11·     Simplexity

1. Emergence
2. Economy
3. Practical simplicity
4. Theoretical simplicity
5. Elemental simplicity
6. Semiotic simplicity
7. Energetics
8. Transformity
9. Life cycles and slipnets
10. Determination and purpose
11. Signs and designs

Emergence

Inquiring into the form of the process we both inhabit and embody, the semiotic cycle, we are complex systems on a quest for simplicity. The idea of simplicity could only occur to a complex system coping with an even more complex environment.

Through the study of development, evolution and self-organization, we are trying to trace our history backwards, toward the origin of all phenomena. Current physical cosmology traces it back to the Big Bang: we have no way to investigate what could have come before that, or whether there was any time before that. But from that point on, the story of life and mind is mostly about complex systems and processes emerging from simpler ones. This includes the development of guidance systems. For instance, Ursula Goodenough and Terrence Deacon ‘suggest that our moral frames of mind emerge from our primate prosocial capacities, transfigured and valenced by our symbolic languages, cultures, and religions’ (Goodenough and Deacon 2003, 801).

The meaning of a sentence like this one is emergent in the reader's mind. The sentence is made up of words, but these words don't have separate meanings of their own that you can sum up to calculate the meaning of the sentence. Every child learning the language utters meaningful one-word “sentences,” but as language develops, words lose the capacity to mean by themselves, and gain the capacity to articulate meanings in context and in combination with other words. In the higher stages of language development, it is the sentence, or its use in context, which endows the words with meaning, not vice versa. It's the relations among the words, and their relations with the language as a whole, and their relations with the situation in which they are uttered – and the consequences (intended or not) of using those words in that situation – that constitute the meaning of the sentence. The whole determines the form of the parts revealed by analysis.

Trying to picture ‘emergence’ may evoke the image of a container, but there is an important difference between the emergence of a new level in a systemic holarchy and emergence of something from inside a container. A child who has emerged from the womb, or a butterfly from a chrysalis, can do without it from that point on. But life, having emerged from physical and chemical processes, cannot do without physical or chemical processes. On this planet, life emerged from the primal seas and crawled out onto the land, but it cannot do without water. Multicellular organisms emerge from the interaction of cells, and cells from the interaction of molecules, but organisms cannot do without cells, nor can cells do without molecules. Morality cannot do without society, nor can society exist without embodied members and dialogue among them.

The previous chapter introduced Terrence Deacon's (2011) answer to the question of how life and mind could have emerged from simpler physical processes. Simplicity and complexity are qualities of order. Disorder is neither simple nor complex, but ‘a complex adaptive system functions best in a situation intermediate between order and disorder’ (Gell-Mann 1994, 249). The order of a physical process is both spatial and temporal. The physical structure can be analyzed into parts, but the function of any part of a system is what it does, i.e. what role it plays in the whole self-organizing system. The development of function accompanies the differentiation of the whole into parts: the system grows in complexity as it grows in size.

Since life itself is a process, an account of its origin must begin with the simplest kind of physical change. Deacon calls this orthograde, defined as ‘consistent with the spontaneous, “natural” tendency to change without external interference’ (2011, 551). One example is the tendency of bodies in a frictionless Newtonian universe to move in straight lines at constant speed. Another is the tendency of an isolated system to approach equilibrium as stipulated by the Second Law of thermodynamics. But since no system within the universe as we know it is absolutely isolated, it is also “natural” for bodies and systems to interfere with each other's movements. This can result in ‘changes in the state of a system that must be extrinsically forced because they run counter to orthograde (aka spontaneous) tendencies’ (549); Deacon calls these contragrade changes.

Can we say that some systems (or states of systems) are structurally simpler than others, aside from the kind of change they are undergoing? Anything absolutely simple would have no parts at all. The next simplest structure would have very few parts. The more functionally different parts an entity has, the more complex it is. A pile of sand has many parts, but we don't call it complex (nor do we call it a system) because there is no functional or structural difference between grains that makes any difference to the structure of the pile – indeed the pile has no structure, unless you count the conical shape it naturally takes as a ‘structure.’

Likewise consider a closed space where the molecules of a gas have distributed themselves evenly in dynamic equilibrium. If we attempted to label each individual molecule and describe how they are arranged in relation to one another, the description would be extremely long and complicated. Yet this is a “simple” situation in the sense that it has a kind of symmetry: there is no relevant difference between any part of the space and any other part, and no significant change over time. This kind of symmetry has to be broken, as they say in physics, in order for an organic simplicity to emerge. As explained in Chapter 3, all organisms (and more generally, all dissipative structures) are far from energetic equilibrium, and are organized to keep their distance from it so they can go on doing whatever they do. Indeed ‘it is the creation of symmetries of asymmetries – patterns of similar differences – that we recognize as being an ordered configuration, or as an organized process, distinct from the simple symmetry of an equilibrium state’ (Deacon 2011, 237).

Our idea of simplicity becomes more complex when we consider morphodynamic processes, which tend ‘to become spontaneously more organized and orderly over time due to constant perturbation.’ These are usually called ‘self-organizing’ but, according to Deacon (2011, 238), ‘might better be described as self-simplifying, since the internal dynamic diversity often diminishes by vastly many orders of magnitude in comparison to being a relatively isolated system at or near thermodynamic equilibrium.’

