The super-informed society

Plasticity and diversity

Plasticity is of course a precondition of diversity and hence of ‘cladogenesis’ or ‘resilience’. If information cannot be changed, there can be no alternatives to it. If, on the other hand, it can be changed very easily then the existence of alternatives makes sense.

Since general information is non-plastic, it is not surprising that it should display low diversity, nor that trivial information, on the other hand, which is highly plastic, should display such high diversity.

Cybernism schema (click to enlarge)

It may be useful to see information, as used in the world of living things, as organised into something resembling an inverted cone, which we can regard as made up of different strata like an onion (see Figure 1).

Its generalities – chronologically the first part of the information to develop – are at the apex. They are non-plastic. There are no alternatives to them. Diversity is low or non-existent. They reflect the experience of the past and one cannot change the past. At the base are the particularities – chronologically the last to develop – the triviata that reflect the most recent experience. They are plastic. There are lots of alternatives. These strata display the highest diversity.

All biospheric organisations of information or cybernisms cannot be represented by a cone of this sort. A primitive cybernism would be represented by Figure 2.

It would display low complexity and low diversity. It would be extremely vulnerable to change. A system equipped with such a cybernism would be unlikely to survive by itself, therefore we would be more likely to find it associated with a lot of similar systems to form a population, one whose behaviour would be characterised by fairly large oscillations. It could be represented by Figure 3.

A society possessing such an arrangement of cybernisms would display low complexity but high diversity. It would not be able to adapt with any great sophistication to its specific environment but it could survive when subjected to environments displaying a considerable degree of improbability.

Alternatively we could find a system equipped with a cybernism that could be represented schematically by a very steep sided cone (Figure 4).

Such a cybernism would display high complexity and low diversity, which would enable a system so equipped to adapt with incredible sophistication to a highly specialised environment but not to survive were this environment to be subjected to any radical changes. Such a cybernism would be adapted to a highly protected environment such as that enjoyed by many parasites. It would be perfectly adaptive, contrary to what Holling [6] tells us, so long as it could be predicted that its environment would remain so protected.

Information increases with development

The final reason why Shannon and Weaver’s theory is inapplicable to the world of living things is that the amount of information contained in a message as it is being emitted, is seen as decreasing (because of the accumulation of linguistic constraints and noise); whereas in the world of living things, the opposite is true, i.e. the information-content of a message can only increase.

Waddington [12] admits that there are a few exceptional cases in the living world in which the information-content of a message does not increase. An obvious example is the passage of electrical impulses through networks of nerves, perhaps too, the transmission of hereditary information in the chromosomes of one organism to those of its offspring. But even then, as Waddington points out,

“Biology has developed mechanisms more flexible than those used by telephone engineers”. [12]

Thus a gene may mutate; when it does, the information that the offspring receives is not exactly the same as that present in its parent.

Shannon and Weaver, I suppose, would answer that a mutation is nothing more than an error in transcription and would thereby fall into the category of ‘noise’, which must reduce the information-content of the message rather than increase it. But this of course would not take into account the rare instances in which mutations lead to adaptive behaviour. Also there are other mechanisms such as “chromosomal deficiencies, duplications, translocations, formation of iso-chromosomes, etc., by which the amount of information can be either increased or decreased”.

However, it is in the transmission of information from the genotype to the phenotype that the “limitations of the theory become of overriding importance and rapidly render it not merely useless but a dangerous snare.”

Thus, the phenotype of an organism is not simply made up of all the proteins associated with all the genes present in the genotype, it is very much more than this. In Waddington’s words, it is

“a highly heterogeneous assemblage of parts, in each of which there are some, but not all, of the proteins for which the genes could act as patterns, and in each of which there are also many other substances and structures over and above the primary proteins corresponding to particular genes.”

It is fairly evident, as Waddington points out, that an adult rabbit running around a field contains a very much greater “amount of variety” or information than a newly fertilised rabbit’s egg. How then, Waddington asks, can one deal with such a situation “in terms of an information theory whose basic tenet is that information cannot be gained?”

Waddington here seems to be associating information with the number of different things a system can do – its ‘variety’ or diversity, i.e. the improbability of a situation to which it can react adaptively. But the organisation of information required to mediate more complex behaviour must also build up with development.

The information content of a natural system

That the information content of a natural system increases as it becomes more complex seems clear to a number of writers, who have sought to measure a system’s complexity in terms of its information-content, using Shannon and Weaver’s concept of information.

Dancoff and Quastler [15] tried to do just this. They postulated that the larger the number of different components in a system, and hence the greater its complexity, the greater must be the amount of information it contains, since the higher must be the improbability of building up such a system by assembling its components in a random manner.

