ABSTRACT
Uncertainty arises at both macro- and micro-levels of knowing. Macro-level uncertainty reflects the changing and uncertain decision environment in which organizations exist. Micro-level uncertainty pertains to specific decision contexts and their relevant knowledge, data, and models. Uncertainty can be split into knowledge uncertainty (epistemic uncertainty) and natural variability (aleatory uncertainty). Scenarios, models, and quantities can be uncertain. Uncertain quantities include empirical quantities, defined constants, decision variables, value parameters, index variables, model domain parameters, and outcome criteria. Knowing the source of uncertainty in empirical quantities makes it easier to choose appropriate methods for addressing that uncertainty. These sources of uncertainty include random error and statistical variation, systematic error and subjective judgment, linguistic imprecision, variability, randomness and unpredictability, disagreement, and approximation. Risk analysis science requires practitioners to be intentional and transparent in their handling of uncertainty.
