Ed Goad said:
> Your thoughts made me think of an analogy that occurred to me this
> weekend. I have been thinking of how a flock of birds can change
> directions so quickly, appearing to move simultaneously and without
> hierarchy. Sunday, while singing in a group of 300 (people, not birds), it
> occurred to me that we were doing the same thing. Possibly we have
> "hardware and software" installed that allowed us to adjust to the same
> pitch (or a harmonizing pitch), tempo, rythym, mood, degree of loudness,
> while integrating words, understanding meanings, feeling feelings, and
> looking around - and do it all so quickly that it appears to be
> simultaneous. Although there was a song "leader", I think most of what
> happened was not connected to the leader's actions. I suspect the birds
> likewise are enabled to pick up rapidly on minute signals from each other,
> and appear led without a leader. How does this apply to learning in
> organizations? I haven't gotten that far, yet...
>
> Thanks,
> Ed Goad
> goader@redstone.army.mil
> - --
and I couldn't resist the opportunity to offer the following, which
elaborates the nature of flocking and its possible application to human
organisation:
SELF-ORGANISATION
implications:
Complex behaviour need not have a complex explanation. Order will emerge
from self-organisation. This points the way to a new more open and
adaptable form of teamwork in which individuals manage themselves within
clear boundaries.
about the idea:
Self-organisation in a simulated flock
The essence of self-organisation is organisation from within a system,
rather than without (to use a Scottish turn of phrase). There is no
external agent outside of a self-organising system telling it what to do,
no top-down chain of command. The behaviour of a self-organising system
emerges from the network of interactions taking place inside it. Once
established, self-organising systems tend to persist, which is one reason
why management theorists are interested in them: they offer clues which
can help the process of creating a self-propelled9 workforce.
[xref-complex adaptive system/emergence]
The Boids9 simulation is an incredibly simple and tiny computer program
that successfully captures the essence of flocking behaviour, to such an
extent that when shown to ornithologists they accused its creator, Craig
Reynolds of faking it by digitising film of birds in flight. Flocking is
one example of what Kevin Kelly calls nature9s favourite organisation
design -the flock or swarm. Fish in schools, birds in flocks, bees and
ants in swarms: coordinated masses of individual agents9. The Boids
simulation is now accepted not just as a suggestion of what the flocking
mechanism in nature might be, but as a description of the actual mechanism
that governs all flocking behaviour in organisms. [note: recently
experimentally verified using transponders fitted to blue footed boobies
in the Galapagos {because they aren't afraid of humans, so the observers
wouldn't distort their behaviour}
The boids: not a film, not directed by Craig Reynolds
Reynolds' basic idea was to place a large collection of autonomous, birdlike
agents - 'boids' - into a computer-generated environment full of walls and
obstacles. Each boid followed three simple rules of behavior:
1. It tried to maintain a minimum distance from other objects in the
environment, including other boids.
2. It tried to match velocities with boids in its neighbourhood.
3. It tried to move toward the perceived centre of mass of boids in its
neighbourhood.
The duck at the front is not the leader
Notice that there is no rule that says: 'Form a flock'. Instead, as in the
Game of Life, [xref Game of Life] the rules were entirely local9, referring
only to what an individual boid could see9 and do in its own vicinity. So if a
flock forms, it forms from the bottom up9 there is no leader boid9 telling
all the others what to do in a top-down9 hierarchical manner. As Nicholas
Negroponte puts it: 3The duck at the front is not the leader.2 When a flock
forms, as it does every time, it is an emergent network phenomenon. [xref-
complex adaptive system/emergence, network and hierarchy ]
It doesn9t matter how the simulation is started off: it can start with the
boids scattered around the computer screen completely at random. The
rules will always force9 the boids to form a flock. Look at it from the
point of view of a single boid: if it is at the edge of the flock, rule 3
tells it to move in. If it is flying faster or slower than the boids near
it, Rule 2 says that it has to slow down or speed up. Rule 1 tells it to
keep its distance from the others. (This distance, like the other rules,
can be altered: different distances produce different types of flock
reminiscent of different bird species). So the boids spontaneously
collect themselves into a flock that can fly around obstacles in a very
fluid and natural manner, sometimes even breaking into subflocks9 that
flow around both sides of an obstacle, rejoining on the other side! In
one of the runs, a boid accidentally9 hit a pole, fluttered around for a
moment as though dazed, and then flew on to rejoin the flock.
