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)
Tuesday, September 28, 2010
Monday, September 27, 2010
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.”
Valentine Coverly from Arcadia by Tom Stoppard
Valentine Coverly from Arcadia by Tom Stoppard
Critical State Complexity
"we’ve connected things so tightly to each other that small failures in one place vibrate throughout the entire system. If America’s dumb decision to use a fraction of its corn crop for ethanol can help set off food riots in thirty-seven countries, or if a series of shortsighted bets on Nevada mortgages can double unemployment in China, we’ve let our systems intertwine too much. If our driving habits can move the monsoon off the Asian subcontinent or melt the Arctic..."
Friday, September 24, 2010
An Odd Kind Of Sympathy (Synchronization)
"The phrase odd sympathy (the actual phrase used was odd kind of sympathy) was used by Dutch mathematician and physicist Christiaan Huygens (1629–95) in a letter to the Royal Society of London pertaining to the tendency of two pendulums to synchronize, or asynchronize, when mounted together on the same beam. Huygens, the inventor of the pendulum clock, noticed the effect while lying in bed. Two pendulums, mounted together, will always end up swinging in exactly opposite directions, regardless of their respective individual motion. This was one of the first observations of the phenomenon of coupled harmonic oscillators, which have many applications in physics.
Huygens originally believed the synchronization was due to air currents shared between the two pendulums, but he dismissed the hypothesis himself after several tests. Huygens would later attribute sympathetic motion of pendulums to imperceptible movement in the beam from which both pendulums are suspended. This idea was later validated by researchers from the Georgia Institute of Technology who tested Huygens' idea.
Using instruments capable of registering movement too small to have been measured in Huygens' time, the Georgia Tech researchers chronicled the nature of the forces at work on the supporting beam. They found that if the pendulums are moving in the same direction, together they tend to move the beam the opposite direction, giving rise to frictional forces that resist motion in the same direction. If however, the pendulums are moving in opposite directions, these forces cancel each other out, causing the beam to remain motionless. Thus, motion, in this example, tends to be perfectly asynchronous
Huygens observed anti-phase synchronization of pendulum clocks. Bennett and co-workers from the Georgia Institute of Technology reported also anti-phase synchronization of pendulum clocks in 2002. However, in-phase synchronization of pendulum clocks has also been observed. This was discussed by a book written by I.I. Blekhman. This was also mentioned in the book by Pikovsky and co-workers. A detailed analysis was provided by Fradkov and Andrievsky from Russia in 2007 regarding the conditions for in-phase or anti-phase synchronization of a 2-pendulum system."
Synchronization metronomes pendulum>
"Synchronisation of 5 coupled metronomes done in Lancaster University, Physics Dep, Nonlinear dynamics & medical physics group.Emails related to this video can be sent to:a.bahraminasabNOSPAM at gmail dot com.Some explanation by 'shoonya' which I think is pretty good:Here you go: metronomes (or "pendula") when on table, oscillate with random phases, since that is how they started & they are "uncoupled" (no energy/information flows from one to other so they do not "know" each other.) When they are all together on the cans, notice that the cans themselves oscillate little, providing coupling/information crossover. which forces "synchronization" in periodic systems (discovered by Huygens in 17th century).A useful book: "Synchronization: A Universal Concept in Nonlinear Sciences " by Arkady Pikovsky, Michael Rosenblum & Jurgen Kurths. A scientific article: http://scitation.aip.org/getabs/servl...My personal homepage:http://www.lancs.ac.uk/staff/bahramin...Reference to the original video: http://youtube.com/watch?v=RMVxVbCIPjg"
Huygens originally believed the synchronization was due to air currents shared between the two pendulums, but he dismissed the hypothesis himself after several tests. Huygens would later attribute sympathetic motion of pendulums to imperceptible movement in the beam from which both pendulums are suspended. This idea was later validated by researchers from the Georgia Institute of Technology who tested Huygens' idea.
Using instruments capable of registering movement too small to have been measured in Huygens' time, the Georgia Tech researchers chronicled the nature of the forces at work on the supporting beam. They found that if the pendulums are moving in the same direction, together they tend to move the beam the opposite direction, giving rise to frictional forces that resist motion in the same direction. If however, the pendulums are moving in opposite directions, these forces cancel each other out, causing the beam to remain motionless. Thus, motion, in this example, tends to be perfectly asynchronous
Huygens observed anti-phase synchronization of pendulum clocks. Bennett and co-workers from the Georgia Institute of Technology reported also anti-phase synchronization of pendulum clocks in 2002. However, in-phase synchronization of pendulum clocks has also been observed. This was discussed by a book written by I.I. Blekhman. This was also mentioned in the book by Pikovsky and co-workers. A detailed analysis was provided by Fradkov and Andrievsky from Russia in 2007 regarding the conditions for in-phase or anti-phase synchronization of a 2-pendulum system."
Synchronization metronomes pendulum>
"Synchronisation of 5 coupled metronomes done in Lancaster University, Physics Dep, Nonlinear dynamics & medical physics group.Emails related to this video can be sent to:a.bahraminasabNOSPAM at gmail dot com.Some explanation by 'shoonya' which I think is pretty good:Here you go: metronomes (or "pendula") when on table, oscillate with random phases, since that is how they started & they are "uncoupled" (no energy/information flows from one to other so they do not "know" each other.) When they are all together on the cans, notice that the cans themselves oscillate little, providing coupling/information crossover. which forces "synchronization" in periodic systems (discovered by Huygens in 17th century).A useful book: "Synchronization: A Universal Concept in Nonlinear Sciences " by Arkady Pikovsky, Michael Rosenblum & Jurgen Kurths. A scientific article: http://scitation.aip.org/getabs/servl...My personal homepage:http://www.lancs.ac.uk/staff/bahramin...Reference to the original video: http://youtube.com/watch?v=RMVxVbCIPjg"
Thursday, September 23, 2010
The Electrocardiogram, Complex Systems Science and Fundamental Laws of Biology
2010-08-18
The heart’s electric currents have been known for one hundred years, but three-quarters of a century later, the ECG is still giving up its secrets. Buchman explains the basic ECG signal and its relationship with the function of the human heart. He then turns to complex systems science to discover hidden structure within the ECG. These lie in frequencies (akin to musical tones); in variability (akin to the change in directions of a walker choosing not-quite-random steps); and in network design (akin to adding/losing elements of a power grid). Finally, he explores the ways in which the ECG might point towards the existence of fundamental laws of biology. Armed with these fundamental laws, we ask how complex systems science might allow us to guide care in the intensive care unit.
The lecture is generously underwritten by Los Alamos National Bank and by Maureen Mestas Abrams, Associate Broker, Prudential Santa Fe Real Estate
View Video
The lecture is generously underwritten by Los Alamos National Bank and by Maureen Mestas Abrams, Associate Broker, Prudential Santa Fe Real Estate
View Video
Blogging Out of Balance
An essay in Seed Magazine by Dave Munger reviews several studies that show that in the filed of science blogs, males outnumber females by almost 3 to 1.
Read More
Read More
Scientific Commons
ScientificCommons is a project of the University of St. Gallen Institute for Media and Communications Management. The major aim of the project is to develop the world’s largest archive of scientific knowledge with fulltexts freely accessible to the public.
ScientificCommons includes a search engine for publications and author profiles. It also allows the user to turn searches into customized RSS feeds of new publications. ScientificCommons also provides a fulltext caching service for researchers.
Stigmergy
Stigmergy – the phenomenon of indirect communication mediated by modifications of the environment – was first conceptualized by zoologist Pierre-Paul Grasse in his ground-breaking work on termite colonies (Grasse 1959). It wasn’t until 1999 that Grasse’s work was brought to a wider audience by Eric Bonabeau et al (1999) in a special issue of Artificial Life. Since then interest in stigmergic systems has blossomed with researchers recognizing the application of Grasse’s insights to stock markets, economies, traffic patterns, supply logistics, computer networks, resource allocation, urban sprawl, and cultural memes. New forms of stigmergy have been exponentially expanded through the affordances of digital technology: Google’s recommendation algorithm, Amazon’s filtering algorithm, wiki, open source software, weblogs, and a whole range of “social media” are now deemed as essentially stigmergic.
