A well-designed goal hierarchy has an upper limit of complexity.

Why is that (other than the trivial "well-designed" == "upper limit of complexity")?

Even the best set of constraint heirachies do not share that benefit.

I don't understand this. Any given set of constraint hierarchies is given, it doesn't have a limit. Are you saying that if you want to construct a constraint set to satisfy some arbitrary criteria you can't guarantee an upper complexity limit? But that seems to be true for goals as well. We have to be careful about using words like "well-designed" or "arbitrary" here.

Constraint systems in the real world are based around the complexity of our moral and ethical systems

Not necessarily. I should make myself more clear: I am not trying to constrain an AI into being friendly, I'm trying to constrain it into being safe (that is, safer or "sufficiently safe" for certain values of "sufficiently").

Consider, for example, a constrain of "do not affect more that 10 atoms in an hour".

Worse, a sufficiently powerful self-optimizer will expand into situations that are outside of environments the human brain did not guess, or could not possibly fit into the modern human head

True, but insofar as we're talking about practical research and practical solutions, I'd take imperfect but existing safety measures over pie-in-the-sky theoretical assurances that may or may not get realized. If you think the Singularity is coming, you'd better do whatever you can even if it doesn't offer ironclad guarantees.

And it's an "AND" branch, not "OR". It seems to me you should be working both on making sure the goals are friendly AND on constraints to mitigate the consequences of... issues with CEV/friendliness.