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Did you just mention privatization, “increase in productivity” and self-interest as a solution? Well, the answer depends a lot if you are in a pre or post equilibrium physical state. The distribution curve in question is more or less a Bell-curve. So maybe it’s time for all of us, to make a proper balance in here, having a brief look onto it from a recent scientific perspective.

Let us consider over-exploitation. Imagine a situation where multiple herders share a common parcel of land, on which they are each entitled to let their cows graze. In Hardin‘s (1968) example (check his seminal paper below), it is in each herder’s interest to put the next (and succeeding) cows he acquires onto the land, even if the quality of the common is damaged for all as a result, through overgrazing. The herder receives all of the benefits from an additional cow, while the damage to the common is shared by the entire group. If all herders make this individually rational economic decision, the common will be depleted or even destroyed, to the detriment of all, causing over-exploitation.

Video – “Balance“: Wolfgang and Christoph Lauenstein (Directors), Germany, 1989. Academy Award for Best Animated Short (1989).

This huge dilemma, know as “The tragedy of the commons” arises from the situation in which multiple individuals, acting independently and rationally consulting their own self-interest, will ultimately deplete a shared limited resource, even when it is clear that it is not in anyone’s long-term interest for this to happen. On my own timeself-interest” allow me to start this post directly with a key passage, followed by two videos and a final abstract. First paper below, is in fact the seminal Garrett Hardin paper, an influential article titled precisely “The Tragedy of the Commons,” written in December 1968 and first published in journal Science (Science 162, 1243-1248, full PDF). One of the key passages goes on like this. Hardin asks:

[…] In a welfare state, how shall we deal with the family, the religion, the race, or the class (or indeed any distinguishable and cohesive group) that adopts overbreeding as a policy to secure its own aggrandizement (13)? To couple the concept of freedom to breed with the belief that everyone born has an equal right to the commons is to lock the world into a tragic course of action. […]

So the question is: driven by rational choice, are we as Humanity all doomed into over-exploitation in what regards our common resources? Will we all end-up in a situation where any tiny move will drive us into a disaster, as the last seconds on the animated short movie above clearly and brilliantly illustrate?

Fortunately, the answer is no, according to recent research. Besides Hardin‘s work has been criticized on the grounds of historical inaccuracy, and for failing to distinguish between common property and open access resources (Wikipedia entry), there is subsequent work by Elinor Ostrom and others suggesting that using Hardin‘s work to argue for privatization of resources is an “overstatement” of the case.

Video – Elinor Ostrom: “Beyond the tragedy of commons“. Stockholm whiteboard seminars. (video lecture, 8:26 min.)

In fact, according to Ostrom work in the study of common pool resources (CPR), awarded in 2009 for the Nobel Prize in Economic Sciences, there are eight design principles of stable local common pool resource management, possible to avoid the present dilemma. Among others, one of her works I definitely recommend reading is her Presidential address on the American Political Science Association, presented back in 1997, entitled, “A Behavioral Approach to the Rational Choice Theory of Collective Action” (The American Political Science Review Journal, Vol. 92, No. 1, pp. 1-22, Mar., 1998). Her impressive paper-work starts like this:

[…] Extensive empirical evidence and theoretical developments in multiple disciplines stimulate a need to expand the range of rational choice models to be used as a foundation for the study of social dilemmas and collective action. After an introduction to the problem of overcoming social dilemmas through collective action, the remainder of this article is divided into six sections. The first briefly reviews the theoretical predictions of currently accepted rational choice theory related to social dilemmas. The second section summarizes the challenges to the sole reliance on a complete model of rationality presented by extensive experimental research. In the third section, I discuss two major empirical findings that begin to show how individuals achieve results that are “better than rational” by building conditions where reciprocity, reputation, and trust can help to overcome the strong temptations of short-run self-interest. The fourth section raises the possibility of developing second-generation models of rationality, the fifth section develops an initial theoretical scenario, and the final section concludes by examining the implications of placing reciprocity, reputation, and trust at the core of an empirically tested, behavioral theory of collective action. […]

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Video – The Divided Brain (Oct. 2011) – In this new RSAnimate, renowned psychiatrist and writer Iain McGilchrist explains how our ‘divided brain’ has profoundly altered human behaviour, culture and society. Taken from a lecture given by Iain McGilchrist as part of the RSA’s free public events programme. To view the full lecture “The Divided Brain and the Making of the Western World“, do jump yourself into another YouTube video.

Photo – Young Glenn Gould in February 1946 with his English Setter dog, Nick.

Darwin by Peter Greenaway (1993) – Although British director Peter Greenaway is best known for feature films like The Cook, the Thief, His Wife and Her Lover, Prospero’s Books, and The Pillow Book, he has also completed several highly respected projects for television, including this 53-minute exploration (now free) of the life and work of Charles Darwin. Darwin is structured around 18 separate tableaux, each focusing on another chapter in the naturalist’s life, and each consisting of just one long uninterrupted shot. Other than the narrator’s voice-over, there is no dialogue.

It is very difficult to make good mistakes“, Tim Harford, July 2011.