Unfortunately, what Dancoff and Quastler actually measured has strictly nothing in common with the sort of complexity encountered in the biosphere. This cannot be measured by adding up its component parts, because it derives its essential features, above all, from the way these parts are organised.

Biospheric organisation, Dancoff and Quastler cannot, of course, take into account, for organisation and the constraints associated with it, as Shannon and Weaver themselves point out, are associated with reduced not increased information. Thus, unless increasing complexity is associated with reduced information and the nematode Ascaris be taken to contain more information than man, Dancoff and Quastler have to ignore the all-important organisational component of complexity.

Thus Atlan [16] expresses certain reservations as to the validity of measuring complexity in terms of information-content, because of

“Le caractère statique et uniquement structurel de la complexité dont il s’agit, a l’exclusion d’une complexité fonctionnelle et dynamique, liée non pas à l’assemblage des elements d’une systeme mais aux interactions fonctionnelles entre ces elements.”

“The static and structural complexity in question, to the exclusion of the functional and dynamic complexity, is not due to the arrangement of the elements of a system but to the functional interactions between those elements.”

Apter criticises Dancoff and Quastler [15] on the grounds that they are only concerned with “the specification of parts with no reference to their interrelationships”. [17] As Apter notes, this means that

“there would be an equal amount of information in a building and a mass of rubble, in a Shakespeare sonnet and a meaningless jumble of letters, indeed, in a living, a dead and a homogenised organism, provided only that there was the same number of building stones in each case and that the relative amounts of these needed were the same and provided the instruction list was the same length in each case.” [17]

In other words, they

“overlook precisely those qualities that are generally accepted as being the significant features of developing rather than simply growing systems.”

Significantly, Dancoff and Quastler themselves admit that their work yields but “crude approximations and vague hypotheses” and that their estimates are “extremely coarse”. Nevertheless they insist that this is “better than no estimates at all”. I do not think this is so. Mathematical calculations based on false premises and making use of inappropriate concepts can only, by virtue of the impression of great scientific accuracy that they convey, serve to mislead people and to obscure the real issues at stake.

The attitude of critical scientists

I have tried to show that the use of the communications concept of information for understanding behaviour in the world of living things cannot conceivably be justified on either theoretical or empirical grounds.

This is not altogether surprising, since it was not designed for this purpose, any more, for that matter, than was the associated concept of entropy.

This is Waddington’s view too. Information theory, he points out,

“was developed in connection with a particular type of process and has limitations which make it extremely difficult if not impossible to use in many of the biological contexts to which people have been tempted to apply it.” [12]

Apter makes much the same point:

“Information theory based on statistical considerations . . . is concerned with how data are transmitted, ignoring, however, any human factors involved.” [17]

Both Atlan [16] and Brillouin [5] as we have seen, also criticise the extension of this theory to the study of the world of living things. Yet in spite of these criticisms, all these writers, with the exception of Apter still explicitly justify its use for this purpose.

Waddington [12] for instance, argues that it allows the concept “to be clearly expressed”, though what I think he really means is ‘quantified’. But what, one might ask, is there to be gained by quantifying a concept that corresponds to nothing in the world of living things to which it is supposed to apply? It can only serve to give an air of spurious precision to, what is in effect, little more than a fiction.

Atlan [16] also regards Shannon and Weaver’s concept of information as “a valuable quantitative tool”. Though he admits that information in the biosphere may be something very different, he still considers that:

“La metaphore n’est pas complètement fausse. En effet, il existe bien des cas en biologie moleculaire, assez isolés mais importants, de transmission d’information au sens rigoureux de Shannon.”

“The metaphor is not completely false. Indeed, there are many cases in molecular biology, quite isolated, but important, of information transmission in the strictest sense of Shannon.”

This seems to be a very unconvincing argument. Indeed, that it should suffice for a theory not to be ‘completely false’ for it to be accepted as part of the Corpus of Science is difficult to reconcile with Science’s much vaunted objectivity and accuracy.

Brillouin’s [5] argument for the extension of Shannon and Weaver’s theory is that if it is “to break out” of “its original habitat of bandwidths and modulations”, then a proper beginning must be made, “which usually means a modest beginning” which presumably he regards Shannon and Weaver’s theory as providing.

But why not allow the concept of information to remain “in its original habitat of bandwidths and modulations?” What evidence does Brillouin or anybody else provide to suggest that its use can profitably be extended to other fields for which it was not designed? The answer, I am afraid, is none whatsoever.

On the contrary, the only function that the extension of the theory is likely to serve is to perpetuate the myth that behaviour is atomised, and random, since the theory attributes precisely such features to the information in the light of which behaviour is mediated. This can clearly only serve to obscure important features of the behaviour of living things, such as, its goal-directedness, its stability and its organisation.

This brings us to the real reason why many of our scientists have accepted the extension of the use of Shannon and Weaver’s theory to so many other fields.

