More like "A developer accidentally uploaded child porn to his Google Drive account and Google banned him for it".

Back when the first moat creation gambit for AI failed (that they were creating SkyNet so the government needs to block anyone else from working on SkyNet since only OpenAI can be trusted to control it not just any rando) they moved onto the safety angle with the same idea. I recall seeing an infographic that all the major players were signed onto some kind of safety pledge, Meta, OpenAI, Microsoft, etc. Basically they didn't want anyone else training on the whole world's data because only they could be trusted to not do nefarious things with it. The infographic had a statement about not training on CSAM and revenge porn and the like but the corpospeak it was worded in made it sound like they were promising not to do it anymore, not that they never did.

I've tried to find this graphic against several times over the years but it's either been scrubbed from the internet or I just can't remember enough details to find it. Amusingly, it only just occurred to me that maybe I should ask ChatGPT to help me find it.

As a small point of order, they did not get banned for "finding CSAM" like the outrage- and clickbait title claims. They got banned for uploading child porn to Google Drive. They did not find it, and them later reporting the data set to an appropriate organization is not why they got banned.

This raises an interesting point. Do you need to train models using CSAM so that the model can self-enforce restrictions on CSAM? If so, I wonder what moral/ethical questions this brings up.

Just a few days ago I was doing some low paid (well, not so low) Ai classification task - akin to mechanical turk ones - for a very big company and was - involuntarily, since I guess they don't review them before showing - shown an ai image by the platform depicting a naked man and naked kid. though it was more barbie like than anything else. I didn't really enjoy the view tbh, contacted them but got no answer back

[delayed]