(Note: The following article appeared in the July 1994 issue of
Technology Review. The article may not be reprinted or published
without the express permission of Technology Review Magaine. The
ideas in the article are developed further in the book "Turtles,
Termites, and Traffic Jams," published by MIT Press.)


CHANGING THE CENTRALIZED MIND

Mitchel Resnick
MIT Media Laboratory
20 Ames Street
Cambridge, MA 02139
mres@media.mit.edu

A flock of birds sweeps across the sky. Like a well-choreographed
dance troupe, the birds veer to the left in unison. Then, suddenly,
they dart to the right and swoop toward the ground. Each movement
seems perfectly coordinated. The flock as a whole is as
graceful--maybe more graceful--than any of the birds within it.

How do birds keep their movements so orderly, so synchronized? Most
people assume that birds play a game of follow-the-leader: the bird at
the front of the flock leads, and the others follow. Indeed, people
assume centralized control for almost all patterns they see in the
world. But that's not necessarily so. In the case of bird flocks, most
don't have leaders at all. Rather, each bird follows a set of simple
rules, for example, matching its velocity to that of the other birds
around it, and keeping a safe distance from the birds on either side.

A bird flock is one of many phenomena organized without an organizer,
coordinated without a coordinator.  In ant colonies, trail patterns
are determined not by the dictates of the queen ant but by local
interactions among the worker ants, such as following a scent that
their fellow ants emit when they find a source of food. In human
societies, macroeconomic patterns arise from the haggling between
millions of buyers and sellers in marketplaces and stock markets
around the world. And in immune systems, armies of antibodies seek out
bacteria in a systematic, coordinated attack--without any "generals"
organizing the overall battle plan.


The Era of Decentralization

A growing number of people are now choosing these kinds of decentralized
models for the organizations and technologies they construct in the world,
and for the theories they construct about the world. One such case began to
unfold on December 7, 1991, when Russian President Boris Yeltsin met with
the leaders of Ukraine and Belarus in a forest dacha outside the city of
Brest. After two days of secret meetings, the leaders issued a declaration:
"The Union of Soviet Socialist Republics, as a subject of international law
and a geopolitical reality, is ceasing its existence." With that
announcement, Yeltsin and his colleagues sounded the final death knell for
a centralized power structure that had ruled for nearly 75 years. In its
place, the leaders established a coalition of independent republics and
promised a radical decentralization of both economic and political
institutions.

The next day, halfway around the world, another powerful institution
announced its own decentralization plans. IBM chairman John Akers
publicly announced a sweeping reorganization of the computer giant,
dividing the company into more than a dozen semi-autonomous business
units, each with its own financial authority and its own board of
directors. The goal was to make IBM more flexible and responsive to
the needs of rapidly changing markets.

The coincident timing of the above two events actually symbolizes a
broad decentralization trend that is sweeping through many different
domains. For example:

* Organizations. All types of organizations--schools, companies, even
countries--are pushing authority and power down from the top,
distributing rights and responsibilities more widely. In U.S.
education, for example, decentralization extends to several levels.
School choice brings market-oriented thinking to the world of
education, asserting that individual families--not state or local
governments--should decide where their children go to school.
Likewise, school-based management moves decision-making authority from
state and district offices to individual schools. And child-centered
learning, now adopted in many classrooms, transforms the teacher from
a central authority into a catalyst, coach, and collaborator.

* Scientific models. For 300 years, researchers' thinking has been
guided by Sir Isaac Newton's model of the physical world as a
clocklike mechanism.  Newton's world is ruled by a centralized notion
of cause and effect--one gear turns, which makes another gear turn,
and so on. Now, a new set of decentralized models and metaphors is
spreading through the scientific community and gradually into the
culture at large. Researchers now view a wide range of
systems--everything from bird flocks to immune responses--less like
clockwork mechanisms and more like complex ecosystems controlled by
decentralized interactions and feedback loops.

