Category: Complicity

All the complex systems we can observe, from organisms to ecosystems, have developed from simpler beginnings. A human life, for instance, develops from a single cell, whose descendants differentiate as they divide and multiply. A fully developed human body has thousands of different types of cells, each doing its separate job to maintain the organic unity of the whole. This quality of highly differentiated unity is what we call complexity.

Differentiation refers to the degree to which a system (i.e. an organ such as the brain, or an individual, a family, a corporation, a culture, or humanity as a whole) is composed of parts that differ in structure or function from one another. Integration refers to the extent to which the different parts communicate and enhance one another’s goals. A system that is more differentiated and integrated than another is said to be more complex.

— Csikszentmihalyi (1993, 156)

Uniformity and conflict are degenerate forms of unity and diversity respectively. Complexity is the logical product of unity and diversity, just as development (or evolution) is the logical product of change and continuity, and information is the logical product of breadth and depth (see Chapter 10· or Fuhrman 2010).

Everyone knows that a single sign can have various meanings for various interpreters. But we often forget that it also works the other way round: a single intention can be expressed (coded, realized, ….. ) in many ways. A single verbal formulation of a precept can prompt the formation of many different habits, and a single habit can be the logical interpretant of many different precepts. These are among the forms of polyversity. We have chosen this term for the element of indeterminacy which may enter into any semiotic process because terms such as polysemy and ambiguity do not seem to cover all cases. Since it is equivalent to the biological pattern of degeneracy, as Edelman called it, we could have chosen that term instead, if we were not already using it for the very different Peircean concept explained in Chapter 7, which comes from mathematics rather than biology or physics.

‘Degeneracy’ is defined by Edelman (2004, 43) as ‘the ability of structurally different elements of a system to perform the same function or yield the same output.’ The ‘words’ of the genetic code – triplets of the nucleotide bases G, C, A and T – are degenerate, since a particular amino acid can be encoded by more than one triplet. Immune systems and nervous systems also incorporate degeneracy (Edelman 2004, Chapter 4; more on this in rePatch ·14), and this tends to promote robustness in systems (Page 2011, 228). Another form of degeneracy in this context is pleiotropy, ‘the phenomenon whereby one single gene has an effect on several different phenotypic traits’ (Hoffmeyer 2008, 127). Symbolic (and especially linguistic) texts involve a double degeneracy: different terms may represent the same concepts, and different concepts may carry out the same guidance function or yield the same behavior pattern. This is in addition to the kind of degeneracy known as ‘polysemy,’ in which a word with the same literal form (such as ‘pit’) has several meanings.

The term degeneracy is obviously related to degenerate, used in English as both verb and adjective. This word also appeared in Chapter 2, with Thoreau’s remark that ‘When our life ceases to be inward and private, conversation degenerates into mere gossip.’ To degenerate is to ‘become of a lower type,’ according to a definition (probably by Peirce) in the Century Dictionary. The moral sense of the term is related to the mathematical sense whereby a point is a degenerate case of a circle as the radius of the circle approaches 0, and a circle is a degenerate case of an ellipse as the eccentricity approaches 0. You could say it refers to the loss of a dimension of complexity.

In his semiotic analysis, Peirce does not say that one symbol can have many meanings, but rather that two symbols which have the same function are ‘replicas of the same symbol’ (EP2:317). According to this usage, two instances of a word (such as ‘degeneracy’) which look and sound the same may nevertheless be different symbols. Or if they are the same symbol but are understood differently, they may be ambiguous or equivocal – a quality which lovers of precision would eliminate from language if they could. A perfect language (see Eco 1995) would presumably eliminate the word/thought gap, and thus we could articulate the one common Logos explicitly and unambiguously. From this viewpoint, the perfect language must be one that hasn’t been fractured and frayed by ‘vulgar’ everyday usage, and the ambiguity which is a feature of natural languages may indeed seem almost morally ‘degenerate’ by comparison. So maybe the technical senses of the word are not so far from Thoreau’s usage after all.

However, it is doubtful whether a ‘perfect’ language would serve as a medium of discovery. If you consider language as a system interacting with biological systems, the degeneracy of each system contributes to the fruitfulness of the interaction.

According to Edelman and Gally (2001), degeneracy is ‘a well known characteristic of the genetic code and immune systems,’ but appears to the most remarkable degree in neural connectivity. Surely it is no fluke that (a) the human brain is the most ‘degenerate’ system we know, and (b) humans are the only systems we know to be capable of generating utterances in natural symbolic languages. The connection is revealed by our gradual discovery that we can’t simply map experience or habits onto brain structures (or vice versa), any more than we can map words directly onto meanings or meanings into signs, without considering context.

Although, in the past, variations in the gross shape of the brain were studied carefully in efforts to find correlations between anatomical features and mental abilities or propensities, it now is accepted that these efforts are largely fruitless. Instead, it is recognized that many different patterns of neural architecture are functionally equivalent, i.e., functional neuroanatomy is highly degenerate.

