Yeah, there’s a difference between being optimized to cope with true unexpected events, and being optimized to cope with a range of possible expected events.
For example, I wouldn’t benefit from being thrown into a fire, or having a ton of bricks dropped on me, or being devoured by a tiger, but I would benefit from having to cope with a range of temperatures or the need to move some unusually heavy objects, or the need to run.
My brain won’t be improved by an incomputable problem, but it will be improved by small changes to my routine and new solvable problems.
By definition you really can’t design a system that is robust to unknown unknowns.
Yeah, there’s a difference between being optimized to cope with true unexpected events, and being optimized to cope with a range of possible expected events.
For example, I wouldn’t benefit from being thrown into a fire, or having a ton of bricks dropped on me, or being devoured by a tiger, but I would benefit from having to cope with a range of temperatures or the need to move some unusually heavy objects, or the need to run.
My brain won’t be improved by an incomputable problem, but it will be improved by small changes to my routine and new solvable problems.
By definition you really can’t design a system that is robust to unknown unknowns.
I agree with this. It seems like it could be more interesting if we found a way to make it more precise, but I guess that was the point of this post.
You can design one that is provably maximally robust given your knowledge.