In Search of Certainty During Uncertainty

The Author Diving in the Deep End

The declaration “I do not know.” may encompass the most powerful key to becoming more uncomfortable with the current and future age of uncertainty. We live in an age of perhaps the greatest uncertainty in our lifetimes. We are uncertain about disease, the economy, social care, travel and virtually every vital and meaningful element of our lives. Therefore, in order to better understand and embrace the age of uncertainty I have found that there may be several schools of thoughts that could produce silver linings within what many perceive to be very dark clouds.

First, during this time of increased uncertainty there is is an opportunity to seek and incorporate new ways of receiving advice and counsel from those who have had or are having similar stressful experiences. Therefore, I have turned to sources such as the German physicist Wilhelm Heisenberg who in 1927 observed, “The more precisely the position of some particle is determined, the less precisely its momentum can be predicted from initial conditions, and vice versa. ” To me this means that there will always be additional factors to consider when confronting any major event within our lives. Therefore, we must not only be prepared to say “I do not know” but also be prepared to observe more carefully and question what further information may be needed to satisfy our feelings of uncertainty.

Second, I believe we must carefully move from “I do not know.” to a state of knowing through probable prediction. During World War II, when the Atom bomb was being developed, scientists were faced with great uncertaintly regarding the lethal outcome of this deadly device. They developed the Monte Carlo simulation which is a computerized mathematical technique that allows people to account for risk in quantitative analysis and decision making. The technique is used by professionals in such widely disparate fields as finance, project management, energy, manufacturing, engineering, research and development, insurance, oil & gas, transportation, and the environment. During a Monte Carlo simulation, values are sampled at random from the input probability distributions. Each set of samples is called an iteration, and the resulting outcome from that sample is recorded. The Monte Carlo simulation does this hundreds or thousands of times, and the result is a probability distribution of possible outcomes. In this way, the Monte Carlo simulation provides a much more comprehensive view of what may happen. It tells you not only what could happen, but how likely it is to happen. Through the use of high speed computer technology, using the Monte Carlo simulation, millions of intergers may be entered and analysed in a brief period of time to determine the level of current and future risk or uncertainty.

The human brain is also capable of conducting deep risk analysis and therefore, I often use my own cerebral software to calculate the level or risk using a frequency and severity (intensity) matrix. Frequency measures how often something has occurred in the past and severity (intensity) measures the level of impact, for example, from the theft of an item to the loss of a human life. When these two factors are measured using a numerical scale ranging from unlikely to very likely, one can generally determine the probability of a future occurrence and its impacts.

Thirdly and finally, once we have admitted “I do not know.” and conducted an analysis of the probability of a future outcome based upon known variables, we may then act in a manner that allows us to transition more confidently from a state of complete uncertainty onto a more certain path. The word certain is derived from the Latin word certus that means settled or sure. Transitioning onto a more certain path, however, does not insure a settled or completely certain state.

According to Nassim Nicholas Taleb, his black swan theory or theory of black swan events is a metaphor that describes an event that comes as a surprise, has a major effect, and is often inappropriately rationalised after the fact with the benefit of hindsight.

Upon any future path you select it is possible and highly probable to encounter various black swans such as disease, economic distruption, technological advancement and many more surprises that may, depending upon how they are addressed, produce negative and / or positive impacts.

However, Taleb does not regard the Covid 19 pandemic as an actual black swan as it was, he believes and has argued, highly predictable. He states in his most recent book Antifragile (2012) that countries must now create the institutional equivalent of “circuit breakers, fail-safe protocols, and backup systems” to address even predictable surprises such as the current global pandemic. In fact, he is suggesting that governments must do a better job of planning for and managing future risks. I believe the same is true of individual citizens as we navigate from total uncertaintity to a world where we may once again confidently connect, collaborate and co – habitate to create new and more sustainable communities of positive social innovation.

To find the best way forward to arriving at this future destination we must, when asked for an emperical answer, always began with “I do not know.” From this starting point, there will be many probable answers that may produce greater certainty in our increasingly uncertain world.

Sources

Heisenberg, W. (1927), “Über den anschaulichen Inhalt der quantentheoretischen Kinematik und Mechanik”.

Palisade, (2020) viewed: https://www.palisade.com/risk/monte_carlo_simulation.asp

Taleb, Nassim Nicholas (2012) Antifragile. New York, NY: Random House.

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