In an unorganized ‘system’ such as a pot of water at room temperature, the molecular motion is almost random, events at that scale showing no orderly pattern. If we tried to specify the trajectory of each molecule in the ‘system,’ the resulting description would be very long indeed (and totally useless for any practical purpose). What appears holistically as the ‘simple symmetry of an equilibrium state’ shows great ‘dynamic diversity’ at the level of individual molecules. But if you introduce an external source of heat, patterns of convection are likely to appear which constrain molecular motion within regular patterns, as if the water were responding systematically to being perturbed, organizing itself to dissipate the heat as fast as possible, so that the movement within the system is simpler to describe. Yet these predictable patterns of change are intrinsic to the substance, not imposed by the external source as the ‘perturbing’ energy is.

Teleodynamics emerge from morphodynamics when a system begins to take control of its own self-simplifying process. In other words, it begins to develop an internal guidance system to regulate its energy economy. Thus arise the cybernetic and semiotic realms of life and mind.

Economy

Semiosis is a mental process inhabited by all sentient beings, and internalized by those capable of learning from experience. Yet it must also be a physical process, powered by energy which every self-organizing process consumes, incorporates and dissipates but does not create. Observing this (or any) process also takes time and energy which does not appear in a representation of it such as the meaning cycle diagram. Attention must be paid: who pays it, to whom, and in what currency?

Self-organizing systems have to rely on external energy sources in order to sustain their own order against the universal tendency to disorder. Those sources are always more or less limited, and using (consuming) them also produces entropy (see Chapter 3). A guidance system likewise has limited resources with which to make its Model of its World, and therefore has incentive to self-simplify. Although it must be open to information about that World, so that its continuing quest for useful resources may be well guided, the Model has to be simpler than the World it represents. ‘Brains have evolved to regulate whole organism relationships with the world’ (Deacon 2011, 528), and since those relationships are complex, the brain has to simplify them.

By the very nature of the translation of the geometry of the properties of the external world into the geometry of the internal functional space, reality is at all times simplified. It has to be so; it is the only way the brain can keep up with reality. It must simplify at all times.

— Llinás (2001, 220)

The economy of the nervous system accounts for our tendency to generalize. We draw simplicity from the multiplicity of percepts by sorting them into types which we recognize. I look out my window and see a red squirrel – that is, a typical member of the species. I don't recognize individual squirrels unless i observe them long and carefully enough to see differences between one squirrel and another. Until then, the squirrel i see is just a token of a type, so i use the name of the type to refer to any of the tokens. Even an “individual” squirrel is a generality, relative to the (more strictly speaking) individual occasions of its appearance: it is the continuity of those appearances through spacetime that constitutes the identity of the “individual” squirrel. We generalize by recognizing typical situations to which we develop habitual responses. In pragmatic terms, the guidance system grows when we combine, separate or improvise responses to novel situations and thus gain self-control. In theoretical terms, our models grow when we explain some events as related to relatively simple patterns already embodied in our models.

Adding more categories to your classification system might seem to enrich it, but if it fragments or dissipates your attention, this will not improve your self-control. To do that, your new way of sorting the world into types will have to facilitate an appropriate response better than your old way. The modified model is likely to work better if it changes your conceptual toolbox rather than adding to it. Since there are pragmatic limits on the size of this toolbox, new tools need to replace, reorganize or renovate the old instead of accumulating. When the tools fit the task better than before, the situation appears simpler because we have a better “handle” on it.

Here again science appears to be a formalized version of common sense, motivated by a simple faith: according to Einstein/Infeld, the scientist ‘certainly believes that, as his knowledge increases, his picture of reality will become simpler and simpler and will explain a wider and wider range of his sensuous impressions.’ The simplicity of the model is directly related to the range of experience it will explain. The core faith of science, that the universe is governed by relatively simple and ultimately discoverable rules or laws, probably reflects the unity and closure of the internal model. Any model, if it is to function effectively as a guidance system, must be as single and simple as possible, for though we can imagine many paths, we can realize only one at a time. (As Yogi Berra once said, ‘When you come to a fork in the road, take it.’) The larger the collection of models, the less portable it is; we can't afford to have a different model for every situation. A reliable guidance system, then, treats the world as a universe – a single interconnected system – even if it professes to believe that universal laws are figments of imagination. (As we will see in the next chapter, that is the nominalist belief as opposed to the realist.)

In any scientific hypothesis, then, simplicity is highly desirable. But in the empirical sciences, the typical method of testing a theoretical model is to investigate one system or one process at a time, in isolation from the rest of the ambience. Likewise, in everyday learning and informal or preconscious modeling, we always have to resolve the tension between the ideal model (which is single, simple and whole) and the ideal method (which analyzes the universe into clearly defined parts and makes many observations of their many interactions). And in order to make more formal sense of this, we have to arrange the part/whole relationships into hierarchies …

for indeed one central result of hierarchical organization is greater simplicity; and yet any analytical approach to understanding simplicity always turns out to be very complex.

