‘black swans’, ‘dragon kings’ and beyond: Towards predictability and suppression of extreme all-hazards events through modeling and simulation

Abstract

Shocks to regional, national and global systems stemming from natural or man-made hazards can have dramatic implications. Disasters such as Katrina (2005), Hurricane Sandy (2012), Alberta (Canada) Floods (2013), and Super Typhoon Haiyan (2013) are examples that highlight the vulnerability of communities to natural hazards and the crippling effect they have on the social and economic well-being. Through foresight and scenario planning, such events can be expected but can they be predicted to support resilience and enable suppression of the impacts? With consideration of emerging and systemic risks and inherent uncertainty associated with surprising events, planning for and managing risk, crisis and disasters requires understanding of the outliers that challenge our resilience. ‘Black Swans’ represent the unpredictable. They represent “… our misunderstanding of the likelihood of surprises” (Taleb in The black swan: the impact of the highly improbable, 2007). A ‘Black Swan’ is described by Taleb (2007) as that which is an outlier, that which is outside the realm of regular expectations which carries with it an extreme impact such as natural disasters, market crashes, catastrophic failure of complex socio-technical systems and terrorist events such as 9/11. Sornette (Int J Terraspace Sci Eng 2(1):1–18, 2009) identifies a different class of extreme events (outliers) that he calls ‘Dragon Kings’. Sornette (2009) argues that Dragon Kings may have properties that make them not only identifiable in real time but also predictable. The evolving science on complexity (and, more specifically, on complex networks) and on resilience suggest that modeling and simulation of such extreme events can assist in the predictability and the suppression of low probability extremely high consequence events such as natural hazards (flood, earthquake, wildfire, tsunami, extreme weather), cyber-attacks, and financial events. Furthermore, the science of complex networks is developing rapidly and has fundamentally reshaped our understanding of complexity, potentially leading to innovative methods for the prediction of emergent behavior on natural and technological networks, as well as specific strategies for designing networks that are more resistant (resilient) to both failure and attack. Governments and owners of critical physical and digital infrastructure may benefit from analyses, advice and exercises that involve predictable and suppressible “Dragon-King” type of low probability extremely high consequence extreme events, as well as from the utilization of recent advances in complex network theory, to ultimately enhance resiliency. This chapter contributes to the discourse on Dragon Kings arguing for continued and concerted efforts to explore this domain.