On the Art of Building and Updating Mental Models About the World at Large

Ajay Shah has a nice article out on how the world has changed between the end of 2021 and today:

By late 2021, some of us knew that the world economy was in for a torrid time. The foundations of price stability seemed to be under question and central banks globally would be raising rates dramatically if they were to protect the hard-won gains in credibility of the post-1983 period. But alongside this, we knew that sharp global tightening would trigger difficulties in as yet unknown aspects of the world economy.
In this difficult situation, we got two more problems. Russia attacked Ukraine and China tried to get to zero covid through repression.

https://www.mayin.org/ajayshah/MEDIA/2023/uncertainty_declined.html

As always, please do read the whole thing. But in today’s post, I do not want to speak so much about the contents of his piece as I want to talk about the advantage of building and updating mental models about the world at large.

What will the world look like at the end of 2023? The correct answer, of course, is “Who the hell knows?”. And so a better question to ask is this one:

Given what you know of what is happening in the world today, what do you think the world will look like by the end of 2023?

If this had been, say, an interview involving a student in a college, I would have asked the student to explain more about what they knew of the world today, and how they had gone about building their mental model. I’m not so interested in the specific answer during such a conversation, although I do expect the broad direction of the answer to make sense. I’m much more interested in what they will choose to highlight in terms of what they know about the world, and how they will use these highlights to build out their mental model. If you want a pithy summary, what facts have they chosen to assemble, and what insights have they gleaned from these facts – that’s what I am very interested in as an interviewer.

In fact, the first sentence of the excerpt above is a good way to think about what I said in the paragraph above. That some of us knew that the world was in for a torrid time is an insight (and from a financial perspective, arguably an actionable one). Persistent and stubbornly high inflation, the inevitable response of the central banks, and the inevitable slowdown that would follow were the facts.

Get in the habit of building such mental models in your own heads. Don’t worry, at the outset, about whether the model will ‘work’ well or not. It almost definitely won’t, and for a variety of reasons. The point of building this first model in your head isn’t so much about getting it right the first time, as it is about understanding why it didn’t work.

Did you not assemble enough facts? Which facts were you missing? How should you get better at assembling those facts?

Did you fail to integrate those facts well enough? Do you need to update your theory about how the world works? How should you get better at building out your grasp of theoretical concepts?

Did your biases impede your ability to formulate an insight? Do you need to update your priors about how the world actually works? How should you get better at shedding your implicit and explicit biases?

And then, for the rest of your lives, you need to iterate on these three sets of questions. The bad news is that your model of the world will never achieve perfect predictive accuracy. The good news is that you will get a little better each time around. This will, eventually, lead you to take better decisions about your career, your finances, your choice of city/country/continent to stay in. And more besides.

And for these reasons, building out this skill is heavily recommended.

And so you should read Ajay’s piece, regardless of whether you agree with his conclusions in it or not. I personally do in this case, but again, that’s not the point. You should read it to learn how to build your own model for the next 12 months, and for the sake of your learning, I hope you get it gloriously wrong the first time around.

Best way to learn!