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Re:How Meta trains large language models at scale by actionfromafar on Thursday June 13, 2024 @03:53AM (#40667079)
For a convenient definition of PII. Isn’t everything a user does in aggregate PII?
Re:How Meta trains large language models at scale by robertlagrant on Thursday June 13, 2024 @05:10AM (#40667492)
I don't think it's PII. If you had someone's movements, you could go and spy on them, find out who they were (i.e. their PII) and then link that back and say "I now know this identified person's movements". I don't think the movements themselves are PII.

Things that aren't PII aren't "convenient" definitions. Doesn't mean everything that isn't PII is fine to share. It's like saying a kidnapping isn't a murder. That's not a convenient definition of murder; it's just a different thing. We shouldn't start talking like witch hunters as soon as we encounter a situation that we haven't memorised a reasonable response to. We should be able to respond reasonably to new situations.

Re:How Meta trains large language models at scale by KaiserPro on Thursday June 13, 2024 @05:32AM (#40667604)
PII is pretty intuitive to define.

Obvious examples: data that easily identifies a person (Photo, name, number, UUID, etc)

Thats trivial to block. Where it gets harder is stuff that on it's own isn't PII, but combined with another source, would be

For example, aggregating public comments on a celeb's post. (ie stripping out usernames and likes and assigning a new UUID to each person.) For a single post, thats good enough. You're very unlikley to be able to identify a single person.

But over multiple posts, thats where it gets tricky.

As with large companies, the process for getting permission to use that kind of data is righty difficult, so it often doesn't get used like that.