Cybernetics ...
  "the science and art of understanding"... - Humberto Maturana
  "interfaces hard competence with the hard problems of the soft sciences" - Heinz von Foerster


Pre-History of Cybernetics

on the shoulders of giants
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THEME: An Affinity for Systematic Models and Explanations

Systematicity: 'Mechanism' and 'Formalism'   As discussed earlier, a systemic perspective was an important component of cybernetics' prehistory. It's important to highlight the fact that cybernetics' originators were not content to merely describe their subjects as 'systems'. They were uniformly interested in analyzing and explaining such systems' dynamics in terms of both internal operations and outward behavior.

Among cybernetics' creators there was an affinity for 'systematicity' in such analyses and explanations. By this we mean to imply two things. The first is the presumption that subject systems operated 'systematically' - i.e., in accordance with specific parameters, factors, rules, etc. The second is that explanations for these definitive operations could be portrayed 'systematically' - i.e., framed with respect to rigorous schemata or frameworks (i.e., models). Phrased more succinctly, the relevant prehistory of cybernetics entails the orientations of 'mechanism' and 'formalism'. Let us now address each of these in turn...

'Mechanism'   In the decades since the 1940's (particularly the 1960's and afterward) many people in the field of cybernetics joined the growing tide of criticism against the objectivist-rationalist paradigm in science. Such criticisms (both within and without the field of cybernetics) commonly highlighted and rejected the view that all subjects could be force-fit into the Newtonian clockwork 'mechanistic' explanatory approach of the 'hard sciences'. This general critique would later help motivate the rise and proliferation of second-order cybernetics (to be discussed later in this history tutorial).

In light of these subsequent developments, it may seem ironic to claim that an affinity for 'mechanism' was essential to cybernetics' origins. It is easy to simply note that Wiener, McCulloch, Bateson, and the others were trained within the Victorian era's 'scientistic paradigm' and move on, treating 'mechanism' as a prejudice of the times and not an intrinsic part of the field. This would be both unwarranted and misleading.

The ongoing critique of the 'scientistic' paradigm has layered a number of allusions and attributions onto the construct of 'mechanism' to make it a better straw man. This apparent irony dispels if one takes care to specify what particular aspects of 'mechanism' underlay cybernetics. Generally speaking, philosophical 'mechanism' has been taken to imply one or more of three basic tenets:

  1. Nature operates in a fashion which is both regular and free from vitalistic motivation, making the 'machine' an apt metaphor for explanations.
  2. Biological organisms (including humans) can be reasonably analyzed and explained as 'machines' in the general sense of the first tenet.
  3. All natural phenomena can be reduced to mechanistic operations involving material objects.

Although it can be claimed that some cyberneticians accepted all 3 tenets, it is only the first two which can be considered universal among the early cybernetics group and hence crucial in the field's prehistory. One very important reason for dispensing with the third tenet (strict materiality) is that it was the immaterial character of 'information' and 'communication' which served as a focal issue in the field's coalescence.

In at least rudimentary form, this constrained version of mechanism can be traced back to the earliest philosophical writings. So long as this orientation remained limited to the domain of scholarly philosophy, it had little effect on historical events. Circa 1600, the mechanistic orientation achieved significance by way of placing scholars in mortal jeopardy from the Church. The burning of Giordano Bruno at the stake and the intimidation of Galileo set examples that would hinder science - especially biological science - for hundreds of years thereafter. Descartes's attribution of mechanical character to organisms avoided such responses by (a) explicitly keeping 'soul' out of the equation and (b) going on to ostensibly prove God's existence (a result the Church no doubt welcomed).

Perhaps the first philosopher to 'get away with' a blunt declaration of mechanism covering biological systems was Julien Offray de La Mettrie. He first claimed mental activity was wholly explanable via physiology in his Histoire naturelle de l'âme (Natural History of the Soul) in 1745, then proceeded to explain physiology in purely mechanistic terms in his L'homme machine (Man a Machine) in 1747. Though he was widely castigated and some of his books were burned, La Mettrie was not officially threatened.

Once it was safe to analyze living systems as 'machines', scientific biology supplanted 'naturalism' as a methodological approach. This in turn led to observations and theories more clearly ancestral to systems thinking and cybernetics. The most widely cited example is that of French biologist Claude Bernard, who introduced the term 'homeostasis' to denote the the maintenance of constant state(s) in the body in 1855. This mechanistic orientation penetrated early psychology via (e.g.) the hydraulic metaphors of psychophysics (mid 1800's) and Pavlov's work on stimulus - response processes (published 1906). Alfred James Lotka's 1924 Elements of Physical Biology became a commonly-cited precedent for systems and cybernetics principles owing in part to its description of regularized processes in the organism. Alfred North Whitehead's 1925 book Science in the Modern World introduced a concept of 'organic mechanism' to describe his vision of process in all things. Walter Cannon's 1929 book Bodily Changes in Pain, Hunger, Fear and Rage provided a mechanistic explanation for the 'homeostasis' concept Bernard had introduced.

