The Dangerous Illusion That Governments Know How to Fight Coronavirus

An algorithm, according to the website Math Vault, is “a finite series of well-defined, computer-implementable instructions to solve a specific set of computable problems.” Indeed, for most of us, the solution of everyday problems is based on the use of pragmatic linear algorithms: given A (a burned-out lightbulb, a soccer team that frequently loses, a marital crisis), the required course of action is B (replace the lightbulb, fire the coach, couples therapy, etc.). However, in contrast to replacing a lightbulb, firing a coach rarely solves the problem. 

Life, in short, is not simple. Yet, most of us rely on astonishingly simplistic algorithmics for problem solving. The coronavirus offers us all an excellent opportunity to snap out of the simplistic linear illusion, certainly where medicine is concerned. The model to which we’ve been habituated – that a virus is treated with antibiotics, and that the treatment for diarrhea is a rice diet –  doesn’t work when we encounter complex biological systems. In these situations, simplicity is supplanted by complexity. The division of viruses into good and bad has now been replaced by the insight that the disposition of microbes in our body does not determine only whether (linearly) we will develop a fever, but also (complexly) how much weight we’ll put on.

Stacey’s Matrix, formulated by the South African economist Ralph D. Stacey, provides a number of important insights into this complexity. To fight the coronavirus, we have all been requested, in the name of linear cause-and-effect relations, to lock ourselves in, so as “to flatten the curve.” This abruptly raised – through a controversial decision-making process – a far more complex curve: people forced into unemployment. Overnight, and without a 14-day incubation period, the economy, a no less complex field than medicine, was afflicted by a new ailment: the leave-without-pay sickness. Only time will tell who will cure it, when and how.

According to Stacey’s model, which originates in the world of management, there are two axes of reference that determine the latitude for decision-making processes. The X axis in the graph refers to the level of the resultant certainty of a particular event. It does not deal with future prediction or prophecy, but with evaluating a probabilistic situation. The more familiar we are with a past event, the easier it is to evaluate what is going to happen, and the less familiar we are, the more difficult it will be. If it’s a “black swan,” something we’ve never before encountered, it will be more difficult to evaluate what the new situation will look like.  

Stacey’s Matrix.

Both those who believe that the coronavirus is at most another type of flu, and those who maintain that it’s the most serious epidemic since the Spanish flu, will be on the left side of the X axis; while those who maintain that the numbers and the data that are being bandied about are not reliable, and therefore it’s impossible to know what is really happening or will happen, will be far on the right side of the X axis. 

The Y axis, in contrast, does not deal with future probability, but with the organizational agreement around the values of the present – and where the coronavirus is concerned, with each community’s social pact. The broader the consensus (for example, in Israel,  “Do not cast me off in old age,” or “We expect our soldiers to defend us” are sentiments most people can identify with), as indicated on the lower part of the Y axis, the easier it is for society to make decisions, even if they entail a steep price.  

And vice versa: the more that substantive and fundamental differences of values exist concerning the motives behind the decisions, concerning the correct point of balance between individual freedom and the common good, and concerning the personal-social price that we are liable to pay, the more difficult it is to arrive at universally agreed decisions (the upper part of the Y axis).