— Howard Pattee (1973, 73)

To the degree that a theory is well integrated into the guidance system, that theory will be difficult to test separately. Moreover, if the subject we are studying is self-organizing, even defining the parts or processes involved in it (so that we can frame hypotheses about relations between them) can be misleading. ‘Holistic aspects that resist formulation in precise terms characterize many organized systems’ (Collier 2003, 104).

Practical simplicity

No matter how much energy or material is flowing through a process, it seems simple enough to us if it flows by itself, effortlessly, like a river following the curve of spacetime, gravity doing all the work. Just as a river carves its own channel to facilitate and concentrate its flow, so we channel our energy through habitual practices.

A habit is an attractor in the state space of the guidance system which governs behavior. Becoming familiar with a type of situation makes it simpler to inhabit when it occurs, making fewer demands on our energy and attention. But in order to respond intelligently to changing conditions, you need to change habits from time to time. Everyone ‘exercises more or less control over himself by means of modifying his own habits’ (Peirce, EP2:413). Modifying a habit will only simplify your life if the modified habit is better adapted to the habits or implicit “laws” of the natural or cultural systems within which you are living.

Science, our collective effort to discover the “laws of nature,” presumably evolved as a way of simplifying our situation, grounded in ‘an intelligence capable of learning by experience’ (Peirce, CP 2.227). This intelligence was not artificial but animate, to use Jeremy Lent's term. Reflecting on our direct interaction with the natural world could make it more predictable, so that we could adapt to it more easily. As it evolved and expressed itself symbolically, this collective intelligence also enabled humans to control some situations by adapting their environments to their own purposes. As long as the human purposes were compatible with those of other inhabitants of those ecosystems, this could be a mutually beneficial or synergetic arrangement. But as humans acquired the power to surround themselves with artificial environments that suited their own purposes, they became ever more conscious of those purposes and less concerned with those intrinsic to healthy ecosystems.

As human settlements grew larger and more complex, the infrastructures they inhabited became increasingly artificial. The progress of civilization led to a regress of ecological sensibilities among humans, while also enabling some humans to acquire wealth and power over others. Concentrations of power made a cultural habit of domination over nature itself, exploiting the labor of the less powerful to extract “resources” from the natural world without regard for the ecological consequences. Eventually the natural economy of energy transformations was superseded, for human conscious purposes, by an economy based on money, a wholly artificial “substance” (as we will see below). The drive to dominate nature became explosive with the Industrial Revolution and the exploitation of a highly concentrated energy source in the form of fossil fuels.

As modern sciences developed, ecology was relegated to one specialized field among many, instead of the deep and respectful knowledge of ecosystems that prevailed among those living in less artificial environments. In those cultures, what we now call “ecology” was a matter of practical simplicity, a common-sense means of optimizing relations between human and more-than-human nature. In contrast, the humans dominating modern corporate and political systems have become increasingly arrogant and wilfully ignorant about the living biosphere. By the 21^st Century, the Anthropocene had become an ecological nightmare.

Theoretical simplicity

As we saw in the previous two chapters, the public, external models and diagrams we use for scientific theorizing are always simpler than the systems they model, just as the brain's internal map of being-in-the-world is simpler than the circumstances of actually being in the world. But theoretical simplicity is not always conducive to practical simplicity. Modern science itself, since the 17th Century, has tended to value theoretical over practical simplicity.

Chalres Peirce was one scientist who realized that scientific thinkers can sometimes mistake logical simplicity for the more natural, instinctive kind.

Modern science has been builded after the model of Galileo, who founded it on il lume naturale [the light of nature]. That truly inspired prophet had said that, of two hypotheses, the simpler is to be preferred; but I was formerly one of those who, in our dull self-conceit fancying ourselves more sly than he, twisted the maxim to mean the logically simpler, the one that adds the least to what has been observed … It was not until long experience forced me to realize that subsequent discoveries were every time showing I had been wrong,— while those who understood the maxim as Galileo had done, early unlocked the secret,— that the scales fell from my eyes and my mind awoke to the broad and flaming daylight that it is the simpler hypothesis in the sense of the more facile and natural, the one that instinct suggests, that must be preferred; for the reason that unless man have a natural bent in accordance with nature's, he has no chance of understanding nature, at all. … I do not mean that logical simplicity is a consideration of no value at all, but only that its value is badly secondary to that of simplicity in the other sense.

— EP2:444

The case of Galileo also illustrates the difference between a hypothesis that seems natural to a scientist and an idea that seems natural to those who rely on the conventional wisdom of their time (such as the belief that all the heavenly bodies revolve around the earth). Was it simple to see that night and day take turns because the earth turns? To see that the tilt of the earth's axis gives us the seasons as we orbit the sun? Modeling the solar system by placing the sun at the centre certainly made it simpler to explain the observed motions of the planets; the heliocentric model turned out to be a powerful attractor in theoretical space. But it took a mental leap to approach it from the more habitual attractor of taking one's own point of view as the centre of the universe.

