Many workers in the biological sciences-physiologists, psychologists, sociologists-are interested in cybernetics and would like to apply its methods and techniques to their own speciality. Many have, however, been prevented from taking up the subject by an impression that its use must be preceded by a long study of electronics and advanced pure mathematics; for they have formed the impression that cybernetics and these subjects are inseparable. The author is convinced, however, that this impression is false. The basic ideas of cybernetics can be treated without reference to electronics, and they are fundamentally simple; so although advanced techniques may be necessary for advanced applications, a great deal can be done, especially in the biological sciences, by the use of quite simple techniques, provided they are used with a clear and deep understanding of the principles involved. It is the author's belief that if the subject is founded in the commonplace and well understood, and is then built up carefully, step by step, there is no reason why the worker with only elementary mathematical knowledge should not achieve a complete understanding of its basic principles. With such an understanding he will then be able to see exactly what further techniques he will have to learn if he is to proceed further; and, what is particularly useful, he will be able to see what techniques he can safely ignore as being irrelevant to his purpose. The book is intended to provide such an introduction. It starts from commonplace and well-understood concepts, and proceeds, step by step, to show how these concepts can be made exact, and how they can be developed until they lead into such subjects as feedback, stability, regulation, ultrastability, information, coding, noise, and other cybernetic topics. Throughout the book no knowledge of mathematics is required beyond elementary algebra; in particular, the arguments nowhere depend on the calculus (the few references to it can be ignored without harm, for they are intended only to show how the calculus joins on to the subjects discussed, if it should be used). The illustrations and examples are mostly taken from the biological, rather than the physical, sciences. Its overlap with Design for a Brain is small, so that the two books are almost independent. They are, however, intimately related, and are best treated as complementary; each will help to illuminate the other. vi

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Many workers in the biological sciences-physiologists, psychologists, sociologists-are interested in cybernetics and would like to apply its methods and techniques to their own speciality. Many have, however, been prevented from taking up the subject by an impression that its use must be preceded by a long study of electronics and advanced pure mathematics; for they have formed the impression that cybernetics and these subjects are inseparable. The author is convinced, however, that this impression is false. The basic ideas of cybernetics can be treated without reference to electronics, and they are fundamentally simple; so although advanced techniques may be necessary for advanced applications, a great deal can be done, especially in the biological sciences, by the use of quite simple techniques, provided they are used with a clear and deep understanding of the principles involved. It is the author's belief that if the subject is founded in the commonplace and well understood, and is then built up carefully, step by step, there is no reason why the worker with only elementary mathematical knowledge should not achieve a complete understanding of its basic principles. With such an understanding he will then be able to see exactly what further techniques he will have to learn if he is to proceed further; and, what is particularly useful, he will be able to see what techniques he can safely ignore as being irrelevant to his purpose. The book is intended to provide such an introduction. It starts from commonplace and well-understood concepts, and proceeds, step by step, to show how these concepts can be made exact, and how they can be developed until they lead into such subjects as feedback, stability, regulation, ultrastability, information, coding, noise, and other cybernetic topics. Throughout the book no knowledge of mathematics is required beyond elementary algebra; in particular, the arguments nowhere depend on the calculus (the few references to it can be ignored without harm, for they are intended only to show how the calculus joins on to the subjects discussed, if it should be used). The illustrations and examples are mostly taken from the biological, rather than the physical, sciences. Its overlap with Design for a Brain is small, so that the two books are almost independent. They are, however, intimately related, and are best treated as complementary; each will help to illuminate the other. vi

No abstract

to the purposes and motivations of the human makers of the rules. Following the Ashby "own world" formulation, a machine is not going to take a dislike to some human cultural manifestation (religion, ideology, lifestyle) in ways that perpetuate strife. AccountabilityWhere, then, is accountability when technology takes the place of functions formerly performed by human beings, or introduces functional capability that was not even possible before? Mechanisms do not have responsibility for their own actions. When technology is woven ever more tightly into the fabric of our lives, there is an accountability that includes both the creator and the installer of the technology. This linkage is not always understood as an explicit responsibility, and is a dangerous point of potential abdication of responsibility. Clarifying and making explicit the accountabilities, which are evolving at the combined rate of evolution of technology and prevailing social preferences, falls into the domain of the systems engineer. What this means is that the system practitioners are accountable for system's effects upon relevant stakeholders and sponsors. Accordingly, system practitioners must develop the methods and tools to keep increasingly autonomous and complex techno-institutional systems within acceptable envelopes of determinism. This implies an emphasis on aligning the desires of participants and beneficiaries with institutional as well as technological architectures.This leads to two main questions. First, how shall we assess whether the human-activity system that performs systems engineering ensures harmony of sponsor requirements with the rules of the intended operations context? Second, how shall we assess whether a system, when realized and activated according to the systems engineering model, will perform, associate, and evolve in accordance with the societal rules currently in force? Non-Determinism in Systems EngineeringEric D. Smith, eric.smith@incose.org T he question "What is a system?" can be asked and answered differently, but the fact that the question refers to a whole-called a "system"-remains. This article shows how a conceptual structuring by abstraction levels with complementary qualitative and quantitative aspects clarifies the nature of a system without resort to strict noncomplementary hierarchical decompositions that ignore complexity. The goal of this work is to foster a fuller cognizance of system descriptions, including model-based systems engineering (MBSE), in which complete and consistent descriptions are sought. A difficulty not currently addressed by MBSE is the inclusion of systems qualities, such as holistic, non-deterministic, and emergent, without which there can be no true description of complex systems.Complexity in mathematical formalizations can be perceived through the presence of intriguing members of mathematics, including random numbers, transcendental numbers, and imaginary numbers. Transcendental numbers, like irrational numbers, cannot be described succinctly as the quotient of two inte...