1年前

A.I.’s un-learning problem: Researchers say it’s virtually impossible to make an A.I. model ‘forget’ the things it learns from private user data

finance.yahoo.com A.I.’s un-learning problem: Researchers say it’s virtually impossible to make an A.I. model ‘forget’ the things it learns from private user data

As it turns out, it’s impossible to remove a user’s data from a trained A.I. model. Deleting the model entirely is also difficult—and there’s little regulation to enforce either option.

A.I.’s un-learning problem: Researchers say it’s virtually impossible to make an A.I. model ‘forget’ the things it learns from private user data

I'm rather curious to see how the EU's privacy laws are going to handle this.

(Original article is from Fortune, but Yahoo Finance doesn't have a paywall)

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207 评论

Can't they remove the data from the training set and start over?
- They can, but the article is taking about removing data from a model that is already in production. Like if someone emails ChatGPT and says "hey, remove my data from this", good luck, because it might be a year before they can release a newly trained model with the data removed.
- Indeed they can, but training a model can take a month or more and cost many millions of dollars, so it's not trivial.
  
  What makes up the cost? Buying CPU cycles and storage? Just curious.
  
  Outside of the costs of hardware, its just power. Running these sorts of computations is getting more efficient, but the sheer amount of computation means that its gonna take a lot of electricity to run.
  
  The GPU cluster. The H100 GPUs are about $40,000 each and you need many.
  
  Interesting. Thanks.
  
  GPU cycles probably, but yeah. That makes up the bulk of the cost. The price of data is assuredly increasing as well, but that's slightly beside the issue.
  
  All of it. At that scale, you're paying for data access, network communication, layers of storage... Basically every single step of computation becomes a meaningful cost
  
  So the REAL issue is how much it costs to remove the info vs how much value the info has? Such as the average Joe's social security number vs a movie star's social security number vs the president's social security number.
  
  I might change 'value the info has' to 'liability it creates', but I think you're right about the cost/benefit situation. Since our laws have not kept up with technology, there are a lot of unanswered questions making it hard to analyze.
- Not really, no. None of the source material is actually stored inside the model's dataset, so once it's in, it's in. Because of the way they are designed, you can't point to a particular document and just delete that one thing. It's like unscrambling an egg.
  
  They can remove ALL the data and start over.
  
  exactly.
  removing one thing from a pile != removing the entire pile.
  b/c the original goal was to not disturb the rest of the pile
  
  If they can't remove individual pieces then they need to remove the whole pile, and rebuild the process in a way that does allow then to remove individual pieces.
  No, I don't care how much time and effort it costs. That is on them for abusing other people's data.
- Yes, but that's not easy... I can't remember exactly, but I think I saw an estimate that the compute time to train just one of the GPT models cost around $66 million. IDK whether that's total cost from scratch, or incremental cost to arrive at that model starting from an earlier model that was already built, but I do know that GPT is still to this day using that September 2021 cutoff which to me kind of implies that they're building progressively on top of already-assembled models and datasets (which makes sense, because to start from scratch without needing to would be insane).
  You could, technically, start from scratch and spend 2 more years and however many million dollars retraining a new model that doesn't have the private data you're trying to excise, but I think the point the article is making is that that's a pretty difficult approach and it seems right now like that's the only way.
  
  Un-robbing a bank also isn't easy, but that doesn't mean I'm able to just say "it too hard :c" and then walk off into the sunset with my looted gains.
- Yes. They can also reload a backup from before the data in question was added to the training data and retrain from that point. This is also what will need to be done if AI companies lose their copyright lawsuits.
  None of this is impossible. Its just expensive. And these are expenses that AI companies could have avoided if they picked their datasets more carefully.
  
  It's crazy that they aren't taking at least daily captures of the model nor having it record what information it processes.
  
  I would be shocked if they don't. It's pretty critical for any software development, AI or not, to retain the ability to roll back changes in the case any change breaks something.
- Information leaking is a thing. Some information is spread across multiple sources without actually being in any of those. If you remove something, the model can still infer the information.
  If macron asks for his name to be deleted, you can retrieve his political opinion by simply knowing the history of interactions of other people with the French government. I just need to tell the model that the person he has no direct information about is named macron, and he can profile him.
  Same with the search engine. The only difference is that the inference of missing information now is done by human brains. The model can substitute them

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