Tag Archives: Sci/tech

Engineering v. Design

Silicon Valley has always been obsessed with efficiency. But lately, it is also obsessed with beauty. In a place where engineers have reigned supreme, the new tech talent war is for designers. (more)

In those parts of the economy that are well modeled by the introductory economics textbook treatment of widgets – firms producing a thing with workers with increasing marginal costs in a somewhat competitive industry, such as durables, clothes, and cars – we’ve seen continuing, very substantial growth in real wages as measured by the purchasing power of things that our economy produces. The reason that real wages in aggregate have stagnated is that much of what people buy are things where there are issues of fundamental scarcity: energy, the land under the houses we buy, and goods and services that are produced in complicated, heavily public-sector-inflected ways. Medical care and educational services are examples of the latter category. (more; HT Tyler)

Many long-term trends over the last few centuries can be plausibly attributed to people getting richer, and thus wanting different things than poor people want. One interesting example: the decline of engineering relative to design.

All products and services have to negotiate between the two extremes of the raw physical world and complex human preferences. That is, products must deal with the physical world in order to give humans what they want. Engineers tend to focus on the physical world, trying to minimize the effects of key resource constraints, while designers tend to focus on how a product looks and feels to customers.

Because we have simple powerful general theories of how the world works, engineering can make use of a lot of math and computer modeling, and can often transfer inventions to very different products. In contrast, since humans are very complex and poorly understood, designers must instead develop intuitions by seeing many specific examples of good and bad design.

As we have become richer, we have become less concerned about raw physical constraints. When we have enough calories in our food, enough insulation in our clothes and walls, and enough mass moved fast enough in our transportation, we focus more on how exactly our food, clothes, etc. make us feel. This includes how we feel about how the product is abstractly described to us – marketing also gets more important as design gets more important.

Rich people also care more about product variety. When we can barely make any affordable car that functions, car design focuses on making one working car at sufficient scale to be cheap enough. Such as the Model T. But when we get better at cars, customers are willing to pay extra to get cars in more variety, to better match the self-image they want to project. So design and marketing come to matter more than simple engineering.

These trends have many implications. Since innovations that accumulate and transfer well are more easily found in engineering, our focus on design slows our rate of economic growth. Also, since local tastes vary, our focus on product variety that better adapts to local tastes gives us fewer gains from globalization. Finally, a focus on design weakens the connection between economic and military power. An economy that is better at making more varied products to make more customers feel good about themselves is less obviously better able to make weapons that kill. After all, engineering matters much more than design and marketing when it comes to weapons of war.

In the em future scenario that I’ve been exploring, income per em falls to subsistence levels. This should increase economic growth rates, the importance of engineering relative to design and marketing, and emphasize scale economies relative to product variety. Our descendants would return to focus more on conquering nature, and on acquiring economic power that translates better into military power.

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Drexler and I Again

Eric Drexler has responded to my last reply. Let me focus on one key issue. I wrote:

The main argument you gave for why a nanotech revolution could happen suddenly is that new nanotech designs could “unfold at the speed of new digital media”, i.e., we could sent such designs around fast as digital files. But if this were all that was needed for a technology to improve rapidly we should now see rapid gains in the design of novels, music, and software.

Drexler responds with quotes from his book:

Even partial upgrades of existing products that involve [merely] replacing structural components with materials that are lighter, stronger, and lower in cost can offer striking advantages. If a business today could deliver replacements for products already in use, but at lower cost and with superior performance by a few key metrics (vehicles with half the mass, electronic systems with ten thousand times greater capacity), one would expect to see rapid replacement of competing products along with the collapse of the supply chains behind them. …

Cycles of product improvement (and replacement) can be swift with an APM production infrastructure; the delays of prototyping, production engineering, and plant construction largely disappear, and production itself can be both fast and scalable. Further, for products adapted to decentralized APM-based production, distribution need not involve shipping and can more nearly resemble an Internet download.

Yes, if a broad mature nanotech ability were to drop out of the sky, then industry could use such an ability to rapidly to displace existing products with large efficiency gains. A sudden appearance of full nanotech would imply a big sudden social change. But the question here is exactly how fast would nanotech abilities appear!

Nanotech production lines take very small chemicals and incrementally bond them to each other, accumulating larger and larger assemblages, until they are big enough to be useful devices. Imagine that such production lines slowly became cheaper, faster, and more reliable, slowly adding to the menu of chemicals they could take in as basic building blocks, and slowly able to reliably create a wider range of chemical bonds at a wider range of relative block orientations. Slowly more of the steps in this production process became more fully automated, and less guided by human intervention. The slower that these improved abilities appeared, the slower would be the gains in performance and cost of the devices made this way.

