Paul Schumann is a futurist and an innovation consultant. He is a proponent of collaborative approaches.
He has been a technologist and technology manager in the semiconductor industry (IBM), internal entrepreneur (IBM), cultural change agent (IBM), and consultant (Technology Futures and Glocal Vantage). With 55 years of professional experience, Paul is still excited about learning, and sharing what he is learning.
He is a 35 year resident of Lost Creek in Austin, Texas.
“For a moment everything was clear, and when that happens you see the world is barely there at all. Don’t we secretly know this? It’s a perfectly balanced mechanism of shouts and echoes pretending to be wheels and cogs, a dreamclock chimingbeneath a mystery-glass we call life. Behind it? Below it and around it? Chaos, storms. Men with hammers, men with knives, men with guns. Women who twist what they cannot dominate and belittle what they cannot understand. A universe of horror and loss surrounding a single lighted stage where mortals dance in defiance of the dark.”
History as the battle between complexity and randomness. Insightful!
Backed by stunning illustrations, David Christian narrates a complete history of the universe, from the Big Bang to the Internet, in a riveting 18 minutes. This is "Big History": an enlightening, wide-angle look at complexity, life and humanity, set against our slim share of the cosmic timeline.
On Early Warning Signs, George Sugihara, Seed Magazine, 12/20/10
Complex systems do not act like simple or even complicate systems.
"They can appear stationary for a long while, then without anything changing, they exhibit jumps in variability—so-called “heteroscedasticity.” For example, if one looks at the range of economic variables over the past decade (daily market movements, GDP changes, etc.), one might guess that variability and the universe of possibilities are very modest. This was the modus operandi of normal risk management. As a consequence, the likelihood of some of the large moves we saw in 2008, which happened over so many consecutive days, should have been less than once in the age of the universe.
Our problem is that the scientific desire to simplify has taken over, something that Einstein warned against when he paraphrased Occam: “Everything should be made as simple as possible, but not simpler.” Thinking of natural and economic systems as essentially stable and decomposable into parts is a good initial hypothesis, current observations and measurements do not support that hypothesis—hence our continual surprise. Just as we like the idea of constancy, we are stubborn to change. The 19th century American humorist Josh Billings, perhaps, put it best: “It ain’t what we don’t know that gives us trouble, it’s what we know that just ain’t so.”
So how do we proceed? There are a number of ways to approach this tactically, including new data-intensive techniques that model each system uniquely but look for common characteristics. However, a more strategic approach is to study these systems at their most generic level, to identify universal principles that are independent of the specific details that distinguish each system. This is the domain of complexity theory.
Among these principles is the idea that there might be universal early warning signs for critical transitions, diagnostic signals that appear near unstable tipping points of rapid change. The recent argument for early warning signs is based on the following: 1) that both simple and more realistic, complex nonlinear models show these behaviors, and 2) that there is a growing weight of empirical evidence for these common precursors in varied systems.
A key phenomenon known for decades is so-called “critical slowing” as a threshold approaches. That is, a system’s dynamic response to external perturbations becomes more sluggish near tipping points. Mathematically, this property gives rise to increased inertia in the ups and downs of things like temperature or population numbers—we call this inertia “autocorrelation”—which in turn can result in larger swings, or more volatility. In some cases, it can even produce “flickering,” or rapid alternation from one stable state to another (picture a lake ricocheting back and forth between being clear and oxygenated versus algae-ridden and oxygen-starved). Another related early signaling behavior is an increase in “spatial resonance”: Pulses occurring in neighboring parts of the web become synchronized. Nearby brain cells fire in unison minutes to hours prior to an epileptic seizure, for example, and global financial markets pulse together. The autocorrelation that comes from critical slowing has been shown to be a particularly good indicator of certain geologic climate-change events, such as the greenhouse-icehouse transition that occurred 34 million years ago; the inertial effect of climate-system slowing built up gradually over millions of years, suddenly ending in a rapid shift that turned a fully lush, green planet into one with polar regions blanketed in ice."
I'm not sure about our ability to find early warning signs in complex systems. Right now to me these attempts remind me of people trying to find ways around the second law of thermodynamics. People were always inventing perpetual motion machines only to have scientists eventually point out the flaw in the machine. Many people refused to believe that nature was so perverse as to not be completely reversible. (See note at end.)
I'm not sure that it's reached the state of a law of complex systems but it sure looks like one: that the future state of a complex system cannot be be predicted. That destroys everything that we thought we knew about logical determinism.
