The Need for General Principles: Software Explanation

“If we look far into the future of our science, what will it mean to say we ‘understand’ the mechanism of behaviour? The obvious answer is what may be called the neurophysiologist’s nirvana: the complete wiring diagram of the nervous system of a species, every synapse labelled as excitatory or inhibitory; presumably, also a graph, for each axon, of nerve impulses as a function of time during the course of each behaviour pattern. This ideal is the logical end point of much contemporary neuroanatomical and neurophysiological endeavour, and because we are still in the early stages, the ultimate conclusion does not worry us. But it would not constitute understanding of how behaviour works in any real sense at all. No man could hold such a mass of detail in his head. Real understanding will only come from distillation of general principles at a higher level, to parallel for example the great principles of genetics— particulate inheritance, continuity of germ-line and non-inheritance of acquired characteristics, dominance, linkage, mutation, and so on.

Of course neurophysiology has been discovering principles for a long time, the all-or-none nerve impulse, temporal and spatial summation and other synaptic properties, y-efferent servo-control and so on. But it seems possible that at higher levels some important principles may be anticipated from behavioural evidence alone. The major principles of genetics were all inferred from external evidence long before the internal molecular structure of the gene was even seriously thought about. Three computers with the same programming instruction set are in an important sense isomorphic in principle, even though their wiring diagrams may be utterly different, one employing valves, another transistors and the third integrated circuits; how all three work is best explained without reference to particular hardware at all”

Richard Dawkins