The epistemic uncertainty of COVID-19: failures and successes of heuristics in clinical decision-making
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The epistemic uncertainty of COVID‑19: failures and successes of heuristics in clinical decision‑making Riccardo Viale1 Received: 6 August 2020 / Accepted: 6 October 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The brief article deals with the following questions: Was the adaptive toolbox of heuristics ecologically rational and specifically accurate in the initial stages of COVID-19, which was characterized by epistemic uncertainty? In other words, in dealing with COVID-19 did the environmental structural variables allow the success of a given heuristic strategy? Keywords Uncertainty · Heuristics · COVID-19 1) Real-life problems occur within a complex and uncertain environment. These are typically ill-defined problems, that is, the goals are not definite; we do not know what qualifies as an alternative and how many alternatives there are; it is unclear what the consequences might be and how to estimate their probabilities and utilities. This environment may also be called Large World (Savage 1954) and it is characterized by uncertainty. Small Worlds are, by contrast, theoretically predictable and without surprises and they are characterized by the knowledge of all relevant variables, their consequences and probabilities. Science aims to transform Large World problems into Small World problems (Viale 2020). This is possible only when Large World problems are characterized by epistemic uncertainty and not by fundamental or ontological uncertainty. The first kind of uncertainty occurs when, ideally, empirical research and the collection of data are able to supply statistical figures that characterize relevant variables, their consequences and probabilities. The second kind of uncertainty deals with events that empirical research is not able to represent probabilistically because of complexity or unpredictable surprises. The first kind of uncertainty usually applies to most biomedical research (for example, trials for a new drug) whereas the second
* Riccardo Viale [email protected] 1
University of Milano-Bicocca, Milano, Italy
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applies to macro-political, environmental and financial phenomena (for example, the prediction of a financial crisis). COVID-19, like any other infection, is typically characterized by epistemic uncertainty.1 In a few years biomedical research will be able to define its viral behavior and possible treatments. But the question is: How can we cope with this infection today and what kind of decision-making would be preferable? What kind of decision-making processes are able to match uncertain environmental tasks and solve the problems? This is an empirical question that was addressed some years ago by cognitive scientists like Herbert Simon, Vernon Smith, Richard Selten and particularly, more directly, Gerd Gigerenzer and the Abc group (Gigerenzer, Todd, and the Abc Group, 1999). The adaptive toolbox of formalized heuristics is the result of those empirical investigations. When dealing with a number o
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