Study uncovers presence of CSAM in popular AI training dataset
LAION-5B contains 1,008 verifiable instances of illegal pictures of children, likely lots more, say researchers
Updated A massive public dataset that served as training data for a number of AI image generators has been found to contain thousands of instances of child sexual abuse material (CSAM).
In a study published today, the Stanford Internet Observatory (SIO) said it pored over more than 32 million data points in the LAION-5B dataset and was able to validate, using the Microsoft-developed tool PhotoDNA, 1,008 CSAM images – some included multiple times. That number is likely "a significant undercount," the researchers said in their paper.
LAION-5B doesn't include the images themselves, and is instead a collection of metadata including a hash of the image identifier, a description, language data, whether it may be unsafe, and a URL pointing to the image. A number of the CSAM photos linked in LAION-5B were found hosted on websites like Reddit, Twitter, Blogspot, and Wordpress, as well as adult websites like XHamster and XVideos.
To find images in the dataset worth testing, SIO focused on images tagged by LAION's safety classifier as "unsafe." Those images were scanned with PhotoDNA to detect CSAM, and matches were sent to the Canadian Centre for Child Protection (C3P) to be verified.
"Removal of the identified source material is currently in progress as researchers reported the image URLs to the National Center for Missing and Exploited Children (NCMEC) in the US and the C3P," the SIO said.
LAION-5B was used to train, among other things, popular AI image generator Stable Diffusion version 1.5, which is well known in certain corners of the internet for its ability to create explicit images. While not directly linked to cases like a child psychiatrist using AI to generate pornographic images of minors, it's that sort of tech that's made deepfake sextortion and other crimes easier.
According to the SIO, Stable Diffusion 1.5 remains popular online for generating explicit photos after "widespread dissatisfaction from the community" with the release of Stable Diffusion 2.0, which added filters to prevent unsafe images from slipping into the training dataset.
We asked Stability AI, which funds and steers the development of Stable Diffusion, if it knew about the presence of CSAM in LAION-5B, and if any of that material made its way into the startup's series of models; the company didn't respond to our questions.
We note that though Stability has released various spins of Stable Diffusion, including version 2.0 with the aforementioned filters, version 1.5, which was studied by the SIO and trained on LAION-5B, was released by another startup called RunwayML, which collaborates with Stability AI.
Oops, they did it again
While it's the first time German non-profit LAION's AI training data has been accused of harboring child porn, the organization has caught flack for including questionable content in its training data before.
Google, which used a LAION-2B predecessor known as LAION-400M to train its Imagen AI generator, decided to never release the tool due to several concerns, including whether the LAION training data had helped it build a biased and problematic model.
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According to the Imagen team, the generator showed "an overall bias towards generating images of people with lighter skin tones and … portraying different professions to align with Western gender stereotypes." Modeling things other than humans didn't improve the situation, causing Imagen to "encode a range of social and cultural biases when generating images of activities, events and objects."
An audit of LAION-400M itself "uncovered a wide range of inappropriate content including pornographic imagery, racist slurs, and harmful social stereotypes."
A few months after Google decided to pass on making Imagen public, an artist spotted medical images from a surgery she underwent in 2013 present in LAION-5B, which she never gave permission to include.
LAION didn't respond to our questions on the matter, but founder Christoph Schuhmann did tell Bloomberg earlier this year that he was unaware of any CSAM present in LAION-5B, while also admitting "he did not review the data in great depth."
Coincidentally or not – the SIO study isn't mentioned – LAION chose yesterday to introduce plans for "regular maintenance procedures," beginning immediately, to remove "links in LAION datasets that still point to suspicious, potentially unlawful content on public internet."
"LAION has a zero tolerance policy for illegal content," the company said. "The public datasets will be temporarily taken down, to return back after update filtering." LAION plans to return its datasets to the public in the second half of January. ®
Updated to add
A spokesperson for Stability AI declined to clarify whether or not the upstart knew of the problematic content in LAION-5B, and instead said its own Stable Diffusion series was trained on a portion of the dataset's images – though we're not told whether that portion had CSAM in it or not.
"Stability AI models were trained on a filtered subset of that dataset," the rep said. "In addition, we subsequently fine-tuned these models to mitigate residual behaviors."
The spokesperson also said it places filters on input prompts and output images to ideally catch and prevent attempts to make unlawful content. "We are committed to preventing the misuse of AI and prohibit the use of our image models and services for unlawful activity, including attempts to edit or create CSAM," they told The Register.
Finally, Stability AI stressed to us that the SIO studied version 1.5 of Stable Diffusion, which the startup did not release. It said it did not agree with the decision by collaborator RunwayML to release that version of the LAION-5B-trained model.