if we assume our initial implementation to be flawed in a way that destroys alignment, why wouldn’t it also be flawed in a way that destroys corrigibility?
I think the people most interested in corrigibility are imagining a situation where we know what we’re doing with corrigibility (e.g. we have some grab-bag of simple properties we want satisfied), but don’t even know what we want from alignment, and then they imagine building an unaligned slightly-sub-human AGI and poking at it while we “figure out alignment.”
Maybe this is a strawman, because the thing I’m describing doesn’t make strategic sense, but I think it does have some model of why we might end up with something unaligned but corrigible (for at least a short period).
The concept of corrigibility was introduced by MIRI, and I don’t think that’s their motivation? On my model of MIRI’s model, we won’t have time to poke at a slightly subhuman AI, we need to have at least a fairly good notion of what to do with a superhuman AI upfront. Maybe what you meant is “we won’t know how to construct perfect-utopia-AI, so we will just construct a prevent-unaligned-AIs-AI and run it so that we can figure out perfect-utopia-AI in our leisure”. Which, sure, but I don’t see what it has to do with corrigibility.
Corrigibility is neither necessary nor sufficient for safety. It’s not strictly necessary because in theory an AI can resist modifications in some scenarios while always doing the right thing (although in practice resisting modifications is an enormous red flag), and it’s not sufficient since an AI can be “corrigible” but cause catastrophic harm before someone notices and fixes it.
What we’re supposed to gain from corrigibility is having some margin of error around alignment, in which case we can decompose alignment as corrigibility + approximate alignment. But it is underspecified if we don’t say along which dimensions or how big the margin is. If it’s infinite margin along all dimensions then corrigibility and alignment are just isomorphic and there’s no reason to talk about the former.
I think the people most interested in corrigibility are imagining a situation where we know what we’re doing with corrigibility (e.g. we have some grab-bag of simple properties we want satisfied), but don’t even know what we want from alignment, and then they imagine building an unaligned slightly-sub-human AGI and poking at it while we “figure out alignment.”
Maybe this is a strawman, because the thing I’m describing doesn’t make strategic sense, but I think it does have some model of why we might end up with something unaligned but corrigible (for at least a short period).
The concept of corrigibility was introduced by MIRI, and I don’t think that’s their motivation? On my model of MIRI’s model, we won’t have time to poke at a slightly subhuman AI, we need to have at least a fairly good notion of what to do with a superhuman AI upfront. Maybe what you meant is “we won’t know how to construct perfect-utopia-AI, so we will just construct a prevent-unaligned-AIs-AI and run it so that we can figure out perfect-utopia-AI in our leisure”. Which, sure, but I don’t see what it has to do with corrigibility.
Corrigibility is neither necessary nor sufficient for safety. It’s not strictly necessary because in theory an AI can resist modifications in some scenarios while always doing the right thing (although in practice resisting modifications is an enormous red flag), and it’s not sufficient since an AI can be “corrigible” but cause catastrophic harm before someone notices and fixes it.
What we’re supposed to gain from corrigibility is having some margin of error around alignment, in which case we can decompose alignment as corrigibility + approximate alignment. But it is underspecified if we don’t say along which dimensions or how big the margin is. If it’s infinite margin along all dimensions then corrigibility and alignment are just isomorphic and there’s no reason to talk about the former.