In university in the early 90’s a group of us came across the Santa Fe Institute. It wasn’t part of the syllabus, it was an outgrowth of the discussions of a group of wonderful friends, studying mathematics, statistics and actuarial science: shout out to Greg, Steven in particular. If I recall correctly it was Greg who introduced it to the group to a book about complexity which we all read and it inspired us greatly.
The Santa Fe institute, had been set up in 1984 to study complexity and complex adaptive systems: how complex behaviour can emerge in systems even with quite simple building blocks and rules. It was inspiring: it seemed to have such wide potential implications: everything from the way ant colony’s work, to the way the brain works, to the way traffic flows through cities, to the way our global economy works. The introduction to genetic algorithms was revelatory – how complex systems can be optimised and managed using adaptive systems mimicking by the way evolution happens through computer simulation.
Given what I have ended up doing, investment management, it gave such a wonder foundational mental model for the way the economy works (Brian Arthur from the institute has done a lot on the economy): that lots of interacting agents (people, companies, governments), each with their own objectives interact with each other in ways that seem to create predictable patterns that maintain for some time, and then through some set of interactions can easily flip over into a completely different state, a different pattern. It disavowed me of the notion that the whole economic system could be condensed into a single all explanatory mathematical model. To this day I still believe it is worth trying to understand the interactions in the system, the patterns that emerge and the potential different states into which it can flip, while always being respectful of an inability to predict what will happen and the inability to know all the potential states.
Complexity research has moved on since the 1990’s and it was fun to find that several investors are now connected with the institute including Michael Mauboussin, another thinker and investor I admire. It inspired me to pick up this book. The book gives a good intro to complexity walking through a bunch of examples.
The wonderful new revelation to me was the connection back to genetics. Genetic algorithms were us borrowing from nature to simulate and solve complex problems. But the book does a wonderful job of explaining how biology at the small cellular and DNA scale is also another complex system with many self-referential characteristics. There is a wonderful connection between genetics and the ideas of self replicating systems, linking back to Godel, Escher Back, another great book from that 1990’s reading club. Godel formally encoded mathematical systems that were able to reference themselves (leading later to the proof of his famous Incompleteness Theorem). I’ve been spending much more time trying to understand biology and genetics so its wonderful to see the connections here to mathematics and complexity theory: The same mental models can be applied to the inner workings of the cell as it reads DNA (a series of amino acids), produces RNA that produces new proteins made from amino acids that then activate other genes to produce new proteins often coming back to then turn off the original protein production. Life is wonderfully complex.
I recommend the book for anyone wanting to get a decent intro to complexity and to get some wonderful insights into some of the complex systems out there: celluar autonoma, genetic algorithms, network systems, foundations of many of the AI models. There is a wonderful chapter on getting computers to understand analogies like we humans do!
Here's something that inspired me... 