TED talk (July 2011) by Tim Harford a writer on Economics who studies Complex Systems, exposing a surprising link among the successful ones: they were built through trial and error. In this sparkling talk from TEDGlobal 2011, he asks us to embrace our randomness and start making better mistakes [from TED]. Instead of the God complex, he purposes trial and error, or to be more precise, Genetic Algorithms and Evolutionary Computation (one of those examples over his talk  is indeed the evolutionary optimal design of an airplane nozzle).

Now, we may ask, if it’s clear to you from the talk whether the nozzle was computationally designed using evolutionary search as suggested by the imagery, or was the imagery designed to describe the process in the laboratory? … as a colleague ask me the other day over Google plus. A great question, since as I believe it will be not clear to everyone watching that lecture.

Though, it was clear to me from the beginning, for one simple reason. That is a well-know work in the Evolutionary Computation area, done by one of its pioneers, Professor Hans-Paul Schwefel from Germany, in 1974 I believe. Unfortunately, at least to me I must say, Tim Harford did not mentioned the author, neither he mentions over his talk, the entire Evolutionary Computation or Genetic Algorithms area, even if he makes a clear bridge between these concepts and the search for innovation. The optimal nozzle design was in fact produced for the first time, on Schwefel‘s PhD thesis (“Adaptive Mechanismen in der Biologischen Evolution und ihr Einfluß auf die Evolutiongeschwindigkeit“), and he did arrive at this results by using a branch of Evolutionary Computation know as (ES) Evolution Strategies [here is a Wikipedia entry]. The objective was to achieve the maximum thrust and for that some parameters should be adjusted, such as in which point the small aperture should be put between the two entrances. What follows is a rather old video from YouTube on the process:

The animation shows the evolution of a nozzle design since its initial configuration until the final one. After achieving such a design it was a a little difficult understanding why the surprising design was good and a team of physicists and engineers gathered to provide an investigation aiming at devising some explanation for the final nozzle configuration. Schwefel (later on with his German group) also investigated the algorithmic features of Evolution Strategies, what made possible different generalizations such as a surplus of offspring created, the use of non-elitist evolution strategies (the comma selection scheme), and the use of recombination beyond the well known mutation operator to generate the offspring. Here are some related links and papers (link).

Albeit these details … I did enjoyed the talk a lot as well as his quote above. There is still a subtle difference between “trial and error” and “Evolutionary search” even if linked, but when Tim Harford makes a connection between Innovation and Evolutionary Computation, it remembered me back the “actual” (one decade now, perhaps) work of David Goldberg (IlliGAL – Illinois Genetic Algorithms laboratory). Another founding father of the area, now dedicated to innovation, learning, etc… much on these precise lines. Mostly his books, (2002) The design of innovation: Lessons from and for competent genetic algorithms. Kluwer Academic Publishers, and (2006) The Entrepreneurial Engineer by Wiley.

Finally, let me add, that there are other beautiful examples of Evolutionary Design. The one I love most – however – (for several reasons, namely the powerful abstract message that is sends out into other conceptual fields) is this: a simple bridge. Enjoy, and for some seconds do think about your own area of work.

I think an influencer has a certain confidence,… that probably not many people have, that … they know that what they are doing is the right thing, cause they are comfortable with it…” ~ Rob Stone, in “Influencers”, June 2011.

[…] “Influencers” is a short documentary that explores what it means to be an influencer and how trends and creativity become contagious today in music, fashion and entertainment. The film attempts to understand the essence of influence, what makes a person influential without taking a statistical or metric approach. Written and Directed by Paul Rojanathara and Davis Johnson, the film is a Polaroid snapshot of New York influential creatives (advertising, design, fashion and entertainment) who are shaping today’s pop culture. “Influencers” belongs to the new generation of short films, webdocs, which combine the documentary style and the online experience. […] from Vimeo, June 2011.

Video – A 1964 film based on the novel Zorba the Greek by Nikos Kazantzakis. The film was directed by Michael Cacoyannis and the title character was played by Anthony Quinn. The supporting cast included Alan Bates as a visiting Englishman as well as Irene Papas. The theme, “Sirtaki” by Mikis Theodorakis, has become famous and popular as a song and as a dance. The movie was shot on location on the Greek island of Crete. Specific places featured include the town of Chania, the Apokoronas region and the Akrotiri peninsula. The famous scene, in which Quinn’s character dances the Sirtaki, was shot on the beach of the village of Stavros. (from YouTube)


Basil (Alan Bates), a young English writer, meets a free-spirited Greek peasant named Zorba (Anthony Quinn) while waiting to travel to the island of Crete. While Zorba pursues a relationship with aging French courtesan Madame Hortense, Basil attempts to court a young widow. Along the way, he learns valuable life lessons from the earthy Zorba, who has an unquenchable joie de vivre (link):