Though the concept of stigmergy has typically been associated with ant- or swarm-like “agents” with minimal cognitive ability or with creatures of a somewhat higher cognitive capacity such as fish (schooling patterns) or birds (flocking patterns) or sheep (herding behavior), stigmergy offers a powerful tool to be deployed in the human domain. The editors of this special issue are thus looking for contributions that have human-human (social, organizational, and socio-technical) stigmergy as the main focus.
Proposals are invited from social scientists, social epistemologists, cognitive scientists, economists, group decision theorists, collective intentionality theorists, computational sociologists, network theorists, multi-agent modelers, and indeed researchers from any discipline that has social complexity and coordination as a core topic.
Papers that are theoretical, experimental, or computational in orientation are welcome. Please send proposals of no more than 300 words to lesliemarsh [at] gmail [dot] com with “Stigmergy/Cognitive Systems Research” in the subject line. The deadline for proposals is Nov 1, 2010.
All papers will be subject to double blind review by a least two referees and accepted papers will be published in a special issue of Cognitive Systems Research
Though the concept of stigmergy has typically been associated with ant- or swarm-like “agents” with minimal cognitive ability or with creatures of a somewhat higher cognitive capacity such as fish (schooling patterns) or birds (flocking patterns) or sheep (herding behavior), stigmergy offers a powerful tool to be deployed in the human domain. The editors of this special issue are thus looking for contributions that have human-human (social, organizational, and socio-technical) stigmergy as the main focus.
Proposals are invited from social scientists, social epistemologists, cognitive scientists, economists, group decision theorists, collective intentionality theorists, computational sociologists, network theorists, multi-agent modelers, and indeed researchers from any discipline that has social complexity and coordination as a core topic.
Papers that are theoretical, experimental, or computational in orientation are welcome. Please send proposals of no more than 300 words to lesliemarsh [at] gmail [dot] com with “Stigmergy/Cognitive Systems Research” in the subject line. The deadline for proposals is Nov 1, 2010.
All papers will be subject to double blind review by a least two referees and accepted papers will be published in a special issue of Cognitive Systems Research
Emergent Behavior Applet
This Java applet was created by Curran Kelleher, a student at UMass Lowell and NECSI. It demonstrates the incredibly wide range of collective behaviors that can emerge from relatively simple rules of interaction.
Use the sliders in the pop-up window to vary several key parameters and see what kinds of behaviors and patterns result.
This is a different and very cool applet demonstrating emergence by varying physical parameters.
Emergent Behavior Applet
Use the sliders in the pop-up window to vary several key parameters and see what kinds of behaviors and patterns result.
This is a different and very cool applet demonstrating emergence by varying physical parameters.
Emergent Behavior Applet
Wednesday, September 22, 2010
Complexity, Change and Well Being
Some interesting thoughts about complexity by Mike Bell from his LinkedIn Group Social Entrepreneurship and Complexity.
Complexity, Change and Wellbeing
Complexity, Change and Wellbeing
View more presentations from Mike Bell.
Friday, September 17, 2010
Capitalizing on Complexity
Capitalizing on Complexity: Insights from the Global Chief Executive Officer Study
“This study is the fourth edition of our biennial Global CEO Study series, led by the IBM Institute for Business Value and IBM Strategy & Change. To better understand the challenges and goals of today’s CEOs, we met face-to-face with the largest-known sample of these senior executives. Between September 2009 and January 2010, we interviewed 1,541 CEOs, general managers and senior public sector leaders who represent different sizes of organizations in 60 countries and 33 industries.”
The beginning few paragraphs of the executive summary read, “In our past three global CEO studies, CEOs consistently said that coping with change was their most pressing challenge. In 2010, our conversations identified a new primary challenge: complexity. CEOs told us they operate in a world that is substantially more volatile, uncertain and complex.
Many shared the view that incremental changes are no longer sufficient in a world that is operating in fundamentally different ways. Four primary findings arose from our conversations:
Today’s complexity is only expected to rise, and more than half of CEOs doubt their ability to manage it. Seventy-nine percent of CEOs anticipate even greater complexity ahead. However, one set of organizations — we call them “Standouts” — has turned increased complexity into financial advantage over the past five years.
Creativity is the most important leadership quality, according to CEOs. Standouts practice and encourage experimentation and innovation throughout their organizations. Creative leaders expect to make deeper business model changes to realize their strategies. To succeed, they take more calculated risks, find new ideas, and keep innovating in how they lead and communicate.
The most successful organizations co-create products and services with customers, and integrate customers into core processes. They are adopting new channels to engage and stay in tune with customers. By drawing more insight from the available data, successful CEOs make customer intimacy their number-one priority.
Better performers manage complexity on behalf of their organizations, customers and partners. They do so by simplifying operations and products, and increasing dexterity to change the way they work, access resources and enter markets around the world. Compared to other CEOs, dexterous leaders expect 20 percent more future revenue to come from new sources.”
Now in line with “full disclosure” and “transparency”, I have to tell you that I worked for IBM for 30 years. In the first ten years of my career with IBM I pursued technology invention and development. I thought that IBM would be successful if we were a leader in technology. In the second ten years I pursued innovation in business practices and product development helping to create the first independent business unit of IBM. Essentially we were doing what came to be called process reengineering some years later. Having first found out that technology development was stymied by the formal business practices of IBM, I then found out that changing business practices did no good if the organizational culture remained the same. The changes were only temporary and quickly snapped back to what they were before. So, I spent the last ten years on organizational culture and how you change it. For about the last seven years, I was a “grass roots” agitator for changing the values of the culture to strengthen creativity, innovativeness, leadership (called situational leadership at the time) and professionalism. After retiring from IBM I wrote a book on my methodology titled Innovate!.
I’m sure that you have guessed by now that my message fell on rocky ground with little soil in the 1980s.
Now, 30 years later and IBM is in the consulting business big time and touting, of all things, creativity.
OK, times change, People and organizations change. I get it.
So, I read the report carefully, marking sections and quotes to call out in this analysis I’m now writing. Unfortunately when I finished the report, I hit a brick wall. The report repeatedly used key words like complexity, creativity, leadership and innovation. These are words that I know well as I’ve lived them for 52 years. I also know that they are some of the fuzziest concepts in the business lexicon. Just about everyone has their own definitions of these words and very few of them agree with each other. Furthermore, the report did not define the words making most of the conclusions suspect. For example, when CEOs said that complexity was their biggest challenge, what definition of complexity did each of them use.
Most of the time when the authors mention complexity, they are really talking about complicatedness. If a system is complicated, cause and effect are related. If a system has the characteristic of organized complexity, cause and effect are no longer related. If the system is characterized by disorganized complexity, cause and effect are again related, but statistically.
Simple, complicated and disorganized complex systems are tractable. Organized complex systems are not. Unfortunately, many of the systems that CEOs (and the rest of us as well) have to deal with now are organized complex systems.
I’m guessing, but I think that this latter type of complexity is what the CEOs are apprehending. Unfortunately the solutions being considered and the recommendations made are not useful for this type of complexity, and may even be harmful.
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 Reality of Complexity
Some Thoughts on Complexity
1, 2, a Few, Many
Capitalizing on Complexity: Insights from the Global Chief Executive Officer Study
“This study is the fourth edition of our biennial Global CEO Study series, led by the IBM Institute for Business Value and IBM Strategy & Change. To better understand the challenges and goals of today’s CEOs, we met face-to-face with the largest-known sample of these senior executives. Between September 2009 and January 2010, we interviewed 1,541 CEOs, general managers and senior public sector leaders who represent different sizes of organizations in 60 countries and 33 industries.”
