When Black Swans Aren't: On Better Recognition, Assessment, and Forecasting of Large Scale, Large Impact, and Rare Event Change

ABSTRACTThe article discusses professional best practice implications stemming from differing varieties of thinking about black swans. The possibilities of rare event recognition in general, and the conforming limits on the forecasting art that arise from different views of possibilities is addressed. In particular, assessing how different philosophical groundings partner with methodological and practice implications to shape and limit practice possibilities is highlighted. Opportunities for securing comparative advantages-individual, organizational, and societal-are revealed by introducing holistic methods for better recognizing, assessing, and managing emerging large scale, large impact, rare events thought by most people to be unpredictable black swans. To achieve this, the article uses mainstream model and analyst failure dynamics to develop a way to better recognize and time large scale, large impact rare event emergence. As part of this discussion, the article assesses the philosophical and factual bases of Nassim Taleb's famous book, The Black Swan: The Impact of the Highly Improbable, and argues that strong-version black swan perspectives (views that meaningful forecasting is not possible in an essentially chaotic world where rare black swans shape reality) are significantly responsible for placing unreal limits on the very possibilities of improving professional best practices, they being grounded in philosophical traditions that needlessly constrain better training, and competent risk assessment and futures forecasting.IntroductionBelief systems guide behavior and shape professional practice (Pinker, 2003), especially taught views about best practices, and consequently influence individual, organizational, and societal effectiveness. Worse than not knowing how to do something within an admittedly complicated, changing world is believing that it cannot be done, behaving accordingly, and then building up societal and professional systems and "best practices" upon false foundations. That is the summary effect, this article argues, of strong varieties of black swan thinking, particularly Nassim Taleb's influential version (Taleb, 2007), wherein it is argued on philosophical grounds that the future cannot be forecast, and especially that large impact, large scale, rare events (LSLIRE)1 and their implications, cannot be foreseen.The world, and change within it, such people argue, is simply too complex, too random, too chaotic to forecast. Because of this, the realm of the possible and of best practice is shaped in very particular philosophically constrained ways. Both quantitative, including statistical, and qualitative foresight and forecasting methods are chimeras: impossible to rely on tools, especially for LSLIRE foresight (Taleb, 2007). Success is luck,2 forecasting expertise, like the teaching of risk assessment and futures forecasting, is fraud, selfdelusion, or foolishness, while the best way to organize society involves building up resilience in the face of the unforeseeable and learning to "benefit from disorder" (Taleb, 2012; Milner, 2012). Indeed, strong-view black swan proponents maintain that society needs to be reorganized around a black swan-based philosophically grounded opinion: "Some make the mistake of thinking that I hoped to see us develop better methods of predicting black swans To deal with black swans, we instead need things that gain from volatility, variability, stress and disorder" (Taleb, 2012).This strong version of black swan centrality is argued even as normal-range event forecasters - recently Nate Silver (2012) - correctly forecast each states' electoral vote in the 2012 U.S. presidential election and crisis (LSLIRE) event forecasters actually do correctly foresee and forecast emergences, including events that Taleb labels as unpredictable black swans.Alternatively, if, philosophically speaking, events commonly labeled as unpredictable black swans, with their implications, can often be recognized, assessed, and sometimes even managed, and if, more broadly, emerging futures, including LSLIREs, can be forecast, then how professionals teach, do, and evaluate best practices in actuarial science, insurance, political economics, risk management, business, government, and other professions concerned with knowing the future can be improved. …