[…] Basil: I don’t want any trouble. Alexis Zorba: Life is trouble. Only death is not. To be alive is to undo your belt and look for trouble. […] Zorba: Damn it boss, I like you too much not to say it. You’ve got everthing except one thing: madness! A man needs a little madness, or else… Basil: Or else? Zorba: …he never dares cut the rope and be free. […] Basil: Teach me to dance, will you? Zorba: Dance? Did you say… dance?! … Come on my boy… together… Let’s go… hop … Again… hop … […] Zorba: Boss, I have so much to tell you, … I never had loved a man like you … […] Zorba: Hey boss, did you ever see a more splendiferous crash?! … Oh, … You can laugh too!… hmmm… Hey!… You laugh! […]

Video [NASA] – Shuttle Endeavour’s final launch at NASA’s Kennedy Space Center on May 16, 2011. Junk parts, like the first and second rocket boosters (left and right intertanks) burning 11,000 pounds of fuel per second, falling back into Earth are visible on a rare and raw NASA footage. Image and audio passages from minute 15 to 20 are truly amazing. I also love the burning sound of those airborne rocket boosters in full throttle on the first footage seconds. Listen carefully. Did you noticed the Florida Cape Canaveral birds too on the back of the audio stream?! And by the way, … what sound is that at 15:27 and then again at 17:17?!

Photo – On May 16, Stefanie Gordon (http://twitpic.com/4yg6hs) happened to be in an airplane flying from New York to Palm Beach, Florida. She was on his way to visit his mother, for her birthday. From the cabin, aboard a Delta jet, she took this awesome photo of Endeavour‘s shutle STS-134 first seconds over his final space tour, with a cell-phone. “It was amazing. Can’t believe we got to witness history!” she wrote on Twitter that day.

Forbidden Images (from CineGraphic Studios, 2007) is a short documentary made for the 72 Hour Film Festival in Frederick, Maryland. All of the clips used in this film came from a reel of 35mm nitrate found in an old theatre somewhere in Pennsylvania. The projectionist clipped these scenes to meet local moral standards of the time. Amazing how sadly all images refer to women. The short 2007 documentary starts with the following paragraphs:

[…] In the past film makers and theatre owners were forced to remove the following so-called scandalous scenes or face arrest. Will our current forms of censorship and moral standards appear just as ridiculous to future audiences? Do NOT let others dictate how you should present yourself or your art…; Risk more than other’s think it’s safe […]

Video lecture by Ken Long (at the Statistics Problem Solvers blog) on Nassim Taleb‘s 4th Quadrant problems [1,2], i.e. a region where statistics not only don’t work but in which statistics are downright dangerous, because they lead you to make predictions as well as control systems that are unprepared for the kinds of systems shocks awaiting you.

Statistical and applied probabilistic knowledge is the core of knowledge; statistics is what tells you if something is true, false, or merely anecdotal; it is the “logic of science”; it is the instrument of risk-taking; it is the applied tools of epistemology; you can’t be a modern intellectual and not think probabilistically—but… let’s not be suckers. The problem is much more complicated than it seems to the casual, mechanistic user who picked it up in graduate school. Statistics can fool you. In fact it is fooling your government right now. It can even bankrupt the system (let’s face it: use of probabilistic methods for the estimation of risks did just blow up the banking system).”, Nassim Taleb, in [1].

[1] Nassim Nicholas Taleb, “The Fourth Quadrant: A Map of the Limits of Statistics“, An Edge Original Essay, Set., 2008. (link)

[2] Nassim Nicholas Taleb,”Convexity, Robustness, and Model Error inside the Fourth Quadrant“, Oxford Lecture (Draft version), Oxford, July 2010. [PDF paper]

A Pedro Cruz experimentation with soft bodies using toxi’s verlet springs. The data refers to the evolution of the top four maritime empires (Portugal, Britain, Spain and France) of the XIX and XX centuries by land extension. The visual emphasis was on their decline. Each circular shape tends to retain an area that’s directly proportional to the extent of the occupied territory on a specific year. At crucial, critical times in history, his visualization approach then follows a cell mitosis like split. Historical data came from Wikipedia. More on his project.

Yes, the ratio of the circumference of a circle to its diameter has is own day also. It’s Pi Day. March 14th. Created by physicist Larry Shaw, Pi Day is a holiday commemorating the mathematical constant π (pi). There is a reason for this date. Pi Day is celebrated on March 14 (or 3/14 in month/day date format), since 3, 1 and 4 are the three most significant digits of π in the decimal form. If you want to check it out, here are the first one million digits of π. Ironically, this is also the date when Albert Einstein was born. So, how about some good music along with that, to celebrate it?!

Video by Yoav Ben-dov www.ybd.net [Hanoi, Vietnam, 24 Feb. 2009]  – A nice example of self-organization as described by complexity theory. There are no fixed “top-down” laws (i.e. traffic lights), and yet the incredible traffic flows continuously. In complexity terms, the collective motion emerges from the multiple local interactions between the “agents” (drivers and pedestrians), mediated by horn sounds, eye contact, and body gestures.

All men can see these tactics whereby I conquer, but what none can see is the strategy out of which victory is evolved.” ~ Sun Tzu, “The Art of War“.