The beginning few paragraphs of the executive summary read, “In our past three global CEO studies, CEOs consistently said that coping with change was their most pressing challenge. In 2010, our conversations identified a new primary challenge: complexity. CEOs told us they operate in a world that is substantially more volatile, uncertain and complex.
Many shared the view that incremental changes are no longer sufficient in a world that is operating in fundamentally different ways. Four primary findings arose from our conversations:
Today’s complexity is only expected to rise, and more than half of CEOs doubt their ability to manage it. Seventy-nine percent of CEOs anticipate even greater complexity ahead. However, one set of organizations — we call them “Standouts” — has turned increased complexity into financial advantage over the past five years.
Creativity is the most important leadership quality, according to CEOs. Standouts practice and encourage experimentation and innovation throughout their organizations. Creative leaders expect to make deeper business model changes to realize their strategies. To succeed, they take more calculated risks, find new ideas, and keep innovating in how they lead and communicate.
The most successful organizations co-create products and services with customers, and integrate customers into core processes. They are adopting new channels to engage and stay in tune with customers. By drawing more insight from the available data, successful CEOs make customer intimacy their number-one priority.
Better performers manage complexity on behalf of their organizations, customers and partners. They do so by simplifying operations and products, and increasing dexterity to change the way they work, access resources and enter markets around the world. Compared to other CEOs, dexterous leaders expect 20 percent more future revenue to come from new sources.”
Now in line with “full disclosure” and “transparency”, I have to tell you that I worked for IBM for 30 years. In the first ten years of my career with IBM I pursued technology invention and development. I thought that IBM would be successful if we were a leader in technology. In the second ten years I pursued innovation in business practices and product development helping to create the first independent business unit of IBM. Essentially we were doing what came to be called process reengineering some years later. Having first found out that technology development was stymied by the formal business practices of IBM, I then found out that changing business practices did no good if the organizational culture remained the same. The changes were only temporary and quickly snapped back to what they were before. So, I spent the last ten years on organizational culture and how you change it. For about the last seven years, I was a “grass roots” agitator for changing the values of the culture to strengthen creativity, innovativeness, leadership (called situational leadership at the time) and professionalism. After retiring from IBM I wrote a book on my methodology titled Innovate!.
I’m sure that you have guessed by now that my message fell on rocky ground with little soil in the 1980s.
Now, 30 years later and IBM is in the consulting business big time and touting, of all things, creativity.
OK, times change, People and organizations change. I get it.
So, I read the report carefully, marking sections and quotes to call out in this analysis I’m now writing. Unfortunately when I finished the report, I hit a brick wall. The report repeatedly used key words like complexity, creativity, leadership and innovation. These are words that I know well as I’ve lived them for 52 years. I also know that they are some of the fuzziest concepts in the business lexicon. Just about everyone has their own definitions of these words and very few of them agree with each other. Furthermore, the report did not define the words making most of the conclusions suspect. For example, when CEOs said that complexity was their biggest challenge, what definition of complexity did each of them use.
Most of the time when the authors mention complexity, they are really talking about complicatedness. If a system is complicated, cause and effect are related. If a system has the characteristic of organized complexity, cause and effect are no longer related. If the system is characterized by disorganized complexity, cause and effect are again related, but statistically.
Simple, complicated and disorganized complex systems are tractable. Organized complex systems are not. Unfortunately, many of the systems that CEOs (and the rest of us as well) have to deal with now are organized complex systems.
I’m guessing, but I think that this latter type of complexity is what the CEOs are apprehending. Unfortunately the solutions being considered and the recommendations made are not useful for this type of complexity, and may even be harmful.
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 Reality of Complexity
Some Thoughts on Complexity
1, 2, a Few, Many
Capitalizing on Complexity: Insights from the Global Chief Executive Officer Study
Wednesday, September 15, 2010
Reality Check
From Weblogg-ed by Will Richardson
"It is the thesis of this book that change—constant, accelerating, ubiquitous—is the most striking characteristic of the world we live in and that our educational system has not yet recognized this fact. We maintain, further, that the abilities and attitudes required to deal adequately with change are those of the highest priority and that it is not beyond our ingenuity to design school environments which can help young people to master concepts necessary to survival in a rapidly changing world. The institution we call “school” is what it is because we made it that way. If it is irrelevant…if it shields children from reality…if it educates for obsolescence…if it does not develop intelligence…if it is based on fear…if it avoids the promotion of significant learnings…if it induces alienation…if it punishes creativity and independence…if, in short, it is not doing what needs to be done, it can be changed; it must be changed."
Neil Postman
Teaching as a Subversive Activity
1968
Forty two years ago. It really, really begs the question…can it?
"It is the thesis of this book that change—constant, accelerating, ubiquitous—is the most striking characteristic of the world we live in and that our educational system has not yet recognized this fact. We maintain, further, that the abilities and attitudes required to deal adequately with change are those of the highest priority and that it is not beyond our ingenuity to design school environments which can help young people to master concepts necessary to survival in a rapidly changing world. The institution we call “school” is what it is because we made it that way. If it is irrelevant…if it shields children from reality…if it educates for obsolescence…if it does not develop intelligence…if it is based on fear…if it avoids the promotion of significant learnings…if it induces alienation…if it punishes creativity and independence…if, in short, it is not doing what needs to be done, it can be changed; it must be changed."
Neil Postman
Teaching as a Subversive Activity
1968
Forty two years ago. It really, really begs the question…can it?
Tuesday, September 14, 2010
The Reality of Complexity
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.”
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.”
Simplicity is Highly Overrated
Don Norman has written a provocative essay on his blog. His reports that research shows that people will purchase a product that has more controls and indicators on it than one with fewer. Humans seem to think that if the product looks complicated it must have more function and be more powerful.
He writes, "...it is the apparent complexity that drives the sale. And yes, it is the same complexity that frustrates those same people later on. But by then, it is too late: they have already purchased the product."
At the end of his essay her comments, "Logic is not the way to answer these issues: human behavior is the key. Avoid the engineer's and economist's fallacy: don't reason your way to a solution -- observe real people. We have to take human behavior the way it is, not the way we would wish it to be. So, of course I am in favor of good design and attractive products. Easy to use products. But when it comes time to purchase, people tend to go for the more powerful products, and they judge the power by the apparent complexity of the controls. If that is what people use as a purchasing choice, we must provide it for them. While making the actual complexity low, the real simplicity high. That's an exciting design challenge: make it look powerful while also making it easy to use. And attractive. And affordable. And functional. And environmentally appropriate. Accessible to all."
My only concern with his essay is that he uses complexity to mean complicated. I will write later on the taxonomy of simplicity and complexity.
He writes, "...it is the apparent complexity that drives the sale. And yes, it is the same complexity that frustrates those same people later on. But by then, it is too late: they have already purchased the product."
At the end of his essay her comments, "Logic is not the way to answer these issues: human behavior is the key. Avoid the engineer's and economist's fallacy: don't reason your way to a solution -- observe real people. We have to take human behavior the way it is, not the way we would wish it to be. So, of course I am in favor of good design and attractive products. Easy to use products. But when it comes time to purchase, people tend to go for the more powerful products, and they judge the power by the apparent complexity of the controls. If that is what people use as a purchasing choice, we must provide it for them. While making the actual complexity low, the real simplicity high. That's an exciting design challenge: make it look powerful while also making it easy to use. And attractive. And affordable. And functional. And environmentally appropriate. Accessible to all."
My only concern with his essay is that he uses complexity to mean complicated. I will write later on the taxonomy of simplicity and complexity.
