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Cassandra, of Greek myth, had the gift of prophecy but the curse of never being believed. In this book, authors Clarke and Eddy turn to modern day Cassandras--those who warn of dire events but whose warnings are unheeded. The book starts with multiple chapters, each dedicated to a different catastrophe. Each catastrophe is explained, with the authors outlining the factors that made each disaster particularly harrowing, and then we are introduced to the individual or individuals who predicted the event, tried to get the powers that be to mitigate it, but were ignored. This ranges from the Madoff scandal to the Fukushima Daiichi nuclear calamity, from the rise of ISIS to the formation of Hurricane Katrina and its fallout. In each instance, the authors have interviewed the Cassandra in question, parsed the technical expertise that underpinned the predictions, and examined the impact (short and long term) of failing to take the warnings seriously.
The second half of the book looks to the future. Bridging the past predictions and future warnings is a chapter where the authors introduce their "Cassandra Coefficient." They use this coefficient to examine how likely a person making a prediction is actually a Cassandra (meaning they have the expertise and grounding to understand the potential for cataclysm and make predictions that will likely come to pass). They also build into the coefficient a number of factors, including how complex the underlying issues are, if decision makers that could avert disaster are diffuse, and whether the predictions is do novel and dire that others have trouble comprehending it or taking it seriously.
Having articulated their coefficient and the way it can be used to differentiate between a Chicken Little and a true Cassandra, they turn to six issues that may pose existential threats to humanity if they are both true and underestimated or ignored. The authors use these potentially looming threats as case studies, aping the chapter structure in the first half of the book but inserting a discussion of the Cassandra candidates' coefficients rather than a discussion of why they were right. In doing so, the authors look at the threats of AI, pandemics, rising sea levels, nuclear winter, the internet of things, meteor strike, and gene editing. These chapters not only crystallize nascent threats, but in many instances also act as overviews of cutting edge technologies and science (with the exception of pandemics, which instead reintroduces the reader to the world that used to be the norm -- where illness lurked around every corner).
Overall the book is well done. It covers a wide range of issues and has the perfect amount of detail to leave the reader well versed in past and future threats. The content is interesting though unsettling. Though some of the potential disasters have lower probabilities in any given lifetime (meteor strike), others are either always possible and have happened before (pandemic) or are already in progress (sea level rise). This gives the reader the not unwarranted feeling that we are not doing enough and may even be too late. My biggest complaint in their book is their failure to mention or synthesize some of the work of Dan Gardner and Philip E. Tetlock (Superforecasting, 2015), which looked at predictions and made the point that experts in a field are often terrible at prediction. In their book, the examined why hedgehogs (those with deep knowledge in one area) are often unable to have the perspective needed to truly examine and weigh and measure facts and sources. Such experts often become over-invested in certain theories or practices, and that results in less accurate predictions and a failure to adapt their predictions as necessary or properly evaluate new information. In that book the authors examined how foxes (those with less in depth knowledge but a willingness to constantly question their conclusions) often were better at prediction. This cuts against one major part of the Cassandra Coefficient, which talks about ability to be a first order thinking, bringing new ideas to bear and being data driven. I wonder if some of the most effective Cassandras will not be strictly experts in a field, but those with some expertise but no pure investment in one line of thinking. Nevertheless, well worth a reader's time.
The subject is very good, but the verbal narration is not that good. Audible needs to work on finding better narrators.