* Psychology. Few concepts seem more obvious than the singular nature
of the mind and self. Each of us experiences life as a single thread
of consciousness, and each of us imagines our own mind as "I," not
"we." But the idea of the unified, centralized mind, first challenged
by Sigmund Freud, has eroded rapidly during the past decade. For
example, Daniel Dennett, a professor of philosophy at Tufts
University, proposes that there is no single stream of consciousness
in the mind. He suggests instead that multiple narratives are
simultaneously created and edited in different parts of the mind.
Similarly, the field of artificial intelligence, once dominated by
centralized models of the mind, now favors decentralization.  Marvin
Minsky, a professor at the MIT Media Lab, argues that the mind is a
society of many simple agents that work together to accomplish complex
tasks.

* Theories of knowledge. For centuries, philosophers strove for
"objective knowledge." They put great faith in the power of logic to
systematize all knowledge, to find ultimate meaning and truth. Today,
philosophers are moving away from the notion of a single unifying
conception of knowledge, arguing instead that knowledge speaks not
with a single voice but with many. For example, traditional theories
of literary criticism assumed that meaning was created by an author
and conveyed through the author's writings. According to this view,
reading is a search for inherent meaning in a document, an attempt to
decipher the intention of the author. But modern schools of
thought--such as poststructuralism, reader-response theory, and
deconstructionism--all focus on readers as the main constructors of
meaning. In this new view, texts have little or no inherent meaning.
Rather, meanings are constantly reconstructed by communities of
readers through their interactions with the text. Meaning itself has
become decentralized.


Centralized Thinking

Even as the influence of decentralized ideas grows in many
disciplines, a deep-seated resistance to such ideas remains. People
seem to have strong attachments to centralized ways of thinking,
assuming that every pattern must have a single cause, an ultimate
controlling factor. The widespread resistance to evolutionary theories
is an example: Many individuals still insist that someone or something
must have explicitly designed the complex, orderly structures that
exist in the biological world. They resist the idea that complexity
can be formed through a decentralized process of variation and
selection.

Similarly, many view the workings of the economy in centralized ways,
assuming singular causes for complex, decentralized phenomena. In
interviews with Israeli children between 8 and 15 years old, for
example, David Leiser, a psychologist at Ben-Gurion University,
discovered that nearly half of the children assumed that the
government sets all prices and pays all salaries. Even children who
said that employers pay salaries often believed that the government
provides the money for the salaries. "The child finds it easier to
refer unexplained phenomena to the deliberate actions of a clearly
defined entity, such as the government," he wrote, "than to impersonal
market forces."

The centralized mindset is not just a misconception of the
scientifically naive. A similar bias toward centralized theories can
be seen throughout the history of science, with scientists remaining
committed to centralized explanations even in the face of discrediting
evidence. The history of research on slime-mold cells, as told by
Evelyn Fox Keller, a professor of science, technology, and society at
MIT, provides a striking example. At certain stages of their life
cycle, slime-mold cells gather into clusters.  Scientists long
believed that this aggregation process was coordinated by specialized
slime-mold cells, known as "pacemaker" cells. According to this
theory, each pacemaker sends out a chemical signal telling other
slime-mold cells to gather around it.

In 1970, Keller and a colleague proposed an alternative model, showing
how slime-mold clusters can form without any specialized cells. In
this model, every individual slime-mold cell emits a chemical signal
and follows signals produced by others. The result: aggregation
without a leader.  Nevertheless, for the following decade, other
researchers continued to assume that pacemakers were required to
initiate aggregation. As Keller writes, with an air of disbelief: "The
pacemaker view was embraced with a degree of enthusiasm that suggests
that this question was in some sense foreclosed."

It is not altogether surprising that people have strong commitments to
centralized approaches. Many patterns and structures in the world are,
in fact, organized by a central designer. When we see neat rows of
corn in a field, we assume correctly that the corn was planted by a
farmer. When we watch a ballet, we assume correctly that the movements
of the dancers were planned by a choreographer. When we participate in
social systems, such as families and school classrooms, we often find
that power and authority are centralized, often excessively so. These
phenomena reinforce the centralized mindset.

