> a time-to-unlearn kind of an acceptable agreement
Why put the burden to end users? I think the technology should allow for unlearning and even "never learn about me in any future models and derivative models".
Why put the burden to end users? I think the technology should allow for unlearning and even "never learn about me in any future models and derivative models".
That’s not even a guarantee. A model can hallucinate information about anyone, and by sheer luck some of those hallucinations will be correct. And as a consequence of forging (see section 2.2.1) you’d never be able to prove whether the data was in the training set or not.
The law cuts off at some point, and declares it 100%.
A company is liable even if they have accidentally retained / failed to delete personal information. That's why we have a lot of standards and compliance regulation to ensure a bare minimum of practices and checks are performed. There is also the cyber resilience act coming up.
If your tool is used by/for humans, you need beyond 100% certitude exactly what happens with their data and how it can be deleted and updated.
Google can't even get 100% certainty that they eg deleted a photo you uploaded. No AI involved. They can get an impressive number of 9s in their 99.9..%, but never 100%.
So this complaint when taken to the absolute like you want to take it, says nothing about Machine Learning at all. It's far too general.
It doesn’t have a 1:1 mapping of each bit of information it’s been trained with, but you can very much extract a subset of that data. Which is why it’s easy to get DallE to recreate the Mona Lisa, variations on that image show up repeatedly in its training courpus.