During the October 1973 Arab-Israeli War (Yom Kippur War) highly strategic manoeuvres occurred on the Suez canal. It was crucial to surpass it on time. Rather quickly. The war was fought on October, between Israel and a coalition of Arab states led by Egypt and Syria, and it began when the coalition launched a joint surprise attack on Israel on Yom Kippur, the holiest day in Judaism, which coincided with the Muslim holy month of Ramadan. Egyptian and Syrian forces crossed ceasefire lines to enter the Israeli-held Sinai Peninsula and Golan Heights respectively, which had been captured and occupied since the 1967 Six-Day War [Wikipedia]. The conflict led to a near-confrontation between the two nuclear superpowers, the United States and the Soviet Union, both of whom initiated massive resupply efforts to their allies during the war.

Anyway, the war began with a massive and successful Egyptian crossing of the Suez Canal during the first three days, after which they dug in, settling into a stalemate. The Egyptian army put great effort into finding a quick and effective way of breaching the Israeli defences. But the Israelis had built a large 18 meter high sand walls with a 60 degree slope and reinforced with concrete at the water line. Egyptian engineers initially experimented with explosive charges and bulldozers to clear the obstacles, before a junior officer proposed using high pressure water cannons. The idea was tested and found to be a sound one, and several high pressure water cannons were imported from Britain and East Germany [Wikipedia]. The water cannons effectively breached the sand walls using water from the canal.

photo – Egyptian forces crossing the Suez Canal on October 7, 1973 [Source: Wikipedia]

After that success, however, a swift passage of the entire army over the Suez canal was needed. The problem was that the Egyptian army had to make a rather quick passage with several different convoys of tanks and regular logistic trucks, over very tiny bridges (fig.) as quick as possible. Some say, that the Egyptian general in charge did not halt any of the convoys, in order to give precedence to some in particular. Instead, contrary to logic, he gave an order for them to continuously flow, without having any official at the bridge entrance to organize them. Any right convoy tank that felt that the other left convoy truck should enter first, he would stop some seconds, and only after that, should make his own bridge passage over Suez. What’s history now, is that the decision, was entirely left to them, locally… and fluid. No “traffic lights” at all, … contrary to the usual hard strict regulaments of any army we know today. If that’s not wise tactics, tell me what it is?! …

 

With an eye for detail and an easy style, Peter Miller explains why swarm intelligence has scientists buzzing.” — Steven Strogatz, author of Sync, and Professor of Mathematics, Cornell University.

From the introduction of, Peter Miller, “Smart Swarms – How Understanding Flocks, Schools and Colonies Can Make Us Better at Communicating, Decision Making and Getting Things Done“. (…) The modern world may be obsessed with speed and productivity, but twenty-first century humans actually have much to learn from the ancient instincts of swarms. A fascinating new take on the concept of collective intelligence and its colourful manifestations in some of our most complex problems, Smart Swarm introduces a compelling new understanding of the real experts on solving our own complex problems relating to such topics as business, politics, and technology. Based on extensive globe-trotting research, this lively tour from National Geographic reporter Peter Miller introduces thriving throngs of ant colonies, which have inspired computer programs for streamlining factory processes, telephone networks, and truck routes; termites, used in recent studies for climate-control solutions; schools of fish, on which the U.S. military modelled a team of robots; and many other examples of the wisdom to be gleaned about the behaviour of crowds-among critters and corporations alike. In the tradition of James Surowiecki‘s The Wisdom of Crowds and the innovative works of Malcolm Gladwell, Smart Swarm is an entertaining yet enlightening look at small-scale phenomena with big implications for us all. (…)

(…) What do ants, bees, and birds know that we don’t? How can that give us an advantage? Consider: • Southwest Airlines used virtual ants to determine the best way to board a plane. • The CIA was inspired by swarm behavior to invent a more effective spy network. • Filmmakers studied flocks of birds as models for armies of Orcs in Lord of the Rings battle scenes. • Defense agencies sponsored teams of robots that can sense radioactivity, heat, or a chemical device as easily as a school of fish can locate food. Find out how “smart swarms” can teach us how to make better choices, create stronger networks, and organize our businesses more effectively than we ever thought possible. (…)

… fortunately for all of us.

The three stages of response to a new idea: 1. Ridicule 2. Outrage 3. Declaration that it’s obvious” ~ Arthur Schopenhauer.

