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Inside the magic box

July 29, 2011

I’d like to start this point with a quotation from this article. I’m not quoting it because I endorse it; it’s rather hysterical and mostly wrongheaded. But about halfway through, it makes an interesting point regarding computers:

And yet, as soon as the children got to use these marvels of science, did they use them scientifically? No. They played Dungeons and Dragons; they entered a world of knights and wizards, and lost themselves in the simulacrum of a lost age. That is to say, they recognized it instantly not as science but as magic, and—if anything—pre-modern, and they were right to do so. For electronic technology is fundamentally different from the mechanical and electrical technology that preceded it. When I was a boy, the car was the limit of our technological desires, and every young man, or nearly, thought nothing of pulling the manifold, changing a head gasket, or fiddling with the carburetor. Of course, we never knew as much as we pretended to know, but at least in principle we could have known the whole thing, and known it to any desired degree of precision.

But that is not so with computers, for no matter how many doctorates one holds in computer science, at some point the system disappears into a world of magic. Thus the hardware engineer finds operating systems bewildering, while the systems programmer is mystified by telecommunications, and the communications engineer can’t help you with applications. Expertise is one area is matched by ignorance in other areas, so that to each practitioner of the computer arts, at some point the whole thing fades into a world of wizardry.

I have no idea whether the author (one John Medaille) had Arthur C. Clarke in mind, but I can’t read the above without thinking of Clarke’s Third Law:

Any sufficiently advanced technology is indistinguishable from magic.

What’s interesting about Medaille’s statement is that it casts “advanced” as an absolute. The way Clarke’s third law is usually taken, it means that for a person from a culture at, say, technology level 5, a piece of technology of level 6 may be comprehensible, but one of level 10 will seem like magic. A stone-age tribesman can understand a bow and arrow, but a gun is a weapon of the gods; I, on the other hand, have a pretty good understanding of how a gun works, and with enough trial and error could probably construct a crude but working firearm. Medaille is saying something different–that when technology advances past a certain point, becomes too complex, it becomes impossible for us to wrap our minds around it, not because we’re not used to it, but because it’s too much. And that makes it magic, and thus, he implies, unholy, evil.

I don’t particularly agree with the final few links in that chain, but to deny that at a certain point technology becomes too complex for us to comprehend, no matter how immersed in it we are, seems to require a level of commitment to transhumanist ideas that I’m not really comfortable with. So if it’s true that we live in a world where technology has progressed beyond our ability to intuitively understand it, what can we do about it, other than go back to the stone age (or the middle ages, like it sometimes seems distributists want) or continue under the assumption that technological progress is good for its own sake?

At this point I’m going to reach (some might say over-reach) for a third quotation from a third writer I don’t have any particular affection for, J.K. Rowling, that also suggests an interesting connection between magic and technology:

Never trust anything that can think for itself if you can’t see where it keeps its brain.

This is said by Mr. Weasley to Ginny regarding Tom Riddle’s secret diary in HPatCoS, but if computers are magic, we can apply this maxim to them as well–perhaps we shouldn’t try to get rid of computers entirely, and perhaps we can’t fully understand them, but still, we ought to be able to see where they keep their brains. This train of thought leads us, I think, to the ideals of Free software. We ought to be able to see our computers’ source code.

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4 Comments leave one →
  1. July 29, 2011 10:48 am

    Reminds me of when we were talking about black box technologies. Some people have a desire to stop technological progress at a certain level, and they have some good reasons, but the line they draw seems kind of arbitrary until you realize they just don’t like black boxes.

    And yeah, computers are different because they’re black boxes in principle, not just because people are too lazy to learn about them.

  2. July 29, 2011 12:40 pm

    It was probably when we were talking about Dan Simmons’ Hyperion, since (mild spoiler) it makes a big deal out of how computers are black boxes. (I’ve been meaning to write something about Hyperion for a while but haven’t gotten around to it…)

    Yeah, it’s interesting how neo-luddites (which distributists often seem to be) don’t talk about the anti-black-boxes reason as often as e.g. the negative social consequences of everyone not owning their own farm… especially since I actually find the anti-black-boxes reason more persuasive in a lot of ways.

  3. David permalink
    August 27, 2011 12:02 am

    I realize this is an old discussion, but I bumped into it only tonight, and I feel the need to respond. I disagree with John’s (and your) point: I actually think that the computer itself is fairly comprehensible, with or without many Ph.D.’s. There are levels and patterns in those levels that make them fairly easy to understand. See, for a very good explanation, Tanenbaum’s “Structured Computer Organization”.

    The algorithms (a subtle but in my mind very important distinction) that run on a computer can be extremely complex, but almost always because the mathematics behind them is so complex (a nod to another of your recent posts). However, in my experience, a basic understanding of the way even the most complex algorithms work can be obtained if viewed in the right context (e.g. with the right schematic). In this case one doesn’t get an understanding to the level of being able to program an algorithm, but would be able to see in some general sense why it works, and even why it would go wrong in certain circumstances. It seems that would be equivalent to John’s picture of the teenage boy “pulling the manifold”.

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