(I agree that building smarter humans is a potentially workable point of intervention. This needs a champion to at least outline the argument, but actually making this happen will be much harder.)
It seems fairly clear to me that we will have the ability to "build smarter humans" within the next few decades, just because there are so many different possible research paths that could get us to that goal, all of which look promising.
There's starting to be some good research done right now on which genes correlate with intelligence. It looks like a very complicated subject, with thousands of genes contributing; nonetheless, =that would be enough to make it possible to do pre-implantation genetic screening to select "smarter" babies with current day technology, and it doesn't put us that far from actually genetically engineering fertilized eggs before implantation, or possibly even doing genetic therapies to adults (although, of course, that's inherently dodgier, and is likely to have a smaller effect).
Other likely paths to IA include:
-We're making a lot of progress on brain-computer interfaces right now, of all types.
-Brain stimulation also seems to have a lot of potential; it was already shown to improve people's ability to learn math in school in published research.
-Nootropic drugs also may some potential, although we aren't really throwing a lot of research in that direction right now. It is worth mentioning, though, that one possible outcome to that research on genes correlated with intelligence might be to figure out what proteins those genes code for and figure out drugs that have the same effect.
-Looking at the more cybernetic side, a scientist has recently managed to create an implantable chip that could connect with the brain of a rat and both store memories and give them back to the mouse directly, basically an artificial hippocampus. http://www.technologyreview.com/featuredstory/513681/memory-implants/
-The sudden focus on brain research and modeling in the US and the UK is also likely to have significant impacts
-There's other, more futuristic possible technologies here as well (nanotech, computer exocortex, ect). Not as likely to happen in the time frame we're talking about, though.
Anyway, unless GAI comes much sooner then I expect it to, I would expect that some of the things on that list are likely to happen before GAI. Many of them we're already quite close to, and there's enough different paths to get to enhanced human intelligence that I put a low probability on all of them being dead ends. I think there's a very good chance that we'll develop some kind of way to increase human intelligence first, before any kind of true GAI becomes possible, especially if we put more effort into research in that direction.
The real question, I think, is how much of intelligence boost any of that that going to give us, and if that's going to be enough to make FAI problems easier to solve, and I'm not sure if that's answerable at this point.
I put "Friendliness" in quotes in the title, because I think what we really want, and what MIRI seems to be working towards, is closer to "optimality": create an AI that minimizes the expected amount of astronomical waste. In what follows I will continue to use "Friendly AI" to denote such an AI since that's the established convention.
I've often stated my objections MIRI's plan to build an FAI directly (instead of after human intelligence has been substantially enhanced). But it's not because, as some have suggested while criticizing MIRI's FAI work, that we can't foresee what problems need to be solved. I think it's because we can largely foresee what kinds of problems need to be solved to build an FAI, but they all look superhumanly difficult, either due to their inherent difficulty, or the lack of opportunity for "trial and error", or both.
When people say they don't know what problems need to be solved, they may be mostly talking about "AI safety" rather than "Friendly AI". If you think in terms of "AI safety" (i.e., making sure some particular AI doesn't cause a disaster) then that does looks like a problem that depends on what kind of AI people will build. "Friendly AI" on the other hand is really a very different problem, where we're trying to figure out what kind of AI to build in order to minimize astronomical waste. I suspect this may explain the apparent disagreement, but I'm not sure. I'm hoping that explaining my own position more clearly will help figure out whether there is a real disagreement, and what's causing it.
The basic issue I see is that there is a large number of serious philosophical problems facing an AI that is meant to take over the universe in order to minimize astronomical waste. The AI needs a full solution to moral philosophy to know which configurations of particles/fields (or perhaps which dynamical processes) are most valuable and which are not. Moral philosophy in turn seems to have dependencies on the philosophy of mind, consciousness, metaphysics, aesthetics, and other areas. The FAI also needs solutions to many problems in decision theory, epistemology, and the philosophy of mathematics, in order to not be stuck with making wrong or suboptimal decisions for eternity. These essentially cover all the major areas of philosophy.
For an FAI builder, there are three ways to deal with the presence of these open philosophical problems, as far as I can see. (There may be other ways for the future to turns out well without the AI builders making any special effort, for example if being philosophical is just a natural attractor for any superintelligence, but I don't see any way to be confident of this ahead of time.) I'll name them for convenient reference, but keep in mind that an actual design may use a mixture of approaches.
The problem with Normative AI, besides the obvious inherent difficulty (as evidenced by the slow progress of human philosophers after decades, sometimes centuries of work), is that it requires us to anticipate all of the philosophical problems the AI might encounter in the future, from now until the end of the universe. We can certainly foresee some of these, like the problems associated with agents being copyable, or the AI radically changing its ontology of the world, but what might we be missing?
Black-Box Metaphilosophical AI is also risky, because it's hard to test/debug something that you don't understand. Besides that general concern, designs in this category (such as Paul Christiano's take on indirect normativity) seem to require that the AI achieve superhuman levels of optimizing power before being able to solve its philosophical problems, which seems to mean that a) there's no way to test them in a safe manner, and b) it's unclear why such an AI won't cause disaster in the time period before it achieves philosophical competence.
White-Box Metaphilosophical AI may be the most promising approach. There is no strong empirical evidence that solving metaphilosophy is superhumanly difficult, simply because not many people have attempted to solve it. But I don't think that a reasonable prior combined with what evidence we do have (i.e., absence of visible progress or clear hints as to how to proceed) gives much hope for optimism either.
To recap, I think we can largely already see what kinds of problems must be solved in order to build a superintelligent AI that will minimize astronomical waste while colonizing the universe, and it looks like they probably can't be solved correctly with high confidence until humans become significantly smarter than we are now. I think I understand why some people disagree with me (e.g., Eliezer thinks these problems just aren't that hard, relative to his abilities), but I'm not sure why some others say that we don't yet know what the problems will be.