The instinct of the genuine scientist is to trust observation of nature more than prior belief about it. He also realizes that the simplicity of a hypothesis does not make it true: we still have need of deductive logic to generate predictions from it, and inductive logic to see whether the observed facts confirm those predictions. The economy of research requires us to select hypotheses for testing, since we don't have the resources or the time to test every wild guess about the nature of nature. Investigation therefore begins with the hypothesis that instinctively seems worth checking out – and then typically turns to analysis, or the quest for the logically elementary.

Conceptual or theoretical simplicity tends to involve reducing a system or process to its simplest parts or elements, those which are not themselves composed of parts. In chemistry, for instance, the elements can combine to form compounds but are not themselves compounds: they can't be resolved into smaller parts by chemical means. But the elements in chemistry are not the same as the elements of physics, or biology, or psychology – or phaneroscopy, which studies the ‘elements of the phaneron’ (introduced in Chapter 5).

In each special science, the simplest structural account of a complex system would explain how all its elements relate to one another to constitute the system. In an essay ‘On the Method of Theoretical Physics,’ Einstein made this observation:

It can scarcely be denied that the supreme goal of all theory is to make the irreducible basic elements as simple and as few as possible without having to surrender the adequate representation of a single datum of experience.

Philosophy of Science, Vol. 1, No. 2 (April 1934), p. 165

Elemental simplicity

The principles of inquiry itself are common to all genuine sciences, because they all deploy the basic elements of reasoning, which are even more basically the elements of semiosis. The various kinds of phenomena observed by the various special sciences also share the elements of all possible phenomena – which brings us back to what Peirce called the ‘elements of the phaneron.’ How do those elements relate to the observations of Einstein and Llinás (above)?

What Llinás called ‘translation of properties of the external world into internal functions,’ or internal representation of the external world, is represented in the gnoxic diagram as perception (or simply ception). To the extent that it really represents the external world, a ‘datum of experience’ offers some resistance to conscious control. That's why we call it a datum, which means in Latin that it is given. It is undeniably present: the mind cannot refuse the gift, although we can deny or distort the memory of it. Mind here simply means that which anything can appear or be present to, and experience (as in Chapter 7) designates a crossing or ‘clash’ between the internal and external worlds.

Any phenomenon, anything that appears, has this quality of being ‘given.’ At this point, there is no difference between “mental” and “physical” phenomena. But by the time it has been singled out for attention as a datum (or a percept), it has already presented itself as individually other than whatever else was present to the mind at the time. Its otherness, or Secondness as Peirce called it, is an element of the phenomenon. Its having any quality at all (apart from its relation to anything else), its Firstness, is also an element of the phenomenon. This felt quality or feeling is already simpler than anything analysis can produce.

A feeling so long as it remains a mere feeling is absolutely simple. For if it had parts, those parts would be something different from the whole, in the presence of which the being of the whole would consist. Consequently, the being of the feeling would consist of something beside itself, and in a relation. Thus it would violate the definition of feeling as that mode of consciousness whose being lies wholly in itself and not in any relation to anything else. In short, a pure feeling can be nothing but the total unanalyzed impression of the tout ensemble of consciousness. Such a mode of being may be called simple monadic Being.

CP 6.345 (1907)

According to Stanislas Dehaene (2014, 99), consciousness is a brain function that ‘grants us a single glimpse of the vast underlying sea of unconscious computations.’ Phenomenologically, that ‘single glimpse’ is what Peirce calls a ‘pure feeling.’ As we heard from the Blue Cliff Record at the end of Chapter 10: If you want to become acquainted with direct perception, it is before mention is made. Feeling is its Firstness, directness is its Secondness, and ‘mention’ comes later as Thirdness. We can only mention a phenomenon, or record it, or recognize it, because it is related to other phenomena in some way other than mere otherness. Systems and processes evidently do relate to other phenomena, and some processes and relations continue over time, which shows that Thirdness is also an element of the phaneron. Peirce made this point in 1878 by using the example of a melody or ‘air’:

It consists in an orderliness in the succession of sounds which strike the ear at different times; and to perceive it there must be some continuity of consciousness which makes the events of a lapse of time present to us. We certainly only perceive the air by hearing the separate notes; yet we cannot be said to directly hear it, for we hear only what is present at the instant, and an orderliness of succession cannot exist in an instant. These two sorts of objects, what we are immediately conscious of and what we are mediately conscious of, are found in all consciousness. Some elements (the sensations) are completely present at every instant so long as they last, while others (like thought) are actions having beginning, middle, and end, and consist in a congruence in the succession of sensations which flow through the mind. They cannot be immediately present to us, but must cover some portion of the past or future. Thought is a thread of melody running through the succession of our sensations.

EP1:128-9

Semiotic simplicity

According to Peirce (CP 7.535), ‘continuity, regularity, and significance are essentially the same idea with merely subsidiary differences’ – the idea of Thirdness. As elements, Firstness, Secondness and Thirdness must all have the elementary kind of simplicity. This is not so obvious in the case of Thirdness as it is with the other two ‘modes of consciousness’.

