ABSTRACT

Artificial Intelligence and cybernetics: Aren't they the same thing? Or, isn't one about computers and the other about robots? The answer to these questions is emphatically, No.

Researchers in Artificial Intelligence (AI) use computer technology to build intelligent machines; they consider implementation (that is, working examples) as the most important result. Practitioners of cybernetics use models of organizations, feedback, goals, and conversation to understand the capacity and limits of any system (technological, biological, or social); they consider powerful descriptions as the most important result.

The field of AI first flourished in the 1960s as the concept of universal computation [Minsky 1967], the cultural view of the brain as a computer, and the availability of digital computing machines came together to paint a future where computers were at least as smart as humans. The field of cybernetics came into being in the late 1940s when concepts of information, feedback, and regulation [Wiener 1948] were generalized from specific applications in engineering to systems in general, including systems of living organisms, abstract intelligent processes, and language.

Cybernetics Today

The term "cybernetics" has been widely misunderstood, perhaps for two broad reasons. First, its identity and boundary are difficult to grasp. The nature of its concepts and the breadth of its applications, as described above, make it difficult for non-practitioners to form a clear concept of cybernetics. This holds even for professionals of all sorts, as cybernetics never became a popular discipline in its own right; rather, its concepts and viewpoints seeped into many other disciplines, from sociology and psychology to design methods and post-modern thought. Second, the advent of the prefix "cyb" or "cyber" as a referent to either robots ("cyborgs") or the Internet ("cyberspace") further diluted its meaning, to the point of serious confusion to everyone except the small number of cybernetic experts.

However, the concepts and origins of cybernetics have become of greater interest recently, especially since around the year 2000. Lack of success by AI to create intelligent machines has increased curiosity toward alternative views of what a brain does [Ashby 1960] and alternative views of the biology of cognition [Maturana 1970]. There is growing recognition of the value of a "science of subjectivity" that encompasses both objective and subjective interactions, including conversation [Pask 1976]. Designers are rediscovering the influence of cybernetics on the tradition of 20th-century design methods, and the need for rigorous models of goals, interaction, and system limitations for the successful development of complex products and services, such as those delivered via today's software networks. And, as in any social cycle, students of history reach back with minds more open than was possible at the inception of cybernetics, to reinterpret the meaning and contribution of a previous era.