Confusion Archive

“I realize that often it’s not what you put into your image that makes it powerful but what you leave out of it,” a photographer once answered upon asked about minimalism. The same thing, I believe, goes with theories.

Theories have long been a part of humanity – attempting to provide accurate explanations of phenomena. Simplicity, since then, is a valuable aspect of an explanation to make it easier to understand and work with. Now this, has been an object of confusion in understanding the principle of parsimony. It reproaches us to choose from a set of otherwise equivalent models of a given phenomenon the simplest one.

Parsimony, as how I understand, is not at all concerned with the simplicity or complexity of a theory. It rather demands to free the explanations from those that make no difference in the predictions. Removing the concepts, variables or constructs that are not really needed to explain the phenomenon could make the development of a model much easier, and would offer less chance of introducing inconsistencies, ambiguities, and redundancies. Thus, upon comparing two theories which appear to be equally accurate, with neither of the theories more probable than the other, the simple one is to be chosen. It is because of its practicality. Now, you may ask, “We’re talking about real-world phenomena (which are randomly complex), so why use simple models?” It’s not about how things on earth work, but rather drawing models from the gathered data.

For example, subject domains like mathematics or philosophy, both have unlimited complexity. If someone initiates and formulates ideas about too complicated foundations for a certain theory , there is very little chance of getting a manageable model. If one starts with too complicated foundations for a theory that potentially encompasses the universe, the chances of getting any manageable model are very slim indeed. This strategy, I believe, is clever. But I don’t think it is always a good thing. It cannot be false because it is a strategy. It could just be either ‘clever’ and ‘stupid’. Certain situations need to be thoroughly discussed and elaborated, clearly expressing details that need to be carefully exposed. As for some phenomena, which require intricate explanations and very detailed presentations, this principle is trivial.

There would be time that a simple model will outperform a more complex model. Nevertheless, I believe that consciously limiting the complexity of the model is not fruitful when the problem is incontrovertibly complex. Instead, if a simple model is found to outperform some particular complex model, the appropriate response is to define a different complex model that captures whatever aspect of the problem led to the simple model performing well.
Parsimony could be criticized as a guiding principle in so many ways. And I think it is because of the unclear agreement on how ‘simplicity’ should be defined. To atleast reduce confusion, I say it’s clever, and on the other hand, flawed.


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