Another important factor is the way people think about themselves.
Your mind (like all others) is composed of thousands of interacting
parts. But you experience yourself as a singular being. This is a
convenient, perhaps necessary, illusion for surviving in the world.
When you do something like paint a picture or organize a party, you
feel as if you are playing the role of the central actor. Only one
entity seems to be in charge: you. So people naturally expect most
systems to involve a central authority.

By clinging to this centralized mindset to explain all phenomena,
politicians, managers, and scientists are working with blinders on,
focusing on centralized solutions even when decentralized approaches
might be more appropriate, robust, or reliable.


Decentralized Thinking Tools

To help people move beyond the centralized mindset and learn new ways
of thinking about decentralized phenomena, I developed a new computer
programming language called StarLogo. This language allows people to
control the actions of thousands of graphic creatures on the computer
screen. The user writes simple rules for the creatures and the
environment in which they live, and then observes the group behaviors
that emerge from their interactions. For example, a user might write
simple rules for individual birds, then observe how the flock behaves.

In one StarLogo simulation, inspired by the controversy over
slime-mold aggregation, the artificial creatures follow two simple
rules: they emit a pheromone (chemical attractant) and, after
"sniffing" the local area, move in the direction in which the
pheromone is strongest. At the same time, the environment causes the
pheromone to diffuse and evaporate. With this simple strategy, the
creatures quickly assemble into clusters. The reason: When a few
creatures get near one another just by chance, they create a pheromone
"puddle," which attracts even more creatures, making the puddle even
bigger and so on.

I have worked with several groups of high school students who have
created decentralized "microworlds" using StarLogo. In one experiment,
two students--Ari and Fadhil--wanted to study traffic jams. So they
created a one-lane highway with a police radar trap to catch cars
going above the speed limit. They then programmed each driver to
follow three simple rules: If you come within two car lengths of the
car in front of you, slow down.  If no cars are within two car lengths
ahead of you, speed up until you reach the speed limit. If you detect
a radar trap (each car is equipped with a detector), slow down.

Both students expected that a traffic jam would form behind the radar
trap, and indeed it did. As cars slowed down for the trap, the cars
behind them were forced to slow down, creating a queue with roughly
equal distances between the cars. When the cars moved beyond the trap,
they accelerated smoothly until they reached the speed limit.

I asked the students what would happen if they removed the radar trap.
The cars would be controlled by just two rules: if you see another car
close ahead, slow down; if not, speed up. They predicted that the
traffic flow would become uniform; cars would be evenly spaced,
traveling at a constant speed. When we ran the program, however, a
traffic jam formed. Along parts of the road, the cars were tightly
packed and moving slowly. Elsewhere, they were spread out and moving
at the speed limit.

At first, the students were shocked. Their comments revealed the
workings of a centralized mindset: They argued that traffic jams need
some sort of centralized "seed," like a radar trap or accident, in
order to form. They couldn't believe that simple interactions among
cars could create a jam.  But as they continued to experiment with the
simulation--modifying the speed and starting positions of the
cars--they developed an understanding of how the traffic jams formed.
When a few cars, by random chance, happened to get near one another,
they slowed down, making it likely that even more cars behind them
would have to slow down, leading to a jam.

Another student, Callie, chose to use StarLogo to simulate the
behavior of termites. Termites are practically blind, yet they are
considered the master architects of the insect world. In fact, on the
plains of Africa, termites construct giant moundlike nests containing
intricate networks of tunnels and chambers. Many people assume that
the queen of the termite colony tells the blind workers what to do.
But, as in ant colonies, the queen is more of a mother to the colony
than a leader. On the termite construction site, no one is in charge
of a master plan. Rather, each termite carries out a series of
relatively simple tasks, relying on its sense of touch and smell.

Termites are thus well suited for StarLogo explorations. Callie
started with the following goal for her StarLogo termite colony:
Termites should gather randomly scattered wood chips and put them into
a few orderly piles.  As with real termites, she didn't want to put
one termite in charge.  Instead, she programmed each termite to walk
around randomly, obeying two simple rules: If you are not carrying
anything and you bump into a wood chip, pick it up. If you are
carrying a wood chip and you bump into another one, drop the chip.

