GREY WALTER - The Cybernetic Brain - page 50

this sort of science thematizes performance rather than knowledge of indi-
vidual parts. And third, this style of explanation had a tendency to undermine
its own modern impulse in what I call the cybernetic discovery of complexity,
to which we can now turn.
IT IS ONE Of THE INTERESTINg CONSEquENCES Of THIS kINd Of mOdEl-
mAkINg—THOugH I ONlY REAlISEd IT AfTER I STARTEd mAkINg THESE TOYS—
THAT A vERY SmAll NumBER Of NERvE ElEmENTS wOuld PROvIdE fOR AN Ex-
TREmElY RICH lIfE.
Grey WaLter, “PRESENTATION” (1971 [1954], 29)
The tortoises were simple and comprehensible artifacts. Anyone could under-
stand how their two-neuron brains worked—at least, anyone familiar with the
relay and triode circuits of the time. But, as Walter argued, “the variation of
behaviour patterns exhibited even with such economy of structure are com-
plex and unpredictable” (1953, 126). He noted, for example, that he had been
taken by surprise by the tortoises' mirror and mating dances (1953, 130). The
tortoises engaged with their environments in unexpected ways, displaying
emergent properties relative to what Walter had designed into them. After the
fact, of course, Walter explained such performances in terms of the tortoises'
running lights, as mentioned above. But it is worth recognizing that such
interpretations were themselves not beyond dispute. On the basis of his own
tortoise reconstructions, Owen Holland (2003, 2101-8) was led to challenge
Walter's interpretation of the source of these dances, arguing that they are a
function of the oscillatory behavior set in motion by physical contact, rather
than anything to do with the running lights. Here it begins to become clear
that the tortoises remained mini-Black Boxes. As Walter put it, “Even in the
simple models of behaviour we have described, it is often quite impossible to
decide whether what the model is doing is the result of its design or its experi-
ence” (1953, 271). 16
The tortoise thus again appears as ontological theater, but in a different
sense from that discussed above. As a piece of engineering, it displayed the
fact that a reductive knowledge of components does not necessarily translate
into a predictive understanding of aggregate performance—one still has to
run the machine and find out what it will do. As I said in chapter 2, I find this
ontologically instructive too. Many people, including me, tend to think that
the world has some determinate structure that is, in principle, fully compre-