Thursday, September 9, 2010
The Science of Cooperation
Utne Readers, Sept. - Oct. 2010
"Elinor Ostrom was an unusual choice for the 2009 Nobel Memorial Prize in Economic Sciences. She is the first woman to receive the prize, and her doctorate is in political science, not economics (though she considers herself a political economist). And while standard economics focuses on competition, her work is about cooperation.
Ostrom’s influential book Governing the Commons: The Evolution of Institutions for Collective Action was published in 1990. But her research on common property goes back to the 1960s, when she wrote her dissertation on groundwater in California. In 1973 she and her husband, Vincent Ostrom, founded the Workshop in Political Theory and Policy Analysis at Indiana University, which has produced hundreds of studies of the ways in which communities self-organize to solve common problems.
Fran Korten, Yes! magazine’s publisher, interviewed Ostrom shortly after Ostrom received the Nobel Prize.
Many people associate “the commons” with Garrett Hardin’s famous essay “The Tragedy of the Commons.” He says that if, for example, you have a pasture that everyone in a village has access to, then each person will put as many cows on that land as he can to maximize his own benefit, and pretty soon the pasture will be overgrazed and become worthless. What’s the difference between your perspective and Hardin’s?
I don’t see the human as hopeless. There’s a tendency to presume people act just for short-term profit. But anyone who knows about small-town businesses and how people in a community relate to one another realizes that many decisions are not made just for profit, and that humans do try to organize and solve problems.
If you are in a fishery or have a pasture and you know that not destroying it is to your family’s long-term benefit, and if you can talk with the other people who use that resource, then you may well figure out rules that fit that local setting and organize to enforce them. But if community members don’t have a good way of communicating with each other or the costs of self-organization are too high, then they won’t organize, and there will be failures."
Read the Article
"Elinor Ostrom was an unusual choice for the 2009 Nobel Memorial Prize in Economic Sciences. She is the first woman to receive the prize, and her doctorate is in political science, not economics (though she considers herself a political economist). And while standard economics focuses on competition, her work is about cooperation.
Ostrom’s influential book Governing the Commons: The Evolution of Institutions for Collective Action was published in 1990. But her research on common property goes back to the 1960s, when she wrote her dissertation on groundwater in California. In 1973 she and her husband, Vincent Ostrom, founded the Workshop in Political Theory and Policy Analysis at Indiana University, which has produced hundreds of studies of the ways in which communities self-organize to solve common problems.
Fran Korten, Yes! magazine’s publisher, interviewed Ostrom shortly after Ostrom received the Nobel Prize.
Many people associate “the commons” with Garrett Hardin’s famous essay “The Tragedy of the Commons.” He says that if, for example, you have a pasture that everyone in a village has access to, then each person will put as many cows on that land as he can to maximize his own benefit, and pretty soon the pasture will be overgrazed and become worthless. What’s the difference between your perspective and Hardin’s?
I don’t see the human as hopeless. There’s a tendency to presume people act just for short-term profit. But anyone who knows about small-town businesses and how people in a community relate to one another realizes that many decisions are not made just for profit, and that humans do try to organize and solve problems.
If you are in a fishery or have a pasture and you know that not destroying it is to your family’s long-term benefit, and if you can talk with the other people who use that resource, then you may well figure out rules that fit that local setting and organize to enforce them. But if community members don’t have a good way of communicating with each other or the costs of self-organization are too high, then they won’t organize, and there will be failures."
Read the Article
Education is a self organizing system, where learning is an emergent phenomenon.
Education scientist Sugata Mitra tackles one of the greatest problems of education -- the best teachers and schools don't exist where they're needed most. In a series of real-life experiments from New Delhi to South Africa to Italy, he gave kids self-supervised access to the web and saw results that could revolutionize how we think about teaching.
Sugata Mitra's "Hole in the Wall" experiments have shown that, in the absence of supervision or formal teaching, children can teach themselves and each other, if they're motivated by curiosity.
This is a very interesting and insightful body of work. He starts with the following premise: There are places on Earth, in every country, where, for various reasons, good schools cannot be built and good teachers cannot or do not want to go.
Then with technology and the Internet, he lets students find there own way to learn, sometimes without any problem to work and sometimes with a problem. He uses very little instructions and no actual "teaching". In some cases he uses what he calls "grandmothers" to encourage the kids.
The results are striking and counter intuitive.
His explanation is that he has created a complex system with emergent properties.
He defines two characteristics of the system:
Self organizing system: A self organizing system is one where the system structure appears without explicit intervention from outside the system.
Emergence: The appearance of a property not previously observed as a functional characteristic of the system.
He then concludes with what I think is a very powerful observation:
Education is a self organizing system, where learning is an emergent phenomenon.
Sugata Mitra's "Hole in the Wall" experiments have shown that, in the absence of supervision or formal teaching, children can teach themselves and each other, if they're motivated by curiosity.
This is a very interesting and insightful body of work. He starts with the following premise: There are places on Earth, in every country, where, for various reasons, good schools cannot be built and good teachers cannot or do not want to go.
Then with technology and the Internet, he lets students find there own way to learn, sometimes without any problem to work and sometimes with a problem. He uses very little instructions and no actual "teaching". In some cases he uses what he calls "grandmothers" to encourage the kids.
The results are striking and counter intuitive.
His explanation is that he has created a complex system with emergent properties.
He defines two characteristics of the system:
Self organizing system: A self organizing system is one where the system structure appears without explicit intervention from outside the system.
Emergence: The appearance of a property not previously observed as a functional characteristic of the system.
He then concludes with what I think is a very powerful observation:
Education is a self organizing system, where learning is an emergent phenomenon.
Often Wrong, But Never in Doubt
Richard Thaler, New York Times, 8/22/10
"Businesses in nearly every industry were caught off guard by the Great Recession. Few leaders in business — or government, for that matter — seem to have even considered the possibility that an economic downturn of this magnitude could happen.
What was wrong with their thinking? These decision-makers may have been betrayed by a flaw that has been documented in hundreds of studies: overconfidence.
Most of us think that we are “better than average” in most things. We are also “miscalibrated,” meaning that our sense of the probability of events doesn’t line up with reality. When we say we are sure about a certain fact, for example, we may well be right only half the time."
This is a really interesting article about how bad we are at forecasting the future.
"...chief financial officers of major American corporations are not very good at forecasting the future. The authors’ investigation used a quarterly survey of C.F.O.’s that Duke has been running since 2001. Among other things, the C.F.O.’s were asked about their expectations for the return of the Standard & Poor’s 500-stock index for the next year — both their best guess and their 80 percent confidence limit. This means that in the example above, there would be a 10 percent chance that the return would be higher than the upper bound, and a 10 percent chance that it would be less than the lower one.
It turns out that C.F.O.’s, as a group, display terrible calibration. The actual market return over the next year fell between their 80 percent confidence limits only a third of the time, so these executives weren’t particularly good at forecasting the stock market. In fact, their predictions were negatively correlated with actual returns. For example, in the survey conducted on Feb. 26, 2009, the C.F.O.’s made their most pessimistic predictions, expecting a market return of just 2.0 percent, with a lower bound of minus 10.2 percent. In fact, the market soared 42.6 percent over the next year."
One of the interesting omissions of this article is that it never mentions the complexity of the future. It blames the failures on "mis-calibration" and "hubris".
Read the Article
"Businesses in nearly every industry were caught off guard by the Great Recession. Few leaders in business — or government, for that matter — seem to have even considered the possibility that an economic downturn of this magnitude could happen.
What was wrong with their thinking? These decision-makers may have been betrayed by a flaw that has been documented in hundreds of studies: overconfidence.
Most of us think that we are “better than average” in most things. We are also “miscalibrated,” meaning that our sense of the probability of events doesn’t line up with reality. When we say we are sure about a certain fact, for example, we may well be right only half the time."
This is a really interesting article about how bad we are at forecasting the future.
