Self-Organization in Societies
Why are ants, wolves and humans organized into
societies? The simplest answer is that these societies enhance
the survival of individuals and, therefore, the populations as
a whole. At the very foundation of the human societies is their
ability to solve vital, complex problems for the individuals
that make up the societies. We as individuals contribute to,
as well as adopt to, these hyperstructures because they make
life easier in one way or another, yet we, individually or collectively,
often do not understand the process involved. Despite the lack
of understanding, our society has changed dramatically, from
small hunting tribes to a highly technological, global society.
One of the apparent paradoxes associated with
human society is its diversity in both goals and means. Subgroups
often tend to disagree significantly. Different individuals,
different political parties, different companies, employers and
employee, etc., create a complex network of contradicting means
and goals. We shall argue that this divergence is not a liability
or even an inconvenience, but is of vital importance and inherent
survival value.
In addition, many problems of the survival
of human society, or even confronting large companies, are of
a nature where the complexity and the magnitude of the issues
involved are of too large of an extent be defined and understood
by a single coherent organization - and much less by the individuals.
An example is the dynamics of the world economy. Nobody fully
understands what is going on, even though it impacts us all,
and the need for understanding is great. A loosely coupled network
of cooperating and competing organizations has for thousands
of years sorted out these problems and eventually generated solutions
- our survival is proof of the success of the process. Individuals
of course play a vital role in this process, but the emergent
dynamics of the society is, more times than not, out of the control
of any individual. Our society is a self-organizing system which
involves many individuals and organizations at the "controls."
Traditional Problem Solving
Most of our day-to-day technical developments
and problem solving are achieved in a linear, premeditative approach:
- Understand the system in question
- Represent the system behavior in an approximate
model or simulation
- Prediction of the system behavior based
on the model or simulation
- Apply the model or simulation to optimize
and control some aspects of the system to meet defined goals
- Repeat the process for corrections or failures
As long as we, as a society of technocrats,
can "understand" the system, the above approach works well and
we can optimize it for our needs. This approach is desirable
because it has the potential to achieve optimal and rapid solutions.
An Alternative
Paradigm for Problem Solving
Distributed systems (biological evolution,
immune systems, human societies, etc.) take a very different
approach to problem solving. When the system is too complex for
analysis (as in global economics), an "understanding" of the
whole is not possible. Without this understanding or when a centralized
control is absent, the linear approach to optimization of a system
is interrupted at the onset. Instead, a solution by distributed
systems relies on a broad diversity of potential solutions at
any time, combined with an emergent system dynamics. Then, given
a change of the overall dynamics of the system - one of the potentials
is selected. If a solution is not found within the current diversity,
the system fails and "dies." If a solution is found, then the
dynamics of the system will "optimize" the solution, but not
by sacrificing the diversity of the system, only by changing
the relative dominance of subsystems. Thus, a solution is found
without premeditation or centralized control.
Social structures that take advantage of our
inherent, self-organizing social dynamics will be best enabled
to cope with our increasingly complex world {Abraham,
1994}. Indeed, we argue that this has happened in modern,
overly centralized governments, such as the USSR, and is the
reason that democracy and capitalism provide the most robust
solutions in modern times {Slater,
1964}. There are also trends towards decentralized corporate
management {Anderson, 1988} {Youngblood,1996}.
Herein lies the thrust of our idea. What we
are suggesting will never replace the linear problem solving
for less complex problems, in fact, the idea requires traditional
problem solving at a local level. But for systems that defy timely
understanding, due to the size or variety of information, only
a distributed approach to problem solving can discover the solution
space.
We believe that in the future, emerging solutions
on distributed networks will hold a respected place in problem
solving and in science, once we accept the limits in our understanding
and once the capability of emerging solutions is demonstrated.
This way of solving problems has been around since the origin
of life and now our technological capabilities allow us to further
understand and improve this capability in a clear and precise
manner by the use of the Net.
Past Views of Social Evolution
The view of human society as a collective organism
is not new. George Dyson, in his recent book, "Darwin Among the
Machines" {Dyson, 1997} surveys the
works of great thinkers over the last 500 years who have touched
on visions which involve evolution in the collective intelligence
or awareness of humans and machines as symbol processors. Despite
the long history of interest in these ideas, it has only been
in the last decades that there is now promise of a quantitative
theory of social dynamics. This new foundation was driven by
the dramatic success of the application of complex systems methods
to biological problems as expressed, for example, in the Artificial
Life movement {Artificial Life}.
In the last two decades there has been a virtual explosion of
interpretations or dynamical theories of social and economic
systems (e.g., citations in {Abraham, 1994}).