Note: The second law of thermodynamics is an expression of the tendency that over time, differences in temperature, pressure, and chemical potential equilibrate in an isolated physical system. From the state of thermodynamic equilibrium, the law deduced the principle of the increase of entropy and explains the phenomenon of irreversibility in nature. The second law declares the impossibility of machines that generate usable energy from the abundant internal energy of nature by processes called perpetual motion of the second kind.
For those of you following my writing you know that I am very interested in complexity. It was nice to see in this article, published in The Futurist,May - June 2011 written by James Irvin and Sandra Schwarzback, highlighting complexity as a technology and listing it as number 19:
"19 Chaos Theories and Complexity Models
Our world is much more complex, interconnected, and dynamic than we once thought. New mathematical concepts are challenging the rationalized, deterministic, scientific models of the Industrial Age. The Industrial Age paradigm held that there is one best way to organize a given thing and that in all cases, a given “rational” outcome is predetermined by nature. The new scientific paradigm will ultimately replace this older mentality. The new Information Age is being driven by applied technology and by two major advances in theoretical science that are altering our view of how the world works: an ecological/ ecosystem model, which supports ecological and environmental diversity, and modern chaos and complexity theories, which emphasize unpredictability, self-organizing systems, and the coexistence of the linear and the random. In the near term, this paradigm shift will significantly change people's views of society, of themselves in relation to society, and of how the world and the greater universe work."
This is a pretty good summary of the importance of the subject (although they get the terminology twisted up).
There were two other things in this article that caught my attention. The first is the way that they describe graphically paradigm revolution as shown below:
I've been drawing this s-curve type of progress this was since the early 1990s and I haven't seen it shown this way at all. I'm speaking about the step down from an old to a new paradigm.
I'm not at all sure about their description of the future as the Robotic - Biotech Age. I would look for a name closer to the technology of the means production that is coming and I think that that has to be nano technology. My second choice would be something in the energy field, but I don't see any thing right now that would revolutionize energy.
A physics talk for non-physicists by Michael Baranger
“The twenty-first century is starting with a huge bang. For the person in the street, the bang is about a technical revolution that may eventually dwarf the industrial revolution of the 18th and 19th centuries, having already produced a drastic change in the rules of economics. For the scientifically minded, one aspect of this bang is the complexity revolution, which is changing the focus of research in all scientific disciplines, for instance human biology and medicine. What role does physics, the oldest and simplest science, have to play in this? Being a theoretical physicist to the core, I want to focus on theoretical physics. Is it going to change also?
Twentieth-century theoretical physics came out of the relativistic revolution and the quantum mechanical revolution. It was all about simplicity and continuity (in spite of quantum jumps). Its principal tool was calculus. Its final expression was field theory.
Twenty-first-century theoretical physics is coming out of the chaos revolution. It will be about complexity and its principal tool will be the computer. Its final expression remains to be found. Thermodynamics, as a vital part of theoretical physics, will partake in the transformation.”
The author describes calculus as being limited to smooth functions that can be approximated by a series of straight lines. “For at least 200 years, theoretical science fed on this calculus idea. The mathematicians invented concepts like continuity and analyticity to describe smoothness more precisely. And the discovery of Calculus led to an explosion of further discoveries. The branch of mathematics so constituted, known as Analysis, is not only the richest of all the branches, but also by far the most useful for applications to quantitative science, from physics to engineering, from astronomy to hydrodynamics, from materials science to oceanography. Theoretical scientists became applied mathematicians, and applied mathematicians are people for whom analysis is second nature. Integrals, differential equations, series expansions, integral representations of special functions, etc . . . . , these are the tools that calculus has provided and that are capable of solving an amazing variety of problems in all areas of quantitative knowledge.”
Scientists and engineers accepted this assumption so long that they forgot completely about it. “Yes, the enormous success of calculus is in large part responsible for the decidedly reductionist attitude of most twentieth century science, the belief in absolute control arising from detailed knowledge. Yes, the mathematicians were telling us all along that smooth curves were the exception, not the rule: we did not listen!”
Chaos is the exception that finally broke through. “Chaos is the rediscovery that calculus does not have infinite power. In its widest possible meaning, chaos is the collection of those mathematical truths that have nothing to do with calculus. And this is why it is distasteful to twentieth century physicists.”
Chaos can exist in both time and space. Chaos is space is called a fractal. “There are many possible definitions of the word fractal. A very loose and general definition is this: a fractal is a geometric figure that does not become simpler when you analyze it into smaller and smaller parts. Which implies, of course, that it is not smooth.”
Fractals exist in mathematics, geometry and almost everywhere in nature.
Chaos in time is the result of dynamical systems, a system that is capable of changing its configuration over time. “The signature of time-chaos is something called “sensitivity to initial conditions”.”
