It might be worth noting that I often phrase questions as "how would we design an FAI to think about that" not because I want to build an FAI, but because I want the answer to some philosophical question for myself, and phrasing it in terms of FAI seems to be (1) an extremely productive way of framing the problem, and (2) generates interest among those who have good philosophy skills and are already interested in FAI.
ETA: Even if we don't build an FAI, eventually humanity might have god-like powers, and we'd need to solve those problems to figure out what we want to do.
According to Eliezer, making AI safe requires solving two problems:
1) Formalize a utility function whose fulfillment would constitute "good" to us. CEV is intended as a step toward that.
2) Invent a way to code an AI so that it's mathematically guaranteed not to change its goals after many cycles of self-improvement, negotiations etc. TDT is intended as a step toward that.
It is obvious to me that (2) must be solved, but I'm not sure about (1). The problem in (1) is that we're asked to formalize a whole lot of things that don't look like they should be necessary. If the AI is tasked with building a faster and more efficient airplane, does it really need to understand that humans don't like to be bored?
To put the question sharply, which of the following looks easier to formalize:
a) Please output a proof of the Riemann hypothesis, and please don't get out of your box along the way.
b) Please do whatever the CEV of humanity wants.
Note that I'm not asking if (a) is easy in absolute terms, only if it's easier than (b). If you disagree that (a) looks easier than (b), why?