It is certainly hard to believe, until one is forced to the belief, that a conception so obtrusively complex as Thirdness is should be an irreducible unanalyzable conception. What, one naturally exclaims, does this man think to convince us that a conception is complex and simple, at the same time! I might answer this by drawing a distinction. It is complex in the sense that different features may be discriminated in it, but the peculiar idea of complexity that it contains, although it has complexity as its object, is an unanalyzable idea. Of what is the conception of complexity built up? Produce it by construction without using any idea which involves it if you can.

— Peirce, EP2:176

Semiosis as re-presentation epitomizes Thirdness as mediation, just as time epitomizes continuity. But semiotic closure can only occur in systems complex enough to be self-organizing, and only those employing symbols in their self-guidance systems can have a concept of semiosis. The concept has to simplify the actual process in order to represent it adequately, so that its interpretant serves the purposes of the system hosting the concept.

To conceive of anything, we attend to its essential features, its essential relations with the rest of the universe, ignoring irrelevant differences between one instance and another. Then, by an act of what Peirce called ‘hypostatic abstraction,’ we give it a name, which can now become part of a general sign, one that leaves it up to the interpreter to select any token of that type as its object. The general term can thus represent any instance of it more or less adequately – even though no user of the concept is actually acquainted with all of them – because the logical breadth of the term includes them all. (Recall Chapter 10 on the logical relations between breadth, depth and information.)

However, the simplicity we gain by generalizing usually comes at the cost of some vagueness. Vagueness allows us to talk about things without specifying exactly what we are talking about (see Peirce, CP 5.447, EP2:351). Individual objects of signs are determinate in more ways than their common names can represent, and greater precision and accuracy of reference and description often takes more time and attention than we can afford. Polyversity, or diversity of usage over time between users, further compounds the difficulty of communicating without fooling ourselves and others.

Theoretical science aims to achieve a maximum of generality with a minimum of vagueness. By generalizing, i.e. focussing on types of phenomena rather than instances or tokens of them, we simplify our models of the world. This in turn simplifies our practice, by directing our attention to what's important and thus conserving energy that otherwise might be dissipated in activities that don't matter. This is our way of optimizing the closure of the practiception cycle. Our external diagram of it enables us to step back and observe the cycle as if from the outside, mapping the flow of time onto cycles, and the cycle onto a circle, the simplest of closed forms.

If we ask whether a percept is simple before it becomes the object of a sign, the answer will depend on what kind of simplicity we are talking about. Being given, and thus requiring no special effort to produce, the percept is certainly simple as far as practice is concerned. But in theory, perception is already semiosis, part of a meaning cycle which is irreducibly complex. This cycle is doing the self-organizing, self-guiding work that produces percepts as well as concepts and precepts. All of these can be viewed as transformations of the energy flowing through the system and through the larger systems in which (as a holon) it must be embedded. There is no semiosis, and no system, without the flow of energy.

Energetics

As we saw in Chapter 4, Peirce spoke of physical matter as ‘mind hidebound with habits’ – this was part of his ‘synechism’ (introduced in Chapter 8), which rejected the idea of an absolute distinction between mind and matter, or between the psychical and the physical. Later Einstein made a similar point about the distinction in physics between energy and matter: he showed that the energy ‘bound’ into a unit of matter is equivalent to its mass multiplied by a very large constant (the speed of light squared). This allowed us to account for the transformation of matter into energy in the nuclear reactions which occur in the sun and thus power life on earth. (It also allowed us to build new weapons of mass destruction, over the protests of Einstein and other scientists … but that's another story.)

Combining Peirce's synechism with Einstein's relativity, we can regard matter as a concentrated, habit-bound embodiment of energy. If the recursive self-organizing processes which generate and constitute living systems determine the form of those embodiments, energy is the matter informed and transformed by those processes. In other words, organized physical structures are embodiments of energy which vary according to the systemic processes which produce them.

All systems transform energy from one form to another, a process that is called ‘work.’

— Odum and Odum (2001, 63)

The self-organizing process aims to optimize itself by consuming energy from external sources, internalizing some of that energy as its own structure and using some of it to do its work. Thus every organism is on a quest for energy in some form that is useful for its work or its self-organization. Once consumed, the energy is no longer available for that use; in thermodynamic terms, it has been dissipated. Consumers of energy are therefore called (by Prigogine) dissipative structures – a category even more general than life itself, for it includes all living things plus entities such as hurricanes, which develop through a ‘life cycle’ vaguely resembling that of a plant or animal. (Their individuality is reflected in our habit of giving them proper names, such as Katrina.) The cognitive or meaning cycle emerges when this more general life cycle is realized in a system with an internal model which guides its behavior and directs its attention.

Dissipative structures could be defined as entities which consume energy and use it constructively. Organisms reach out for energy “packaged” in a form they can consume. The consumed energy is then converted into an internally useful form. Your food, for instance, is repackaged by digestion into a form that your cells can use as a power supply for their work, which in turn sustains the structural basis of your work. Your ‘habits’ and ‘structures’ are functionally equivalent in the sense that their relative permanence or stability depends on some of the energy you consume being used to grow, modify or repair them. These habit-structures form the matter of the internal guidance system which directs your external or observable behavior.