"...chief financial officers of major American corporations are not very good at forecasting the future. The authors’ investigation used a quarterly survey of C.F.O.’s that Duke has been running since 2001. Among other things, the C.F.O.’s were asked about their expectations for the return of the Standard & Poor’s 500-stock index for the next year — both their best guess and their 80 percent confidence limit. This means that in the example above, there would be a 10 percent chance that the return would be higher than the upper bound, and a 10 percent chance that it would be less than the lower one.
It turns out that C.F.O.’s, as a group, display terrible calibration. The actual market return over the next year fell between their 80 percent confidence limits only a third of the time, so these executives weren’t particularly good at forecasting the stock market. In fact, their predictions were negatively correlated with actual returns. For example, in the survey conducted on Feb. 26, 2009, the C.F.O.’s made their most pessimistic predictions, expecting a market return of just 2.0 percent, with a lower bound of minus 10.2 percent. In fact, the market soared 42.6 percent over the next year."
One of the interesting omissions of this article is that it never mentions the complexity of the future. It blames the failures on "mis-calibration" and "hubris".
Read the Article
Wednesday, September 8, 2010
Complexity/Chaos Stories: Butterflies, Keystones and Climbers
Cynthia Kurtz, Story Colored Glasses, 9/3/10
This is an interesting and insightful blog entry (although somewhat long). Cynthia Kurtz describes herself as a “researcher, writer, and programmer who works on the ‘listening side’ of organizational and community narrative.”
In this essay, she looks at the subject of complexity through the lens of narrative, and apologizes to her readers. “Since I posted some thoughts about complexity a while back, I've been surprised both by the number of people who have been interested in what I said (and encouraged me to write more), and by the degree to which I find myself wanting to write more. I still have much to write about narrative, but I also seem to want to write more about complexity as it relates to sensemaking and decision support. Since this blog is supposed to be about narrative, I keep feeling a need to apologize whenever I write about complexity.
But really there is nothing to be sorry for. My work on the "listening side" of narrative centers on the place where stories and patterns come together. Narrative incorporates complexity because stories self-organize into emergent patterns, and complexity incorporates narrative because complex systems are historical systems. I remember when I first realized this, and what a rush it was to discover synergy between two fields I had come to love. Thus, dear reader, henceforth I resolve to stop apologizing for combining these topics!”
The metaphor (story) about the butterfly in Brazil and the tornado in Texas came from Lorenz. “Lorenz's first talk on the topic in 1972 was titled ‘Predictability: Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?’ His answer was not ‘yes’ but an emphatic ‘impossible to say’.” Kurtz shows how this correct interpretation of the impact of minor perturbations in the weather morphed into predictability, linking cause and effect.
She gives a selection of excerpts and then points out, “These excerpts, and almost all popular and business interpretations of the butterfly effect, transform a statement about uncertainty to one about certainty. The second story changes the butterfly effect from tiny actions piling up in unpredictable ways to tiny actions having predictable and controllable impacts. I have taken to calling this second story the "underbutterfly effect," because the butterfly in these versions is a powerful underdog who changes the world, not one of millions of other butterflies (not to mention innumerable more powerful creatures) whose feeble flaps are lost in the sea of uncertainty in which we live.”
Kurtz examines two other narratives that have morphed into stories we want to believe in. We changed the story of the butterfly because we can’t seem to accept that a large part of our world exists without cause and effect in play. Causality is deeply ingrained in our world view.
“In 1969 Robert T. Paine introduced the idea of a keystone species to ecology”, she writes. “Paine discovered this phenomenon in an experiment during which he removed a single species of sea star from a small area of shoreline and found that it had far-reaching effects on species diversity. Most importantly, the effect produced by its removal was out of proportion to its relative abundance in the community.” Like the butterfly narrative, this story morphed driven by our desire for certainty. The keystone became what she calls a topstone. “As with the underbutterfly story, the topstone story began to surface soon after Paine started publishing papers about his concept. What seems to have happened is that people involved in wildlife conservation started trying to identify keystone species in order to wisely use limited conservation budgets. Political, cultural and special-interest complexities joined the mix, and the keystone species concept widened and weakened as a result. For environmental study, retrospective discovery might suffice, but for environmental action, people wanted certainty.”
Her last narrative is about the adaptive landscape. “I first encountered Sewall Wright's adaptive landscape metaphor in college, and as a visual thinker I found it useful right away. Even though the metaphor is severely limited, many evolutionary theorists use it as a visual shorthand for thinking about genetic change. The way the metaphor works is this. Populations are located in X and Y dimensions to describe their genetic makeup (in a radically simplified way). They exist on a landscape where the height of each point describes the fitness of the population with that particular XY combination of genetic variables.” By describing fitness as a peak, the metaphor conveyed a lot of uncertainty. A small nudge could send the species down in any direction into a valley. Physicists tend to look at this type of metaphor in the opposite direction where potential energy increase in the peaks and valleys are lower potential energy.
I have to admit that with my physics background I had trouble with section of her discussion because when I first saw the metaphor, I thought to my self that it was upside down. The trend would be for the species to always roll down the hill into the “genetic valley of death.”
Kurtz writes, “One more and then I'm really done, I promise. This is from The Quark and the Jaguar by Murray Gell-Mann:
Biologists conventionally represent fitness as increasing with increasing height, so that maxima of fitness correspond to the tops of hills and minima to the bottom of pits; however, I shall use the reverse convention, which is customary in many other fields, and turn the whole picture upside-down.
Gell-Mann then gets into the difficulties of this flip, seemingly without realizing it:
If the effect of evolution were always to move steadily downhill -- always to improve fitness -- then the genotype would be likely to get stuck at the bottom of a shallow depression and have no opportunity to reach the deep holes nearby that correspond to much greater fitness. At the very least, the genotype must be moving in a more complicated manner than just sliding downhill.
That is precisely the problem with flipping the landscape: that when you do so, things that are in reality very complicated seem simple, and certain.”
This desire to correct uncertainty runs strong in us. She writes, “If you think about it, this is not at all surprising. We have been conditioned since an early age to believe in this equation:
uncertainty + science = certainty
When we meet an equation like this:
uncertainty + science = more uncertainty
We react, and a second story arises. That can't be right. There must be another explanation. That's what Edward Lorenz said when his computer generated a new weather system based on what he thought were the same inputs. He called in the hardware engineers to find the broken vacuum tube.”
She summarizes her essay in a section titled “A Generation, or Two Or Three, to Sink In. “If people tell second stories about complexity because we aren't ready for the first stories, I think our children are ready. In many of my narrative projects I ask people to rate the predictability of events in stories -- it's useful to map perceptions of stability and instability across conceptual space. I've noticed a pattern across several projects that older people are more likely to associate instability with negative outcomes in stories. Younger people are more likely to mark stories as both unstable and positive.
I was thinking about all this the other day while playing with my son, and two things happened that gave me food for thought. The first was that we watched the movie Clifford's Really Big Movie. It's a great movie, and it's in our pantheon now and will probably be watched many more times. One of my favorite parts of the movie is this lovely song, which my six-year-old understood and liked immediately. It goes, in part:
You've gotta get lost if you wanna get found
Gotta wind up to get unwound
Things only look up from down below
And I can't come home until I go
It only gets better after it gets worse
Happy ever after needs a scary part first
You've gotta fall down to get back on
And I can't come home until I'm gone.”
Later, she writes, “According to my surely-biased reading, there are three ways the authors of business books about complexity and chaos provide reassurance to those in charge. One is to drain the power out of the major discoveries by highlighting the second stories, which do exist in science and so can be called scientific: the underbutterfly, the topstone, and the easy roller. The first stories can be waved away as "internal disputes" that don't matter.