“Sensitivity to initial conditions is the death of reductionism. It says that any small uncertainty that may exist in the initial conditions will grow exponentially with time, and eventually (very soon, in most cases) it will become so large that we will lose all useful knowledge of the state of the system. Even if we know the state of the system very precisely now, we cannot predict the future trajectory forever. We can do it for a little while, but the error grows exponentially and we have to give up at some point.”
Time and space chaos are closely related. “Every chaotic dynamical system is a fractal-manufacturing machine. Conversely, every fractal can be seen as the possible result of the prolonged action of time-chaos.”
Chaos can exist for very simple systems and is always nonlinear.
“At the present time, the notion of complex system is not precisely delineated yet. This is normal. As people work on complex systems more and more, they will gain better understanding of their defining properties. Now, however, the idea is somewhat fuzzy and it differs from author to author. But there is fairly complete agreement that the “ideal” complex systems, those which we would like most to understand, are the biological ones, and especially the systems having to do with people: our bodies, our groupings, our society, our culture. Lacking a precise definition, we can try to convey the meaning of complexity by enumerating what seem to be the most typical properties. Some of these properties are shared by many non-biological systems as well.”
Complex systems contain many constituents interacting nonlinearly.
The constituents of a complex system are interdependent.
A complex system possesses a structure spanning several scales. At every scale we find a structure.
A complex system is capable of emerging behavior. “Emergence happens when you switch the focus of attention from one scale to the coarser scale above it. A certain behavior, observed at a certain scale, is said to be emergent if it cannot be understood when you study, separately and one by one, every constituent of this scale, each of which may also be a complex system made up of finer scales. Thus the emerging behavior is a new phenomenon special to the scale considered, and it results from global interactions between the scale’s constituents.”
A complex system is capable of self organization. “The combination of structure and emergence leads to self-organization, which is what happens when an emerging behavior has the effect of changing the structure or creating a new structure.”
A complex adaptive system can exhibit self reproduction. “There is a special category of complex systems which was created especially to accommodate living beings. They are the complex adaptive systems. As their name indicates, they are capable of changing themselves to adapt to a changing environment. They can also change the environment to suit themselves. Among these, an even narrower category are self-reproducing: they know birth, growth, and death.”
Complexity involves an interplay between chaos and non-chaos.
Complexity involves an interplay between cooperation and competition. “Once again this is an interplay between scales. The usual situation is that competition on scale n is nourished by cooperation on the finer scale below it (scale n+1).”
I find the author’s discussion on entropy unsatisfactory and unconvincing. After several pages of proof and discussion, he writes, “The conclusion is that our dimensionless entropy, which measures our lack of knowledge, is a purely subjective quantity. It has nothing to do with the fundamental laws of particles and their interactions. It has to do with the fact that chaos messes up things; that situations that were initially simple and easy to know in detail, will become eventually so complicated, thanks to chaos, that we are forced to give up trying to know them.”
Having learned about entropy from thermodynamics and being able to derive the concept of entropy from simple considerations of the Carnot Cycle, it’s a real property to me. One implication of thermodynamic entropy is the impossibility of perpetual motion. Energy gets dissipated in the form of heat. Perhaps I’m not knowledgeable enough to see the difference between thermodynamic entropy and information entropy. Perhaps I still have more to learn, or unlearn…
Arcadia is a play by Tom Stoppard that weaves time, social mores, mathematics and science. It can be interpreted on many levels. Of interest to me is that in many ways, this play is about complexity, and the play is complex (or at least complicated).
Lets start with the title. Arcadia refers to a vision of pastoralism and harmony with nature. The term is derived from the Greek province of the same name which dates to antiquity; the province's mountainous topography and sparse population of pastoralists later caused the word Arcadia to develop into a poetic byword for an idyllic vision of unspoiled wilderness. Arcadia is associated with bountiful natural splendor, harmony, and is often inhabited by shepherds. The concept also figures in Renaissance mythology. Commonly thought of as being in line with Utopian ideals, Arcadia differs from that tradition in that it is more often specifically regarded as unattainable. Furthermore, it is seen as a lost, Edenic form of life, contrasting to the progressive nature of Utopian desires.
The inhabitants were often regarded as having continued to live after the manner of the Golden Age, without the pride and avarice that corrupted other regions. It is also sometimes referred to in English poetry as Arcady. The inhabitants of this region bear an obvious connection to the figure of the Noble savage, both being regarded as living close to nature, uncorrupted by civilization, and virtuous. (From Wikipedia)
The Latin phrase “Et in Arcadia ego”appears on the tomb in a 1647 painting by Nicolus Poussin. It is meant as a cautionary of the impermanence of life: even in Arcadia you will die.