By the early 1940's, mechanism in biological studies had reached the point where people were attempting to build machines simulating the function of biological 'machines'. This is well illustrated in the artificial neuron work of McCulloch and Pitts, which fed directly into the creation of cybernetics.

'Formalism'   The first above-cited tenet of 'mechanism' (regarding the machine-like regularity of operations) set the stage for developing coherent models for systems of interest. One of the most distinctive contributions of both cybernetics and general systems theory was the formal (overwhelmingly mathematical) modeling of systems and system dynamics. Such modeling permitted reliable, quantitative analysis of extant systems as well as predictive simulations of prospective systems or states of systems. However, neither general systems theory nor cybernetics can claim to have literally originated mathematical analysis of systems. Another formal method for modeling - using logic rather than numbers per se - also proved to be useful when dealing with systems in terms of state space representations or their 'data processing' capacities.

The development of such formalisms and their applications in what we now call 'systems analysis' date far back into the prehistory of cybernetics. The Pythagoreans were developing geometric and mathematical models for perceptual phenomena in the 5th century BC, and the first propositional calculus is credited to the Greek philosopher Chrysippus in the 3rd century BC. The development of more abstract mathematics - especially algebra - progressed through the Middle Ages in the Middle East. The creation of calculus by Newton and Leibniz in the late 17th century provided yet another set of tools (some of which had been lost with Archimedes long before). Moreover, Leibniz spent the latter part of his career touting logic and mathematics as a 'universal language' for modeling anything and everything - combining the themes of formalism and transdisciplinary range. It was also around this time (1696) that Johann Bernoulli introduced his Principle of Optimality to explain his observation that achieving 'optimality' is a fundamental property of motion in natural systems - the first explicit specification of a dynamic system parameter. During the 1700's Euler and Gauss in particular added a number of useful implements to the growing mathematical toolkit.

By the middle of the 19th century we find mathematics first being applied to analyze instabilities in the newly-arrived regulated machines. By 1840, British Astronomer Royal G.B. Airy, previously cited for his application of feedback to control his telescope, undertook the first applied systems analysis with differential equations to understand instabilities in his initial designs. James Clerk Maxwell similarly applied differential equations to produce his definitive 1868 analysis of instability problems with James Watt's flyball governor. The contributions of Poincaré in the 1880's set the stage for modern modeling and analysis of systems dynamics.

By the 1920's mathematical modeling was being applied to a variety of systems. L. F. Richardson created what he called 'politicometrics' and developed formal models of governmental and international issues such as disarmament, conflict, and war. Minorsky's improved 1922 controller for steering ships was based on mathematical models accounting for nonlinear effects in a closed-loop system. Bell Laboratories undertook widespread application of mathematical models and techniques to analyze telephonic communications network behaviors in the 1920's, generating much of the data and frameworks upon which Claude Shannon would later base his information theory. In 1927 came the first formal analysis of a closed loop control system, in which H. S. Black demonstrated the utility of negative feedback in reducing distortion in telephone repeater amplifiers. This trend accelerated up to the outbreak of World War II, with relevant examples including H.L. Házen's 1934 generalized account of mathematical control theory for system controllers and H.W. Bode's 1938 application of magnitude and phase frequency response plots of a complex function to analyze closed-loop stability in electronic systems.

By the early 1940's, sophisticated mathematical tools were available for modeling and analyzing relatively complex systems, and these tools' utility had been demonstrated in practice. Furthermore, these tools had already been applied in analyzing the sort of closed-loop control circuits that would be a focus in the formation of cybernetics. Both the McCulloch and the Wiener teams had constructively and instructively employed such methods by the time the original 'cybernetics group' came together.

The importance of structured or formal modeling to cybernetics is well illustrated in Gregory Bateson's Steps to an Ecology of Mind (2000 edition, pp. 406-407):

"Another tactic of mathematical proof which has its counterpart in the construction of cybernetic explanations is the use of "mapping" or rigorous metaphor. ... In cybernetics, mapping appears as a technique of explanation whenever a conceptual "model" is invoked or, more concretely, when a computer is used to simulate a complex communicational process. But this is not the only appearance of mapping in this science. Formal processes of mapping, translation, or transformation are, in principle, imputed to every step of any sequence of phenomena which the cyberneticist is attempting to explain. These mappings or transformations may be very complex, e.g., where the output of some machine is regarded as a transform of the input; or they may be very simple ...

The relations which remain constant under such transformation may be of any conceivable kind.

This parallel, between cybernetic explanation and the tactics of logical or mathematical proof, is of more than trivial interest. Outside of cybernetics, we look for explanation, but not for anything which would simulate logical proof. This simulation of proof is something new. We can say, however, with hindsight wisdom, that explanation by simulation of logical or mathematical proof was expectable. After all, the subject matter of cybernetics is not events and objects but the information "carried" by events and objects. We consider the objects or events only as proposing facts, propositions, messages, percepts, and the like. The subject matter being propositional, it is expectable that explanation would simulate the logical."


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The Subject of Cybernetics

on the shoulders of giants