It follows that you are a consumer of information (defined as whatever informs your guidance system) as well as an energy consumer. Indeed the process described in this paragraph is essentially the same as the semiotic cycle, and can be visualized with the same diagram labelled in a slightly different way (e.g. ‘quest’ and ‘consumption’ for ‘practice’ and ‘perception’). Consumable information is made up of signs, which are products of a semiosic process, which turns energy into meaningful forms. But signs are meaningful only when they are recycled, i.e. when they generate an interpretant which makes a difference to the system or through the system. In semiosis, ‘consumption’ is recycling – and in the process, some of the “signal” gets degraded into “noise.”

If eveything that counts is a transformation of energy, then energy is the real currency of the real economy. On this basis, ecologist Howard Odum has developed a consistent way of evaluating the embodied energy that constitutes the real wealth of Planet Earth. Odum's term energetics (Odum 2007, 34) is a more suitable term for this branch of science than the conventional term thermodynamics, because it is all about energy and only partially about heat (which, being constituted by random molecular motion, is a relatively degraded or disorganized form of energy). We will therefore use the term energetics from this point on.

Transformity

In Odum's formulation above, work is the generic name for a process which changes one form of energy into another. Energy is the matter of all systemic processes, and unlike the inert “matter” of Newtonian physics, it actually does all the work, powering every process. Indeed, as we have seen (Chapter 3), we have no way of measuring (or even defining) energy except in terms of the observable work it does. Thus both systems and processes consist of energy transforming itself.

Systems are more or less concentrated embodiments of energy, inhabiting processes which themselves take various forms according to the habits of the systems in which they are involved. These habits are in turn informed by semiosic processes, which channel energy into the channeling of energy. Thus information as embodied in various forms is a concentrated form of energy, while information as a process – namely Thought, in the Peircean sense of that word – is a kind of meta-energy acting as a formal cause of other processes.

Sometimes work involves transforming physical and/or semiotic matter from one form to another, and systemic processes are themselves embodiments of energy. Whether we see them as relatively habit-bound (inert) or more spontaneously active (alive), all are themselves products of energy transformation. All work makes a physical difference at some level, but it can only matter by making a semiotic difference to the living – to some teleodynamic system which in itself consumes, transforms and embodies energy. Every living system is driven by life itself to persist on its far-from-equilibrium course, and to propagate itself and other favored forms as far as possible.

The processes that make up the biosphere consume or transform energy which comes ultimately from sources outside of it, mostly from the sun or the hot interior of the earth. But the transformations occur in a hierarchy like the “food chain,” in which some systems consume others to embody and store energy in “higher” or more versatile forms. By measuring the energy circulating in various forms through the self-transforming processes of the biosphere, Odum (2007) shows a way to quantify the energy economy, giving us a measure of real wealth.

Food, shelter, clothing, fuels, minerals, forests, fisheries, land, buildings, art, music and information are real wealth. Money by itself is not. Money is circulated among people who use it to buy real wealth.

— Odum and Odum (2001, 91)

Although our embodied energy concept had been in use since 1967 and was used in [the first edition of] Environment, Power, and Society, emergy units were defined in 1983 to clarify the confusion that arose from use of the same units for both embodied energy and energy. We purposely avoided the confusing practice of taking over a common word in general use for a quantitative measure. Instead, we sought a new word. David Scienceman … suggested the word emergy, which implies energy memory. Emergy records the available energy previously used up, expressed in units of one kind but carried as a property of the available energy of continuing outputs.

— Odum 2007, 100

At the top of the energy hierarchy is information, which depends on a copying cycle. Widely shared information is the highest of all transformities.

Odum (2007, 97)

Life cycles and slipnets

Odum's formulation of the energy hierarchy, along with his schematic diagrams, help to simplify our models of measurable emergy flows. What makes them relevant to us is the form of our embodiment, which defines what counts as work for us by determining what we can consider useful. But embodiment is itself a process, and some basic values of a living system change as one moves through the life cycle. The meaning cycle finds itself to be a wheel within this wheel, a specific development of a more general cyclic pattern common to all dissipative structures.

These energy-transforming systems range in scale from a virus or a single cell through various ecosystems to the whole Earth System (and beyond?). Ecosystems tend to follow a developmental path which begins with fast-growing species rapidly exploiting the available resources. These are gradually replaced by the slower growth of more specialized species who can conserve their energy as their paths of interaction become more well-established and efficient. But this development also makes the system less resilient, more vulnerable to disturbances, as structures and behavior become more rigidly defined (more fast in the sense of ‘fixed’). Robert Ulanowicz (1997, 81) compares this to the growth of a nervous system from youth to a ‘maturity’ which leads to ‘senescence’ and loss of flexibility, ending in death. For an ecosystem, this ‘senescence’ leads to a relatively sudden collapse as the system can no longer adapt to changing circumstances.