Arcadia has another meaning that is connected to complexity. Arcadia is named after Arcas. In Greek mythology, Arcas was the son of Zeus and Callisto. Callisto was a nymph of the goddess Artemis. Zeus, being a flirtatious god, wanted Callisto for a lover. As she would not be with anyone but Artemis, Zeus cunningly disguised himself as Artemis and seduced Callisto. The child resulting from their union was called Arcas.
Hera (Zeus' wife), became jealous, and in anger, transformed Callisto into a bear. She would have done the same or worse to her son, had Zeus not hidden Arcas in an area of Greece that would come to be called Arcadia, in his honor. There Arcas safely lived until one day, during one of the court feasts held by King Lycaon, Arcas was placed upon the burning altar as a sacrifice to the gods. He then said to Zeus "If you think that you are so clever, make your son whole and unharmed." At this Zeus became enraged. He made Arcas whole and then directed his anger toward Lycaon, turning him into the first werewolf. (Some of the myths have Arcas cut into pieces and served to Zeus.) (See Arcas, Greek Myth Index, and Callisto.)
The significance of this double meaning of the title will become meaningful as I describe the play.
Quoting from SFF Net, “Arcadia is a play that stands up to numerous readings and viewings. The synopsis below barely scratches the surface of its complexity and depth. It also gives away a couple of major plot points best experienced first-hand. Read on at your peril.
The action of Arcadia takes place in single space, a room on the garden front of a very large country house in Derbyshire, but in two times, the present and the early years of the nineteenth century. It opens as Thomasina Coverly, a precocious thirteen-year-old math student, receives a lesson from her tutor, twenty-two-year-old Septimus Hodge. The two are discussing Fermat's theorem, Newton and other matters of mathematics and physics when they are interrupted by Ezra Chater, a third-rate poet. Chater accuses Hodge of having been spied in a "carnal embrace" with Mrs. Chater, a charge Hodge makes little effort to deny. Meanwhile, Thomasina's mother, Lady Croom, is wrangling with her landscape architect, Richard Noakes, who wants to clutter the immaculately kept grounds with a gloomy hermitage and other gothic paraphernalia.
The second scene moves to the twentieth century. Coverly descendants still reside at the estate: young Chloe, mathematician Valentine and mute, mysterious Gus. They are also hosts to best-selling author Hannah Jarvis, there to research a history of the estate's gardens, and to literary scholar Bernard Nightingale, who intends to prove that Lord Byron, the great Romantic poet, visited Sidley Park and killed Ezra Chater in a duel.
The next scene, however, demonstrates that, even though Byron did visit Sidley Park in 1809, it was Hodge whom the cuckolded Chater challenged to a duel.”
The structure of the play is based on the interplay of two time periods in the same room combined with the social mores of each time period. The back and forth nature of the play increases in tempo until the close of the play when both sets of characters are in the same scene.
Thomasina is indeed perceptive, creative and bold. Picking up the dialog in Scene 3:
THOMASINA: You are churlish with me because mama is paying attention to your friend. Well, let them elope, they cannot turn back the advancement of knowledge. I think it is an excellent discovery. Each week I plot your equations dot for dot, xs against ys in all manner of algebraical relation, and every week they draw themselves as commonplace geometry, as if the world of forms were nothing but arcs and angles. God's truth, Septimus, if there is an equation for a curve like a bell, there must be an equation for one like a bluebell, and if a bluebell, why not a rose? Do we believe nature is written in numbers?
SEPTIMUS: We do.
THOMASINA: Then why do your equations only describe the shapes of manufacture?
SEPTIMUS: I do not know.
THOMASINA: Armed thus, God could only make a cabinet.
SEPTIMUS: He has mastery of equations which lead into infinities where we cannot follow.
THOMASINA: What a faint-heart! We must work outward from the middle of the maze. We will start with something simple. (She picks up the apple leaf.) I will plot this leaf and deduce its equation. You will be famous for being my tutor when Lord Byron is dead and forgotten.
With this dialog, the concept of complexity and fractals is introduced.
The conversation quickly turns to another theme:
SEPTIMUS: Back to Cleopatra.
THOMASINA: Is it Cleopatra? I hate Cleopatra!
SEPTIMUS: You hate her? Why?
THOMASINA: Everything is turned to love with her. New love, absent love, lost love – I never knew a heroine that makes such noodles of our sex. It needs only a Roman general to drop anchor outside the window and away goes the empire like a christening mug in a pawn shop. If Queen Elizabeth had been a Ptolemy history would have been quite different – we would be admiring the pyramids of Rome and the great Sphinx of Verona.
