[godelski]

I'm an AI researcher, here's my beliefs (it'll be clear in a second why I say belief and not claim objective facts)

1) you can't be sure it's gone. It's even questionable if data can be removed (longer discussion needed). These are compression machines, so the very act of training is compressing that information. The question really becomes how well that information is compressed or embedded into the model. On one hand, the models (typically) aren't invertible so the information is less likely to be compressed lodslessly. On the other hand, the models aren't invertible, so reversing them is probabilistic and they are harder to analyze in this sense.

2) as you may gather from 1) there's almost certainly more issues like this. There are many unknown unknowns waiting to be discovered. Personally this is why I'm very upset the field is so product focused and that a large portion regards theory as pointless. Theory does two things for us because it builds a deeper and more nuanced understanding. Theory advancing allows us to develop faster as we can iterate on paper rather than through experimentation. This allows us to better search the solution space and even understand our understanding. This also leads to better safety of models as it is necessary to understand them to understand where they fail and how to prevent those failures. Experimentation alone is incredibly naïve. It is like proving the correctness of your programs through testing (see the issues with TDD). Tests are great but they are bounds, not proofs. They can suggest safety, give you some level of confidence in safety, but they cannot guarantee it. We all know that the deeper understanding of your code the better tests you can write, and this is the same thing here. That theory is reducing your unknown unknowns and even before strong proofs are made we can get wider coverage in our testing.

I think we're so excited right now we're blinding ourselves. If we're cutting off or reducing fundamental research then we are killing the pipeline of development. Theory is the foundation that engineering sits on top of. But what worries me is that there's so many unknown unknowns and everyone is eagerly saying "we're just need 'good enough'" or "what's the minimum viable product". These are useful tools/questions but they have limits and it gets dangerous when putting out the minimum at scale