Decoding Black Swans and Other Historic Risk Events

Shital Thekdi is a professor of analytics and operations at the University of Richmond. She has co-authored many papers on risk management and decision-making. She has a Ph.D. in systems and information engineering from the University of Virginia and an M.S.E. and a B.S.E. in industrial and operations engineering from the University of Michigan. She has several years of experience working in industry, with extensive supply chain management and operational analytics experience.Terje Aven has been a professor in risk science at the University of Stavanger, Norway, since 1992. Previously, he was also Professor (adjunct) in risk analysis at the University of Oslo and the Norwegian University of Science and Technology. He has many years of experience as a risk analyst in industry and as a consultant. He is the author of many books and papers in the field, covering both fundamental issues and practical risk analysis methods. He has led several large research programs in the risk area, with strong international participation. He has developed many master programs in the field and has lectured on many courses in risk analysis and risk management. Aven is the Editor-in-Chief of the Journal of Risk and Reliability, and Area Editor of risk analysis in policy. He has served as president of the International Society for Risk Analysis (SRA) and chairman of the European Safety and Reliability Association (ESRA) (2014–2018).

• Foreword About the Authors AcknowledgmentsChapter 1: Framework Used to decode the Risk EventsChapter 2: Historical Events to be Decoded Global Pandemics Industrial Accidents Infrastructure Failures Natural Disasters Acts of Terrorism and War Food Safety Chapter 3: Historical Perspective on Risk Chapter 4: Historical Precedent for Remembering and Understanding Risk Issues Chapter 5: Characterization of Surprise and Unpredictability Chapter 6: Severity of Consequences in Relation to Uncertainties and Knowledge Titanic case – Evaluation of Consequences Chapter 7: Uncertainty Characterizations Fukushima Daiichi Case – Evaluation of Probabilistic Risk Assessment at Nuclear Plants Chapter 8: Types of Knowledge That Inform Understanding of Risk 9/11 case – Classification of Knowledge Chapter 9: Credibility of Knowledge Food Additives Case – Credibility of Knowledge Chapter 10: Factors Influencing Understanding and Communication of Risk, Uncertainties, and Probabilities Cuyahoga River Fire – Communication of Risk-Related Information Chapter 11: Biases, Misinformation, and DisinformationBiases and Moral Hazards – East Palestine Train Derailment and Similar Freight AccidentsCOVID-19 Misinformation and Disinformation Chapter 12: Balancing Various Dimensions of a Risk ApplicationBP Oil Spill – Dimensions of Risk for Oil and Gas Operations and Related RegulationChapter 13: The Weight Given to ResilienceHurricane Katrina – Why New Orleans Was Vulnerable and How Resilience EmergedChapter 14: The Big Picture of Risk Science Surrounding Major Historical EventsTornadoes – The Big Picture Around Risk IssuesSmoking, Social Media, and Processed Foods – Linking Three Global Risk IssuesChapter 15: How Risk Science Improves the Ability to Address the Gaps in the Themes PresentedChapter 16: Who Is the Risk Analyst and What Are the ExpectationsChapter 17: Unresolved Issues in Risk Science Identified in the Presented ThemesAbraham Lincoln Assassination – Hindsight Bias versus Noise Leading to a Risk EventChapter 18: ConclusionsFurther Reading Index