markatlarge
Joined 1 year ago
Joined 1 year ago
They’re also running AI-based classifiers on Drive content, and that second layer is far more opaque and far more prone to false positives.
That’s how you get situations like mine: ~700 problematic images in a ~700k-image dataset triggered Google to delete 130,000+ completely unrelated files and shut down my entire developer ecosystem. Hash-matching is predictable.
AI classification is not. And Google’s hybrid pipeline: isn’t independently vetted isn’t externally audited isn’t reproducible
has no recourse when it’s wrong
In practice, it’s a black box that can erase an innocent researcher or indie dev overnight. I wrote about this after experiencing it firsthand — how poisoned datasets + opaque AI detection create “weaponized false positives”: https://medium.com/@russoatlarge_93541/weaponized-false-posi...
I agree with the point above: if open, developer-accessible perceptual hashing tools existed — even via bloom filters or ZK membership proofs — this entire class of collateral damage wouldn’t happen.
Instead, Big Tech keeps the detection tools proprietary while outsourcing the liability to everyone else. If their systems are wrong, we pay the cost — not them.
The dataset had been online for six years. In my appeal I told Google exactly where the data came from — they ignored it. I was the one who reported it to C3P, and that’s why it finally came down. Even after Google flagged my Drive, the dataset stayed up for another two months.
So this idea that Google “did a good thing” and 404 somehow did something wrong is just absurd.
Google is abusing its monopoly in all kinds of ways, including quietly wiping out independent developers: https://medium.com/@russoatlarge_93541/déjà-vu-googles-using...
Your dataset wasn’t the problem. The real problem is that independent developers have zero access to the tools needed to detect CSAM, while Big Tech keeps those capabilities to itself.
Meanwhile, Google and other giants openly use massive datasets like LAION-5B — which also contained CSAM — without facing any consequences at all. Google even used early LAION data to train one of its own models. Nobody bans Google. But when I touched NudeNet for legitimate testing, Google deleted 130,000+ files from my account, even though only ~700 images out of ~700,000 were actually problematic. That’s not safety — that’s a detection system wildly over firing with no independent oversight and no accountability.
Big Tech designed a world where they alone have the scanning tools and the immunity when those tools fail. Everyone else gets punished for their mistakes. So yes — your dataset has done good. ANY data set is subject to this. There needs to be tools and process for all.
But let’s be honest about where the harm came from: a system rigged so only Big Tech can safely build or host datasets, while indie developers get wiped out by the exact same automated systems Big Tech exempts itself from.
A scanning system will never be perfect. But there is a better approach: what the FTC now requires Pornhub to do. Before an image is uploaded, the platform scans it; if it’s flagged as CSAM, it simply never enters the system. Platforms can set a low confidence threshold and block the upload entirely. If that creates too many false positives, you add an appeals process.
The key difference here is that upload-scanning stops distribution before it starts.
What Google is doing is scanning private cloud storage after upload and then destroying accounts when their AI misfires. That doesn’t prevent distribution — it just creates collateral damage.
It also floods NCMEC with automated false reports. Millions of photos get flagged, but only a tiny fraction lead to actual prosecutions. The system as it exists today isn’t working for platforms, law enforcement, or innocent users caught in the blast radius.