Chapter 8 broaches our understanding of communication systems and their intimacy with strategic practice. Beginning with the general (strategist) Napoleon’s forms of communication–technological warfare and the subsequent reliance on innovation in communication devices, especially those of coding and decoding communications in military conflicts, we consider the workings and implications of electronic, digital computing systems for strategy. Via Alan Turing’s Imitation Game, we introduce the debate on the nature of intelligence, consciousness and conscience (self-awareness), setting the scene for an elaboration on the development from cybernetics to contemporary machine-learning algorithms in the subsequent chapter.

Machine learning (ML) is a data-driven modeling approach that has become popular in recent years, thanks to major advances in software and hardware. Given enough data about a complex system, ML allows a computer model to imitate that system and predict its behavior. Unlike a deductive modeling approach, which requires some understanding of a system to be able to predict its behavior, the inductive approach of ML can predict the behavior of a system without ever understanding it in a traditional sense. Climate is a complex system, but there is not enough observed data describing an unprecedented event like global warming on which a computer model can be trained. Instead, it may be more fruitful to use ML to imitate a climate model, or a component of it, to greatly speed up computations. This will allow the parameter space of climate models to be explored more efficiently.