Seven scientists are convicted in Italy for not predicting an earthquake well enough. Reporters sued for not predicting the weather incorrectly. A strange turn of events tied to a fundamental popular misunderstanding of complexity.
The human mind adores simple rules. When things are complicated, we like to use analysis to break separate parts out, and solve them as separate problems. Thanks to Newton and Descartes, reductionists believe that all problems can be solved this way if you are patient enough to break large problems into enough pieces. It is reassuring to think that all things are knowable.
In stark contrast to this is idea that many phenomena are complex. That is, the internal dependencies are such that no part operates independently of the others. That is, you can not isolate a part of the problem and solve that independently of the other other parts. The weather. Earthquakes. An ecosystem. The marketplace. A social network. A business. And many more. They are all around us, but most people are blind to the implications.
In Italy scientists have been convicted for ‘false assurances’ before before earthquake. They reported that the series of earthquakes experienced were consistent with patterns normally seen, and a bigger quake unlikely. But earthquakes are inherently chaotic, and soon after that an unlikely record breaking 6.3 magnitude quake hit the town built mostly of un-reinforced masonry, and more than 300 people died. A tragedy to be sure, but is this the fault of the geophysicists?
Earthquakes are inherently unpredictable. Chaos theory give this a name: the butterfly effect which is also known as “sensitive dependence upon initial conditions” which refers to way that very very small perturbations can, over time, make a tremendous change in the outcome. Errors in reading the initial conditions do not smooth out and go away as time progresses (as would be expected from an Enlightenment view of the world) but instead these errors build up over time. This is not a flaw with the prediction model, but actually an intrinsic quality of the world. Some might consider it a success of science that so many people believe in the power to predict earthquakes to such an extent that the inability to predict one would be considered a crime.
Perhaps the field of geophysics could have been more vocal about the inability to predict anything about earthquakes — but that is misleading as well. There are certain trends that can be statistically predicted: i.e. California will have so many earthquakes averaging a certain magnitude over a period of years. The science can even be more helpful in predicting which parts of the land will be more or less effected on the average, or how to prepare in general for earthquakes. This is critically important. But at the same time there is no ability to predict a single event accurately to high precision. How can this make sense?
This idea of “unpredictability in the midst of relative stasis” is very hard for anyone to understand. Nicholas Nassim Taleb has written several books, most notably “Fooled by Randomness” where he takes wall street denizens to task for inventing narratives to explain the price swings in the stock market, when in fact those price swings have all the hallmarks of chaos. Finding explanations for observed behaviors is a survival skill that the human mind does naturally. Concluding that a behavior is “simply randomness” can be deeply disturbing, and most people reject it.
If the public at large is unwilling to accept that certain things are inherently random, what is next: suing the weatherman when he predicts incorrectly? In another story we find that a Belgian town may sue over soggy Weather Forecasts when the weather in fact turned out to be nicer than normal in some parts. People simply have an unjustified faith in the ability for scientists to predict the weather.
Human organizations and businesses also complex (a.k.a wicked problem). Certain macro trends can be seen in advance (e.g. approximately the number of people who will buy smart phones this month) and still details can be entirely unpredictable (e.g. whether a particular customer prefer an iPhone 5 or a Samsung Galaxy). The fact that general trends can emerge tends to convince people that with good enough models and powerful enough computers the entire market could be “solved” and laid out as a simple business process. We need to remember that complexity comes hand-in-hand with unpredictability.
One reason people find unpredictability so hard, is the assumption that a system can only “make” something simpler than itself. To make a complicated car takes a much more complicated factory. This seems intuitive, but Stephen Wolfram, in his book “A New Kind of Science” shows that incredibly complex patterns can emerge from incredibly simple calculations. I have literally illustrated this concept with the Julia Set (fractal) decorating this blog; an incredibly complex pattern that results from fundamentally a very simple calculation. Complex systems surround us, but without understanding them, we are blind.
If you want to know more about complexity, I can recommend an excellent book on the subject: in “Complexity: A guided tour” (see my review) Melanie Mitchell starts at the beginning and explains how all complexity result from iteration: weather systems are masses of air molecules repeatedly interacting, ecosystems have large numbers of organisms all interacting and competing, stock traders constantly trying to outwit each other, etc. The ability to explore complexity required computing systems. She explains Gödel’s Theorem, Turing’s Machine, and Wolfram’s Rule 110. I can’t recommend this book highly enough for anyone wanting to grasp the basics. Well written, non-mathematical treatment of an admittedly esoteric topic.
One can only hope for a better appreciation of unpredictability, because as long as there are misunderstandings about complexity, as long as the public believes that everything in the world is ultimately calculable, there will continue to be a high risk for any scientist working with complex phenomena that they will be blamed when the unpredictable happens.