Drexler on Engineering

Most of my economics colleagues know little about engineering. Yet much of what they actually want to do in the world, i.e., get people to adopt new better institutions, is better seen as engineering than as science. To help educate them, I quote from Eric Drexler in his new book, explaining the difference between science and engineering:

The essence of science is inquiry; the essence of engineering is design. Scientific inquiry expands the scope of human perception and understanding; engineering design expands the scope of human plans and results. …

•     Scientists seek unique, correct theories, and if several theories seem plausible, all but one must be wrong, while engineers seek options for working designs, and if several options will work, success is assured.
•     Scientists seek theories that apply across the widest possible range (the Standard Model applies to everything), while engineers seek concepts well-suited to particular domains (liquid-cooled nozzles for engines in liquid-fueled rockets).
•     Scientists seek theories that make precise, hence brittle predictions (like Newton’s), while engineers seek designs that provide a robust margin of safety.
•     In science a single failed prediction can disprove a theory, no matter how many previous tests it has passed, while in engineering one successful design can validate a concept, no matter how many previous versions have failed. ..

Simple systems can behave in ways beyond the reach of predictive calculation. This is true even in classical physics. …. Engineers, however, can constrain and master this sort of unpredictability. A pipe carrying turbulent water is unpredictable inside (despite being like a shielded box), yet can deliver water reliably through a faucet downstream. The details of this turbulent flow are beyond prediction, yet everything about the flow is bounded in magnitude, and in a robust engineering design the unpredictable details won’t matter.  …

The reason that aircraft seldom fall from the sky with a broken wing isn’t that anyone has perfect knowledge of dislocation dynamics and high-cycle fatigue in dispersion-hardened aluminum, nor because of perfect design calculations, nor because of perfection of any other kind. Instead, the reason that wings remain intact is that engineers apply conservative design, specifying structures that will survive even unlikely events, taking account of expected flaws in high-quality components, crack growth in aluminum under high-cycle fatigue, and known inaccuracies in the design calculations themselves. This design discipline provides safety margins, and safety margins explain why disasters are rare. …

The key to designing and managing complexity is to work with design components of a particular kind— components that are complex, yet can be understood and described in a simple way from the outside. … Exotic effects that are hard to discover or measure will almost certainly be easy to avoid or ignore. … Exotic effects that can be discovered and measured can sometimes be exploited for practical purposes. …

When faced with imprecise knowledge, a scientist will be inclined to improve it, yet an engineer will routinely accept it. Might predictions be wrong by as much as 10 percent, and for poorly understood reasons? The reasons may pose a difficult scientific puzzle, yet an engineer might see no problem at all. Add a 50 percent margin of safety, and move on.

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  • I’d like to see some evidence that your economics colleagues lack this kind of far-mode understanding of engineering. You seem to position yourself within the economics community as the one with engineering knowledge, but you have never shown how your near-mode understanding of engineering translates into a distinctive far-mode view.

  • Daniel Carrier

    “In science a single failed prediction can disprove a theory”

    In theory, yes. In practice, a single failed prediction is more likely to show lax experimental standards.

    • Philip Goetz

      Or some other misunderstanding. I was going to make the same point. It is the usual state of affairs in biology to have many studies on the same topic, and “it has been proven” means something like “four out of six studies concluded” (or, distressingly often, “four out of the six studies that I refer to in this paper, out of twenty studies on this topic, concluded).

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  • Gregory Lemieux

    This is a bit of a side note, but one of the other reasons complex engineered systems do not fail is maintenance. This is something that we engineers take into account and mandate in our designs. It is one of the ways we bound the problem. Perhaps the idea of maintenance can be translated to the sphere of problems that economists seek to affect.

    • IMASBA

      Realistically speaking any socio-economic system needs maintenance because no system is 100% waterproof (for example laws that reference “rational persons”) so corruption and perversion are always possible and must be fought continuously, just look at how people managed to turn the ideas of the world’s first hippee into a dogmatic, hateful and bigoted institution.

  • Philip Goetz

    “When faced with imprecise knowledge, a scientist will be inclined to improve it, yet an engineer will routinely accept it.”

    I have always had exactly the opposite problem in my jobs. Mathematically-inclined scientists such as computer scientists want to use imprecise knowledge. Non-scientists and biologists forbid them from using imprecise knowledge, because they use engineering metaphors as their guide to how knowledge must be accumulated. They think that annotating a genome is like building a space shuttle, where one builds small components, tests them thoroughly in isolation, and then when absolutely sure that component works, goes on and builds components built out of those small components, and so on until they have a space shuttle. Whereas the mathematician understands that doing that throws out 99% of the data by the time you reach your conclusion.

    • I think computer scientists count as engineers rather than scientists.

      Non-scientists and biologists forbid them from using imprecise knowledge, because they use engineering metaphors as their guide to how knowledge must be accumulated.

      That’s what Hanson does, isn’t it? Isn’t “small clues” basically an engineering metaphor? From a scientific standpoint, a small clue is unlikely to take you toward a true theory, but from an engineering standpoint, it can serve as the basis for useful adjustments.

      • Philip Goetz

        “I think computer scientists count as engineers rather than scientists.”

        As a computer scientist, I say, “AAARGH!”

        Computer science is science, not engineering. Computer programming and computer engineering are engineering. They are different fields. A computer programmer is not a computer scientist. Computer science basic research is a real thing, and like economics, maybe someday it would get funding, if more people realized that.

        Anyway, my point was that in my experience, it’s the mathematically-numerate scientists who are more comfortable with uncertainty. Engineers don’t accept uncertainty; they over-engineer enough to bring themselves back into the realm of certainty. So I think the way Drexler says it has it backwards.

      • I stand corrected on computer scientists.

        A tangent on your difference with Drexler: I’ve wondered what it means when I think an explanation applies but the direction is reversed. Prima facie, it seems strange, doesn’t it? One might think it would tend to discredit both sides. If you and Drexler agree that a conflict expresses the tension between scientific and engineering metaphors but disagree about which is which, doesn’t that tend to suggest you both are imagining an application that doesn’t exist? I mean, what explains why you and Drexler would agree that the wrong mindset is being applied but disagree about which one it is? The evidence can’t be very strong for either mindset being the cause.

        Maybe (hopefully) that’s wrong: you can see that a problem is due to one or the other opposed mindsets without being clear on which one. I don’t for the moment see how.

      • Philip Goetz

        I think Drexler (or Robin) is playing on a stereotype of science that is both false (of science done properly) and true (describes the conscious beliefs of many scientists).

      • Scientists, then, think of scientific practice in terms of engineering metaphors? Have any theory about why they’d do that?

      • Philip Goetz

        I think good scientists seek truth, good engineers seek solutions, and bad scientists and bad engineers seek certainty. Science has a bias towards certainty because of how papers are published, which in turn caters to the limited memory of humans. The right way to do science is to keep track of all the conditional probabilities, but that’s too hard for humans to do.

      • Alistair

        Totally agree.

        I’m a numerate systems analyst working with engineers, and they really are uncomfortable/pyschologically averse to uncertainty. They spend all their time designing-out miniscule risk in a way that massively over-engineers and wastes time and resources.

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