Three little rules for self-organisation
Reynolds9 view is that this dazed9 boid proves that the overall behaviour
of the boids is actually emergent. Nowhere in the rules does it say what
the boid should do if it crashes into something. So part of the message
is this: if we can explain something that appears to be incredibly
complicated like flocking, with three little rules, are there any other
things that seem complicated that might turn out to be equally simple?
The answer is yes: this idea of emergent self-organisation has been
succesfully applied to explain the behaviour of traders in the stock
market, and is generally applicable to any situation in which agents9 are
free to choose, without central control. [xref- increasing returns and
lock-in] We can hear this in the language of news reports: the market
decided that the 3M flotation was overpriced9 is a statement about the
emergent behaviour arising from thousands of little transactions on the
stock exchange; there was no-one telling them to not buy the 3M shares,
nobody called a meeting.
Sensitivity to initial conditions
Initial conditions are often important in complexity theory. This is
clearly illustrated in Boids. In Boids it is all the other boids that
largely determine what an individual boid will do. Think about releasing
birds one at a time into a space: you could imagine that you have hundreds
of pigeons in a net inside the Albert Hall. When the first pigeon is
released its options are completely open, it can fly where it likes
because the only rule that applies to it is rule 1: don9t bump into
anything, and the Albert Hall is huge. Release another pigeon and the
options narrow dramatically: both birds now have to fly towards each other
and match speeds in order to obey rules 2 and 3. The next one out of the
net has no choices at all: it must head for the perceived centre of mass9
(in between the first two birds) and match speed with them. What we have
here is a robust phenomenon that is both sensitive and insensitive to
initial conditions: insensitive, because a flock always forms, sensitive
because the direction of flight is determined by the results of the first
few interactions.
Rules are tendencies
The rules aren9t strict rules, they are perhaps better described as
tendencies. Birds tend to fly together in flocks, they tend to move
towards the centre of the flock. Natural selection has ensured that birds
that didn9t have this strong tendency were eaten by predators. So the
rules make sense for the organisms most of the time; but if they weren9t
broken from time to time there would be no growth or change. It is in the
nature of complex adaptive systems to push at the boundaries; species are
always trying to expand out of their current niches. Witness the coyotes
were found in the Bronx, reported in the Observer, 2nd June 1996.
Critical Mass: human flocking
Critical Mass is an organised coincidence9 which takes place in many
cities in the UK. It started in San Francisco in 1994 and has spread
across America and Europe. It is a once-a-month bike ride through major
cities in the rush hour. The idea is to enjoy cycling in the city and to
make a point about transport policy at the same time. Several hundred
cyclists turn out and peacefully take over the streets for a couple of
hours, just by riding en masse. All sorts of people are involved, from
office workers to local government officers and transport campaign
activists.
Critical Mass is genuinely self-organised: although it was started by a
small group of cycling activists they are not in charge of it and cannot
control it. Someone will suggest a route and the group moves off in that
direction. Once the flock9 is moving its direction is determined by the
vagaries of other traffic, traffic signals and the mood of the people who
happen to be at the front at the time. Just as in Boids , a flock forms
in a ragged organic way, under the pressure of the rules. In London
traffic it is clear that not staying close to the other cyclists is
dangerous: taxis and cars take the place of hawks, to establish rule 3:
move toward the perceived centre of mass near you if you want to escape
the cars. Rule 1 is just obvious: keep a minimum distance from other
objects in the environment; as is rule 2: ride at the same speed as your
neighbours. One participant commented:
3The pressure of the pressure of the rules is amazing. I once got
separated from the main group with about ten others- suddenly the traffic
closed in, including cars whose drivers wanted to hold us personally
responsible for delaying their journey home by a few minutes. The urge to
rejoin the group as quickly as possible was incredible!2
The emergence of the same three rules in a human system9 is compelling
evidence for the generality of the rules of self-organisation: Brian Eno
speculates that there are three general classes of rules of which the
boids rules are a particular case: a generative rule, a diminishing rule,
and a maintenance rule.
