Responses 010 (2010-2011)

Making ten long responses to ten shorter stems is not a new thing; Moses did it by putting ten commandments in Exodus 20 and then explicating them in Exodus 21-23. (Yes, you can't understand the Ten Commandments unless you realise that they're the executive summary of the next three chapters.)

Well, this is the tenth response to a list of ten questions that I first posted on 17 October. (I'll give a link-list at the end just to be helpful.) Question 10 in the list says, "A model is a simplified representation of some aspect of the world. In what ways may models help or hinder the search for knowledge?"

This is in many ways my favourite question. It's quite clear that by 'simplified' and 'representation', you should already know where the question might lead. There are two main points: a model is designed to simplify things, therefore making it easier to grasp the main points and understand something; a model is a representation, a sort of working miniature of something.

What then are the ways that a model can help or hinder the search for knowledge? (I'll note here that the phrase 'search for knowledge' also occurs in Questions 2 and 7, which is an unusual repetition and can be useful.)

You can analyse this in terms of a) simplicity and its pros and cons, and b) representations and their pros and cons. Let's look at simplicity first, and then representations.

Simplicity is of course a great tool for analysis; the reductio arguments are almost always helpful in cutting away the deadwood. However, oversimplification is a problem. This can occur in two ways: a) elimination of too much, thus making the model lose its power as a representation; and b) reification (or conflation), in which we take many elements of a model and reduce them to one. Examples: a) modeling the human brain as a digital computer of great complexity — which won't capture the various gradient effects of the human nervous system and its chemical environment; b) the infamous IQ model which reduces human intelligence to a single score, despite the fact that intelligence varies by environmental context, can be defined in many ways, and has never been proven to be a survival trait (haha, let us pause here in memory of Arthur C Clarke).

Representations range, of course, from symbols to icons to pictures and so on, scaling upwards. Representations are useful the way that substituting a simpler term for a more complex one can be useful; they are more portable and easier to manipulate. But in this case, we're talking about representations of aspects of the world. The problem in any discipline is whether the representation is valid; that is, does this scaled-down description of the world behave the way the real world should? You may also have the problems of transferability (can you use the model to represent other, similar things?) or reproducibility (can you transplant the model and have it work somewhere else). Representations are also problematic in that when you work with a representation, you may come to believe that it is the real thing; it's like mistaking a glossy brochure about holistic education for the actual attempt to provide an holistic education.

Obviously, there are many more problems and advantages to talk about, but this should provide a good start. Just remember that in science, for example, Ockham's Razor is often taken to be a necessity (the 'principle of parsimony') but there is no logical reason to think that this is true. Justifiable reduction and unjustifiable simplification are very, very close neighbours.

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Here's a list of links:

Question List for 2010-2011

Response to Question 1
Response to Question 2
Response to Question 3
Response to Question 4
Response to Question 5
Response to Question 6
Response to Question 7
Response to Question 8
Response to Question 9

You might also want to check the tags below, and any other tags which the linked posts might have in addition to these.

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