SEPTIMUS; God save us.
THOMASINA: But instead, the Egyptian noodle made carnal embrace with the enemy who burned the great library of Alexandria without so much as a fine for all that is overdue. Oh, Septimus! - can you bear it? All the lost plays of the Athenians! Two hundred at least by Aeschylus, Sophocles, Euripides – thousands of poems – Aristotle's own library brought to Egypt by the noodle's ancestors! Can we sleep for grief?
SEPTIMUS: By counting our stock. Seven plays Aeschylus, seven Sophocles, nineteen from Euripides, my lady! You should no more grieve for the rest of them for a buckle lost from your first shoe, or your lesson book which will be lost when you are old. We shed as we pick up, like travelers who must carry everything in their arms, and what we let fall will be picked up by those behind. The procession is very long and life is very short. We die on the march. But there is nothing outside the march so nothing can be lost to it. The missing plays of Sophocles will turn up piece by piece, or be written again in another language. Ancient cures for diseases will reveal themselves once more. Mathematical discoveries glimpsed and lost to view will have their time again. You do not suppose my lady, that if all of Archimedes had been hidden in the great library of Alexandria, we would still be at loss for a corkscrew? I have no doubt that the improved steam-driven heat-engine which puts Mr. Noaks into an ecstasy that he and it and the modern age should all coincide, was well established on papyrus.
This theme has to do with evolution. For Teilhard de Chardin, the noosphere emerges through and is constituted by the interaction of human minds. The noosphere has grown in step with the organization of the human mass in relation to itself as it populates the earth. As mankind organizes itself in more complex social networks, the higher the noosphere will grow in awareness. This is an extension of Teilhard's Law of Complexity/Consciousness, the law describing the nature of evolution in the universe. (See Wikipedia)
It also describes human history. Complexification is the driving force of history, and individuals only retard or advance that natural inevitable change.
In scene 4, in modern time, Hannah and Valentine are talking. In the course of research into the history of Sidley Park, they have discovered Thomasina's notes and mathematics lesson book. Hannah reads from the book:
HANNAH: I, Thomasina Coverly, have found a truly wonderful method whereby all the forms of nature must give up their numerical secrets and draw themselves through number alone. The margin being too mean for my purpose, the reader must look elsewhere for the New Geometry of Irregular Forms discovered by Thomasina Coverly.
In other words, fractals.
Valentine explains what he thinks Thomasina is writing about, and Hannah asks:
HANNAH: Is it difficult?
VALENTINE: The maths isn't difficult. It's what you did at school. You have some x-and-y equation. Any value for x gives you a value for y. So you put a dot where it's right for both x and y. Then you take the next value for x which gives you another value for y, and when you've done that a few times you join up the dots and that's your graph of whatever the equation is.
HANNAH: And is that what she's doing?
VALENTINE: No. Not exactly. Not at all. What she's doing is, every time she works out a value for y, she's using that as her next value for x. And so on. Like a feedback. She's feeding the solution back into the equation, and then solving it again. Iteration, you see.
HANNAH: And that's surprising, is it?
VALENTINE: Well, it is a bit. It's the technique I'm using on my grouse numbers, and it hasn't been around for much longer than, well, call it twenty years.
Valentine describes the work he is doing trying to understand population trends of grouse in the Park. He has data of all the grouse shot since 1870, and is trying to understand the mathematical relationship. He is attempting to formulate the logistic equation for population growth. In discrete form, this equation is known as the logistic map, a very simple equation that exhibits chaotic properties in well defined regions.
Valentine comments, “It's about the behavior of numbers. This thing works for any phenomenon which eats its own numbers – measles epidemics, rainfall averages, cotton prices, it's a natural phenomenon in itself. Spooky.”
“When your Thomasina was doing maths it had been the same maths for a couple of thousand years. Classical. And for a century after Thomasina. Then maths left the real world behind, just like modern art, really. Nature was classical, maths was suddenly Picassos. But now nature is having the last laugh. The freaky stuff is turning out to be the mathematics of the natural world.” After being pressed by Hannah, Valentine continues, “If you knew the algorithm and fed it back say ten thousand times, each time there'd be a dot somewhere on the screen. You'd never know where to expect the next dot. But gradually you'd start to see this shape, because every dot will be inside the shape of this leaf. It wouldn't be the leaf, it would be a mathematical object. But, yes. The unpredictable and the predetermined unfold together to make everything the way it is. It's how nature creates itself, on every scale, the snowflake and the snowstorm.”