The second method of making complexity palatable to those in charge is to make it seem magical. That is why the phrase "order for free" is so wildly attractive in these books, and why people love to throw around terms like "strange attractor" and "fitness landscape" and "coevolution" -- because they are magic words of power that seem to promise something for nothing. Even "nonlinear" effects are spoken of mainly for the idea of something small going in and something big (and beneficial to the reader) coming out. I see this rose-colored view of complexity in most (but not all) business writings about complexity. Consider for example the way people talk about coevolution: nearly every treatment of business coevolution I have read has talked about it like nothing can possibly go wrong. But in real coevolution things can and do go horribly wrong at times. It is these sorts of distortions that not only give complexity concepts a bad name (because rarely can such wild claims of magical power be justified) but also spread confusion about the true utility of complexity and chaos based approaches.
And finally, the third and most used tool in the business complexity writer's toolkit is that the sky is falling. You need this, say the business books, because the world has changed in such dramatic ways that you can't possibly survive without it. People who use this tool ramp up the fear quotient by making claims such as that "an organization is a complex adaptive system" -- the implication being, and you had better find out what that means, and quick. But organizations are not complex adaptive systems! More precisely, they are not only complex adaptive systems. An organization is a lot of people. Those people interact with each other in many ways, some of which are complex and emergent, and some of which are not. Organization and self-organization, hierarchy and meshwork are inextricably bound up together in organizations, and saying an organization "is" one without the other is sheer nonsense and is probably meant to entice rather than inform. There are no only-complex social groupings in human life. Every gathering of ten huts has a path through it. Every lunch meeting has a leader. Every subway car has a social structure, if even only for the two minutes the same people are in it. That's what we do. There may be such things as only-complex systems in the lives of social insects, but even there some hierarchy (in the form of central pheromonal control) is usually mixed in.”
She concludes with, “My advice, if anyone wanted it, would be this. First, stop saying everything is complex, and start talking about how complexity and hierarchy can work to mutual benefit.”
“When you don't fear complexity, when you see it as a part of reality but not a ‘whole new world’ dominated by a falling sky, you don't have to muzzle it. The underbutterfly and the topstone and the easy roller can go plague other people. You can take the butterfly and the keystone and the steadfast climber as they come to you, in stride. You can learn to recognize them, deal with them, work with them and even in time welcome them as old friends. You'll just know better than to hand over your car keys to them.”
As it turns out, this is the conclusion I had recently reached intuitively. She has done all the work that suggests that this is correct. I was drawing from my experience with physics and squaring Newtonian, Quantum and Relativistic physics. All are present in everything. It’s just in certain conditions one view works best. But you have to know when you are in what type of physics. To complicate matters, there are at least three different types of “messy” complexity and one type more tractable. For example in the behavior of markets there are trends, cycles and complexity. Complexity is in the fine structure of the behavior of the market.
Read Her Blog
This is an interesting and insightful blog entry (although somewhat long). Cynthia Kurtz describes herself as a “researcher, writer, and programmer who works on the ‘listening side’ of organizational and community narrative.”
In this essay, she looks at the subject of complexity through the lens of narrative, and apologizes to her readers. “Since I posted some thoughts about complexity a while back, I've been surprised both by the number of people who have been interested in what I said (and encouraged me to write more), and by the degree to which I find myself wanting to write more. I still have much to write about narrative, but I also seem to want to write more about complexity as it relates to sensemaking and decision support. Since this blog is supposed to be about narrative, I keep feeling a need to apologize whenever I write about complexity.
But really there is nothing to be sorry for. My work on the "listening side" of narrative centers on the place where stories and patterns come together. Narrative incorporates complexity because stories self-organize into emergent patterns, and complexity incorporates narrative because complex systems are historical systems. I remember when I first realized this, and what a rush it was to discover synergy between two fields I had come to love. Thus, dear reader, henceforth I resolve to stop apologizing for combining these topics!”
The metaphor (story) about the butterfly in Brazil and the tornado in Texas came from Lorenz. “Lorenz's first talk on the topic in 1972 was titled ‘Predictability: Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?’ His answer was not ‘yes’ but an emphatic ‘impossible to say’.” Kurtz shows how this correct interpretation of the impact of minor perturbations in the weather morphed into predictability, linking cause and effect.
She gives a selection of excerpts and then points out, “These excerpts, and almost all popular and business interpretations of the butterfly effect, transform a statement about uncertainty to one about certainty. The second story changes the butterfly effect from tiny actions piling up in unpredictable ways to tiny actions having predictable and controllable impacts. I have taken to calling this second story the "underbutterfly effect," because the butterfly in these versions is a powerful underdog who changes the world, not one of millions of other butterflies (not to mention innumerable more powerful creatures) whose feeble flaps are lost in the sea of uncertainty in which we live.”
Kurtz examines two other narratives that have morphed into stories we want to believe in. We changed the story of the butterfly because we can’t seem to accept that a large part of our world exists without cause and effect in play. Causality is deeply ingrained in our world view.
“In 1969 Robert T. Paine introduced the idea of a keystone species to ecology”, she writes. “Paine discovered this phenomenon in an experiment during which he removed a single species of sea star from a small area of shoreline and found that it had far-reaching effects on species diversity. Most importantly, the effect produced by its removal was out of proportion to its relative abundance in the community.” Like the butterfly narrative, this story morphed driven by our desire for certainty. The keystone became what she calls a topstone. “As with the underbutterfly story, the topstone story began to surface soon after Paine started publishing papers about his concept. What seems to have happened is that people involved in wildlife conservation started trying to identify keystone species in order to wisely use limited conservation budgets. Political, cultural and special-interest complexities joined the mix, and the keystone species concept widened and weakened as a result. For environmental study, retrospective discovery might suffice, but for environmental action, people wanted certainty.”
Her last narrative is about the adaptive landscape. “I first encountered Sewall Wright's adaptive landscape metaphor in college, and as a visual thinker I found it useful right away. Even though the metaphor is severely limited, many evolutionary theorists use it as a visual shorthand for thinking about genetic change. The way the metaphor works is this. Populations are located in X and Y dimensions to describe their genetic makeup (in a radically simplified way). They exist on a landscape where the height of each point describes the fitness of the population with that particular XY combination of genetic variables.” By describing fitness as a peak, the metaphor conveyed a lot of uncertainty. A small nudge could send the species down in any direction into a valley. Physicists tend to look at this type of metaphor in the opposite direction where potential energy increase in the peaks and valleys are lower potential energy.
I have to admit that with my physics background I had trouble with section of her discussion because when I first saw the metaphor, I thought to my self that it was upside down. The trend would be for the species to always roll down the hill into the “genetic valley of death.”
Kurtz writes, “One more and then I'm really done, I promise. This is from The Quark and the Jaguar by Murray Gell-Mann:
Biologists conventionally represent fitness as increasing with increasing height, so that maxima of fitness correspond to the tops of hills and minima to the bottom of pits; however, I shall use the reverse convention, which is customary in many other fields, and turn the whole picture upside-down.
Gell-Mann then gets into the difficulties of this flip, seemingly without realizing it:
If the effect of evolution were always to move steadily downhill -- always to improve fitness -- then the genotype would be likely to get stuck at the bottom of a shallow depression and have no opportunity to reach the deep holes nearby that correspond to much greater fitness. At the very least, the genotype must be moving in a more complicated manner than just sliding downhill.
That is precisely the problem with flipping the landscape: that when you do so, things that are in reality very complicated seem simple, and certain.”
This desire to correct uncertainty runs strong in us. She writes, “If you think about it, this is not at all surprising. We have been conditioned since an early age to believe in this equation:
uncertainty + science = certainty
When we meet an equation like this:
uncertainty + science = more uncertainty
We react, and a second story arises. That can't be right. There must be another explanation. That's what Edward Lorenz said when his computer generated a new weather system based on what he thought were the same inputs. He called in the hardware engineers to find the broken vacuum tube.”
