Technology (21): Dan Wang on Technology as Process and Learning by Doing

This is an extract from a much longer article by Dan Wang. His point about the learning-doing feedback loop applies to just about everything, of course.

The goal of [this piece, and Definite Optimism as Human Capital] is to broaden the terms in which we discuss “technology.” Technology should be understood in three distinct forms: as processes embedded into tools (like pots, pans, and stoves); explicit instructions (like recipes); and as process knowledge, or what we can also refer to as tacit knowledge, know-how, and technical experience. Process knowledge is the kind of knowledge that’s hard to write down as an instruction. You can give someone a well-equipped kitchen and an extraordinarily detailed recipe, but unless he already has some cooking experience, we shouldn’t expect him to prepare a great dish.

I submit that we have two big biases when we talk about technology. First, we think about it too much in terms of tools and recipes, when really we should think about it more in terms of process knowledge and technical experience. Second, most of us focus too much on the digital world and not enough on the industrial world. Our obsession with the digital world has pushed our expectation of the technological future in the direction of cyberpunk dystopia; I hope instead that we can look forward to a joyful vision of the technological future, driven by advances in industry.

Process knowledge is represented by an experienced workforce. I’ve been studying the semiconductor industry, and that has helped to clarify my thoughts on technological innovation more broadly. It’s easy to identify all three forms of technology in the production of semiconductors: tools, instructions, and process knowledge. The three firms most responsible for executing Moore’s Law—TSMC, Intel, and Samsung—make use of each.

The three firms most responsible for executing Moore’s Law—TSMC, Intel, and Samsung—make use of each. All three companies invest north of $10 billion a year to push forward that technological frontier. The tools and IP held by these firms are easy to observe. I think that the process knowledge they possess is even more important. The process knowledge can also be referred to as technical and industrial expertise; in the case of semiconductors, that includes knowledge of how to store wafers, how to enter a clean room, how much electric current should be used at different stages of the fab process, and countless other things. This kind of knowledge is won by experience. Anyone with detailed instructions but no experience actually fabricating chips is likely to make a mess.

When firms and factories go away, the accumulated process knowledge disappears too. Industrial experience, scaling expertise, and all the things that come with learning-by-doing would decay.

Knowledge should circulate throughout the supply chain, flowing both up and down the stack. Successful industries tend to cluster into tight-knit production networks. The easiest way to appreciate the marvel of clusters is to look at Silicon Valley, where capital, academia, a large pool of eager labor, and companies both large and small sit next to each other. To any of us who have spent some time in Silicon Valley, it’s obvious that this concentration of economic linkages is part of the magic that makes the system work… It’s not just chips: autos, electronics, biotech, aviation, and machine parts all tend to be geographically clustered.

Proximity makes it easier to generate process knowledge. But what happens when we tear apart these production networks by separating design and manufacturing? Sometimes it’s no big deal, sometimes it works out great. But I believe that in most cases, dislocation makes it more difficult to maintain process knowledge.

Both the design process and production process generate useful information, and dislocation makes it difficult for that information to circulate. I think we tend to discount how much knowledge we can gain in the course of production, as well as how it should feed back into the design process. Maybe it’s easier to appreciate that with an example from computing. Arjun Narayan tells me that good software design requires a deep understanding of chips, and vice versa. The best developers are those who understand how processes interact both up and down the stack.

What happens when we stop the flow of knowledge up the stack?

Let’s try to preserve process knowledge. The decline of industrial work makes it harder to accumulate process knowledge. If a state has lost most of its jobs for electrical engineers, civil engineers, or nuclear engineers, then fewer young people will enter into these fields. Technological development slows down, and it turns into a self-reinforcing cycle of decline. I think we should try to hold on to process knowledge.

The internet is important, and we’re likely still underrating its effects. But I don’t think that we should let innovation be confined entirely to the digital world, because there’s still too much left to build. The world isn’t yet developed enough that everyone has access to shelter, food, water, and energy at a low share of income. Hundreds of millions still live in extreme poverty, which means that manufacturing and logistics haven’t overcome the obstacles of delivering cheap material comfort to all.

And I submit we can’t bring ourselves to calling it the “developed” world until we’ve built so many other things, a point made best by Peter Thiel. We go to work in subways built in the ‘70s, guided by signals equipment put in place in the ‘20s. We’ve been moving more slowly across the planet ever since we decommissioned the Concorde, at a time when global travelers want faster access to major hubs. Are we sure that the developed world is not undergoing its own premature deindustrialization? When people bring up that the fact that the digital world has become very fun, I tend to think that the response smacks of “Let them eat iPhones.”

I’m not saying that manufacturing has special moral worth, and I’ve previously acknowledged that much of manufacturing is unpleasant and hazardous. I’m interested in industry because I see the maintenance of an industrial base as a precondition to building the science fiction technologies of the future.

Dan Wang – How Technology Grows

See also:

This extract from Dan’s 2021 Newsletter about U.S. acquisition of German industrial technology after the Second World War:

Taking Nazi Technology: Allied Exploitation of German Science After the Second World War by Douglas M. O’Reagan gave me more material on thinking about technology. After Germany surrendered, American scientists with a courtesy rank of Colonel combed through German industrial labs. They were there to seize its technological secrets. They discovered two things: that Germany wasn’t much ahead of the US—not even the mighty IG Farben in the chemical industry. And second, that the vast amounts of data and industrial recipes they microfiched and sent back to the US were mostly useless. Knowledge couldn’t be written down to be transported; it had to move in the form of people like Wernher von Braun. It was wonderful to read this historical case of the theme that technology is people, which has been one of the core ideas discussed in my essays (as well as by many other people before me). I wrote more about this book in my piece on US prosecutions of scientists.

I'd love to hear your thoughts and recommended resources...