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CYBERNETICS: A Definition
Origins of "cybernetics"The term itself began its rise to popularity in 1947 when Norbert Wiener
used it to name a discipline apart from, but touching upon, such established
disciplines as electrical engineering, mathematics, biology, neurophysiology,
anthropology, and psychology. Wiener, Arturo Rosenblueth, and Julian Bigelow
needed a new word to refer to their new concept, and they adapted a Greek
word meaning "the art of steering" to evoke the rich interaction of
goals, predictions, actions, feedback, and response in systems of all kinds
(the term "governor" derives from the same root) [Wiener 1948]. Early
applications in the control of physical systems (aiming artillery, designing
electrical circuits, and maneuvering simple robots) clarified the fundamental
roles of these concepts in engineering; but the relevance to social systems
and the softer sciences was also clear from the start. Many researchers from
the 1940s through 1960 worked solidly within the tradition of cybernetics
without necessarily using the term, some likely (R. Buckminster Fuller) but
many less obviously (Gregory Bateson, Margaret Mead). Limits to knowingIn working to derive functional models common to all systems, early
cybernetic researchers quickly realized that "the science of observed
systems" cannot be divorced from "the science of observing
systems" [von Foerster 1974] --- because it is we who observe. The
cybernetic approach is centrally concerned with this unavoidable limitation
of what we can know: our own subjectivity. In this way cybernetics is aptly
called "applied epistemology". At minimum, its utility is the production
of useful descriptions, and, specifically, descriptions that include the
observer in the description --- so-called "second-order
cybernetics", in contrast to "first-order cybernetics", the
science of feedback, goals, and information without distinguishing an
observer. Cybernetic descriptions of psychology, language, arts, performance,
or intelligence (to name a few) may be quite different from more
conventional, hard "scientific" views --- although cybernetics can
be rigorous too. Implementation may then follow in software and/or hardware,
or in the design of social, managerial, and other classes of interpersonal
systems. Origins of AI in cyberneticsIronically but logically, AI and cybernetics have each gone in and out of
fashion and influence in the search for machine intelligence. Cybernetics
started in advance of AI, but AI dominated between 1960 and 1985. From the
late 1980s, difficulties in AI led to renewed search for solutions that
mirror prior approaches of cybernetics. Warren McCulloch and Walter Pitts
were the first to propose a synthesis of neurophysiology and logic that tied
the capabilities of brains to the limits of Turing computability [McCulloch
& Pitts 1965]. The euphoria that followed spawned the field of AI
[Lettvin 1989] along with early work on computation in neural nets, or, as
then called, perceptrons. However the fashion of symbolic computing rose to
squelch perceptron research. Only when discontent slowly grew over repeated
failures to achieve machine intelligence by symbolic means within AI did
interest in neural networks rise again in the late 1980s. However this is not
to say that current fashion in neural nets is a return to where cybernetics
has been. Much of the modern work in neural nets rests in the philosophical
tradition of AI and not that of cybernetics. Philosophy of cyberneticsAI is predicated on the presumption that knowledge is a commodity that can
be stored inside of a machine, and that the application of such stored
knowledge to the real world constitutes intelligence [Minsky 1968]. Only
within such a "realist" view of the world can, for example,
semantic networks and rule-based expert systems appear to be a route to
intelligent machines. Cybernetics in contrast has evolved from a
"constructivist" view of the world [von Glasersfeld 1987] where
objectivity derives from shared agreement about meaning, and where
information (or intelligence for that matter) is an attribute of an
interaction rather than a commodity stored in a computer [Winograd &
Flores 1986]. These differences are not merely semantic in character, but
rather determine fundamentally the source and direction of research performed
from a cybernetic, versus an AI, stance. InfluencesWinograd and Flores credit the influence of Humberto Maturana, a biologist
who recasts the concepts of "language" and "living
system" with a cybernetic eye [Maturana & Varela 1988], in shifting
their opinions away from the AI perspective. They quote Maturana:
"Learning is not a process of accumulation of representations of the
environment; it is a continuous process of transformation of behavior through
continuous change in the capacity of the nervous system to synthesize it.
Recall does not depend on the indefinite retention of a structural invariant
that represents an entity (an idea, image or symbol), but on the functional
ability of the system to create, when certain recurrent demands are given, a
behavior that satisfies the recurrent demands or that the observer would
class as a reenacting of a previous one." [Maturana 1980] Cybernetics
has directly affected software for intelligent training, knowledge
representation, cognitive modeling, computer-supported cooperative work, and
neural modeling. Useful results have been demonstrated in all these areas.
Like AI, however, cybernetics has not produced recognizable solutions to the
machine intelligence problem, or at least not for domains considered complex
in the metrics of symbolic processing. Many beguiling artifacts have been
produced with an appeal more familiar in an entertainment medium or to
organic life than a piece of software [Pask 1971]. Meantime, in a repetition
of history in the 1950s, the influence of cybernetics is being felt
throughout the hard and soft sciences, as well as in AI. This time however it
is cybernetics' epistemological stance --- that all human knowing is
constrained by our perceptions and our beliefs, and hence is subjective ---
that is its contribution to these fields. BibliographyLettvin, Jerome Y., "Introduction to Volume 1" in W S
McCulloch., Volume 1, ed., Rook
McCulloch, Salinas, California: Intersystems Publications, 1989, 7-20. -end-
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