Black Swans

What do Google, Lehman Brothers, religion and 9/11 have in common?

In his 2001 and 2007 best-sellers[1], Lebanese-American author and thought Leader Nassim Nicholas Taleb develops the Black Swan Theory, by providing empirical facts and theoretical frameworks, to the notion of unlikely events. A Black Swan is an outlier event which — ex-ante — is considered impossible and hard-to-predict, but it has long-lasting and drastic consequences, by changing the course of our history. And finally — ex-post — much effort goes into concocting deterministic explanations that make it sound less random, and more part of the domain of destiny.

In Latin early 2nd century poetry, a black swan was an allegory for rarity: in the boundaries of the known world of the time, swans could only be white. Nearly sixteen centuries later, European explorers in Australia made their first encounter with a black swan, a bird indigenous to the area ever since the black swan is a metaphor of unlikely, nearly-impossible-to-predict, outliers events.

The most common misconception of foresight is that the discipline has the tools to forecast black swans before they happen. In the words of Dr Stefanie Babst from NATO Strategic Analysis and Planning[2]:

“For sure, strategic foresight is not about predicting the future. Nobody can predict what precisely the year(s) to come will bring. But understanding key global and regional trends, detecting critical uncertainties and risk factors and developing scenarios about potential future developments makes a lot of sense if one wants to avoid nasty surprises.”

In a nutshell, developing black swan scenarios in a foresight context is more about the “what if” and “how to” than the “what” and “when”. In recent expert interviews in the automotive sector, one clear pattern emerged: automotive executives are afraid of the increasing digitalization of the car — which on the other end they welcome, as it increases the value of the car in an otherwise shrinking industry. They mostly fear the emergence of a “car operating system” which might do to car manufacturers what Microsoft DOS and Windows did to computer producers in the 90s: commoditize them and make them irrelevant. If this were to be a black swan event, the key for the automotive executive would be to identify scenarios in which, upon the emergence of a dominating car operating system, cars would not be commodities. Build stronger and sustainable franchises. The truth to the matter is that they are spending a lot of time and resources fighting for the black swan not to happen. In other words, foresight will not provide the tools to prevent another unpredictable financial crisis, but it will be useful to identify the leverages, the scenarios and the resources needed to survive one.

In addition to that, it is worth to pause further on the notion of predictability of rare events. Assuming that history was to repeat itself and that the past would be a good proxy for future occurrences — which is not — a unique event is — by definition — an outlier, an event with a tiny small probability of manifesting. To statistically predict its future occurrences, within a certain degree of confidence, we would need to have a large data set, containing many examples of those rare events, which is impossible by definition! In addition to that, history does not repeat itself, and the black swans are events so rare, to be unpredictable, because of the many complex forces underlying them. As Mark Blyth summarizes it:

“[Taleb] also rightly notes that ever‐increasing quantities of information are relevant only in simple situations, such as in predicting the range of human height, but are misleading in more random arenas, such as financial markets. “

Black Swans: so what?

The bottom line is that from black swans, past, and future, we can learn how to build stronger and more robust companies and institutions. In his 2009 Financial Times Article[3], Taleb — himself a former investment banking trader — proposes “Ten principles for a Black Swan-proof world” as a way to prepare our society from the next rare financial crisis, by assessing the key learning from the 2007–8 financial black swan:

1. What is fragile should break early while it is still small: evolution relies on black swans to separate the weak from the strong.
2. No socialisation of losses and privatisation of gains.
3. People who were driving a school bus blindfolded (and crashed it) should never be given a new bus: There should be no second chance for the people and institutions who lead society to the financial crash.
4. Do not let someone making an “incentive” bonus manage a nuclear plant — or your financial risks: incentives only work when there are clear disincentives; otherwise we separate risks and returns.
5. Counter-balance complexity with simplicity: capitalism is a globalized world is more prone to bubbles. But the more complex the product, the harsher the aftermath of the bubble.
6. Do not give children sticks of dynamite, even if they come with a warning. It is not enough to label derivatives as complex and therefore dangerous. If the traders do not fully understand the risks, and the buyers do not understand the risk, and the watchdogs, audit and certification institutions do not understand the risks, the warning will not be enough.
7. Only Ponzi schemes should depend on confidence. Governments should never need to “restore confidence”.
8. Do not give an addict more drugs if he has withdrawal pains.
9. Citizens should not depend on financial assets or fallible “expert” advice for their retirement.
10. Make an omelette with the broken eggs.

In conclusion

The emergence of Google, the demise of Lehman Brothers, the growth of monotheistic religions and the tragedy of 9/11, are all black swan: rare and unpredictable, landscape changing and unstoppable, and random, despite our efforts to rationalize them. Strategic foresight cannot predict black swans, but can help assessing future the “what if” and “so what” of possible rare events in the future, by providing a framework to understand the implications of an operating system emerging in the automotive sector, or an AI singularity, or even the monopolization of all grocery retail.

References

[1]Taleb, N.N., 2001. Fooled by Randomness: The Hidden Role of Chance in the Markets and in Life.

Taleb, N.N., 2007. The black swan: The impact of the highly improbable (Vol. 2). Random House.

[2] https://www.securityconference.de/news/article/natos-strategic-foresight-navigating-between-black-swans-butterflies-and-elephants/

[3] https://www.ft.com/content/5d5aa24e-23a4-11de-996a-00144feabdc0

Originally published at blog.thefutureof.report on January 31, 2019.