[…] However, Cage himself never softened. The culture might have moved on, but he kept on his radical edge, continuing his revolution in a quiet way for those who cared not only to listen, but to act on and live by his words. Through the 1980’s, Cage’s influence was felt in the underground, influencing many of the more interesting cultural movements of that decade–the birth of indy rock, the renewal of Conceptual Art, and the rise of Language Poetry. Many of these artists studied Cage in the ’60s and ’70s and went on to synthesize newer aesthetic/cultural concerns with older Cageian ideals. While the 80’s played out in the media with Wall Street Yuppies and decadent consumerists grabbing the spotlight, many of us spent time on the edge of the culture, which in turn planted the seeds for the more politically charged times in which we now live. […] The final essay here is “Poethics of a Complex Realism” by Joan Retallack and note the word realism in the title. Retallack begins her essay with an invocation of American Pragmatist John Dewey’s “Art As Experience” and launches into a long discussion of the idea of weather as it relates to the ideas of John Cage. Cage said that he wanted his music to be like the weather–unpredictable, omnidirectional, impermanent, and always changing–complex systems that parallel the conditions of our daily life. He did several works involving the weather, modeling his ideas after nature (again, a tip of the hat to American Transcendentalist Henry David Thoreau), which are described here. Retallack takes the word play of weather/whether and sets up a correspondence between the physical (realized) and the theoretical (unrealized). She then posits an ethic based on the principle of weather/whether. Imagine, she says, a culture sophisticated and open enough to be able to accept difference and otherness, a culture that rejects the oversimplified media response of black/white, yes/no, a culture that embraces complexity and contradiction–a “breathable” culture. And it is here where the book brilliantly dovetails with the multicultural attitudes sweeping the country today. Cage stands in opposition to the reductive and closed ideas that multiculturalism have come to stand for. While multiculturalism plays by the media-supplied dualistic rules, Cage seems to dump the idea of rules altogether and instead celebrates the idea of difference and unpredictability as a prerequisite to understanding and accepting the difficulties inherent in a pluralistic culture. It appeals to this reader as the path of least resistance and being based in action, seems entirely workable. The multicultural debate has made many people aware of the issues, but it stands in theory only and lacks the kind of pragmatism and functionality that could lead to real change as prescribed here. […], in Kenneth Goldsmith, University of Buffalo, 1995, reviewing and revisiting “John Cage Composed In America“, Essays edited by Marjorie Perloff & Charles Junkerman 1994, 286 pages, paperback, The University of Chicago Press, USA.

Video – John Cage, appearing on a 1960 CBS gameshow called I’ve Got A Secret (from Ian Leslie + Alex Ross). Cage’s ‘secret’ is that he is an avant-garde composer. After being introduced by the presenter he performs a piece called Water Walk (… more).

[…] Dumb parts, properly connected into a swarm, yield smart results. […] ~ Kevin Kelly. / […] “Now make a four!” the voice booms. Within moments a “4” emerges. “Three.” And in a blink a “3” appears. Then in rapid succession, “Two… One…Zero.” The emergent thing is on a roll. […], Kevin Kelly, Out of Control, 1994.

video -‘Swarm Showreel’ by SwarmWorks Ltd. December 2009 (EVENTS ZUM SCHWÄRMEN – Von Entertainment bis Business).

