[P&N] Chapter 3: Models of Models of Models of Models of Things
Citation: Edward A. Lee, 2017: Plato and the Nerd - the creative partnership of humans and technology. MIT Press, Cambridge, MA
What is Technology?
We have been talking about technology all the time, no matter the annual “Apple Event” or the chatting among people. But what is technology anyway?
As mentioned in the previous chapter, the engineers focus on how to create objects that best fit the model while scientists do so the other way around. “Technology” is defined in the dictionary of Merriam-Webster as follows:
- The practical application of knowledge, especially in a particular area: engineering.
- A manner of accomplishing a task especially using technical processes, methods, or knowledge new technologies for information storage.
- The specialized aspects of a particular field of endeavor.
From this point of view, “technology” is more created by engineers than scientists. In the book P & N, Lee states:
Technology is not a collection of Platonic truths that have always been lurking in the background, waiting to be discovered, but is rather a rich sociological tapestry of ideas created by human inventors.
which again assured my intuition about the term technology.
Such technology can be too complicated for a single person to understand thoroughly, and therefore comes an important way to simplify the complexity - layering.
The human brain has difficulty keeping in mind simultaneously more than a few distinct components.
Complexity Simplified
In page 51 of the book P & N, Lee writes:
In fact, the point I want to make is that the human brain is incapable of comprehending any design that has 1.4 billion individual components, each with a potentially different function, despite the fact that the human brain has some 100 billion neurons, each of which does more than a transistor.
I barely disagree with this statement. The whole point of whether this statement holds or not lies on the exact meaning of “comprehending” in this context. Why are human beings able to produce hundreds of thousands of this kind of product everyday without even “comprehending” its design? This question occurred to me as soon as I read that statement.
Does that indicate it’s a self-contradictory statement? As far as I am concerned, it’s a little bit overreacting to say so since the natural language is always ambiguous. My variant of Lee’s statement is: If one is asked to explain how does a computer work by only looking at the structure of the 1.4 billion transistors, he would fail. So we can say that we can comprehend the design or we can’t, both of which would make sense under some particular contexts, totally depending on what do we mean by “comprehend”. (This is a rather nerdy paragraph.)
So how do we even try to understand the 1.4-billion-component design? According to Lee, we use models of models of models of models of … models of a transistor, which gives the designers “freedom from choice”.(P.54) (Speaking of this, the title of this chapter is really provocative and successfully addresses the great idea behind it.)
Below a platform there are many possibilities, offering more choices than any human can handle. Above the platform, there are fewer choices to be made. You can design more systems by creating a network of transistors than you can using logic gates.
The term “freedom from choice” again blew my mind, I have never thought of the process of simplification that way, but it immediately made sense to me when I saw it. Human beings are always having trouble making decisions - even when it comes to simple questions such as what to eat for breakfast or lunch. A lot of people would hesitate between several options for a long time. But after today, I can confidently tell those people - “You guys are actually driving the technology to develop!” It reminds me of another widely used debate topic - “Is it the laziness that drives people to create new things?”. It is to some extent, isn’t it?
While engineers are benefiting a lot from the layering of the modeling paradigms, scientists seem to be struggling trying to apply the same strategy to scientific researches. Why? - Lee left this very interesting question to the subsequent chapter, so we’ll see.
Reductionism
As for reductionism, in my opinion, think of things in such way appropriately and critically would indeed help us to understand the problem better, but not in a extreme way to “reduct” problems to powders.