formalization as transparency and as mapmaking: mapmaking is memoizing

This is something I wrote at metaeducat10n. I'm not blockquoting it, because it's undergoing editing:


Transparency (check out the different meanings!) is an interesting metaphor for formalization.

Non-formalized processes are not transparent: you can't see inside the mind of the decision-maker, even if that means your own mind (although in the latter case, you can work towards slowly seeing it again).

Formalization is about making unconscious processes (and the implicit knowledge used in them) conscious. It is about establishing a good foundation for arguments and reasonings, as they may, upon inspection, turn out to be ill-founded. Formalization, like transparency, makes this inspection objective (since anyone can look at it, anyone can judge it), and easier to perform (because of the memoization provided by formalization, retrieval is quick).

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Map-making is memoizing. In formalization, it can memoize both one's perceptions (for the writer who writes in a formal language) or the interpretation process (for a reader/interpreter of an informal text).

Formalization, like mapmaking, has two advantages:
* it makes future retrieval of the content quick and inexpensive.
* by shining light on a whole picture at the same time, it allows one to see the picture under different perspectives (in which one can check if certain supposedly-straight lines really are straight, thanks to free rides) and different zoom levels (where one can check whether the formalized local impressions are globally coherent). This way, one refines one's impressions, by correcting the incoherencies (e.g. contradictions, as well as weaker forms of absurdity).

Imagine someone who decided to formalize his knowledge about the geometry of a sculpture from memory, and ended up drawing an Escher cube. Upon seeing his whole cube, such a person would immediately revise his interpretations/formalizations of his local impressions, because they cannot all hold together.

Herb Simon: computers are pattern-crunchers

One of the central ideas motivating my research is expressed by Herb Simon in the following quote:

Q: So you have moved from field to field as you could bring new tools to bear on your study of decision making?

A: I started off thinking that maybe the social sciences ought to have the kinds of mathematics that the natural sciences had. That works a little bit in economics because they talk about costs, prices and quantities of goods. But it doesn't work a darn for the other social sciences; you lose most of the content when you translate them to numbers.

So when the computer came along -- and more particularly, when I understood that a computer is not a number cruncher, but a general system for dealing with patterns of any type -- I realized that you could formulate theories about human and social phenomena in language and pictures and whatever you wanted on the computer and you didn't have to go through this straitjacket of adding a lot of numbers.

As Dijkstra said, Computer Science is not about computers. It is about processes.

It is a very common error is for people to make an argument like the following:

Stock prices have to do with human behavior. Therefore they are unpredictable. It's not like physics, where computers and mathematical models are useful.

I go all "oy vey" whenever I hear arguments like this... and then, they accuse me of reductionism.

My mom doesn't like it when I interview doctors trying to formalize their knowledge about my problem, so I can truly understand my problems. At the same time, she says (non-sarcastically) I should go into biomedical research.