In economics and management, uncertainty is frequently conflated with another fundamental aspect of decision-making: ***risk***. From a conventional perspective, rational agents are assumed to make choices based on projected outcomes, weighing the anticipated value of each decision. This value is often captured by a ***utility function***, which represents an agent’s preferences across a given set of options. Typically, expected utility is calculated by taking the weighted sum of utility values and multiplying them by their respective probabilities. However, this approach is built upon a series of assumptions—assumptions that often fail to hold up under scrutiny. Firstly, it presumes that the decision-making agent is perfectly rational, a notion contradicted by countless real-world examples of human behavior. Secondly, it assumes that agents possess a clear and accurate understanding of their values, their available choices, and the probability-weighted rewards of each decision—an idea increasingly challenged by findings in cognitive science, behavioral economics, and psychology. But perhaps most crucially, this model assumes that probabilities for each possible outcome are *knowable* in the first place. This conflation of risk with uncertainty represents a fundamental failure to maintain a distinction that was once well understood in economics. Towering figures such as John Maynard Keynes and Frank Knight were careful to differentiate ***risk*** from ***uncertainty***. More recently, economists Mervyn King and John Kay have revived this distinction, offering a precise framing of the issue: > *We have chosen to replace the distinction between risk and uncertainty deployed by Knight and Keynes with a distinction between **resolvable** and **radical** uncertainty. Resolvable uncertainty is uncertainty which can be removed by looking something up (I am uncertain which city is the capital of Pennsylvania) or which can be represented by a known probability distribution of outcomes (the spin of a roulette wheel). With radical uncertainty, however, there is no similar means of resolving the uncertainty – we simply do not know. (...) Radical uncertainty cannot be described in the probabilistic terms applicable to a game of chance. It is not just that we do not know what will happen. We often do not even know the kinds of things that might happen.*[^1] This distinction is crucial. ***Risk*** refers to a form of ***resolvable uncertainty***—the kind that can be tamed through prior knowledge, historical data, probability distributions, or statistical models. Risk applies when we can reasonably assign probabilities to different outcomes, such as the likelihood of rolling a six on a die, the probability of default on a financial loan, or the expected return of an investment portfolio based on past market behavior. But not all uncertainty is risk. ***Radical uncertainty*** represents the ***unknown unknowns***—the uncharted territory beyond our capacity to assign meaningful probabilities. These are situations where we not only lack the knowledge to determine outcomes but are also unable to enumerate the full range of possibilities in the first place. Unlike a game of roulette, where the number of potential results is known in advance, radical uncertainty describes an open-ended space in which new, unforeseen variables may emerge at any time. It is a critical mistake to treat radical uncertainty as if it were merely risk in disguise. Doing so gives a false sense of control, as if all unknowns could be captured in a neat probability model. Intellectual honesty demands that we recognize the limits of our knowledge and resist the temptation to smuggle radical uncertainty into the realm of calculable risk. Risk is ***not*** uncertainty. It is a special case of uncertainty—one that applies only when outcomes are well-defined and probabilities are known. But beyond the boundaries of resolvable uncertainty lies an abyss of unpredictability that no equation can contain. The challenge is not to collapse radical uncertainty into risk, but to develop tools that allow us to navigate the unknown without pretending it is something we can simply measure away. [[Probability|Next page]] <hr> [^1]: King, Mervyn A, and J A Kay. Radical Uncertainty : Decision-Making for an Unknowable Future. London, The Bridge Street Press, 2020.