Unique Capabilities of the Net (Internet plus
humans)
The Net has three significant, arguably unique, capabilities beyond prior human-technological
systems: (1) the ability to integrate quickly heterogeneous systems (the breadth
of systems), (2) its ability to capture detailed signatures of the access
and use of information (the depth of systems) and (3) its ability, with
relatively minimal loss, to relate and transmit information (the accuracy
of communication) The Net has the ability within one hyper-system to integrate:
- Information storage: both in the
form of simple data and complex text and images. This was earlier
done in off-line libraries and a variety of data banks.
- Communication: Communication was
earlier done either by the relatively slow movement of people
or documents or, in recent times, by telephone or other electronic
technologies. However, complex documents, simple data and images
can now be transported instantaneously and close to cost-free
from anywhere to everywhere. Geographical barriers are virtually
gone.
- Traditional computing: the automated
(simple) information processing of huge amounts of data.
- Human processing: The human ability
to analyze, understand and process limited, but highly complex
information.
Until very recently (1), (2) and (3) were physically separated processes,
all combined by human intervention (4). Now (1), (2) and (3) are integrated
in a more standardized medium so (4) is no longer the slowest link and now
can be active at a more efficient and useful level. Thus, the time scale
for knowledge organization and creation is drastically shorter. This new
integration has been overwhelming to humans, but tools are readily being
developed in this infant hyper-structure to overcome this initial shortcoming [see
firefly.net, amazon.com, alexa.com].
- The Net can capture the complexity (the
depth) of how information is associated by retaining all references
between data on the network. A simple example of how much of
this relational information is currently lost is the use of
scientific publications. While papers contain citations that
connect the current paper with the information in other papers,
the more immediate and detailed information about the numbers
and types of readers of the papers could be only obtained in
the past at great expense. Now with the advent of online publications,
such information is explicitly available at effectively no
cost. In general, the Net can capture all traces of the use
of information. As more and more of the human activities occur
on the Net, these traces will capture the full complexity of
our interactions and activities that were formerly lost. While
currently not used to any extent (except in the examples noted
above), these traces represent implicit knowledge of how we
interact and how new knowledge is created. In the past it has
been difficult to do experiments involving the access and formation
of knowledge, but by conducting experiments on the Net, as
demonstrated in a later section, the situation has been reversed
and now is data rich, instead of data poor.
- Traditional human-to-human communication
results in a rapid loss of information a bit removed from its
creator (the children's game of passing a phrase around a circle
is a telling example of the high noise-to-signal ratio of verbal
communication). By contrast, information exchanged or related
on the Net, whether in web pages or emails, suffers minimal
loss of information during transmission or linking, in the
same way that the content of a book is not altered when exchanged
or a citation to a journal is not degraded over time. The advantage
on the Net of reduced loss or noise is at a sacrifice of bandwidth
or dynamic range with current technologies: the elimination
of vocal, facial and gestural expressions which do not accompany
one-to-one communication. In this discussion, we do not include
the misinterpretation that still occurs in understanding the
exchanged information; this source of miscommunication occurs
independent of the mechanism of exchange.
The degradation of verbal communication is
one possible explanation for the maximum critical number of participants
for effective problem solving in all human systems, from social
functions to organizations. Why does a committee cease to function
above a certain size, even though greater resources are available?
With the stronger presence of these three capabilities
in human use and interactions on the Net, we propose that an
informational "phase change" will occur: for the first time we
can capture our creation, manipulation and rejection of knowledge,
encompassing a much broader range of the complexity of our existence
- information which was earlier lost in the traditional person-to-person
interactional noise or never available. With this phase change
of information processing capability comes the possibility of
an enhanced dynamic that, while an essential part of human organizations,
has been limited in extent and responsiveness.
Self-Organizing Knowledge
Large problems are sometimes "solved" without
our explicit intervention and may only be seen as problems in
retrospect. A "solution" emerges and takes care of the problem
without any single person identifying the problem or orchestrating
the solutions.
A simple demonstration of a self-organizing
solution is the formation of a path in a forest. The undefined
goal is a path that is usable and of minimum length between two
destinations and is adaptable to variations in local conditions.
The self-organizing path evolves over time and includes contributions
from a variety of people and animals with a broad diversity of
goals (mode of travel, destinations, security, etc.) and changing
forest conditions (weather, tree falls, dangerous locations,
etc.). A comparable "designed" path would require a thoughtful
process of premeditated selection of the goals to be optimized,
an analysis of the forest layout and dynamics, a plan to meet
the goals, and the implementation of the solution.
Self-organizing solutions have existed long
before humans became capable of alternative approaches to problem
solving. And as we continued to develop our individual, organizational
and governmental abilities as problem solvers, the self-organizing
societal dynamics continued to function in the background of
our social dynamics. For example, the shift from an agricultural-based
society to an industrial-based society occurred without any group
of individuals being responsible. The society self-organized
into another form. Only in retrospect, it is clear that a number
of key factors had to be in place to make such a shift possible.