[…] In a darkened Las Vegas conference room, a cheering audience waves cardboard wands in the air. Each wand is red on one side, green on the other. Far in back of the huge auditorium, a camera scans the frantic attendees. The video camera links the color spots of the wands to a nest of computers set up by graphics wizard Loren Carpenter. Carpenter’s custom software locates each red and each green wand in the auditorium. Tonight there are just shy of 5,000 wandwavers. The computer displays the precise location of each wand (and its color) onto an immense, detailed video map of the auditorium hung on the front stage, which all can see. More importantly, the computer counts the total red or green wands and uses that value to control software. As the audience wave the wands, the display screen shows a sea of lights dancing crazily in the dark, like a candlelight parade gone punk. The viewers see themselves on the map; they are either a red or green pixel. By flipping their own wands, they can change the color of their projected pixels instantly.
Loren Carpenter boots up the ancient video game of Pong onto the immense screen. Pong was the first commercial video game to reach pop consciousness. It’s a minimalist arrangement: a white dot bounces inside a square; two movable rectangles on each side act as virtual paddles. In short, electronic ping-pong. In this version, displaying the red side of your wand moves the paddle up. Green moves it down. More precisely, the Pong paddle moves as the average number of red wands in the auditorium increases or decreases. Your wand is just one vote.
Carpenter doesn’t need to explain very much. Every attendee at this 1991 conference of computer graphic experts was probably once hooked on Pong. His amplified voice booms in the hall, “Okay guys. Folks on the left side of the auditorium control the left paddle. Folks on the right side control the right paddle. If you think you are on the left, then you really are. Okay? Go!”
The audience roars in delight. Without a moment’s hesitation, 5,000 people are playing a reasonably good game of Pong. Each move of the paddle is the average of several thousand players’ intentions. The sensation is unnerving. The paddle usually does what you intend, but not always. When it doesn’t, you find yourself spending as much attention trying to anticipate the paddle as the incoming ball. One is definitely aware of another intelligence online: it’s this hollering mob.
The group mind plays Pong so well that Carpenter decides to up the ante. Without warning the ball bounces faster. The participants squeal in unison. In a second or two, the mob has adjusted to the quicker pace and is playing better than before. Carpenter speeds up the game further; the mob learns instantly.
“Let’s try something else,” Carpenter suggests. A map of seats in the auditorium appears on the screen. He draws a wide circle in white around the center. “Can you make a green ‘5’ in the circle?” he asks the audience. The audience stares at the rows of red pixels. The game is similar to that of holding a placard up in a stadium to make a picture, but now there are no preset orders, just a virtual mirror. Almost immediately wiggles of green pixels appear and grow haphazardly, as those who think their seat is in the path of the “5” flip their wands to green. A vague figure is materializing. The audience collectively begins to discern a “5” in the noise. Once discerned, the “5” quickly precipitates out into stark clarity. The wand-wavers on the fuzzy edge of the figure decide what side they “should” be on, and the emerging “5” sharpens up. The number assembles itself.
“Now make a four!” the voice booms. Within moments a “4” emerges. “Three.” And in a blink a “3” appears. Then in rapid succession, “Two… One…Zero.” The emergent thing is on a roll.
Loren Carpenter launches an airplane flight simulator on the screen. His instructions are terse: “You guys on the left are controlling roll; you on the right, pitch. If you point the plane at anything interesting, I’ll fire a rocket at it.” The plane is airborne. The pilot is…5,000 novices. For once the auditorium is completely silent. Everyone studies the navigation instruments as the scene outside the windshield sinks in. The plane is headed for a landing in a pink valley among pink hills. The runway looks very tiny. There is something both delicious and ludicrous about the notion of having the passengers of a plane collectively fly it. The brute democratic sense of it all is very appealing. As a passenger you get to vote for everything; not only where the group is headed, but when to trim the flaps.
But group mind seems to be a liability in the decisive moments of touchdown, where there is no room for averages. As the 5,000 conference participants begin to take down their plane for landing, the hush in the hall is ended by abrupt shouts and urgent commands. The auditorium becomes a gigantic cockpit in crisis. “Green, green, green!” one faction shouts. “More red!” a moment later from the crowd. “Red, red! REEEEED !” The plane is pitching to the left in a sickening way. It is obvious that it will miss the landing strip and arrive wing first. Unlike Pong, the flight simulator entails long delays in feedback from lever to effect, from the moment you tap the aileron to the moment it banks. The latent signals confuse the group mind. It is caught in oscillations of overcompensation. The plane is lurching wildly. Yet the mob somehow aborts the landing and pulls the plane up sensibly. They turn the plane around to try again.
How did they turn around? Nobody decided whether to turn left or right, or even to turn at all. Nobody was in charge. But as if of one mind, the plane banks and turns wide. It tries landing again. Again it approaches cockeyed. The mob decides in unison, without lateral communication, like a flock of birds taking off, to pull up once more. On the way up the plane rolls a bit. And then rolls a bit more. At some magical moment, the same strong thought simultaneously infects five thousand minds: “I wonder if we can do a 360?”
Without speaking a word, the collective keeps tilting the plane. There’s no undoing it. As the horizon spins dizzily, 5,000 amateur pilots roll a jet on their first solo flight. It was actually quite graceful. They give themselves a standing ovation. The conferees did what birds do: they flocked. But they flocked self- consciously. They responded to an overview of themselves as they co-formed a “5” or steered the jet. A bird on the fly, however, has no overarching concept of the shape of its flock. “Flockness” emerges from creatures completely oblivious of their collective shape, size, or alignment. A flocking bird is blind to the grace and cohesiveness of a flock in flight.
At dawn, on a weedy Michigan lake, ten thousand mallards fidget. In the soft pink glow of morning, the ducks jabber, shake out their wings, and dunk for breakfast. Ducks are spread everywhere. Suddenly, cued by some imperceptible signal, a thousand birds rise as one thing. They lift themselves into the air in a great thunder. As they take off they pull up a thousand more birds from the surface of the lake with them, as if they were all but part of a reclining giant now rising. The monstrous beast hovers in the air, swerves to the east sun, and then, in a blink, reverses direction, turning itself inside out. A second later, the entire swarm veers west and away, as if steered by a single mind. In the 17th century, an anonymous poet wrote: “…and the thousands of fishes moved as a huge beast, piercing the water. They appeared united, inexorably bound to a common fate. How comes this unity?”
A flock is not a big bird. Writes the science reporter James Gleick, “Nothing in the motion of an individual bird or fish, no matter how fluid, can prepare us for the sight of a skyful of starlings pivoting over a cornfield, or a million minnows snapping into a tight, polarized array….High-speed film [of flocks turning to avoid predators] reveals that the turning motion travels through the flock as a wave, passing from bird to bird in the space of about one-seventieth of a second. That is far less than the bird’s reaction time.” The flock is more than the sum of the birds.
In the film Batman Returns a horde of large black bats swarmed through flooded tunnels into downtown Gotham. The bats were computer generated. A single bat was created and given leeway to automatically flap its wings. The one bat was copied by the dozens until the animators had a mob. Then each bat was instructed to move about on its own on the screen following only a few simple rules encoded into an algorithm: don’t bump into another bat, keep up with your neighbors, and don’t stray too far away. When the algorithmic bats were run, they flocked like real bats.
The flocking rules were discovered by Craig Reynolds, a computer scientist working at Symbolics, a graphics hardware manufacturer. By tuning the various forces in his simple equation a little more cohesion, a little less lag time. Reynolds could shape the flock to behave like living bats, sparrows, or fish. Even the marching mob of penguins in Batman Returns were flocked by Reynolds’s algorithms. Like the bats, the computer-modeled 3-D penguins were cloned en masse and then set loose into the scene aimed in a certain direction. Their crowdlike jostling as they marched down the snowy street simply emerged, out of anyone’s control. So realistic is the flocking of Reynolds’s simple algorithms that biologists have gone back to their hi-speed films and concluded that the flocking behavior of real birds and fish must emerge from a similar set of simple rules. A flock was once thought to be a decisive sign of life, some noble formation only life could achieve. Via Reynolds’s algorithm it is now seen as an adaptive trick suitable for any distributed vivisystem, organic or made. […] in Kevin Kelly, “Out of Control – the New Biology of Machines, Social Systems and the Economic World“, pp. 11-12-13, 1994 (full pdf book)

