Charlie Munger: Adding Mental Models to Your Mind’s Toolbox
In The Art of War Sun Tzu said “The general who wins a battle makes many calculations in his temple before the battle is fought.”
Those ‘calculations’ are the tools we have available to think better. One of the best questions you can ask is how we can make our mental processes work better.
Charlie Munger says that “developing the habit of mastering the multiple models which underlie reality is the best thing you can do.”
Those models are mental models.
They fall into two categories: (1) ones that help us simulate time (and predict the future) and better understand how the world works (e.g. understanding a useful idea from like autocatalysis), and (2) ones that help us better understand how our mental processes lead us astray (e.g., availability bias).
When our mental models line up with reality they help us avoid problems. However, they also cause problems when they don’t line up with reality as we think something that isn’t true.
In Peter Bevelin’s Seeking Wisdom, he highlights Munger talking about autocatalysis:
If you get a certain kind of process going in chemistry, it speeds up on its own. So you get this marvellous boost in what you’re trying to do that runs on and on. Now, the laws of physics are such that it doesn’t run on forever. But it runs on for a goodly while. So you get a huge boost. You accomplish A – and, all of a sudden, you’re getting A + B + C for awhile.
He continues telling us how this idea can be applied:
Disney is an amazing example of autocatalysis … They had those movies in the can. They owned the copyright. And just as Coke could prosper when refrigeration came, when the videocassette was invented, Disney didn’t have to invent anything or do anything except take the thing out of the can and stick it on the cassette.
***
This leads us to an interesting problem. The world is always changing so which models should we prioritize learning?
How we prioritize our learning has implications beyond the day-to-day. Often we focus on things that change quickly. We chase the latest study, the latest findings, the most recent best-sellers. We do this to keep up-to-date with the latest-and-greatest.
Despite our intentions, learning in this way fails to account for cumulative knowledge. Instead we consume all of our time keeping up to date.
If we are prioritize learning, we should focus on things that change slowly.
The models that come from hard science and engineering are the most reliable models on this Earth. And engineering quality control – at least the guts of it that matters to you and me and people who are not professional engineers – is very much based on the elementary mathematics of Fermat and Pascal: It costs so much and you get so much less likelihood of it breaking if you spend this much…And, of course, the engineering idea of a backup system is a very powerful idea. The engineering idea of breakpoints – that’s a very powerful model, too. The notion of a critical mass – that comes out of physics – is a very powerful model.
After we learn a model we have to make it useful. We have to integrate it into our existing knowledge.
Our world is mutli-dimensional and our problems are complicated. Most problems cannot be solved using one model alone. The more models we have the better able we are to rationally solve problems.
But if we don’t have the models we become the proverbial man with a hammer. To the man with a hammer everything looks like a nail. If you only have one model you will fit whatever problem you face to the model you have. If you have more than one model, however, you can look at the problem from a variety of perspectives and increase the odds you come to a better solution.
“Since no single discipline has all the answers,” Peter Bevelin writes in Seeking Wisdom, “we need to understand and use the big ideas from all the important disciplines: Mathematics, physics, chemistry, engineering, biology, psychology, and rank and use them in order of reliability.”
