Outside of the field of risk analysis, an important theoretical conversation on the slippery concept of uncertainty has unfolded over the last 40 years within the adjacent field of environmental risk. This literature has become increasingly standardized behind the tripartite distinction between uncertainty location, the nature of uncertainty, and uncertainty level, popularized by the “W&H framework.” This article introduces risk theorists and practitioners to the conceptual literature on uncertainty with the goal of catalyzing further development and clarification of the uncertainty concept within the field of risk analysis. It presents two critiques of the W&H framework's dimension of uncertainty level—the dimension that attempts to define the characteristics separating greater uncertainties from lesser uncertainties. First, I argue the framework's conceptualization of uncertainty level lacks a clear and consistent epistemological position and fails to acknowledge or reconcile the tensions between Bayesian and frequentist perspectives present within the framework. This article reinterprets the dimension of uncertainty level from a Bayesian perspective, which understands uncertainty as a mental phenomenon arising from “confidence deficits” as opposed to the ill-defined notion of “knowledge deficits” present in the framework. And second, I elaborate the undertheorized concept of uncertainty “reducibility.” These critiques inform a clarified conceptualization of uncertainty level that can be integrated with risk analysis concepts and usefully applied by modelers and decisionmakers engaged in model-based decision support.
The uncertainty language framework used by the Intergovernmental Panel on Climate Change (IPCC) is designed to encourage the consistent characterization and communication of uncertainty between chapters, working groups, and reports. However, the framework has not been updated since 2010, despite criticism that it was applied inconsistently in the Fifth Assessment Report (AR5) and that the distinctions between the framework’s three language scales remain unclear. This article presents a mixed-methods analysis of the application and underlying interpretation of the uncertainty language framework by IPCC authors in the three special reports published since AR5. First, I present an analysis of uncertainty language term usage in three recent special reports. The language usage analysis highlights how many of the trends identified in previous reports—like the significant increase in the use of confidence terms—have carried forward into the special reports. These observed trends, along with ongoing debates in the literature on how to interpret the framework’s three language scales, inform an analysis of IPCC author experiences interpreting and implementing the framework.
"Mission-oriented" public research organizations invest in R&D to improve decision-making around complex policy problems from climate change to asteroid impacts, thus producing public value. However, the estimation of benefits produced by such R&D projects is notoriously difficult to predict and measure - a challenge that is magnified for global catastrophic risks (GCRs). GCRs are highly uncertain risks that may pose enormous negative consequences for humanity. This article explores how public research organizations systematically reduce key uncertainties associated with GCRs. Building off of recent literature highlighting the organizational and political factors that influence R&D priority-setting at public research organizations, this article develops an analytical framework for explaining R&D priority-setting outcomes that integrates the key stages of decision analysis with organizational and political dynamics identified in the literature. This framework is then illustrated with a case study of the NASA Planetary Defense Coordination Office, which addresses the GCR of near-Earth object (asteroid and comet) impacts. The case study reveals how organizational and political factors interact with every stage in the R&D priority-setting process - from initial problem definition to project selection. Lastly, the article discusses the extent to which the case study can inform R&D priority-setting at other public organizations, particularly those addressing GCRs.