The dynamics of ant swarms share an uncanny similarity with the movement of various fluids (video above). Micah Streiff and his team from the Georgia Institute of Technology in Atlanta captured writhing groups of ants behaving just like liquids. You can watch them diffuse outwards from a pool, tackle jagged surface like a viscous fluid or flow from a funnel (from NewScientist | 2010 best videos).

[…] Fire ants use their claws to grip diverse surfaces, including each other. As a result of their mutual adhesion and large numbers, ant colonies flow like inanimate fluids. In this sequence of films, we demonstrate how ants behave similarly to the spreading of drops, the capillary rise of menisci, and gravity-driven flow down a wall. By emulating the flow of fluids, ant colonies can remain united under stressful conditions. […], in Micah Streiff, Nathan Mlot, Sho Shinotsuka, Alex Alexeev, David Hu, “Ants as Fluids: Physics-Inspired Biology,” ArXiv, 15 Oct 2010. http://arxiv.org/abs/1010.3256 .

“The first serious infowar is now engaged. The field of battle is WikiLeaks. You are the troops”. ~ WikiLeaks, Dec. 3, 2010. / “It’s not wrong to lie, cheat, steal, corrupt, and torture. It’s wrong to let people know about it”. ~ Robby Pickert (@zerocl). / “I do not agree with what you have to say, but I’ll defend to the death your right to say it.” ~ Voltaire

One thing that WikiLeaks have shown, among many others, is that the (“corporate“) United States of America are no longer worried about open democracies along with their 1st amendment free speech. What WikiLeaks is doing, is just part of what any proper journalism should be doing, but scarcely does. So, here’s a simple piece of advise: if WikiLeaks goes down, we all (as open free democracies) go down. Do not doubt one second about it…, We are all Julian Assange, now…; So do please stop with that “You can’t handle the truth” anecdote idiosyncrasy shit. The sad irony of all these, is that Assange himself, is now the most persecuted hunted man on planet Earth, instead of Bin Laden

note – As I have twitted this morning, 10 AM GMT time at https://twitter.com/#!/ViRAms/status/10638501351530496, WikiLeaks were still available at http://wikileaks.ch after a 48h trial succession of WWW host places, including Amazon.com, who left them on the string very badly. Let’s now see how much that endures…)

note II (Dec. 5) – On Dec. 4, WikiLeaks.ch was down but soon 3 new mirror sites were available at http://wikileaks.de http://wikileaks.fi http://wikileaks.nl . It’s a cat and mice game.

“I was never interested in Facebook or MySpace because they feel like malls to me. Twitter actually feels like the street. You can bump into anybody on Twitter.” — Science-fiction novelist William Gibson – New York (October 11, 2010)

“There is almost certainly an evolutionary drive toward increasing complexity in the face of entropy. That’s practically a definition of life. Technology is so powerful and attractive to us because it holds the promise of greater complexity and greater connectedness. Atoms to molecules to cells to organelles to organisms. What’s next? No one knows for sure, but it sure ain’t Facebook.” — American media theorist Douglas Rushkoff, writer, columnist, early cyberpunk culture adopter, and advocacy of open source solutions to social problems.

Precursors of social networks in the late 1800s include Émile Durkheim and Ferdinand Tönnies. Tönnies argued that social groups can exist as personal and direct social ties that either link individuals who share values and belief (gemeinschaft) or impersonal, formal, and instrumental social links (gesellschaft) [in Linton Freeman, “The Development of Social Network Analysis“, Vancouver, Empirical Press, 2004 (here is a valuable must-read review on it)]. Durkheim gave a non-individualistic explanation of social facts arguing that social phenomena arise when interacting individuals constitute a reality that can no longer be accounted for in terms of the properties of individual actors. He distinguished between a traditional society – “mechanical solidarity” – which prevails if individual differences are minimized, and the modern society – “organic solidarity” – that develops out of cooperation between differentiated individuals with independent roles. Then, Georg Simmel (1908-1971), writing at the turn of the twentieth century, was the first scholar to think directly in social network terms. His essays pointed to the nature of network size on interaction and to the likelihood of interaction in ramified, loosely-knit networks rather than groups.

