Thanks for posting this. Some things to add to my reading list.
If you consider this "(potentially) useful training for making progress on Friendly AI", then do you expect that a person who has worked through this material will have a good sense of whether they are qualified to actually try to make progress on FAI (or will be evaluable for that by someone with more experience working on FAI)? I want to do as much as I can to contribute to FAI, whether directly (by working on the actual problems) or indirectly (e.g. getting rich and donating a lot to SIAI), whichever I end up being most efficient at. Right now I'm not efficient at much of anything, because of some severe issues with mental energy that I'm only now starting to possibly resolve after several years, but once I am more competent at life in general, I want to at least investigate the possibility that I could be directly useful to FAI research. (I'm not a savant or a mutant supergenius, but I am at least a normal genius.) If, at that point, I can get through all of this math successfully, will that be an indication that I should look further?
My best guess at productive subgoal for FAI is development of decision theory along the lines given in the last post, in order to better understand decision-making and the impossible problem in particular (how to define preference given an arbitrary agent's program; what is a notion of preference that is general enough for human preference to be an instance).
About a year ago I was still at the "rusty technical background" stage, and my attempts to think about decision theory were not quite adequate. Studying mathematics helped significantly by a...
This post enumerates texts that I consider (potentially) useful training for making progress on Friendly AI/decision theory/metaethics.
Rationality and Friendly AI
Eliezer Yudkowsky's sequences and this blog can provide solid introduction to the problem statement of Friendly AI, giving concepts useful for understanding motivation for the problem, and disarming endless failure modes that people often fall into when trying to consider the problem.
For a shorter introduction, see
Decision theory
The following book introduces an approach to decision theory that seems to be closer to what's needed for FAI than the traditional treatments in philosophy or game theory:
Another (more technical) treatment of decision theory from the same cluster of ideas:
Following posts on Less Wrong present ideas relevant to this development of decision theory:
Mathematics
The most relevant tool for thinking about FAI seems to be mathematics, where it teaches to work with precise ideas (in particular, mathematical logic). Starting from a rusty technical background, the following reading list is one way to start:
[Edit Nov 2011: I no longer endorse scope/emphasis, gaps between entries, and some specific entries on this list.]