Understanding Uncertainty

Abstract

There is more information we don't know than we do know for making most critical decisions involving risks. Our focus must be on understanding and effectively dealing with what we don't know. As a first step in achieving this focus, a classification of the types of uncertainties that must be addressed and the sources of these types of uncertainties is presented. The purpose is to provide a framework for discussion about addressing uncertainty, particularly in risk analyses. Both uncertainty and variability of information are addressed using four main classes: Metrical uncertainty and variability in measurement, Structural uncertainty due to complexity, including models and their validation, Temporal uncertainty in future and past states Translational uncertainty in explaining uncertain results. The factors that contribute uncertainty and error to these classes are identified, and their interrelationships indicated. Both subjective and objective aspects are addressed.