Then Valentine makes the following comment about the significance of complexity, “It makes me so happy. To be at the beginning again, knowing almost nothing. People were talking about the end of physics. Relativity and quantum looked as if they were going to clean out the whole problem between them. A theory of everything. But they only explained the very big and the very small. The universe, the elementary particles. The ordinary-sized stuff which is our lives, the things people write poetry about - clouds - daffodils - waterfalls - and what happens in a cup of coffee when the cream goes in - these things are full of mystery, as mysterious to us as the heavens were to the Greeks. We're better at predicting events at the edge of the galaxy or inside the nucleus of an atom than whether it'll rain on auntie's garden party three Sundays from now. Because the problem turns out to be different. We can't even predict the next drip from a dripping tap when it gets irregular. Each drip sets up the conditions for the next, the smallest variation blows prediction apart, and the weather is unpredictable the same way, will always be unpredictable. When you push the numbers through the computer you can see it on the screen. The future is disorder. A door like this has cracked open five or six times since we got up on our hind legs. It's the best possible time to be alive, when almost everything you thought you knew is wrong.”
Parenthetically, this is the excitement I feel as a physicist (education only) about complexity science.
One of the other themes that run through this play (there are many) is thermodynamics and entropy.
Hannah and Valentine are talking in modern time:
VALENTINE: Listen - you know your tea's getting cold.
HANNAH: I like it cold.
VALENTINE: (Ignoring that) I'm telling you something. Your tea gets cold by itself, it doesn't get hot by itself. Do you think that's odd?
HANNAH: No.
VALENTINE: Well, it is odd. Heat goes to cold. It's a one-way street. Your tea will end up at room temperature. What's happening to your tea is happening to everything everywhere. The sun and the stars. It'll take a while but we're all going to end up at room temperature. When your hermit set up shop nobody understood this. But let's say you're right, in 18-whatever nobody knew more about heat than this scribbling nutter living in a hovel in Derbyshire. Towards the end of the play when the four characters are on stage at the same time:
SEPTIMUS: So, we are all doomed!
THOMASINA: (Cheerfully) Yes.
VALENTINE: Like a steam engine, you see. She didn't have the maths, not remotely. She saw what things meant, way ahead, like seeing a picture.
SEPTIMUS: This is not science. This is story-telling.
THOMASINA: Is it a waltz now?
SEPTIMUS: No.
VALENTINE: Like a film.
HANNAH: What did she see?
VALENTINE: That you can't run the film backwards. Heat was the first thing which didn't work that way. Not like Newton. A film of a pendulum, or a ball falling through the air - backwards, it looks the same.
HANNAH: The ball would be going the wrong way.
VALENTINE: You'd have to know that. But with heat - friction - a ball breaking a window
HANNAH: Yes.
VALENTINE: It won't work backwards.
HANNAH: Who thought it did?
VALENTINE: She saw why. You can put back the bits of glass but you can't collect up the heat of the smash. It's gone.
SEPTIMUS: So the Improved Newtonian Universe must cease and grow cold. Dear me.
VALENTINE: The heat goes into the mix. (He gestures to indicate the air in the room, in the universe.)
THOMASINA: Yes, we must hurry if we are going to dance.
VALENTINE: And everything is mixing the same way, all the time, irreversibly ...
SEPTIMUS: Oh, we have time, I think.
VALENTINE: ... till there's no time left. That's what time means.
SEPTIMUS: When we have found all the mysteries and lost all the meaning, we will be alone, on an empty shore.
THOMASINA: Then we will dance. Is this a waltz?
SEPTIMUS: It will serve.
I believe what Stoppard is trying to indicate here is the possible linkage between complexity and entropy. A subject I will write about later.
A complex system cannot be taken apart and put back together remaining the same as it was before. You can do that with a complicated system, even though you will lose energy in the process.
And, that brings back to the title - Arcadia - the place where in spite of its perfection, everyone still dies. And, Arcas who is burned up or cut into pieces as a test for Zeus, to see if he can reverse the process and unlike Humpty Dumpty, put Arcas back together again.
Arcadia, Tom Stoppard, Faber and Faber, 1993 Arcadia (Dramatized), Tom Stoppard, L. A. Theatre Works, 2010 (CD)
“It makes me so happy. To be at the beginning again, knowing almost nothing. People were talking about the end of physics. Relativity and quantum looked as if they were going to clean out the whole problem between them. A theory of everything. But they only explained the very big and the very small. The universe, the elementary particles. The ordinary-sized stuff which is our lives, the things people write poetry about - clouds - daffodils - waterfalls - and what happens in a cup of coffee when the cream goes in - these things are full of mystery, as mysterious to us as the heavens were to the Greeks. We're better at predicting events at the edge of the galaxy or inside the nucleus of an atom than whether it'll rain on auntie's garden party three Sundays from now. Because the problem turns out to be different. We can't even predict the next drip from a dripping tap when it gets irregular. Each drip sets up the conditions for the next, the smallest variation blows prediction apart, and the weather is unpredictable the same way, will always be unpredictable. When you push the numbers through the computer you can see it on the screen. The future is disorder. A door like this has cracked open five or six times since we got up on our hind legs. It's the best possible time to be alive, when almost everything you thought you knew is wrong.”
