Why Catastrophes Happen

By: Mark Buchanan

Published: 2000

Read: 2018


Are there general rules in situations where scientists have so far failed to find predictable patterns (for instance, the timing of the next big earthquake, the form a snowflake might take, the next big move in the stock market, etc.).

The book looks at examples of natural or social systems that are out of balance; systems that are in a so-called “critical state”: when stressed, they are in a constant battle between stability and instability. For instance, dropping grains of sand on a sand pile creates a critical state. Over time, with every new piece of sand dropping on the sand pile, the magnitude of what happens next becomes unpredictable.

This book claims that systems that are in a critical state, under certain conditions, show universal features in their behavior and have ubiquitous properties that arise again and again in things driven away from equilibrium and in situations where history matters.

Worth Reading:

Love reading about systems that start out simple and naturally become more complex, a concept that comes back again and again (in explaining life, intelligence, consciousness, etc.)

The descriptions of critical states in nature (forest fires, earthquakes, snowflakes, gas phase transitions) are very interesting and it is somewhat awesome to read that while all are unpredictable, there seems to be a single universal pattern that governs much of the way in which these systems behave.

The book becomes more speculative and forced in the exploration of critical states in social settings, such as the stock market, spread of diseases, and other broad societal patterns (wars, city size and structure, evolution of scientific paradigms).

A bit more of a formal structure to the book would have been helpful, especially in terms of specific definitions (of a critical state and its components, etc.). There are clear links with the concepts of entropy, network/information theory, biology, and emergent behavior and exploring those related concepts in more detail here would have been interesting.

Key Takeaways:

  • Complex systems may emerge when parts interact in a simple way.
  • Complex systems share universal features.
    • Their future behavior is typically unpredictable.
      • A small change in the system can bring about sudden, unexpected cascades of changes (or not).
    • Their past behavior may show certain statistical patterns.
      • Power laws: when a feature doubles, its occurrence changes by a fixed factor.
    • It is difficult or impossible to determine individual causes of historic behavior.

If (i) you can only understand the behavior of critical state systems after the fact through analyzing historic statistics and if you can’t predict what happens next and (ii) there are no specific individual causes, then “who cares”? What is the takeaway? Is there any lesson to be learnt that is helpful for the future? Make sure you are anti-fragile? That you are able to adapt and “benefit” from any kind of future unpredictable behavior?

An interesting part of the book is that the science behind critical states takes the form of simulation games. Simulating natural or social critical states in (computer) games with very basic parameters produces statistical results that very closely match what is observed in real life. It will be interesting to see if/how these games will develop further (as computing power / ability to deal with complexity increases). There is probably some obvious connection with the increased focus (in business) on experimentation (simulation) as a means of improving performance and behavior .

The book also explores interesting critical states in civil society. For instance, social groups that interact with each other within given fixed social structures. The relative “power” of each group may change over time. As the powers of groups shift over time, there are pressures on the existing social structure to retain its social stability or to break it. In other words, the social structure is in a critical state. As tensions to break its structure pass a certain threshold, the stress may finds it release in some form (armed conflict, argument, revolution) and the system will find a new equilibrium. In the theory of critical states, the size of the change is inherently unpredictable and it doesn’t make sense to look for singular explanations. It is interesting apply this type of thinking to everyday political situations and understand how inherently unpredictable they are. 

Key Concepts:

In a system that is made up of individual system parts, each part may act in accordance with “simple” and predictable rules, but because there are so many parts that interact with and influence each other, the emerging behavior of the system as a whole becomes complex and unpredictable. If a system displays this type of emergent unpredictable behavior, it is said to be in a critical state.

While the behavior of the system may be unpredictable and complex, it is not random. When you rewind the clock and go back in time to observe the system’s past behavior, patterns emerge.

This pattern typically is a power law: every time a certain defining feature (earthquake strength, % change in stock market) is doubled (or halved), the number of times such a feature occurred in history increases or decreases by a fixed factor.  

The power law produces scale invariant or self-similar systems: systems that look fundamentally the same at a bigger or smaller scale (think of fractals in computer land).

Because the system looks the same at every level, there is no fundamental difference between a very large event or a very small event (a massive or small earthquake, a huge or small stock market move, a large or small slide in a sand dune).

The key implications are that there is no such thing as a typical fluctuation (patterns of change are neither regular nor random), there is no reason to think that a very large swing is unusual or needs further explaining, and it is fundamentally impossible to predict the magnitude of the upcoming change. [Not highlighted in this book is that the notion of “average” is not meaningful in a power law system; over time the average typically increases as there is no peak to events].

It is claimed that another characteristic of these systems is that any attempt to look for a singular cause to explain complex behavior is doomed to fail – there are no simple, deterministic laws for complex chains of events. [As Peter Thiel would say, the event is over-determined.]

The only thing that can be said about critical states is that under certain conditions, systems of interacting objects show universal features in their behavior (meaning: the power law). These ubiquitous properties arise again and again in things driven away from equilibrium and in things in which history matters.

Leave a Reply