She summarizes her essay in a section titled “A Generation, or Two Or Three, to Sink In. “If people tell second stories about complexity because we aren't ready for the first stories, I think our children are ready. In many of my narrative projects I ask people to rate the predictability of events in stories -- it's useful to map perceptions of stability and instability across conceptual space. I've noticed a pattern across several projects that older people are more likely to associate instability with negative outcomes in stories. Younger people are more likely to mark stories as both unstable and positive.
I was thinking about all this the other day while playing with my son, and two things happened that gave me food for thought. The first was that we watched the movie Clifford's Really Big Movie. It's a great movie, and it's in our pantheon now and will probably be watched many more times. One of my favorite parts of the movie is this lovely song, which my six-year-old understood and liked immediately. It goes, in part:
You've gotta get lost if you wanna get found
Gotta wind up to get unwound
Things only look up from down below
And I can't come home until I go
It only gets better after it gets worse
Happy ever after needs a scary part first
You've gotta fall down to get back on
And I can't come home until I'm gone.”
Later, she writes, “According to my surely-biased reading, there are three ways the authors of business books about complexity and chaos provide reassurance to those in charge. One is to drain the power out of the major discoveries by highlighting the second stories, which do exist in science and so can be called scientific: the underbutterfly, the topstone, and the easy roller. The first stories can be waved away as "internal disputes" that don't matter.
The second method of making complexity palatable to those in charge is to make it seem magical. That is why the phrase "order for free" is so wildly attractive in these books, and why people love to throw around terms like "strange attractor" and "fitness landscape" and "coevolution" -- because they are magic words of power that seem to promise something for nothing. Even "nonlinear" effects are spoken of mainly for the idea of something small going in and something big (and beneficial to the reader) coming out. I see this rose-colored view of complexity in most (but not all) business writings about complexity. Consider for example the way people talk about coevolution: nearly every treatment of business coevolution I have read has talked about it like nothing can possibly go wrong. But in real coevolution things can and do go horribly wrong at times. It is these sorts of distortions that not only give complexity concepts a bad name (because rarely can such wild claims of magical power be justified) but also spread confusion about the true utility of complexity and chaos based approaches.
And finally, the third and most used tool in the business complexity writer's toolkit is that the sky is falling. You need this, say the business books, because the world has changed in such dramatic ways that you can't possibly survive without it. People who use this tool ramp up the fear quotient by making claims such as that "an organization is a complex adaptive system" -- the implication being, and you had better find out what that means, and quick. But organizations are not complex adaptive systems! More precisely, they are not only complex adaptive systems. An organization is a lot of people. Those people interact with each other in many ways, some of which are complex and emergent, and some of which are not. Organization and self-organization, hierarchy and meshwork are inextricably bound up together in organizations, and saying an organization "is" one without the other is sheer nonsense and is probably meant to entice rather than inform. There are no only-complex social groupings in human life. Every gathering of ten huts has a path through it. Every lunch meeting has a leader. Every subway car has a social structure, if even only for the two minutes the same people are in it. That's what we do. There may be such things as only-complex systems in the lives of social insects, but even there some hierarchy (in the form of central pheromonal control) is usually mixed in.”
She concludes with, “My advice, if anyone wanted it, would be this. First, stop saying everything is complex, and start talking about how complexity and hierarchy can work to mutual benefit.”
“When you don't fear complexity, when you see it as a part of reality but not a ‘whole new world’ dominated by a falling sky, you don't have to muzzle it. The underbutterfly and the topstone and the easy roller can go plague other people. You can take the butterfly and the keystone and the steadfast climber as they come to you, in stride. You can learn to recognize them, deal with them, work with them and even in time welcome them as old friends. You'll just know better than to hand over your car keys to them.”
As it turns out, this is the conclusion I had recently reached intuitively. She has done all the work that suggests that this is correct. I was drawing from my experience with physics and squaring Newtonian, Quantum and Relativistic physics. All are present in everything. It’s just in certain conditions one view works best. But you have to know when you are in what type of physics. To complicate matters, there are at least three different types of “messy” complexity and one type more tractable. For example in the behavior of markets there are trends, cycles and complexity. Complexity is in the fine structure of the behavior of the market.
Read Her Blog
Tuesday, September 7, 2010
The Case for the Commons
Raj Patel, Utne Reader, Sept - Oct 2010
"The first three times I heard the word commons, I had no idea what it meant. Hearing the phrase House of Commons in a media report from the British Parliament, I guessed that being a part of the commons meant being rich, white, and aggressively drunk. The next time, it appeared in a British children’s television series in the 1970s—The Wombles, about a group of furry creatures who practiced the dark arts of recycling on Wimbledon Common. I imagined a common to be a place littered with exciting things that were removed by the Wombles to be reused in their burrow. The third time was on a holiday in New York, where my family was told that if we wanted to have the full American experience, we needed to head to Woodbury Common, a large shopping complex outside New York City. (I got a sweater with an American flag on it.) Common, I thought, was American English for “shopping center.” What I never quite understood was that common could be not only a place, but also a verb to describe how to value and share the world around us.
Although it is often associated with Britain and its colonies, the commons as place and process can be found in societies from Central America to South Asia and, most recently, cyberspace. A commons is a resource, most often land, and refers both to the territory and to the ways people allocate the goods that come from that land. The commons has traditionally provided food, fuel, water, and medicinal plants for those who used it—it was the poorest people’s life-support system."
I highly recommend this article if you want to understand how very important the concept of the commons is in society today. Now, more than ever, there is a struggle going on between enclosure and commons. And it's important for our future that we protect and enlarge the commons.
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"The first three times I heard the word commons, I had no idea what it meant. Hearing the phrase House of Commons in a media report from the British Parliament, I guessed that being a part of the commons meant being rich, white, and aggressively drunk. The next time, it appeared in a British children’s television series in the 1970s—The Wombles, about a group of furry creatures who practiced the dark arts of recycling on Wimbledon Common. I imagined a common to be a place littered with exciting things that were removed by the Wombles to be reused in their burrow. The third time was on a holiday in New York, where my family was told that if we wanted to have the full American experience, we needed to head to Woodbury Common, a large shopping complex outside New York City. (I got a sweater with an American flag on it.) Common, I thought, was American English for “shopping center.” What I never quite understood was that common could be not only a place, but also a verb to describe how to value and share the world around us.
Although it is often associated with Britain and its colonies, the commons as place and process can be found in societies from Central America to South Asia and, most recently, cyberspace. A commons is a resource, most often land, and refers both to the territory and to the ways people allocate the goods that come from that land. The commons has traditionally provided food, fuel, water, and medicinal plants for those who used it—it was the poorest people’s life-support system."
I highly recommend this article if you want to understand how very important the concept of the commons is in society today. Now, more than ever, there is a struggle going on between enclosure and commons. And it's important for our future that we protect and enlarge the commons.
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Suburbia's Other Underbelly
Angst-ridden films like American Beauty and Revolutionary Road depict suburbia as an incubator of emptiness, portraying the “poverty” of middle-class comfort and sameness. But Governing (May 2010) reports that as of 2008 the suburbs of the nation’s largest metro areas were home to “1.5 million more poor residents than the cities themselves,” suggesting that modern day suburban anxiety has little to do with Hollywood’s back-lot realism.
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Friday, September 3, 2010
Complexity and the Future of Education
The increasing pace of what French philosopher-paleoanthropologist Teilhard de Chardin characterized as the “complexification of human circumstances” has made the nexus between complexity and education a timely and purposeful subject for examination.
On The Horizon announces a Special Issue on “Complexity and the Future of Education,” and invites authors to submit papers addressing the implications of an increasingly complex, problematic and uncertain future for today’s didactic and determinist educational processes.
CONTACT: Tom P. Abeles, editor
CRITICAL DATES: 15 October 2010 – 1 page proposals due
1 November 2010 – Notice of Acceptance
1 January 2011 – Draft of Papers due
1 February 2011 – Final Paper due
PAPER PARAMETERS: Papers should be in essay style, conforming to basic guidelines under the author section of the publisher, Emerald. Length may be up to 5,000 words, with structured abstracts, key words, and footnotes as appropriate; and it may include links to Websites. Submissions must be sent in MSWord as an e-mail attachment.
