Science and modeling.

It's time for anothe installment of "Ask a ScienceBlogger". This week's question:

If you could shake the public and make them understand one scientific idea, what would it be?

Here, because others have already snagged my standard answer to this question, and because I've already embraced unrealistically high expectations in the last 24 hours, I'm going to opt for something a little more challenging.

I want the public to understand something about how science uses models.

When scientists are trying to understand systems and phenomena, they turn to models. A model is a simplified version of the complicated reality. Often, a model will leave a lot of details from the real system out to look at what the bits that remain do and how they fit together. Sometimes, a model will posit analogues to stuff we understand fairly well (like Tinkertoy connectors or springs) to account for the behavior of stuff that is quite different (like bonds between atoms in molecules). Models can help us make predictions, some pretty rough and others reasonably accurate. Models can help us identify the crucial features of a system without which the exciting effects wouldn't happen. Models can give us a hope of understanding phenomena where there's so much going on that our little brains feel like they're going to explode.

The tricky thing about models is that, while they aren't the truth with a capital-T, they capture something true.

Scientists know that models are some distance from reality, but they test the heck out of them. They want the model to get the piece of reality it's supposed to capture just right, and they have little patience for bad models.

Understanding all the ins and outs of just how models work is a fairly intense philosophical question -- I'm not expecting the public to have complete comprehension of a question I'm working on myself as part of my day job. But for the public to grasp at least a bit of the role modeling plays in the scientific project of making sense of a complicated world would be a good thing.


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if people understand the general idea of modelling i hope they don't stumble onto physics models before they hit ecological models, cuz the former just spoils the game.

i hope they don't stumble onto physics models before they hit ecological models, cuz the former just spoils the game.

Newtonian physics is a model which is taught very early, and, I
suspect, much easier to understand than most ecological
models. Whatever the bad effects of 'spoiling the game' are, they are
already present.

This is a tough thing you seek, but I agree with you. Models of different kinds pervade our everyday lives, most of them with a predictive bent (weather forecasts, crash testing cars, traffic signalling, supermarket queues), but we may not realise it. I wonder whether people would react differently to model predictions of climate change if they knew how much that type of modelling already affects them.

Then there are models developed for hypothesis generation or to help test what we think we know. The philosophical underpinnings for these are quite different from predictive models. They're probably harder or less intuitive, and yet they're gold.

"All models are wrong, but some are useful" -- isn't that how it goes? I forget who said that."

It was G.E.P. Box. But nobody can find the original reference!


See the Wikiquote entry on George E.P. Box for the reference.

As it happens, I've been thinking about models a fair bit lately. See my recent blog post on the trouble with models.

I'd like to mention two other types of models:

  • a measurement model is always present (though often unrecognized) when we make observations;
  • a statistical or analytical model is always present when we make inferences.

I agree entirely that conveying to the public how science uses models would be a good thing. But I think it's quite a challenge!