The power of water, and reflections on critical thinking
A testimony to the power of water, in recent Australian floods.
Water level in rivers follows the Log-Pearson 3 probability distribution(see attached picture)
Tightly clustered around the mean, with little variation, and a limit on how far the left hand tail can go (ie “dry”)
The right hand tail though is much fatter than the standard normal distribution. Even though it remains a very low probability event, the consequences keep going; they don’t trail off to insignificance like in the standard normal
In forecasting and then living the future, we see something like the Log-Pearson 3 distribution in practice. We get accustomed to extrapolating from previous “normalish” experience which works so often that it becomes a reasonable technique and standard practice. Our monkey brain is poorly adapted for remembering the lessons of fat tails and properly estimating their effect on our plans
When the underlying process though is NOT a generator of standard normal, but rather has elements of chaos and uncertainty in it, we can get to experience the surprise of consequences which conform to power laws: unpredictable as to frequency of occurrence or seasonality, and unpredictable in terms of magnitude of consequence.
Our monkey brain will tend to discount the early indications of potential disaster as a combination of a number of well-known biases and fallacies. Remember that cognitive biases get turned into fallacies when you start experiencing the consequences. Ask the guy holding the camera in the video clip.
We often can’t know the degree of chaos in the underlying process until we discover results that suddenly and stubbornly refuse to conform to standard normal expectations.
In digiworld you get do overs.
In realworld, you get the opportunity to learn from other peoples’ catastrophes; you don’t get to learn from your own catastrophes.
This is the basis for Nassim Taleb‘s (“Black Swan”) discussion of 4th Quadrant problems: when our statistically based insights can actually expose us to far more risk than standard models can/will describe.
Taleb’s advice on living in the 4th Quadrant: What Is Wise To Do (Or Not Do) In The Fourth Quadrant
1) Avoid Optimization, Learn to Love Redundancy
2) Avoid prediction of remote payoffs—though not necessarily ordinary ones
3) Beware the “atypicality” of remote events.
4) Time. It takes much, much longer for a times series in the Fourth Quadrant to reveal its property.
5) Beware Moral Hazard.
6) Metrics. Conventional metrics based on type 1 randomness don’t work in the Fourth Quadrant.
- Black Swans (spectrum.ieee.org)
- “Nassim Taleb” and related posts (dailymarkets.com)
- Steven Poole’s non-fiction choice | Review (guardian.co.uk)
- Vivian Norris: A Walk Through Paris With Nassim Nicholas Taleb (huffingtonpost.com)
- Using R for Introductory Statistics, Chapter 5 (r-bloggers.com)
- Watch Ben Bernanke Get Ambushed With Question About Nassim Taleb (businessinsider.com)
- Books of The Times: Explaining the Modern World and Keeping It Short (nytimes.com)
- Reflections on strategic leadership (kansasreflections.wordpress.com)
- Black Swan may be one of those rare things (theglobeandmail.com)
- Reflections on “Sonic Boom” by Greg Easterbrook (kansasreflections.wordpress.com)
- Reflecting on a strategic inflection point at CGSC in Army education (kansasreflections.wordpress.com)
- Late night reflections on theory (kansasreflections.wordpress.com)
- Reflections on Starobin’s Five Roads to the Future (kansasreflections.wordpress.com)
- More reflections on Mintzberg on planning (kansasreflections.wordpress.com)
- Reflective learning in the markets (kansasreflections.wordpress.com)
- Thanksgiving reflection (kansasreflections.wordpress.com)
- “Just being alive is an extraordinary piece of good luck.” (or the very best pieces from Nassim Nicholas Taleb) (beinghuman.blogs.fi)
- Reflections on economy, China and education (kansasreflections.wordpress.com)