The Black Swan Problem. Håkan Jankensgård

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CHAPTER ONE The Swans Revisited

      THE BLACK SWAN OF the popular imagination is one that swoops down from a clear blue sky, creating massive disorder in a very short amount of time. We expect it to be sudden and dramatic. The archetypical Black Swan is perhaps the 9/11 attack on the twin towers in New York in 2001. Virtually nobody could have been able to imagine such a thing. It was simply not on the mental map that something like that should even exist. Yet it happened, and in a single stroke, the world was a different place. The path we were on changed. The attack led to a whole new security apparatus, the war on terror, and the war in Iraq, to mention but a few of its consequences.

Actually, the ‘out of the blue’ aspect is not part of the original framework. Some Swans cited by Taleb take years if not centuries to play out. According to Taleb, Black Swans have just three attributes, none of which refers to suddenness. First, they are highly improbable. Second, they are highly consequential. Third, they make perfect sense after the fact.¹ When people talk about Black Swans it is usually the first two aspects they focus on, as if the term were essentially shorthand for low probability high impact risks. Simplifying in this way is wholly consistent with the reason that the Black Swan problem exists in the first place, reflecting as it does our tendency to reduce the number of dimensions of the phenomenon before us down to something more tractable and convenient.

      Equating Black Swans with ‘mere’ low probability high impact risk, however, is to do the concept significant injustice. In reality, the Black Swan framework is valuable because it represents an altogether different way of approaching the world. Taleb asks us to reconsider some of our core assumptions about the very nature of the randomness we face as decision‐makers and the inferences we make based on what we can observe. Furthermore, he brings our attention to the crucial role of expectations and attitudes in dealing with uncertainty. The problem, Taleb explains, is one of not being humble enough with respect to the limitations of our knowledge. If we believe the world consists of a certain kind of randomness and that we can have mastery over it, we may be in for some pretty bad surprises if those beliefs do not conform with reality. We can try to impose crisp and stylized ideas that appeal to our aesthetic sensibilities as much as we want, but the chaotic world we live in refuses to bend. This insistence on abstract beauty is what Taleb has in mind when he labels something as ‘Platonic’, after the famed Greek philosopher who saw loveliness in order and maintained that it could be superimposed on the messy reality we can observe with our senses (Taleb, 2007, p.19).

THE NATURE OF RANDOMNESS

      Randomness refers to unpredictability. It applies whenever the outcome for some variable, such as the number of visitors to the Louvre on a given weekday, cannot be known with certainty beforehand. It is a function of our inability to know and predict the future. Try as we might, we never seem able to build those perfect forecasting algorithms that get it right all the time. In fact, as Taleb is at pains to point out, our overall track record in forecasting is awful (more on this later).

Why is there a general failure to predict what the future will bring? To answer this question, first consider that one very basic source of randomness is the physical world itself, which is constantly changing through processes that we do not fully comprehend. Science marches on, chipping away at the ignorance that produces apparent randomness. But despite the many laws of nature that have been uncovered, we never know where the next lightning will strike or how ocean currents will respond to changes in melting ice sheets. In the end, there are too many variables and too many complicated feedback loops in these highly dynamic systems. On top of that there is human civilization itself. While once rudimentary and mostly local, over time society has become complex beyond imagination. Technical innovations have made possible advanced systems that increasingly connect people across different parts of the globe. It is fundamentally unknowable what outcomes these vast and interconnected systems of interacting people and technologies will produce. Human agency by itself ensures why the future keeps bringing so many surprises, as the 9/11 attack illustrates. It should be clear that we are up against a complexity that is beyond our ability to predict successfully.

The difficulties we face in predicting the future is related to the problem of induction, a classic problem in philosophy. While data can certainly teach us a great deal about the workings of the world, the philosopher and sceptic David Hume made us realize that we cannot arrive at secure knowledge on the basis of empirical observations. The problem of induction says that no matter how many observations you obtain, you cannot know for sure that the observed pattern is going to hold in the future. This inherent limitation is at the heart of the Black Swan concept. Any knowledge obtained through observation, Taleb says, is fragile. It is what the Black Swan metaphor itself is meant to convey. Recall that millions of observations on white swans had seemingly verified the notion that all swans are white, and it only took one observation of a black one to falsify it. Along the same lines, Peter Bernstein (1996) observed in his epic story about risk that: ‘… history repeats itself, but only for the most part’² (emphasis added). This sentence really sums it all up and explains why induction is treacherous ground for making СКАЧАТЬ