For a system capable of learning from experience, each reiteration of the learning cycle carries it another step along the larger-scale path of its life cycle, toward the final self-definition of a closed structure. But that “perfect” closure is never realized, because the structure gets recycled when it becomes too rigid in its habits to cope with the ever-changing perturbations coming at it from external realities. According to Salthe (1993), senescence results from (or correlates with) information overload. An organism, when it can no longer “go with the flow” without losing its integrity, simply stops, dies, and becomes food for other organisms. An overmature ecosystem, when stressed, is more likely to revert to an immature form, its delicate web of interrelationships replaced by fast-growing invasive species.

Living entities tend to be partial to their own wholeness – nobody wants to be recycled prematurely. Mature systems can avoid this fate by maintaining a reserve of flexibility, which means keeping some of their unused options open. A perfectly efficient structure would be perfectly senescent, and its behavior perfectly mechanical, never making errors because it never tried anything new. Some neuroscientists have suggested that inefficiencies in brain function and uncertainties in reasoning may have an important biological function.

Randomness introduces variability in the way in which an organism interacts with its environment. In particular, a constant process of “shaking up” the organization of input would allow for new solutions.

— Metzinger (2003, 246)

Robert Ulanowicz (1997) demonstrates the crucial function of diversity in the life cycle of an ecosystem. He begins with the principle that a mature ecosystem tends to maximize the orderly dissipation of the energy available to it, and he uses information theory to devise a way of measuring this characteristic, which he calls ‘ascendency.’ (He spells it differently from ‘ascendancy’ because that term suggests the dominance pattern of a social hierarchy, which is not the kind of hierarchy at work in ecosystem development). Maximum ascendency or orderliness in an ecosystem would amount to a niche for everything and everything in its niche, with each component perfectly adapted to its niche and perfectly efficient in its energy transactions. But this goal can never be fully realized because there are always ‘inefficient, incoherent, redundant events and processes’ going on in it, and the measure of these he calls ‘overhead.’ All systems appear to strive toward ascendency and closure, but too much success would undermine their health, their wholeness.

In particular, the endpoint of senescence, owing as it does to insufficient overhead, engenders in us a new appreciation for the necessary role that inefficient, incoherent, redundant, and ofttimes stochastic events and processes play in maintaining and even creating order throughout the lifetime of a system (Conrad 1983). Our human inclination is to seek an ever more orderly and efficient world – which is only natural, considering the degree of chaos and mayhem that characterizes human history. But our intuition tells us that there also can be too much of a good thing. We often speak of individuals' lives and whole societies that are too rigidly structured as being ‘suffocating.’ As we have seen, ecosystems, too, can create too much structure and thereby become ‘brittle.’ Thus, efficiency can become the road to senescence and catastrophe.

— Ulanowicz (1997, 92)

True science is distinctively the study of useless things. For the useful things will get studied without the aid of scientific men. To employ these rare minds on such work is like running a steam engine by burning diamonds.

— Peirce, CP 1.76 (c. 1896)

The pattern outlined by Ulanowicz in terms of ascendency and overhead also turns up in cognitive cycles – even in computer models of creativity, such as those developed by Douglas Hofstadter and his colleagues in the Fluid Analogies Research Group. They investigated creative mental processes such as analogy-making by creating and running software models of them. One, called Copycat, employed a flexible conceptual network called a ‘slipnet’; the design incorporated enough randomness to enable a trial-and-error process, but also included biases which enabled the process to reach closure.

The important thing is that at the outset of a run, the system is more open than at any other time to any possible organizing theme (or set of themes); as processing takes place and perceptual discoveries of all sorts are made, the system loses this naive, open-minded quality, as indeed it ought to, and usually ends up being ‘closed-minded’— that is, strongly biased towards the pursuit of some initially unsuspected avenue.

— Hofstadter and FARG (1995, 228)

In a complex guidance system, such as a nervous system, fallibility of the parts turns out to be necessary to the viability of the whole. Llinás (2001, 264) summarized Warren McCullogh's explanation of how ‘reliability could arise from nonreliable systems’ as follows:

He felt that reliability could be attained if neurons were organized in parallel so that the ultimate message was the sum of the activity of the neurons acting simultaneously. He further explained that a system where the elements were unreliable to the point that their unreliabilites were sufficiently different from one another would in principle be far more reliable than a system made out of totally reliable parts.

Determination and purpose

As systems, situations, stories or symbols develop (unfold) and articulate themselves, they take ever more definite forms, becoming more determinate. The roots -fin- and -term- both refer to limits, ends or boundaries; to define a word (or term) is to determine its subsequent usage in a given discourse, i.e. to fix implicit or explicit boundaries within which it can be used. Determination as a life process is essentially what Jesper Hoffmeyer called ‘semiotic causality, i.e. bringing about things under guidance of interpretation in a local context.’ Nothing happens without some kind of efficient cause, just as no work gets done without energy; but the type of work that gets done is determined by the regulation of a guidance system grounded in semiosis. ‘Semiotic causality thus gives direction to efficient causality, while efficient causality gives power to semiotic causality’ (Hoffmeyer 2008, 64).