This is a brief summary of two essays by Roger Lewin, The Reality of Complexity and Leading at the Edge: How Leaders Influence Complex Systems (coauthored with Birute Regine). Both of these essays refer to his two books on complexity, Weaving Complexity and Business: Engaging the Soul at Work, also coauthored with Birute Regine, and Complexity: Life at the Edge of Chaos.
In The Reality of Complexity, Lewin writes, “We argue that managers, consultants, entrepreneurs, executives, other business professionals indeed, anyone who works can take some comfort in the fact that they are not alone in riding a bucking bronco of change that demands a different understanding of the world. Science, too, is in the midst of an important intellectual shift, a true Kuhnian paradigm shift that parallels what is happening in business, or, more accurately, is the vanguard of that change. Where once the natural world was viewed as linear and mechanistic, where simple cause-and-effect solutions were expected to explain the complex phenomena of nature, scientists now realize that much of their world is nonlinear and organic, characterized by uncertainty and unpredictability. As in science, managers are discovering that their world is not linear but rather predominantly nonlinear, not mechanistic but rather organic and complex. It’s amazing how far we have been able to take the linear model for understanding the world, both in science and in business. But in the new economy, the limitations of the mechanistic model are becoming starkly apparent. A new way of thinking is required.
The realization that much of the world dances to nonlinear tunes has given birth to the new science of complexity, whose midwife was the power of modern computation, which for the first time allows complex processes to be studied. The science is still in its infancy, and is multifaceted, reflecting different avenues of study. The avenue most relevant to understanding organizational dynamics within companies and the web of economic activity among them is the study of complex adaptive systems. Simply defined, complex adaptive systems are composed of a diversity of agents that interact with each other, mutually affect each other, and in so doing generate novel behavior for the system as a whole, such as in evolution, ecosystems, and the human mind. But the pattern of behavior we see in these systems is not constant, because when a system’s environment changes, so does the behavior of its agents, and, as a result, so does the behavior of the system as a whole. In other words, the system is constantly adapting to the conditions around it. Over time, the system evolves through ceaseless adaptation.
Complexity scientists are learning about these dynamics of complex systems principally through computer models, but also through observation of the natural world. “That’s all fine and dandy for scientists and academicians,” one executive commented when we made this point, “but what’s it got to do with me and my problems?” The point is that business organizations are also complex adaptive systems. This means that what complexity scientists are learning about natural systems has the potential to illuminate the fundamental dynamics of business organizations, too. Companies in a fast-changing business environment need to be able to produce constant innovation, need to be constantly adapting, and be in a state of continual evolution, if they are to survive.”
He believes that relationships are the new bottom line. Not just who you are linked to but caring relationships driven by values. He notes, “We can restate this in the language of complexity science as follows: in complex adaptive systems, agents interact, and when they have a mutual effect on one another, something novel emerges. Anything that enhances these interactions will enhance the creativity and adaptability of the system. In human organizations this translates into agents as people, and interactions with mutual effect as being relationships that are grounded in a sense of mutuality: people share a mutual respect, and have a mutual influence and impact on each other. From this emerged genuine care. Care is not a thing but an action to be care-full to care about your work, to care for fellow workers, to care for the organization, to care about the community. We saw that genuine care enhanced the relationships in these companies, with CEOs engendering trust and loyalty in their people, and the people being more willing to contribute to the needs of the company. In the context of complexity science, care, which enhances relationships, in turn enhances companies’ creativity and adaptability.”
This is an extremely novel interpretation. We’ve had management based on science in the past with the result that people became abstracted to be a number and a replaceable cog in a machine. (Remember Charlie Chaplin’s Modern Times.) Now, complexity science may provide the justification for oft debated, human centered management.
“We can see, therefore, that management practice guided by complexity science leads us to a very human orientation, and this was a surprise, counterintuitive. Of course, there have been many human-centered approaches in management before, amongst the more notable being political scientist Mary Parker Follett’s work done in the 1920s and 1930s in the United States, in which there has been a recent resurgence of interest. For more than half a century, there has been a constant battle between human-oriented management and scientific or mechanistic management, with the latter prevailing. But it is only now, and for the first time, that there is a science behind this way of thinking that gives a legitimacy to the whole realm of human-centered management. With complexity science, we have human-oriented management practice emerging from science, a novelty.”
