less badly written: “This is the first case to accuse xAI of training on CSAM, and the complaint does not go into great detail on that claim. Previously, Ars reported on a controversial dataset that was later scrubbed after researchers found CSAM in the training data, but there’s no indication xAI trained on that data. In a press release from lawyers representing Doe, it explained that Doe’s images were included in a CSAM Hash List maintained by NCMEC, and “that same material” allegedly “was part of the dataset xAI used to build Grok’s image and video generating capabilities.” The complaint similarly only alleged that “CSAM depicting Plaintiff with its longstanding well-known hash values has been used as a part of the dataset used by xAI.””
From my understanding a hash completely changes when a single part of it is changed. That’s the point of a hash. Sounds like they identified the hashed images from the training set.
there are other, more robust, ways of fingerprinting images than hashing the data. I’m not sure how it works exactly though, but I can imagine it is not completely different from how shazam can pick out a song in a noisy environment.
Nope. They use perceptual hashing. That way water marking and cropped images still trigger against the casm scanners.
The known casm results in a specific hash. Modified versions of that will result in a different hash but such that the “distance” is meaningful. The distance is how many bits need to flip to match the known casm hash.
It can lead to false positives so that’s why manually checking occurs. It’s also why people got very upset that Apple and perhaps others were going to automatically do these checks during upload to the cloud. When performed against billions of images, the false positive rate becomes huge and manually checking becomes too much overhead so people would be falsely accused.
It’s very likely what they found in groks models is a false positive but in this case they can probably compel twitter to prove it’s a false positive.
you would think, but then it would be lost when any part of the image changed (like adding a watermark or jpeg compression) instead it is a reversable algorithm https://www.researchgate.net/figure/mage-reconstructions-from-PhotoDNA-hashes-4_fig4_374838370
Ya it doesn’t make sense. I think it’s probably facial recognition and since she’s in the training dataset, her face pops up when the model gets pulled in that direction.
They wouldn’t have access to the dataset, I don’t see how they could know for the Arts explanation. Maybe it learned the hash and reproduces it but that doesn’t seem likely. Even the part about adding hashs to track the images doesn’t make much sense. That would imply they are distributing it somehow.
I don’t get why X isn’t running age detection on the output though.