brianeyci wrote:Starglider wrote:This is a significant motivation for myself and many people I know to devote everything we can to working on (very) high-risk high-reward technologies that could avoid the whole mess, if we can develop them in time.
But are you really a scientist?

I'm primarily an engineer. Artificial intelligence research is comparable to rocketry, in that it does involve a lot of maths and (cognitive) science, and there are lots of trials and carefully instrumented prototypes that are somewhat like experiments (sometimes you try and isolate variables and focus on subcomponents, sometimes it's just an all-up integration test). But it's still basically engineering, in that the objective is to produce a system that has certain capabilities, rather than an attempt to find out something about how the universe works.
The people I personally know who are actually doing
useful work in nanotechnology, biotechnology and brain-computer interfacing are split roughly 50/50 between taking an engineering approach (focus on building stuff that works) and a scientific approach (make discoveries about structures and laws, publish them - as a direct continuation of preexisting chemistry and biology). That said the distinction is frequently an academic one (no pun intended, honest) and a very strong background in the relevant areas of science is (of course) essential regardless of the exact approach.
I would caution about letting this idea get to your head. The world will always need weed wackers, and Mike has said before about a lot of science grads wanting "glamour work" when in reality very few get there.
What I would like to do is irrelevant. The only question is whether there is a nontrivial chance of me making a useful contribution, and as it happens there is. That said to have a chance of making significant progress you pretty much have to work on it with obsessive fervor, which would be hard if one didn't enjoy it, so unsurprisingly I and most of the other people I know in these fields do enjoy them.
A lot of sciencey people are looking forward to the "death" of the "marketing" and "no skill" types, but when the depression comes they'll be very little money to go around for research that will take decades and everything will be devoted to securing the status quo and using proven technologies.
They're just being idiotic, or at least amusing naive.
In other words, I don't see the depression being good for academic or science types at all.
That was my point. A massive recession is bad news because it makes funding/staff/resources much harder to find. But this really has no impact on strategy, other than maybe some contingency planning, because we're already proceeding as fast as possible. If I was optimising my personal welfare instead of maximising the chance of contributing to a vital field, I would make different decisions.