> Now we're looking at (maybe) 11 years to develop a working rocket to go to an asteroid.

It's worse than that. There will be no deep-space journey to an asteroid. Instead, a near-Earth asteroid would be selected or a small asteroid will be moved to near-Earth orbit using unmanned robotic craft. The 'manned asteroid mission' will not go any further than the Apollo missions did. And it would not do anything other than just take some samples and bring them back to Earth. Little in-situ science, and definitely no in-situ resource extraction. It really raises the question of why we're sending up humans in the first place.

There _may_ be deep-space (i.e. anything outside of Earth orbit) missions in the 'future', but they would need big and complex manned spacecraft that have yet to emerge from the drawing board.

We're not going outside of Earth orbit any time soon, not if we're to rely on NASA.

It's currently being done in a way that makes in inseparable from the SLS rocket, an out-dated and over-budget project enabled by government inertia and congressional pork. Also, the Orion MPCV itself doesn't represent much of an upgrade over existing manned space capsules; if it's to go anywhere outside of Earth orbit it's going to need a much larger and more complex space habitat attachment: http://en.wikipedia.org/wiki/D... which has yet to be developed.

> Computers don't understand handwaving and "you know what I mean" -- yet (while mathematicians are very fond of it)

Yup.

> OTOH it's not so clear-cut in that computer programming is also communication between people

No. If all you wanted to do was tell someone how to, say, divide two numbers, you wouldn't tell them through a computer program. You'd tell them through English. Computer programs are always (except in very rare circumstances) ways of communicating with computers. That they can be written in a way to also be useful for other humans is secondary; you can also write French in a way that English-speaking people would find easier to understand.

Of course, there's pseudo-code, which IS actually intended for human communication, and it's an interesting case study since it 'borrows' from computer languages but has the same kind of ambiguities and nuances as human language. It's also interesting in that lots of high-level languages have been efforts to create 'executable pseudocode' i.e. pseudocode that removes imprecision in intent.

Any sort of ambiguity means there must be a method of resolving the ambiguity. This is true no matter if you're talking about human language, math, or programming. In language and math, the method of resolving ambiguity is context. That is, the person you're communicating the concepts with presumably knows enough about what you're talking about to be able to resolve the ambiguity.

Note that both math formulas and programs are pieces of communication, nothing more. Programs are a way of communicating intent to a computer. Mathematical notation is a way of communicating intent to another human being.

Being skilled in a subject is mostly how much you practice at it. I'm sure that if you put as much time into math as you did programming, your opinion wouldn't be the same. I'm a mathematician-turned programmer and I agree with the article.

One thing, though, is that programmers have a lot of tools to help them out. High-level languages like python, interactive development environments, debuggers, and of course being able to run the program and see how it behaves. All of these tools serve to hugely augment one's natural brain capacity (over, say, having to code everything in assembly). But mathematicians have no such tools yet. To be a mathematician, you have to juggle around numerous concepts in your head simultaneously and make sure they all work with each other. Studies have shown that one of the best predictors of mathematical ability is working memory, and it's not surprising why.

By the way, why don't mathematicians adopt tools that let them easily and automatically check that their work is correct? I think it's entirely a cultural issue, not a technological one. Computational tools for mathematics (like Coq and Agda) are still stuck in the 'assembly' period. They're hard to use, because there has never been a strong demand for them from the wider math community and so they never developed as well as computer languages did. And when the math community got involved in computer science, they tended to target more abstract stuff like proof systems and category theory, instead of just sticking to the basics and coming up with a proof checker that's as easy to use as python is (and there's absolutely no reason why such a thing couldn't be made). So I'd say mathematics is a good 5 decades behind computer science. But it has to catch up eventually.

Funding is a necessary, but not sufficient, condition for research to take place. It's only the first step.

Having a good supervisor is extremely important. The arrangement where your supervisor is a person who is knowledgable, up-to-date, and respected in their field, and draws on his years of experience to guide your through work and train you as a scientist, is the ideal on which the supervisor-student relationship is based on. A person like that more than deserves to have their name on the work you do while under their tutelage.

But going by what I've seen, such a relationship is, sadly, rare. A lot of students are victims of supervisors who either "don't care" or have been effectively outside their field of study for so long (with all the grant-writing) that they have simply no clue about research anymore. Your first experience seems to be the norm.

Because it's almost literally impossible for someone to actually put in all of the work required to publish hundreds of papers during their career. A paper might typically take six months of gruelling, full-time work. Instead of actually doing the work, what a lot of scientists do is they bring in a lot of students and act as project supervisors, as it says in the article: "Many of these prolific scientists are likely the heads of laboratories or research groups; they bring in funding, supervise research, and add their names to the numerous papers that result." In other words, they drop in for maybe half an hour every two weeks or so to get an 'update' (without really understanding anything), throw around some bs pieces of 'advice' (which everyone ignores) and then leave.

You bootstrap it by not trying to transfer all of this to space at once. Start with just a simple plan that takes small asteroids and brings them (or chunks of them) over to Earth orbit for processing. Stuff that's hard to build (like computers) are usually lightweight. Send them up from Earth in bulk.

But all of this is beside the point. That asteroid mining is difficult I completely concede. But how would sticking humans into the equations fix anything at all? Any gain in repair ability would be at the expense of a huge amount of additional complexity and risk in keeping the humans alive and functioning.

It's worth pointing out that all existing practical proposals for Mars colonization that I've seen involve sending hard-to-manufacture supplies (basically anything other than structural materials) to the colonies for at least a century afterwards. If that's what you're going to do then why not just cut humans out of the equation.

You hit the nail on the head. The problem isn't AI. The problem is that scaling it up to industrial levels is hard. And the absolute WORST way of solving that problem is making manned mining ships, raising the complexity, cost, and risk by 100x.

Why does it have to? Build them out of cheap, expendable, easily-replaceable parts. Which you can do, because the entire premise of asteroid mining is that it will make the cost of building and deploying space equipment dead cheap (otherwise why do it in the first place?)

Sure, but the problem is that once the coolness factor wears off, they stop doing it. It's not sustainable.

We don't? We already have AI that can autonomously land on other bodies and extract material. In fact we've had it for 4 decades. See: almost any planetary lander/rover ever. It seems the barrier to mining is more up-front cost and on-site materials processing than AI.

I'm a techno-optimist but I agree with you. The rate things are going, it isn't going to make much sense to have people living in space colonies. I can't think of any good reason to do it other than the coolness factor. Unfortunately a lot of people are emotionally invested in this idea and will fight logic tooth and nail to promote their fantasies.