Accounting for Unknown Unknowns in Managing Multi-hazard Risks

A significant challenge in managing multi-hazard risks is accounting for the possibility of events beyond our range of experience. Classical statistical approaches are of limited value because there are no data to analyze. Judgment or subjective assessments are also of limited value because they are derived from within our range of experience. This chapter proposes a new framework, Decision Entropy Theory, to assess probabilities and manage risks for possibilities in the face of limited information. The theory postulates a starting point for assessing probabilities that reflect having no information in making a risk management decision. From this non-informative starting point, all available information (if any) can be incorporated through Bayes’ theorem. From a practical perspective, this theory highlights the importance of considering how possibilities for natural hazards could impact the preferred alternatives for managing risks. It emphasizes the role for science and engineering to advance understanding about natural hazards and managing their risk. It ultimately underscores the importance of developing adaptable approaches to manage multi-hazard risks in the face of limited information.