Last week I wrote about the need for experimentation over models. Models are generally too abstract and far afield from reality that it’s hard to get any accurate answers.
If you want to find out if an intervention works, try it. Do experiments on it. Carry out pilot projects and see what happens.
Don’t model just model something to see what’s “likely to happen”. What’s “likely to happen” in your model is going to be highly dependent on the assumptions you make, which in turn are likely to highly dependent on your view of the world. We tend to see what we expect to see, which can make modelling a particularly self-referencing exercise if we’re not careful. Experiments help us see the world as it really is.
But that’s not the full story. Don’t discount modelling just yet.
Joshua Epstein makes a great case for modelling in what is one of the best essays on modelling I’ve read so far. He has one particularly salient point about models that I’d never thought of before: that building models is done by everyone all the time; it’s just that people don’t build explicit models all the time.
By building an explicit model, listing down assumptions and having all the numbers laid out in front of you, at least you know what’s going into your thinking. Not building explicit models, on the other hand, doesn’t mean you’re not using a model, as Epstein explains:
It is just an implicit model that you haven’t written down.
The choice, then, is not whether to build models; it’s whether to build explicit ones. In explicit models, assumptions are laid out in detail, so we can study exactly what they entail. On these assumptions, this sort of thing happens. When you alter the assumptions that is what happens. By writing explicit models, you let others replicate your results.
Overall, the points Epstein makes on modelling are practical and well thought out, and certainly worth the read. Models are, in a nutshell, great at testing assumptions and straightening out thinking before any real decision is made, even if that decision is to go ahead on a pilot project.
I love to read and write. Professionally, data science, technology, and sales ops are my thing. In my non-professional life, I aspire quite simply to be a good person, and encourage others to do the same. For those who care, I test as INFJ in the MBTI.