Abbass H.A. Computational Red Teaming: Risk Analytics of Big-Data-to-Decisions Intelligent Systems

Springer, 2015. — 239 p.
This book is about elite types of thought processes and architectures for big data and modeling that can enable smart and real-time decisions. Today’s world is abundant with data and models; many new problems are formulated and solved everyday; many artificial-intelligence, mathematical, and statistical models exist, but there is a lack of scholarly work to demonstrate how to bring these data, models, and opportunities together to produce value for organizations. This book does exactly that and is written in a style designed to bridge management and computational scientists.
This is a book about Computational Red Teaming (CRT): a computational machine that can shadow the operations of any system. The Shadow CRT Machine can think together with, or on behalf of, the system by asking “what–if” questions, assessing threats and risks, challenging the system, environment, and competitors, and using its well-engineered predictive models and computational thinking tools to make the right decision at the right time. Red Teaming (RT) is traditionally a decision-aiding art used by the military to role play an adversary, play the devil’s advocate against one’s own concepts, plans, strategies, or systems to “test and evaluate” them to improve decision making. This book has been written to distill general principles from RT, and generalize and transform RT, the art, into CRT, the science. The discussion will depart from the military context to demonstrate the utility and applicability of CRT to individuals and organizations. CRT transforms the classical “test-and-evaluation” process to a continuous and proactive “test-and-redesign” process.