Saturday, 11 August 2018
Does cybernetics understand complexity?
This is the definition of complexity that I have believed up until this point, in a beautifully argued explanation by Ross Ashby:
“The word ‘complex’, as it may be applied to systems, has many possible meanings, and I must ﬁrst make my use of it clear. There is no obvious or preeminent meaning, for although all would agree that the brain is complex and a bicycle simple, one has also to remember that to a butcher the brain of a sheep is simple while a bicycle, if studied exhaustively (as the only clue to a crime) may present a very great quantity of signiﬁcant detail. Without further justiﬁcation, I shall follow, in this paper, an interpretation of ‘complexity’ that I have used and found suitable for about ten years. I shall measure the degree of ‘complexity’ by the quantity of information required to describe the vital system. To the neurophysiologist the brain, as a feltwork of ﬁbers and a soup of enzymes, is certainly complex; and equally the transmission of a detailed description of it would require much time. To a butcher the brain is simple, for he has to distinguish it from only about thirty other ‘meats’, so not more than log2 30, i.e., about ﬁve bits, are involved. This method admittedly makes a system’s complexity purely relative to a given observer; it rejects the attempt to measure an absolute, or intrinsic, complexity; but this acceptance of complexity as something in the eye of the beholder is, in my opinion, the only workable way of measuring complexity.” (Ashby, 1973 – “Some peculiarities of Complex Systems”, Cybernetic Medicine, Vol 9, no. 1)
On the face of it, this is perfectly sensible. But there are things in life which are not like bicycles or brains, butchers or detectives.
If I was to point to three problems with Ashby’s view, they are:
- The problem of reference and meaning: Ashby sees information as being about something – the brain to the butcher is information about something, just as it is to the brain surgeon.
- The problem of ergodicity – Ashby’s examples are inanimate and static in the information they present – but nothing in life is really like this, and neither are observers (or what a friend of mine calls “systems of reference”). Whatever information is conveyed and how we think about information is not ergodic. That means that the features of its “alphabet” are different from one moment to the next.
- The problem of the non-arbitrariness of the diachronic emergence of understanding. This is the really tricky one, but basically the fact that human agree on distinctions, that we are capable of love, that somehow we resonate with each other in the face of phenomena is not the product of a kind of random search for coherence in the manner of Ashby’s “homeostat”. There seems to be some underlying principle which guides it.
Music and education are where these problems become most apparent. Bach’s music, for example, is often called “complex” because of its counterpoint. But if you examine it closely, all Bach’s music is simply an elaboration of chords which are rather like a hymn. And what Bach does with the chords is not to add entropy (or disorder); instead, he adds and overlays new patterns, or redundancies! His complexity arises from the interaction of redundancy. If he added entropy, the music would never have any coherence. But there’s something else. These emergent patterns are not random. Each of them appears to be a re-articulation of some fundamental symmetry which is expressed through the whole thing – even when they appear to be initially “surprising”. The music is holographic in the way that Bohm describes. Its aesthetic closure appears to be arrived at when sufficient redundant descriptions are overlaid and coordinate rather like different colours of the spectrum combine to make white light.
Cybernetics has no understanding of how this might happen as far as I can see. We need something else.
Comments please in course: Improvisation Blog: Does cybernetics understand complexity?