— Edelman and Gally (2001)

By substituting linguistic terms here, we could generate a valid comment on polyversity: Although, in the past, various texts were studied carefully in efforts to establish the proper name or correct expression of a specific concept, it now is accepted that these efforts are largely fruitless. Instead, it is recognized that many different idioms are functionally equivalent, i.e., language in use is highly degenerate. According to Peirce’s ‘Ethics of Terminology’ (EP2), this tendency must be resisted in the sciences, but only a limited community of specialists could actually attain the level of precision recommended by Peirce.

Biologically as well as linguistically, degeneracy works in both directions, and this is crucial for evolvability:

Applying suitable quantitative measures, we have found that degeneracy is high in systems in which very many structurally different sets of elements can affect a given output in a similar way. In such systems, however, degeneracy also can lead to different outputs. Unlike redundant elements, degenerate elements can produce new and different outputs under different constraints. A degenerate system, which has many ways to generate the same output in a given context, is thus extremely adaptable in response to unpredictable changes in context and output requirements. The relevance to natural selection is obvious.

— Edelman and Gally (2001)

A related usage is Ernst Mayr’s reference to the ‘degeneracy’ of the genetic code, which makes possible ‘neutral’ mutations – cases where a change in base pairs has no effect on amino-acid production, so that ‘different’ statements in that code make no difference to the development of the organism (Mayr 1988, 141; Loewenstein 1999, 188 remarks that ‘there is synonymity, but no ambiguity in the communications ruled by the genetic code’).

In physics, Boltzmann’s definition of entropy makes it measurable in terms of the relation between the possible microstates of a system and its macrostate. To picture this, consider a large number of particles moving around randomly in a closed space. An account of the various positions and velocities of all the particles at any given time describes a microstate of the system. A macrostate of the system, on the other hand, is assessed by measuring properties of the system as a whole, such as its temperature. Many different microstates of such a system can coexist with a single macrostate. For instance, when we measure the kinetic energy over the whole space, it makes no difference to the macrostate where the faster- and slower-moving particles are located within the space. If we consider the locations of the fast-moving particles, for instance, very few of the possible microstates will have them all grouped tightly together, while the number of microstates in which they are more evenly distributed will be much larger; in other words, it is ‘much more probable that the energy states will explore the entire range of possibilities’ (Depew and Weber 1995, 262).

As the number of possible microstates corresponding to a given macrostate increases, the macrostate becomes increasingly degenerate, in the sense in which a code or a language is degenerate when it constains multiple, and thus ambiguous, ways of coding the same information. Boltzmann called this measure of degeneracy W.

Boltmann’s formula for entropy (S = kln W) thus correlates entropy with degeneracy (Depew and Weber 1995, 262).

The notion of supervenience appears to be closely related: ‘A property is supervenient when the same macrostate can be accessed by any number of microstates’ (Depew and Weber 1995, 471); Deacon (2011, 552) defines supervienience as ‘the relationship that emergent properties have to the base properties that give rise to them.’

What is called convergent evolution is another manifestation of degeneracy: for instance, different kinds of eyes have evolved in separate lines of descent among animals, but they all serve the same purpose in each animal’s life. It has also been noted that plants or animals in one bioregion may be very similar in form and behavior to counterparts in another region – may occupy ‘the same’ niche – even though they are entirely different and unrelated species. Same function, different structures; or same form, different lineage; these too are forms of polyversity, on a larger scale of time.

Polyversity is also crucial to the perceptual process, in proportion to the complexity of the animal’s Umwelt. ‘An essential aspect of object-oriented behavior is therefore that the same object has to be simultaneously represented in multiple ways’ (Jeannerod 1997, quoted in Millikan 2004, 178).

Models exist in order to simplify the modeler’s relations with the world. We may gain in precision by adding more detail to a model, but this may reduce its usefulness.

We assume that even the most complex symbol system, like the brain, has a correct and detailed physical description, at least in principle, but we recognize that a correct model need not be a useful model. Recall Einstein’s reply when asked if everything has a correct physical description. He said, “Yes, that is conceivable, but it would be of no use. It would be a picture with inadequate means, just as if a Beethoven symphony were presented as a graph of air pressure.”

— Pattee (2004)

Maynard Smith and Szathmáry (1999, 146) take Einstein’s point a bit further:

… complex systems can best be understood by making simple models. … the point of a model is to simplify, not to confuse. … if one constructs a sufficiently complex model one can make it do anything one likes by fiddling with the parameters: a model that can predict anything predicts nothing.

According to Peirce, the main ‘difficulties of explanatory science’ have not been that adequate hypotheses were in short supply, but ‘that different and inconsistent hypotheses would equally acount for the observed facts’ (EP2:467).

The identity of every phenomenon, and every cause, is its otherness from every other, including the very system in which it is embedded. In scientific inquiry, we simplify our models of changes in the phenomenal world by focussing on one causal factor at a time.

