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Cybernetics

The term cybernetics is much misused in the popular media. Often used to convey notions of high-technology, robotics, and even computer networks like the Internet, in reality, cybernetics refers to the study of communications and control in animal and machine.

Great mathematicians of the past such as Wilhelm Leibniz (1646–1716) and Blaise Pascal (1623–1662) had been interested in the nature of computing machinery long before these machines had ever been realized. They concerned themselves with philosophizing over what special peculiarities might be present in machines that had the ability to compute. In the mid-1930s Alan Turing (1912–1954) developed the idea of an abstract machine (later to become known as the "Turing Machine"). Turing machines introduced the possibility of solving problems by mechanical processes that involved a machine stepping through a sequence of states under the guidance of a controlling element of some sort. This laid the fundamental groundwork that was then developed by Norbert Wiener (1894–1964) into what has become cybernetics.

In 1948 Wiener concluded that a new branch of science needed to be developed. This field would draw from the realms of communication, automatic control, and statistical mechanics. He chose the word cybernetics, deriving it from the Greek word for "steersman" which underlines one of the essential ingredients of this field—that of governance or control. He defined cybernetics to be "control and communication in the animal and the machine." What really makes cybernetics stand apart from other fields in science and engineering is that it focuses on what machines do rather than the details of how they actually do it.

Classically, the study of a particular piece of conventional mechanical machinery—for example, a typewriter—would not be considered complete until all of the intricacies of the physics of movement of the constituent parts had been accounted for. This constitutes a Newtonian view of systems—one that commences with a perspective of Newtonian mechanics and builds from there. Cybernetics, on the other hand, accentuates the behavior and function of the machine as a whole. The result of this stance is that cybernetics is not restricted to dealing with mechanical or perhaps electrical machines only; instead it applies to anything that might possibly be viewed in some way as a machine—including organisms. That is, cybernetics looks at all the elements that are common denominators in that class of entities that might describe as machines. Wiener concluded that for a system to be classed as cybernetic, communication between parts of a system was a necessary characteristic, as was feedback from one part to another. The presence of feedback means that a cybernetic system is able to measure or perceive a quantity of some sort, then compare this to a required or desired value, and then instigate some strategy or behavior that affects change in that quantity. This is as much true of a heater and thermostat used to regulate temperature in a house, as it is of a bird that seeks refuge in a bird bath on a hot day.

Historically, the human body, in particular the human brain, has been viewed by many as a type of machine. This perception was generated by people who were hopeful of finding a way of modeling human behavior in the same way that they could model human-made machines—an approach with which they were comfortable. Much effort was directed toward understanding the operation of the human brain in this light.

Throughout the nineteenth and early twentieth centuries, significant advances were made in understanding the physiology of the human brain. Research into the structure of the cerebral cortex, the discovery of the brain as the center of perception, and the identification of neurones and synapses were all contributors to the conclusion that the brain is the regulator, controller, and seat of behavior of the human species. Because these ideas are fundamental to cybernetics, the human brain and the notion of intelligence are also considered as subjects that are within the realm of the cybernetic field. As a consequence, a great deal of research has been carried out in the areas of biological control theory, neural modeling, artificial intelligence (AI), cognitive perception, and chaos theory from a perspective that resulted from the development of cybernetics.

With respect to computer systems, cybernetics has been prominent in two areas. The first is artificial intelligence, where computer algorithms have been developed that attempt to exhibit some traits of intelligent behavior—initially by playing games and later by processing speech and carrying out complex image and pattern manipulation operations. The second is in robotics, which frequently encompasses artificial intelligence and other cybernetic areas such as communication and automatic control using feedback. Early robotic systems were nothing more than complex servo-mechanisms that carried out manual tasks in place of a human laborer; however, the modern cybernetic approach is to attempt to construct robots that can communicate and be guided toward acting together as a team to achieve a collective goal. This has generated interest in a new type of adaptive machine that has the capacity to re-organize its strategies and behavior if its environment or mission changes.

Finally, beyond a computing context, cybernetics offers some advantages in our understanding of nature. First, it permits a unified approach to studying and understanding machine-like systems. This results from the distinct way in which the cybernetic viewpoint of systems is formulated; it is not restricted to particular machine or system types. For example, we can draw a correspondence between an electro-mechanical system like a collection of servo-motors and linkages that give a robot locomotion, and a biological system like the nervous and musculo-skeletal systems of a caterpillar. One is not required to undertake greatly differing analyses to gain an appreciation of both. Secondly, it offers a manageable way of dealing with the most predominant type of system—one that is highly complex, non-linear, and changes over time.