At first, we were both skeptical that this decentralized strategy
would work. The strategy did not prevent termites from taking wood
chips away from existing piles. So while termites were putting new
wood chips on a pile, other termites might be taking wood chips away
from it. It seemed like a good prescription for getting nowhere. But
we ran the program with 1,000 termites and 1,500 wood chips.

Much to our surprise, the number of piles steadily declined and the
number of wood chips in each pile grew. After several program
iterations--in each iteration every termite took a step or picked up
or dropped a chip--the wood chips had been gathered into hundreds of
small piles. After 2,000 iterations, there were 100 piles with an
average of 15 wood chips in each.  After 10,000 iterations, there were
fewer than 50 piles left, with an average of 30 wood chips in each
pile. And after 20,000 iterations, only 34 piles remained, with an
average of 44 wood chips in each pile.

The process was slow and frustrating to watch, as termites often
carried wood chips away from well-established piles. But it worked.
And as we watched the termites on the screen, it became obvious why
this simple strategy is effective. Whenever the termites remove all
the wood chips from a particular spot, the pile never restarts, since
termites drop chips only where others already reside. The termites
might drag chips back and forth between piles, but once a pile is
gone, it is gone forever. So the total number of piles keeps
shrinking.


Some Guiding Principles

People are usually fascinated by such decentralized phenomena. But
when they try to understand or create their own decentralized systems,
they often slip back into centralized ways of thinking. Through my
work with high-school students, I have developed several guidelines to
help people make sense of decentralized systems, highlighting some
pitfalls to avoid and some possibilities not to overlook. For example:

* Positive feedback isn't always negative. Positive feedback is
frequently symbolized by the screeching sound that results when a
microphone is placed near a speaker. It is usually viewed as
destructive because the situation often spirals out of control. By
contrast, negative feedback is often symbolized by a thermostat that
keeps room temperature at a desired level by turning the heater on and
off as needed. It is thus considered useful because it keeps
conditions under control. When I asked high-school students about
positive feedback, most were unfamiliar with the term. But when I
explained what it meant, the students quickly generated examples, most
of which involved a loss of control, often with destructive
consequences. One student talked about scratching a mosquito bite,
which made the bite itch even more, so she scratched it some more,
which made it itch even more. Another student talked about
stock-market crashes: a few people start selling, which makes more
people start selling, and so on.

Despite these negative connotations, positive feedback often plays a
positive role in decentralized phenomena. Brian Arthur, an economist
at the Santa Fe Institute, points to the geographic distribution of
cities and industries as an example of a self-organizing process
driven by positive feedback. After a small nucleus of high-technology
electronics companies started in Santa Clara County south of San
Francisco, an infrastructure developed to serve the needs of those
companies. That infrastructure encouraged even more electronics
companies to locate in Santa Clara County, which encouraged the
development of an even more robust infrastructure. And thus Silicon
Valley was born.

* Randomness can create order. Like positive feedback, randomness has
a bad image. Most people think randomness simply makes things
disorderly. They view randomness as annoying at best and destructive
at worst. But randomness plays a crucial role in many self-organizing
systems by creating fluctuations that act as natural seeds from which
patterns and structures grow.

At concerts or sporting events, for example, spectators sometimes join
together in seemingly spontaneous synchronized clapping. How do they
coordinate their applause without a conductor? Initially, when
everyone starts clapping, the applause is totally unorganized. Even
people clapping at the same tempo are wildly out of phase with one
another. But through some random fluctuation, a small subset of people
happen to clap at the same tempo, in phase with one another. That
rhythm stands out, just a little. People in the audience sense this
emerging rhythm and adjust their own clapping to join it. The emerging
rhythm thus grows stronger and even more people conform to it.
Eventually, nearly everyone in the audience is clapping in a
synchronized rhythm. Amazingly, the whole process takes just a few
seconds, even with thousands of people participating.

