Cybernetics is a word that immediately recalls those glorious years--about the middle of the last century--when the foundations of modern computer science (CS) were first laid. But more than 50 years later, is cybernetics still topical? Novikov gives us an answer with a short yet dense journey from the past to the future of cybernetics, by encompassing recent and heterogeneous trends in CS and related fields with surprising coherence.

The most classical interpretation of cybernetics concerns the scientific study of communication and control in systems (both of natural and artificial type). The most important findings in cybernetics can be related to its founder, Norbert Wiener, as well as a few other contemporary scholars such as William Ashby and Stafford Beer. They published their main results between 1948 and 1959, a decade Novikov calls “the romantic age” of cybernetics (which he renames cybernetics 1.0). This was followed by a long period of disillusion, perhaps due to overestimated expectations, and a more recent maturity period, which allows researchers to envision, with cleaner eyes, the prospects of this science in the future.

Novikov takes the reader along on a journey into the philosophical and methodological facets of cybernetics and related subjects like control, management, and system theory. He strives to show the reader that modern cybernetics is the “science of general regularities of control and data processing in animals, machines and society,” that is, Wiener’s cybernetics at the intersection of control theory, information theory, operations research, artificial intelligence, and so on. (In contrast, the classical interpretation of cybernetics is like an umbrella term, including all sciences dealing with problems of control and data processing.) To this end, he distinguishes between “cybernetics” and “Cybernetics” (yes, with different cases), the classical and modern interpretations of cybernetics, respectively.

In order to characterize modern cybernetics, Novikov discusses laws, regularities, and principles in cybernetics and related sciences, not without reasonable criticisms of the lightness with which some (often untrue) statements are elevated to principles (an example above all: the 80/20 principle, which some engineers are keen to apply almost everywhere).

As a general meta-theory, cybernetics can be applied to a number of topics with unexpected coherency, including networks (of all types), multiagent systems, and intelligent systems (the author does not spare some criticism on the abuse of the word “intelligent” in many inappropriate cases), as well as very recent topics such as big data management that, in perspective, call for new theories like big control.

On these bases, Novikov recognizes that organization is the new ingredient for future cybernetics (which he calls cybernetics 2.0), because organization is the preliminary process for designing and implementing systems, which are then controlled in their functioning. In this respect, an organization theory is called for as a new direction for future cybernetics, with the desired objective of improving the applicability of “strong” sciences (characterized by a rigorous scientific language) and at the same time the validity of results of “weaker” sciences (which have a less constrained language but produce fuzzier results).

The book is not an easy read, especially for those not accustomed to all the specificities of cybernetics. As a journey from the past to the future of cybernetics, at the end the voyager may feel fatigued by the extreme density with which complex concepts are reported and discussed. Also, the book gives a general impression of a subjective discussion in strict accordance with the personal viewpoint of the author. Nevertheless, the book is enlightening in showing the present and the future of cybernetics, as well as in proving that cybernetics is a science that must be present in the cultural background of any CS scholar.

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