The Great Mental Models Vol. 3 by Shane Parrish

Systems and Mathematics

I just finished the third volume of the incredible The Great Mental Models series. This final edition focuses on Systems and Mathematics. In particular, it analyzes Feedback Loops, Scale, Churn, Algorithms, Emergence, Irreducibility, Compounding, Sampling, Randomness, Regression to the Mean, Equivalence, Global and Local Maxima.

Systems are rarely static. They are continuously adjusting toward equilibrium, but they rarely stay in balance for long. In our lives we often act like we can reach an equilibrium: once we get into a relationship, we’ll be happy; once we move, we’ll be productive; once X thing happens, we’ll be in Y state. But things are always in flux. We don’t reach a certain steady state and then stay there forever. The endless adjustments are our lives.

This calls to mind the Red Queen’s race from Through the Looking-Glass. The idea is that constant effort is required to maintain an outward appearance of stasis. Balance requires work and energy.

The concept of randomness is explicated in great detail in the mathematical half of the book. Readers familiar with Nassim Taleb and the brilliant black swan argument will immediately make intertextual connections. Our society and especially our “experts” dramatically overvalue the average at the expense of the outlier. In reality, the outlier can have a vastly more profound influence on the course of events.

We can forget that the past was as random as the future will be. In hindsight, history can seem ordered and logical. When we open a history book, we see structured narratives. Events have a beginning, a middle, and an end. It only seems this way in retrospect. Not only are past events random, so is the information we have about them.

There are additional volumes of The Great Mental Models series in the works. I look forward to devouring them upon release.