Nowadays, however, the paraphernalia of increasing intelligent tools (network metrics) are widely available, mainly to the exponential role of the science of complex networks. As stated by Matthias Scholz (Network Science.org / Webpage)  (…) Network science has received a major boost caused by the widespread availability of huge network data resources in the last years. One of the most surprising findings, popularized by Albert-László Barabási and his team, is that real networks behave very distinct from traditional assumptions of network theory. Traditionally, real networks were supposed to have a majority of nodes of about the same number of connections around an average. This is typically modelled by random graphs. However, modern network research revealed that the majority of nodes of real networks is very low connected, and, by contrast, there exists some nodes of very extreme connectivity (hubs). This power-law characteristics, termed scale-free by Barabási, can be found in many complex real networks from biological (natural) to social man-made networks (…).

Book cover – Linton Freeman, “The Development of Social Network Analysis“, Vancouver, Empirical Press, 2004 (and a valuable review on it).

While embedding themselves on social-networking, people do tend to forget this, of course, but here are 2 or 3 things you should know about Social Networks before stupefying registering yourself on FarmVille (actually, this is a limited list of some of the actual metrics usually employed on current network analysis provided with a short description – So, … do really ponder yourself where you are – on the street or in the mall!):

Betweenness (link) The extent to which a node lies between other nodes in the network. This measure takes into account the connectivity of the node’s neighbours, giving a higher value for nodes which bridge clusters. The measure reflects the number of people who a person is connecting indirectly through their direct links. | Bridge (link) An edge is said to be a bridge if deleting it would cause its endpoints to lie in different components of a graph. | Centrality (link) This measure gives a rough indication of the social power of a node based on how well they “connect” the network. “Betweenness”, “Closeness”, and “Degree” are all measures of centrality. | Centralization (link) The difference between the number of links for each node divided by maximum possible sum of differences. A centralized network will have many of its links dispersed around one or a few nodes, while a decentralized network is one in which there is little variation between the number of links each node possesses. | Closeness (link) The degree an individual is near all other individuals in a network (directly or indirectly). It reflects the ability to access information through the “grapevine” of network members. Thus, closeness is the inverse of the sum of the shortest distances between each individual and every other person in the network.  The shortest path may also be known as the “geodesic distance”. | Clustering coefficient (link) A measure of the likelihood that two associates of a node are associates themselves. A higher clustering coefficient indicates a greater ‘cliquishness’. | Cohesion (link) The degree to which actors are connected directly to each other by cohesive bonds. Groups are identified as ‘cliques’ if every individual is directly tied to every other individual, ‘social circles’ if there is less stringency of direct contact, which is imprecise, or as structurally cohesive blocks if precision is wanted. | …

Fig. – Hue (from red=0 to blue=max) shows the node betweenness. (link)

… Degree (link) The count of the number of ties to other actors in the network. See also degree (graph theory). | (Individual-level) Density (link) The degree a respondent’s ties know one another/ proportion of ties among an individual’s nominees. Network or global-level density is the proportion of ties in a network relative to the total number possible (sparse versus dense networks). | Flow betweenness centrality (link) The degree that a node contributes to sum of maximum flow between all pairs of nodes (not that node). | Eigenvector centrality (link) A measure of the importance of a node in a network. It assigns relative scores to all nodes in the network based on the principle that connections to nodes having a high score contribute more to the score of the node in question. | Local Bridge (link) An edge is a local bridge if its endpoints share no common neighbors. Unlike a bridge, a local bridge is contained in a cycle. | Path Length (link) The distances between pairs of nodes in the network. Average path-length is the average of these distances between all pairs of nodes. | Prestige (link) In a directed graph prestige is the term used to describe a node’s centrality. “Degree Prestige”, “Proximity Prestige”, and “Status Prestige” are all measures of Prestige. See also degree (graph theory). | Radiality (link) Degree an individual’s network reaches out into the network and provides novel information and influence. | Reach (link) The degree any member of a network can reach other members of the network. | Structural cohesion (link) The minimum number of members who, if removed from a group, would disconnect the group. | Structural equivalence (link) Refers to the extent to which nodes have a common set of linkages to other nodes in the system. The nodes don’t need to have any ties to each other to be structurally equivalent. | Structural hole (link)  Static holes that can be strategically filled by connecting one or more links to link together other points. Linked to ideas of social capital: if you link to two people who are not linked you can control their communication.

Of course, some of these metrics are redundant over each other, and in fact there is some intelligence on having this on-purpose redundancy. But I would say that Path Length and Cliqueness, Eigenvector centrality, Betweenness, Clustering coefficient, Degree and last but not least Flow (btw, here‘s my own poetic lateral view of it), would be the most important of them all, even if, these all depends on what you are, on what you see, on what you feel, and mostly on what you somehow rather expect from it as a whole experience over time. So, finally, let me just add that all these metrics will not avoid people from writing/sharing experiences like: Son las 7 y 30 y estoy cagando” followed by “Son las 5 y 31 y ya cagado“. Unfortunately, what follows is precisely a video parody on Facebook not far from his own reality. As usual, you are always free to choose from the geriatric-like shelter malls or the open-air streets…

[...] People should learn how to play Lego with their minds. Concepts are building bricks [...] V. Ramos, 2002.

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