This intuition seems correct in typical human situations. Everything is highly optimized already with different competing considerations, so optimizing for X does indeed necessarily sacrifice the other things that are also optimized for. So if you relax the constraints for X, you get more of the other things, if you continue optimizing for them.
However, it does not follow from this that if you relax your constraint on X, and take a random world meeting at least the lower value of X, your world will be any better in the non-X ways. You need to actually be optimizing for the non-X things to expect to get them.
it does not follow from this that if you relax your constraint on X, and take a random world meeting at least the lower value of X, your world will be any better in the non-X ways
Thanks but I don’t see the relevance of the reversal test. The reversal test involves changing the value of a parameter but not the amount of optimization. And the reversal test shouldn’t apply to a parameter that is already optimized over unless the current optimization is wrong or circumstances on which the optimization depends are changing.
This intuition seems correct in typical human situations. Everything is highly optimized already with different competing considerations, so optimizing for X does indeed necessarily sacrifice the other things that are also optimized for. So if you relax the constraints for X, you get more of the other things, if you continue optimizing for them.
However, it does not follow from this that if you relax your constraint on X, and take a random world meeting at least the lower value of X, your world will be any better in the non-X ways. You need to actually be optimizing for the non-X things to expect to get them.
Great point!
Thanks but I don’t see the relevance of the reversal test. The reversal test involves changing the value of a parameter but not the amount of optimization. And the reversal test shouldn’t apply to a parameter that is already optimized over unless the current optimization is wrong or circumstances on which the optimization depends are changing.