* A traffic jam isn't just a collection of cars. It is fair to think
of most objects as a collection of particular parts. For example, a
particular chair might have four particular legs, a particular seat,
and a particular back. But this is not so with objects like the
termite wood-chip piles. The composition of the piles is always
changing, as termites take away some wood chips and add other wood
chips. After a while, few if any of the original wood chips might be
in the pile, but the pile is still there. The wood-chip pile is thus
an example of an "emergent object"--it emerges from interactions among
lower-level objects. Similarly, a traffic jam is an emergent object,
continuing to exist even though the composition of cars within it is
always changing.

Students often have difficulty thinking about emergent objects. For
example, two students, Frank and Ramesh, tried to use StarLogo to
simulate an ant cemetery, in which ants gather their dead colleagues
into neat piles. This problem was virtually identical to that of
programming termites to create wood-chip piles. But Frank and Ramesh
resisted the simple decentralized approach that Callie used for the
termites. They were adamant that dead ants should never be taken from
a cemetery once placed there. How can a cemetery grow, they argued, if
the dead ants in it are continually being taken away? With this
strategy, however, Frank and Ramesh ended up with lots of little
cemeteries rather than a few big ones, simply because a cemetery, once
started, could never disappear. If Frank and Ramesh had viewed the
cemetery as an emergent object and allowed the composition of ant
cemeteries to vary with time, they would have had much greater success
in creating large ant cemeteries.

* The hills are alive. In his book Sciences of the Artificial, Herbert
Simon, a Nobel laureate economist from Carnegie Mellon, describes a
scene in which an ant is walking on a beach. Simon notes that the
ant's path might be quite complex, but it does not necessarily reflect
the complexity of the ant. Rather it might reflect the complexity of
the beach. Simon's point: don't underestimate the role of the
environment in influencing and constraining behavior.

Many people seem to resist the idea of an active and influential
environment. For example, when I told a student about a StarLogo
program in which ants find food by following pheromone trails, he was
worried that the trails would continue to attract ants even after the
food source at the end of the trail had been fully depleted. In his
mind, the ants had to take some positive action to get rid of the
pheromone. In fact, he proposed an elaborate scheme in which the ants,
after collecting all of the food, deposited a second pheromone to
neutralize the first pheromone. It didn't occur to him that the first
pheromone would simply evaporate away.


Foundation for Discovery

A friend of mine has a daughter named Rachel. By the time she was
three years old, Rachel had already developed a theory about why it
rains on some days and not on others. "The clouds rain when the
thunder tells them to rain," she explained. In her mind, some type of
centralized decision making was necessary. Thunder commanded, and the
clouds obeyed.

It is not surprising that Rachel came up with a centralized
explanation for the rain. Most likely, she was unaware that other
types of explanations even existed. But as Rachel grows up, will she
continue to rely on centralized explanations? If she takes a physics
course in high school, will she understand gravity as two objects
pulling on one another with equal force, or will she think of gravity
as a one-way force, with one large object pulling on a smaller one? If
she takes an economics course in college, will she understand that
interest rates and money supply can affect each other, or will she
assume that one is the cause and the other is the effect? If the
unemployment rate rises dramatically, will she search for explanations
with multiple, interacting causes, or will she immediately assume some
type of evil conspiracy?

An elementary or high-school course that teaches Ten Golden Rules of
Decentralized Thinking probably would not have much effect on someone
with a firmly entrenched centralized mindset. Young students are
likely to become comfortable with decentralized ideas only if they get
opportunities to design, create, explore, and play with decentralized
systems.

What's needed are computer-based construction kits that let children
like Rachel create their own decentralized microworlds. At school,
Rachel might create an artificial environment with giraffes,
elephants, and her other favorite animals, and program each to follow
a few simple rules. She could then observe what patterns emerge from
the interactions and how simple changes can affect the entire
ecosystem.  At home, she and her friends might simulate how people
gather into groups at a party. By working on projects like these,
Rachel could come to understand the importance of decentralized ideas
in explaining the world around her.

By the time Rachel was four, she had developed a new theory about the
rain.  "The clouds get together at night, and they decide whether it
should rain the next day," she explained. This new theory still
involves some centralized planning, but there was no longer a central
actor, the thunder, in charge of the whole process. If Rachel is
surrounded by new types of computational tools and ideas as she grows,
one can only wonder what new theories she'll develop to explain the
rain.