In Leading at the Edge, the authors write, “At the cusp of the twenty-first century, we are experiencing unprecedented structural shifts in our economy brought about by the revolutions in computation and communication technologies. Today the world is linked in ways unimaginable just a decade ago. A new kind of economy is emerging–the connected economy--a shift that rivals the onset of the Industrial Revolution in its impact on society and the way commerce is transacted. And with this shift, the business world finds itself in the throes of revolutionary change. Where once companies imagined themselves to be the master’s of their own destiny, in a connected economy companies find themselves as interdependent players in a fluid and vacillating economic web, where their fate, more than ever, is affected by the behavior of other members.
The change is not only real, but it is also accelerating, driven by rapid technological innovation, the globalization of business, and, not the least of it, the arrival of the Internet and the new domain of Internet commerce. Change–the pace of innovation, of forming and reforming alliances among companies, of corporate mergers, emerging markets–all driven by this connected economy, creates an environment of urgency in the workplace and a need to respond, adapt, anticipate that is unprecedented in the world of business as we knew it. Consequently, business leaders are preoccupied with change itself–how to generate it, how to respond to it, how to avoid being overcome by it. But, as Intel’s Andy Grove indicates, change is not exactly a welcome guest in business: "With all the rhetoric about change, the fact is that we managers hate change, especially when it involves us."
During these changing times, leaders and managers are finding many of their background assumptions and time-honored business models inadequate to help them understand what is going on, let alone how to deal with it. Where managers once operated with a Tayloresque mechanistic model of their world, which was predicated on linear thinking, control, and predictability, they now find themselves struggling with something more nonlinear, where limited control and a restricted ability to predict outcomes are the order of the day.
Consequently, many managers and executive professionals are uneasy and eagerly seeking new ways of dealing with change in their organizations, as the current $17 billion-a-year management consulting business would indicate. In the new connected economy, the limitations of the mechanistic model are becoming starkly apparent and a different mode of thinking is needed. In the connected economy of the twenty-first century, leaders cannot afford to try to succeed with management methods that were developed in a different age and for a different type of business environment.”
The authors conducted a study of organizations that exhibited some of the fundamental characteristics of a complexity science informed organization – “organizationally flat, have fewer levels of hierarchy, and promote open and plentiful communication and diversity. Complexity science argues that these properties enhance a system’s capacity for adaptability, thus, in the case of business, giving them a cutting edge in these fast-changing times. The companies we chose for our study therefore shared the properties of being organizationally flat and having rich, open communication. But we had no idea what we would find in the realm of organizational dynamics, of leadership and management style, and people’s work experience.
What we discovered was a style of leadership that unleashed enormous human potential in these organizations. We saw similar patterns among the leaders–CEOs, executive directors, chairmen, senior executives, managers–in how they worked with their business as a complex system. Because these patterns in leadership style emerged in companies of very different sizes and very different economic sectors, we infer that we are seeing something fundamental in how to lead change in organizations so that it is more adaptable and how to cultivate a culture in the workplace that is better able to embrace and create change.”
They found a way of leading change--an organic approach that is informed by complexity principles; and a style of leadership, paradoxical leadership that cultivates conditions for constructive change in organizations.
Later, the authors explain, “These elements of an organic approach for leading change are a different way of doing things in that these leaders didn’t make changes, they cultivated conditions for change to occur. Instead of implementing strategies or plans, they generated ambiguity and uncertainty, encouraged risks, attended to relationships which allowed the organization to rearrange itself. They engaged the whole person and forged connections between people which in turn made their organization more whole and connected.
If organizations are complex systems, leading in an interconnected, dynamic system requires a different way of being a leader. Leading in a dynamic system is more like an improvisational dance with the system rather than a mechanistic imperative of doing things to the system, as if it were an object that could be fixed. This casts the meaning of leadership itself in a different light that dispels certain beliefs and myths about what it means to be a leader in a traditional sense.”
The three myths of leadership that a complexity view dispels are autonomy, control, and omniscience.
The authors write, “What we have done is identify an intellectual framework, a scientific understanding of organizational dynamics that puts these behaviors under one umbrella of complexity, which shows why these behaviors are effective. We can see that these behaviors, such as mutuality and care, are efficacious in the business environment, not because being "nice" to people is a good and human thing to do, which, of course, it is; but because we are positively engaging the agents and the dynamics of the complex adaptive system, and moving the system toward the zone of creative adaptability.”