The practice of changing one variable at a time while holding others constant is important, but it is incomplete. Additional investigation is required, both to show how a causal factor is coupled in a system of causes and to reveal the ways in which these links change over time. It does not require considering everything at once, as some seem to fear, but can be done by coordinating diverse investigations.

— Oyama, Griffiths and Gray (2001, 4-5)

Lotman likewise points out the limitations of ‘the scientific practice which dates from the time of the Enlightenment, namely to work on the “Robinson Crusoe” principle of isolating an object and then making it into a general model.’ This accounts for the ‘transmission’ model of communication, which takes the sender, the message and the receiver as separate units. This practice is also incomplete, because a working semiotic system has to be ‘immersed in semiotic space’ – in the semiosphere, ‘the semiotic space necessary for the existence and functioning of languages’ (Lotman 1990, 123).

According to Lotman (1990, 104), ‘symbols with elementary expression levels have greater cultural and semantic capacity than symbols which are more complex.’ The simpler an utterance seems to the interpreter, the less semiotic energy he has to put into interpretation, and the more it seems to mean in itself. But when it comes to language, observes Northrop Frye (1982, 211),

there are different kinds of simplicity. A writer of modern demotic or descriptive prose, if he is a good writer, will be as simple as his subject matter allows him to be: that is the simplicity of equality, where the writer puts himself on a level with his reader, appeals to evidence and reason, and avoids the kind of obscurity that creates a barrier. The simplicity of the Bible is the simplicity of majesty, not of equality, much less of naïveté: its simplicity expresses the voice of authority. The purest verbal expression of authority is the word of command … The higher the authority, the more unqualified the command …

Pragmatically, obedience to the voice of authority simplifies guidance, makes an ethos “elementary” – but also incomplete, as a guidance system.

The scientific way of reducing complexity is typically an understanding of causes. In modern times, what we call ‘reductionism’ often involves reducing causality to what Aristotle called ‘efficient cause.’ But more recently, several scientists have resurrected versions of Aristotle’s other causes: see Peirce (EP2 selections 9 and 22), Salthe (1993), Ulanowicz (1997, 12-13), Rosen (2000), Deely (2001). Deacon’s (2011) concept of teleodynamics is an update of Aristotle’s ‘final cause.’

One way of distinguishing among Aristotle’s four ‘causes’ is to apply them to the building of a house. The material cause consists of the construction materials such as bricks or lumber, while the formal cause is the Bauplan or design (perhaps represented by a blueprint) that informs the construction process. The building’s form is constrained by the ambient conditions in which the house is built – gravity, climate and so on – so the formal cause can never be made fully explicit in the blueprint, or it would be bigger than the house! The efficient cause is the hands-on, energy-consuming work of the construction crew, and the final cause the purpose for which it is built, namely that somebody should live in it.

Efficient and final causes relate mostly to dynamic functioning or behavior, while formal and material causes relate to embodiment or structure. In terms of process, though, the difference between structure and function is a matter of time scale. A structure can be viewed as a deeply entrenched and consolidated kind of habit. The difference between form and matter is also relative to scale: for instance, cells constitute the matter of which flesh is made, but under the microscope, a cell appears as the form of a system made of molecules.

The final causes of an organism’s behavior can be seen as the role played by its whole life in the larger life of its species. The formal causes, which generally appear at the focal level (Ulanowicz 1997), shape the organism’s role in the life of the current ecosystem.

‘Final’ cause can be thought of as ‘ultimate context’ so long as we do not take ‘ultimate’ in any absolute sense. A scalar level may be ‘ultimate’ to us because it is above any level we are equipped to focus on. This does not imply that there is no higher level, only that whatever higher level there may be is beyond the reach even of speculation. Nor is any final cause necessarily the only final cause of the phenomenon in question. (It is obvious that efficient causes can be plural, but not so obvious with the more vague or general kinds of cause.)

The above is applied to an act or behavior. From a somewhat different point of view, Peirce preferred to both cause and what is caused as ‘facts’ (follow link to rePatch 14 for details).

There’s nothing more ruthless than life itself, and there’s no other source of compassion.

That which kills life does not die; that which gives life to life does not live. This is the kind of thing it is: there’s nothing it doesn’t destroy, nothing it doesn’t complete. Its name is Peace-in-Strife. After the strife, it attains completion.

Chuang Tzu (Watson 1968, 83)

— does this not describe how the second law of thermodynamics (or of energetics) works in the world?

Once the whole is divided, the parts need names.
There are already enough names.
One must know when to stop.

— Tao Te Ching 32 (Feng and English)

Sometimes the best time to stop is just before beginning.

The ‘beauty’ of the woods through which I walk is my recognition both of the individual trees and of the total ecology of the woods as systems. A similar esthetic recognition is still more striking when I talk with another person.

— Gregory Bateson (1972, 332)

Walking through the woods, talking through the words: intimologies.