Semiosis always involves final causes, or as Peirce called them, habits. If a habit becomes completely fixed, its transformation is terminated, and the determination process has reached its end: the spirit or energy which gave life to it has been dissipated. Time is the continuous disappearance of possibilities into the past, either through irrevocable closure as determinate facts or events, or through vanishing into the mist of the might-have-been. Our very lives are processes involved in, and constrained by, other processes. We value things, or consider them useful, according to their involvement in some process we inhabit. But most of our habits and implicit values are either preconscious or postconscious. They are the psychical remnants of the same self-simplifying process which generates physical complexity.

The work done by semiosis is information, a process which transforms the guidance system thus informed. Considering information as product rather than process, it is embodied energy which, when incorporated in a continuing semiosic process, can alter the courses of subsequent energy flows. The more complex information is (either as process or product), the more attention it requires. Any system capable of attention will therefore value cognitive simplicity, to the extent that its attention is limited. Science is a special case of this, and the economy of research (Peirce, CP 1.85 etc.) must take into account the limitations on energy and attention as well as funding limitations.

The value of simplicity, and the form it takes, both depend on the kind of complexity embodied in the system. Transformity accounts for practical value, but what about theoretical or esthetic value? We don't value one work of art over another because more energy went into its making, just as we don't value a theory for its practical applications alone. What makes it good for us beings engaged in semiotic work is not only what keeps us alive but what makes life worth living. The value of semiotic work is its significance, and our sense of that arises from our instinctive sense of what we are here to do – the role we play in the drama of creation. Humans, for instance, are at their best as a species when carrying out the specifically human mission.

Animals of all races rise far above the general level of their intelligence in those performances that are their proper function, such as flying and nest-building for ordinary birds; and what is man's proper function if it be not to embody general ideas in art-creations, in utilities, and above all in theoretical cognition?

— Peirce, EP2:443

Life, he said, is like a festival; just as some come to the festival to compete, some to ply their trade, but the best people come as spectators, so in life the slavish men go hunting for fame or gain, the philosophers for the truth.

Kirk and Raven 1957, 228

Signs and designs

Two chapters ago, we considered the Einstein/Infeld description of the physicist as ‘somewhat like a man trying to understand the mechanism of a closed watch,’ and some disadvantages of choosing the artificial mechanism of a watch as a symbol of the natural order. Why then was that choice made? One possible reason is that the watch has been conventionally used to represent complexity of structure ever since Newton's celestial mechanics presented us with a “clockwork universe” – so rather than think up a new one, Einstein and Infeld simply went along with convention. Besides, Einstein and Infeld were writing in 1938, when physics was flushed with its success in modeling both celestial and quantum mechanics. The one kind of thing it was unable to model very well was the living kind. Since then, science has taken a few tentative steps toward explaining the physical and semiotic basis of life itself; but this has meant leaving the clockwork universe behind, and venturing into the realm of complex nonlinear systems. Yet it's the same old quest for theoretical simplicity that leads to the science of complexity.

The irony of the watch analogy is that the very purpose of a watch is to tell the time, and time – certainly an element of every process – is ignored when we focus on the structure of the watch. It can certainly be analyzed into many different functional parts, just as an organism can. But a watch does not develop those parts or those functions: they are specified and assembled by an external agency, the watchmaker. You can't grow a watch, because it is not integrated from within.

An organism is alive because its integrity and its parts, with their structures and functions, mutually define each other through the process of development. This entails that ‘a living organism taken apart suffers the Humpty-Dumpty problem’ (Deacon 2011, 164). But a machine, no matter how complicated, is not a complex system in that sense. Since the parts are not mutually determined, you can remove or replace them without affecting the other parts, and they don't spontaneously change or decay when you take them out of context. That's why a kidney or heart transplant is much more difficult to achieve than, say, a filter or pump transplant in a water purification system. But while the “transplant” metaphor refers originally to moving a whole plant from one place to another, the “transplanting” of parts from body to body is a symptom of our technological tendency to treat the body mechanistically. A more holistic medical science would respect the complexity of the body by investigating the systemic causes of heart or kidney disease, so that it could be prevented by a change of habits (such as diet and exercise) – in which case surgical intervention would rarely be needed.

Our choice of metaphors is virtually a choice of the diagrams on which our reasoning will be based. Peirce's threefold classification of human purposes (art, utility and theoretical cognition) is organically related to his division of the normative sciences (those which set up standards by which work is guided) into logic, ethics and esthetics (EP2:199). Logic as a normative science is the ethics of reasoning, which implies that the logically good (i.e. true) argument is a species of the ethically good. This in turn ‘appears as a particular species of the esthetically good’ (EP2:201).

Peirce did not claim any expertise in esthetics, but the investigation of it in his Harvard Lectures of 1903 describes the esthetically good in terms of the relation between simplicity and complexity:

In the light of the doctrine of categories I should say that an object, to be esthetically good, must have a multitude of parts so related to one another as to impart a positive simple immediate quality to their totality; and whatever does this is, in so far, esthetically good, no matter what the particular quality of the total may be.

EP2:201

But is this an “objective” quality, really inherent in things regardless of whether anyone is aware of them, or is “beauty in the eye of the beholder,” as they say? The next chapter will address this question.

Next chapter: Reality and Objectivity →

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