Only in retrospect, do we understand and model the process with
the traditional process of knowledge creation. A simple example
illustrates the impact on emergent problem solving of the unique
capabilities of the Net described in the last section.
Because informational systems have not been
studied as self-organizing systems, some explanation is necessary
of the nomenclature borrowed from other fields. We distinguish "self-organized
knowledge" as being different in origin, not necessarily in kind,
from "traditional knowledge". We define traditional knowledge
as being derived from the premeditative actions of people or
predetermined processes of automated information processing to
associate facts and draw conclusions. It represents a condensation
of information and is localized in time and space - in books,
speeches, memories. Self-organized knowledge, in contrast, originates
from the self-organizing dynamics of human hyperstructures, without
the action of a central coordinating processor. Once self-organized
knowledge is formed, it can either be observed and transformed
into traditional knowledge, e.g., through writing.
Self-Organization
on Networks: An example
A simple experiment was done by Bollen and
Heylighen {Bollen, 1996a} in Belgium
that illustrates the concept of self-organizing knowledge through
human interaction. The idea was to use the Net to make hypertext
webs more intelligent {Drexler, 1991}
{Bollen, 1996b} by reinforcing paths
of people using the various sites, similar to the perceived reinforcement
of pathways in the brain by frequency of use {Gaines,
1994} {Heyligen, 1996}.
The researchers created 150 web sites, each
identified by a word from the 150 most common words in English.
Under the word, a list of 10 randomly chosen words from the list
of 150 words were displayed. Upon entering one of the 150 sites,
the user was asked to pick the word from the list that most closely
is associated with the header word. Upon choosing a word, the
order of the list is recalculated based on the frequency of selection
and then the user is taken to a new site that corresponds to
the selected word, and the process is repeated. The researchers
found that the lists stabilized to a fixed order after about
4000 selections in a site. The resulting ordered lists determined
a common semantics despite the heterogeneity of users.
This simple task of ordering is easy for an
individual but of little utility due to large individual variation
in semantic differences. Alternatively, the task is difficult
to complete for a committee of experts, while the result would
be more useful. The network solution achieved a result representing
useful collective knowledge, but with minimal instruction and
effort for the collective group of individuals. This example
captures the essence of developing an self-organizing knowledge
system that combines the advantages of both human and computer
networks to quickly solve a semantically complex problem. From
this example, one can imagine a host of previously challenging,
if not intractable, problems that could be addressed once the
methodology is developed.
Conclusions
The above text presents preliminary arguments
on the possible future of "problem solving" or collective decision
making in our society and organizations. We have argued that
a dynamic process underlies all life: the ability of self-organizing
systems to "solve" essential problems, will take on new functionality
as our society increasingly utilizes the Net for human interaction.
In the development of the ideas presented in
this paper, we have realized that the experience gained in studying
complex behavior of biological or physical systems is not generally
applicable to knowledge systems. Self-organizing knowledge formation
represents a system that appears to be unique: it is not dissipative,
nor constrained by limited resources, in the sense as are previously
studied examples of self-organization in constrained systems.
No equivalent laws of conservation or dissipation exist for knowledge,
as do for material resources: the act of giving knowledge does
not erase knowledge in the giver and new knowledge is not created
at the expense of prior knowledge.
These unique characteristics of self-organizing
knowledge systems are further enabled by the unique capabilities
of the Net: in addition to providing improved temporal and spatial
system dynamics, the Net has relatively loss-less transmission
and linking of information, unlike our predominant verbal communication.
The symbiotic intelligence of the combined human-hardware-software
system, which constitute the Net is believed to be able to operate
at a higher level of functionality, both in numbers of individuals
and the complexity of capability.
The implications of the arguments presented
in this paper are far reaching to future dynamics of organizations,
society and economics. With the increased use of the Net in our
economy and society, many of the problems that have challenged
traditional forms of management may find solutions. The main
consequence will be for management and governments to facilitate
the use of collective problem solving when problems arise in
systems that are not understood. Organizations may find that
to function at a higher level of performance, policies will be
pursued that encourage diversity, increased access to information
and decentralized control.
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Additional Links for Symbiotic Intelligence
Project
Good summary: http://www.computerworld.com/managementtopics/management/story/0,10801,64912,00.html
http://www.fathom.com/media/trailDemo.html
http://itri.loyola.edu/ConvergingTechnologies/
http://www.edu-cyberpg.com/Technology/trends.html
Relevant workshop: http://www.santafe.edu/~dynlearn/colcog/
For the symintel site:http://www.man.ac.uk/sociologyonline/course/soccyber/self.htm
Long list of referrals: http://www.mikro.org/Events/OS/wos2/Levy-pp/liensIC.html
