A sex offender convicted of making more than 1,000 indecent images of children has been banned from using any “AI creating tools” for the next five years in the first known case of its kind.
Anthony Dover, 48, was ordered by a UK court “not to use, visit or access” artificial intelligence generation tools without the prior permission of police as a condition of a sexual harm prevention order imposed in February.
The ban prohibits him from using tools such as text-to-image generators, which can make lifelike pictures based on a written command, and “nudifying” websites used to make explicit “deepfakes”.
Dover, who was given a community order and £200 fine, has also been explicitly ordered not to use Stable Diffusion software, which has reportedly been exploited by paedophiles to create hyper-realistic child sexual abuse material, according to records from a sentencing hearing at Poole magistrates court.
Where does the training data come from to create indecent images of children?
It doesn’t need csam data for training, it just needs to know what a boob looks like, and what a child looks like. I run some sdxl-based models at home and I’ve observed it can be difficult to avoid more often than you’d think. There are keywords in porn that blend the lines across datasets (“teen”, “petite”, “young”, “small” etc). The word “girl” in particular I’ve found that if you add that to basically any porn prompt gives you a small chance of inadvertently creating the undesirable. You have to be really careful and use words like “woman”, “adult”, etc instead to convince your image model not to make things that look like children. If you’ve ever wondered why internet-based porn generators are on super heavy guardrails, this is why.
Thanks for the reply, it’s given me a good idea of what’s most likely happening :)
It’s a shame that the rest of the thread went to shit, but unfortunately it’s an emotional topic, and brings out emotional responses
I’m not going to say that csam in training sets isn’t a problem. However, even if you remove it, the model remains largely the same, and its capabilities remain functionally identical.
It is true, a 10 year old naked woman is just a 30 year old naked woman scaled down by 40%. /s
No buddy, there isn’t some vector of “this is the distance between kid and adult” that a model can apply to generate what a hypothetical child looks like. The base model was almost certainly trained on more than just anatomical drawings from Wikipedia - it ate some csam.
If you’ve seen stuff about “Hitler - Germany + Italy = Mousillini” for models where that’s true (which is not universal) it takes an awful lot of training data to establish and strengthen those vectors. Unless the generated images were comically inaccurate then a lot of training went into this too.
Right, and the google image ai gobbled up a bunch of images of black george washington, right? They must have been in the data set, there’s no way to blend a vector from one value to another, like you said. That would be madness. Nope, must have been copious amounts of asian nazis in the training set, since the model is incapable of blending concepts.
The whole point of diffusion models is that you can generate new concepts using training data. Models trained on any nsfw images can combine those concepts with any of its non-nsfw concepts. Of course, that’s not to say there isn’t CSAM in any training data, because there objectively has been in the past, but there doesn’t need to be any to generate it.
Ai is able to fill in the last field in a table like “Old / young” vs “Clothed / naked” when given three of the four fields.
Csam is in the training data. From a few months ago