xrefs attractor, evolution of cooperation, evolution and coevolution,
increasing returns and lock-in
refs
Brian Eno, A year with swollen appendices: Brian Eno9s diary, Faber and Faber,
1996, ISBN 0-571-17995-9, #9.99
Kevin Kelly, Out of Control: the new biology of machines, Fourth Estate, 1994,
ISBN 1-85702-308-0, #8.99
Michael McMaster, The Intelligence Advantage: Organising for Complexity,
Butterworth Heinemann, 1996, ISBN 0-7506-9792-X, #14.99
Nicholas Negroponte, Being Digital, Coronet Books, 1995, ISBN 0-34064-930-5,
#6.99
M Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and
Chaos,
Penguin, 1994, ISBN 0 6708 5045 4 #7.99
Various versions of the Boids simulation are available at Artificial Life
websites on the Internet. There are several of these, where software can be
obtained either as freeware9 or shareware9.
relevance
What does Boids9 tell us?
Two key messages: complex behaviour need not have a complex explanation
and order will emerge from self-organisation. Management theorists
develop complex explanations for behaviour in the workplace; it is often
the case that a few underlying rules are powering9 all the complex
behaviour observed on the surface. The Shifting the shift patterns9
restaurant case study of in evolution and coevolution9 can be viewed as
an example of locked-in behaviour maintained by a few rules: the rule were
changed and the behaviour changed. [xref- evolution and coevolution]
The rules at work
In the restaurant case the clue is that all the staff were sure that they
would suffer personally, although they could see the benefits of the
proposed change. This is a clue to the interdependency that Boids-type
rules generate. The environment for the birds in the simulation is mainly
made up of other birds. In a restaurant, the actions of the workers are
similarily strongly interdependent. If one waiter doesn9t turn up for
work all the waiting staff suffer. When tips are pooled a peer-pressure
rule ensures that everyone pulls their weight. So we can describe the
interactions of the staff as taking place on a fitness landscape in which
the shape of the landscape is mainly determined by the actions of the
other staff. They are their own environment (this idea has echoes of the
self-referentiality of autopoiesis). [xref- autopoiesis ] When the rules
were changed by their manager introducing the new shift pattern, they all
changed their behaviour together, like a flock.
A new view of team leadership
The illusion of coordination which emerges in Boids can also be viewed as
an attractor9. [xref- attractor]. Where is the leadership in the
leaderless flock? Leadership is the emergent behaviour of the whole
system. Is this perhaps what is going on in teams? How often do we
assume that there must be a leader? As Michael McMaster says 3Try viewing
leadership as an attractor.2 In the restaurant example their manager is
also one of the team: she is not leading in the sense of telling people
what to do from minute to minute. Her role as manager is to set the rules
to create the appropriate emergence. This is the true meaning of
self-organisation: like many scientific terms it can be misleading, a
clearer though more unweildy term would be rule-driven
self-organisation9.
Self-organisation points the way to a new more open and adaptable form of
teamwork in which individuals manage themselves within clear boundaries.
[xref- dialogue, Self-organising For Success]
the above is a chapter from my now back in print book [see sig below]
but Coleridge got there before us all, in the 1830s ( a guess] as david
whyte points out in 'the heart aroused'
Best wishes
Arthur Battram
--= from Arthur Battram, organisational learning consultant
Author of 'Navigating Complexity: the essential guide to complexity theory in business and management' published by the Industrial Society International, currently reprinting [April '99], as the first edition just sold out!
Learning-org -- Hosted by Rick Karash <rkarash@karash.com> Public Dialog on Learning Organizations -- <http://www.learning-org.com>