THEME: The media today routinely describes BOTH the major problems confronting humankind AND their potential solutions as being “complex.” Some educational boosters have even begun to cite “increasing complexity” as yet another reason why we must produce more graduates in science, math and technology. Critics counter that the modern sciences fail to acknowledge the complexity of the real world, and foster a misleading certainty of expectations that leads people to pursue simple solutions for complex problems, and to discount contrarian ideas and “inconvenient truths.”
Practitioners in many disciplines are sharply divided over the potential role of the current model of formal education in preparing society to live and work in a complex world. Some, in leadership development, for example, believe that only a small fraction of the population possess the natural “cognitive competence” to coherently address complex issues. These people, they argue, should be identified by testing in early childhood and given special schooling that nurtures their rare innate abilities for the good of us all.
On the other hand, some educators believe that “ordinary” people can be taught practical skills for addressing complex issues, and that young people today are already learning to deal with complexity through their experience with computer games and simulations. But scholars of complexity science counter that simply adding analytical skills to traditional curricula would be wholly insufficient to convey a general understanding of complex phenomena. They foresee the need for a complete restructuring of established epistemology.
Meanwhile, technophiles are embracing the “singularity” scenario, in which the complexity of a growing share of important decisions exceeds human reasoning capacity, and where significant problems are delegated to artificial intelligences and “humachine” hybrids. If all our intellectual “heavy lifting” were assigned to smart machines, would education focus on the humanities and creative arts as a means of enriching lives made routine and predictable by intelligent decision-making systems?
Alternatively others argue that spontaneous cyber-collaboration will enable us to mobilize humanity’s collective competencies and sensibilities to master our increasingly complex circumstances without ceding control of our destiny to smart machines. This vision of the future suggests an entirely different mission for educators.
While education is clearly a major influence on how we deal with complexity today, how we eventually arrange to cope with increasing complexity will just as clearly influence the content and delivery of education in the not-too-distant future.
*Papers submitted in response to this Call for Papers will also be considered for inclusion in a 2-day Forum on the Future of Education co-sponsored by On the Horizon and the World Future Society in Vancouver, B.C. in July 2011.
On The Horizon announces a Special Issue on “Complexity and the Future of Education,” and invites authors to submit papers addressing the implications of an increasingly complex, problematic and uncertain future for today’s didactic and determinist educational processes.
CONTACT: Tom P. Abeles, editor
CRITICAL DATES: 15 October 2010 – 1 page proposals due
1 November 2010 – Notice of Acceptance
1 January 2011 – Draft of Papers due
1 February 2011 – Final Paper due
PAPER PARAMETERS: Papers should be in essay style, conforming to basic guidelines under the author section of the publisher, Emerald. Length may be up to 5,000 words, with structured abstracts, key words, and footnotes as appropriate; and it may include links to Websites. Submissions must be sent in MSWord as an e-mail attachment.
THEME: The media today routinely describes BOTH the major problems confronting humankind AND their potential solutions as being “complex.” Some educational boosters have even begun to cite “increasing complexity” as yet another reason why we must produce more graduates in science, math and technology. Critics counter that the modern sciences fail to acknowledge the complexity of the real world, and foster a misleading certainty of expectations that leads people to pursue simple solutions for complex problems, and to discount contrarian ideas and “inconvenient truths.”
Practitioners in many disciplines are sharply divided over the potential role of the current model of formal education in preparing society to live and work in a complex world. Some, in leadership development, for example, believe that only a small fraction of the population possess the natural “cognitive competence” to coherently address complex issues. These people, they argue, should be identified by testing in early childhood and given special schooling that nurtures their rare innate abilities for the good of us all.
On the other hand, some educators believe that “ordinary” people can be taught practical skills for addressing complex issues, and that young people today are already learning to deal with complexity through their experience with computer games and simulations. But scholars of complexity science counter that simply adding analytical skills to traditional curricula would be wholly insufficient to convey a general understanding of complex phenomena. They foresee the need for a complete restructuring of established epistemology.
Meanwhile, technophiles are embracing the “singularity” scenario, in which the complexity of a growing share of important decisions exceeds human reasoning capacity, and where significant problems are delegated to artificial intelligences and “humachine” hybrids. If all our intellectual “heavy lifting” were assigned to smart machines, would education focus on the humanities and creative arts as a means of enriching lives made routine and predictable by intelligent decision-making systems?
Alternatively others argue that spontaneous cyber-collaboration will enable us to mobilize humanity’s collective competencies and sensibilities to master our increasingly complex circumstances without ceding control of our destiny to smart machines. This vision of the future suggests an entirely different mission for educators.
While education is clearly a major influence on how we deal with complexity today, how we eventually arrange to cope with increasing complexity will just as clearly influence the content and delivery of education in the not-too-distant future.
*Papers submitted in response to this Call for Papers will also be considered for inclusion in a 2-day Forum on the Future of Education co-sponsored by On the Horizon and the World Future Society in Vancouver, B.C. in July 2011.
Wednesday, September 1, 2010
Wealth Gaps Yawns - and So Do the Media
"Last March, the Insight Center for Community Economic Development released the revelatory report "Lifting as We Climb: Women of Color, Wealth, and Americas Future;' which measures wealth gaps according to gender and race. The results are a national embarrassment, but it's a good guess that you missed the story-because almost no one deemed the data newsworthy."
This article in Utne Reader, September - October, 2010 is well worth reading. As a matter of fact the whole edition is full of valuable information for anyone interested in what's happening to the U.S.
A number of years a go, I got interested in this topic because I perceived that I had just lived through the greatest redistribution of wealth in my life time. And, I had just learned about a new tool to display data, the Motion Chart created by Hans Rosling. Google has the official public version of the tool in its Google Gadgets.
I posted this on my Ning site earlier, but lost it when Ning starting charging. I got the data from the Federal Reserve Board. I had the link to the report, but the report is no longer there (curious). I had hoped I could update the data beyond 2004. There is some data and analysis on Wikipedia but it also ends in 2004.
Personal assets are plotted as a function of personal income by percentile of income. Data was available from 1989 to 2004. You can increase the size of the chart by clicking on the expand symbol in the bottom right hand corner of the video.
What this Motion Chart shows is how much faster wealth and income has grown for the upper percentile of U.S. citizens. What the article and the Wikipedia article talk about is how this is accentuated for women and people of color.
You can download a copy of the video here. By the way, the Google Gadget provides an embeddable flash file, but Blogger wouldn't accept it.
This article in Utne Reader, September - October, 2010 is well worth reading. As a matter of fact the whole edition is full of valuable information for anyone interested in what's happening to the U.S.
A number of years a go, I got interested in this topic because I perceived that I had just lived through the greatest redistribution of wealth in my life time. And, I had just learned about a new tool to display data, the Motion Chart created by Hans Rosling. Google has the official public version of the tool in its Google Gadgets.
I posted this on my Ning site earlier, but lost it when Ning starting charging. I got the data from the Federal Reserve Board. I had the link to the report, but the report is no longer there (curious). I had hoped I could update the data beyond 2004. There is some data and analysis on Wikipedia but it also ends in 2004.
Personal assets are plotted as a function of personal income by percentile of income. Data was available from 1989 to 2004. You can increase the size of the chart by clicking on the expand symbol in the bottom right hand corner of the video.
What this Motion Chart shows is how much faster wealth and income has grown for the upper percentile of U.S. citizens. What the article and the Wikipedia article talk about is how this is accentuated for women and people of color.
You can download a copy of the video here. By the way, the Google Gadget provides an embeddable flash file, but Blogger wouldn't accept it.
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