Today the industries that create novels, music, and software all have the advantages Drexler foresees – they have little in the way of tech-induced delays of prototyping, production engineering, and plant construction. Production itself is both fast and scalable. Even so, those industries are not improving the efficiency of their products at rates much faster than when they suffered greatly from such delays. So the elimination of such delays is clearly not sufficient to imply much faster gains in final product value.

If there are reasons to expect nanotech abilities to improve rapidly, they must be additional reasons beyond those given above.

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Drexler Responds

Three weeks ago I critiqued Eric Drexler’s book Radical Abundance. Below the fold is his reply, and my response: Continue reading "Drexler Responds" »

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My Critique Of Drexler

My last post quoted Drexler on science vs. engineering. Here he is on exploratory engineering:

Exploring, not the time-bound consequences of human actions, but the timeless implications of known physical law. …. Call it “exploratory engineering”; as applied by Tsiolkovsky a century ago, this method of study showed that rocket technology could open a world beyond the bounds of the Earth. Applied today, this method shows that atomically precise technologies can open a world beyond the bounds of the Industrial Revolution.

Drexler’s most famous book was his ’86 Engines of Creation, but his best was his ’92 Nanosystems, which explored nanotech engineering. The book shows impressive courage, venturing far beyond familiar intellectual shores, impressive breadth, requiring mastery of a wide range of science and engineering, and impressive accomplishment, as little in there is likely to be very wrong. This makes Drexler one of my heroes, and an inspiration in my current efforts to think through the social implications of ems.

Alas, Drexler also deserves some criticism. His latest book, Radical Abundance, like several prior books, goes well beyond physical science and engineering to discuss social implications at length. Alas, though his impressive breadth doesn’t extend much into social science, like most “hard” sci/tech folks Drexler seems mostly unaware of this. He seems to toss together his own seat-of-the-pants social reasoning as he can, and then figure that anything he can’t work out must be unknown to all. Sometimes this goes badly. Continue reading "My Critique Of Drexler" »

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Why Do Algorithms Gain Like Chips?

Computer hardware has famously improved much faster than most other kinds of hardware, and most other useful things. Computer hardware is about a million times cheaper than four decades ago; what other widely useful thing comes has grown remotely as fast? Oddly, computer algorithms, the abstract strategies by which computer hardware solves real problems, seem to have typically improved at a roughly comparable rate. (Algorithm growth rates seem well within a factor of two of hardware rates; quotes below.) This coincidence cries out for explanation.

On the surface the processes that produce faster hardware and faster algorithms seem quite different. Hardware is made by huge companies that achieve massive scale economies via high levels of coordination, relying largely on internal R&D. Algorithms instead seem to be made more by many small artisans who watch and copy each other, and mostly focus on their special problem area. How is it that these two very different processes, with very different outputs, both grow at roughly the same remarkably fast rate? The obvious hypothesis is that they share some important common cause. But what? Some possibilities:

  • Digital – Both computer hardware and algorithms are digital technologies, which allow for an unusually high degree of formal reasoning to aid their development. So maybe digital techs just intrinsically grow faster. But aren’t there lots of digital techs that aren’t growing nearly as fast?
  • Software – Maybe software development is really key to the rapid growth of both techs. After all, both hardware and algorithm experts use software to aid their work. But the usual descriptions of both fields don’t put a huge weight on gains from being able to use better productivity software.
  • Algorithms – Maybe progress in hardware is really driven behind the scenes by progress in algorithms; new algorithms are what really enables each new generation of computer hardware. But that sure isn’t the story I’ve heard.
  • Hardware – Maybe there are always lots of decent ideas for better algorithms, but most are hard to explore because of limited computer hardware. As hardware gets better, more new ideas can be explored, and some of them turn out to improve on the prior best algorithms. This story seems to at least roughly fit what I’ve heard about the process of algorithm design.

This last story of hardware as key has some testable predictions. It suggests that since gains in serial hardware have slowed down lately, while gains in parallel hardware have not, parallel algorithms will continue to improve as fast as before, but serial algorithm gains will slow down. It also suggests that when even parallel hardware gains slow substantially in the future, because reversible computing is required to limit power use, algorithm gains will also slow down a comparable amount.

If true, this hardware as key theory also has policy implications. It suggests that it is much better to subsidize hardware research, relative to algorithm research; even with less research funding algorithm gains will happen anyway, if just a bit later. This theory also suggests that there is less prospect for self-improving algorithms making huge gains.

So what other explanations can we come up with, and what predictions might they make?

Added 5June: There are actually several possible ways that software progress might be determined by hardware progress. In the post I mentioned better hardware letting one explore more possible ideas, but it could also be that people already knew of better algorithms that couldn’t work on smaller hardware. Algorithms vary both in their asymptotic efficiency and in their initial overhead, and we might slowly be switching to bigger overhead algorithms.

Those promised quotes: Continue reading "Why Do Algorithms Gain Like Chips?" »

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