Scientists, and in particular, aristo-scientists, are committed to that view, of the world that we can refer to as the ‘paradigm of science’ – the only one that justifies the performance of those tasks that they have been trained to perform, and on whose performance hinges their status as the high priests of our industrial society.

In terms of the paradigm of science, behaviour must, above all, be seen as atomised and random, i.e. as disorganised and goal-less. Otherwise, how can they justify induction – the random accumulation of data – as the basic method of acquiring knowledge?

How else can they justify the ‘analytic’ or ‘reductionist’ method which consists in breaking things up into their component parts, and hence in systematically eliminating, as a prelude to their scientific study, whatever organisation they might have previously displayed?

How else can they justify examining systems in controlled laboratory conditions and hence in isolation from all the other systems with which they have co-evolved, and in the context of which their true goal-directed function can only be determined?

How else can they justify quantification – that sine-qua-non of scientific method – unless the accent is on measurable components rather than on their unmeasurable organisation?

Finally, how else can they justify ‘statistical method’, whose basic postulate, as Needham [18] tells us, is that the laws of the biosphere are but words we give to statistical regularities? This being so, it is not difficult to see the attraction to scientists of Shannon and Weaver’s theory.

By defining information the way they have, they have done the scientific world a truly great service. They have contributed to the coherence of that most unsatisfactory corpus of knowledge that we call science, and enabled it to embrace that much more of the knowledge that could – if otherwise organised – help us to understand – which at present we do not – the essential features of the world we live in and what we are doing to it.

They have also done our economists and industrialists a good turn. Information, that is both random and atomised, whose value is neither dependent on its meaning, its accuracy or its relevance, and that is measured in terms of anonymous ‘bits’, provides those who have mastered the technology of computers and microelectronics, with the ideal commodity for mass-production, mass-commercialisation and mass-accumulation.

They have also provided them all with the theory in terms of which it is possible to rationalise and hence legitimise, in the most ‘scientific’ and hence the most credible language possible, the blind and euphoric hope that such a technology may be creating for us a new paradise on earth – the Information Rich Society – one, that in the light of the latest scientific breakthroughs, may appear less speculative than the other now largely discarded paradises of our disillusioned past.

References

1.	A. Hald, “Towards the Information Rich Society”. The Futurist, August 1981.
2.	Claude E. Shannon and Warren Weaver, The Mathematical Theory of Communication. The University of Illinois Press, Urbana 1967.
3.	Everett M. Rogers and D Lawrence Kincaid, Communications Networks: Toward a New Paradigm for Research. Collier Macmillan, London 1981.
4.	Edward Goldsmith, “Thermodynamics or Ecodynamics?”. The Ecologist Vol. 11 No. 4, 1981.
5.	L. Brillouin, “Information Communication and Meaning”. In Walter Buckley and Anatol Rapoport, eds., Modern System Research for the Behavioural Scientist. Aldine, Chicago 1968.
6.	C. S. Holling, “Resilience and Stability of Ecosystems”, Erich Jantsch and G H Waddington Eds., “Evolution and Consciousness”, Addison Wesley, New York 1976.
6a.	K. S. Lashley, Brainmechanism and Intelligence. Chicago 1929.
7.	Donald Mackay, “Communication and Meaning – A Functional Approach”. In F. S. C. Northrop and Helen H. Livingstone, eds. Cross Cultural Understanding. Harper & Row, London 1964.
8.	C. H. Waddington, “The Theory of Evolution Today”. In Arthur Koestler and R. Smythies, eds., Beyond Reductionism. Hutchinson, London 1969.
9.	See Lancelot Law Whyte: Internal Factors in Evolution. Tavistock, London 1965.
10.	See C. H. Waddington, The Strategy of the Genes. Allen & Unwin, London 1957.
11.	Paul Weiss, L’Archipel Scientifique. Maloine SA, Paris 1974.
12.	C. H. Waddington, “The Basic Ideas of Biology”. In C. H. Waddington, ed., Towards a Theoretical Biology. Edinburgh University Press, Edinburgh 1970.
13.	Keith Oatley, Perceptions and Representations. Methuen, London 1978.
14.	Jacob von Uetthall. “Strolls through the Worlds of Animals and Man”. Translated by C. H. Schriller, ed, Instinctive Behaviour. Methuen, London 1957.
15.	S. M. Dancoff and H. Quastler, “The Information Content and Error Rote of Living Things”. In Quastler, ed., Information theory in Biology. University of Illinois Press, Urbana 1953.
16.	Henri Atlan, Entre le Cristal et la Fumée. Le Seuil, Paris 1979.
17.	Michael Apter, Cybernetics and Development. Pergamon Press, Oxford 1966.
18.	J. Needham, La Science Chinoise et L’Occident. Le Seuil, Paris.