sarkology

“it’s not so simple…”

Posted in Uncategorized by sarkology on May 21, 2010

This post is about people who think “it’s not so simple”, without further specifics, is a valid complaint.

First of all, of course it’s not so simple! But that’s besides the point. Such a complaint can always be made. No model can capture all the details of a particular phenomena. A map exactly the same size as the territory would be useless.

Yet why do people feel as if leaving out details is bad?

One. People are not pure truth-seekers. A lot of what we do when we profess beliefs and give forth arguments is about signaling. One common way of saying “but it’s not that simple!” is making an accusal of reductionism. Reductionism in their minds, is a very ugly thing. It slices and dices and absolutely butchers the phenomena under study such that it no longer feels like the model is the phenomena. So ‘reducing’ the complexity of human minds to something like psychology, is just plain wrong. Am I an autistic or something? Don’t I understand the richness of our our mental lives?

Two. Reasoning isn’t about logic, it’s about arguing. To understand particular aspects of any phenomena, we need to abstract out some of its features. That’s what understanding consists of. When Newton saw that what makes the apple fall and what makes the planets orbit are the same thing, there was understanding. Whenever you solve a puzzle, and have that “Aha!” moment, your mind succeeded in looking at the problem in such a way that the solution becomes apparent. This is because you are drawing an analogy between the current puzzle you are solving, and a previous case. So understanding is about being able to pay attention to what matters, ignoring the rest, and imposing a structure. But this isn’t what arguing is about. Argument is not about constructing a model. It’s about scoring points. Throwing at the opposition anything you can including the kitchen sink. Just have a look at any organized debate. So the more stuff you can use in an argument, the better. Who cares about what is relevant to which models? Seeing something as hopelessly complex allows you to bring in anything at all to fling at your opponent.

Three. People are confusing ‘how’ and ‘why’. We are not used to explanation in its modern scientific sense. In paleolithic or even ancient times, explanation just wasn’t applied to natural phenomena. We don’t ask “Why is the sky blue?” but “Why did she throw a rock at him?”. We ascribe reasons to agents. This we do because we have a built in folk psychology. Of course, we did start asking questions such as “Why is there lightning?” but our folk techniques get in the way and we come up with explanations like “Thor is angry. He throws lightning blots down.”. So, we carried over our folk methods of explanation and applied them to non-agent phenomena. In folk psychology explanations, we provide contingencies such that the actions of particular agents become comprehensible. In this case we already know what is relevant: events that would affect emotions and goals. This is a ‘how’ explanation. Things happen in sequence, one causing the other. This is not how we approach things in non-agent phenomena. In explaining why the sky is blue, we don’t already know what is relevant. An explanation would consists precisely in knowing which parts to pay attention to and which to ignore. For example, the thermal motion, or the chemical composition of the particles are irrelevant to Rayleigh scattering, what matters is their size. To recap, ‘how’ explanations take mechanisms for granted and provide contingencies to pin down what exactly did happen. ‘Why’ explanations directs our attention to relevant features and provides a model. So it’s not so simple, the phenomena is not so simple, because there are certainly other things going on. But what we want to know is what precisely is going on within the phenomena, we don’t already know the relevant players, so this isn’t about specifying contingencies to nail down specifics. This is about discovering the relevant principles involved. And to do this we require simple models.

Four. Explanations are not predictions. This is related to Three. We understand the principles behind weather. Yet accurate weather forecasts cannot go beyond 5 days. This is a failure not so much our understanding of weather, but a limitation of our calculation abilities. You can understand how parts of a pinball machine affects the ball’s trajectory, but you cannot predict where exactly the ball would go.

There are cases where the complaint “It’s not so simple” is valid, but not just like that. If the model is oversimplifying, that can only because it leaves out relevant features of the phenomena that it seeks to explain, or needs to use in order to explain. There is an easy way to tell if your simplicity complaint is valid. If in addition, you can provide further details to challenge the validity of the model, then your criticism just might have some use to it.

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