“Reporting Complexity (with Complexity):General Systems Theory, Complexity and Simulation Modeling“

See the PPT slides from a vid-conference lecture from Santa Fe to

INDIANA UNIVERSITY – PURDUE UNIVERSITY
INDIANAPOLIS
School of Public and Environmental Affairs
School of Journalism 
COURSE: Mass Media & Public Affairs
March 31, 2010
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A number of friends and associates, for whom we have the greatest respect, say this is one of the best, most enriching conferences in the U.S.  It is not cheap, but there are vacation condos to be found in the area that would help to make this affordable.

We are back with our 4th UCLA Lake Arrowhead Conference on Human Complex Systems.
from Wednesday April 25, 2007 through Sunday April 29, 2007.

We look forward to
another cross-disciplinary gathering of social scientists who employ
cutting-edge agent-based computational modeling and related
computational ideas and methods in their research and teaching. As in
past years, dozens of presenters from numerous disciplines are
presenting. We are also hosting evening panels, a live simulation, and
opportunities for networking and relaxation amid gorgeous surroundings.

Advancing Agent Modeling in the Social Sciences


The conference is a forum for sharing the most recent advances — in
theory, methodology and application – in the area of agent modeling
throughout the social sciences (e.g., Anthropology, Communication
Studies, Economics, Geography, History, Political Science, Sociology,
Urban Planning). We also welcome social scientists in professional
schools (e.g., Business, Education, International Relations, Public
Health, Public Policy, Social Welfare) and in the public and private
sectors. Researchers and theorists in Psychology, Media Studies and
social aspects of Cognitive Science, Artificial Intelligence, Robotics
and related disciplines also welcome!

For a paper presentation, authors present for 20 minutes and receive an
additional 10 minutes for Q&A. We also welcome 90-120 minute
symposium proposals consisting of 3-4 individual papers on a related
topic of inquiry. Finally, we are open to someone wishing to organize
an evening panel discussion on a �hot topic� in agent modeling.

A
couple of articles have passed across our desk in recent days that
illustrate the impact — and  importance of understanding —
decentralized (or “distributed”) systems and complex adaptive systems.

For starters, take a look at “Reinventing 911
How a swarm of networked ­citizens is building a better ­emergency broadcast system.”
http://www.wired.com/wired/archive/13.12/warning.html

Author Gary Wolf writes: “I've been talking with security experts about one of the thorniest
problems they face: How can we protect our complex society from massive
but unpredictable catastrophes? The homeland security establishment has
spent an immeasurable fortune vainly seeking an answer, distributing
useless, highly specialized equipment, and toggling its multicolored
Homeland Security Advisory System back and forth between yellow, for
elevated, and orange, for high. Now I've come [to Portland, Oregon] to take a look at a
different set of tools, constructed outside the control of the federal
government and based on the notion that the easier it is for me to find
out about a loose dog tying up traffic, the safer I am from a terrorist
attack.

“To understand the true nature of warnings, it helps to see them not
as single events, like an air-raid siren, but rather as swarms of
messages racing through overlapping social networks, like the buzz of
gossip. Residents of New Orleans didn't just need to know a hurricane
was coming. They also needed to be informed that floodwaters were
threatening to breach the levees, that not all neighborhoods would be
inundated, that certain roads would become impassible while alternative
evacuation routes would remain open, that buses were available for
transport, and that the Superdome was full.

“No central authority possessed this information. Knowledge was
fragmentary, parceled out among tens of thousands of people on the
ground. There was no way to gather all these observations and deliver
them to where they were needed. During Hurricane Katrina, public
officials from top to bottom found themselves locked within
conventional channels, unable to receive, analyze, or redistribute news
from outside. In the most egregious example, Homeland Security
secretary Michael Chertoff said in a radio interview that he had not
heard that people at the New Orleans convention center were without
food or water. At that point they'd been stranded two days.

“By contrast, in the system Botterell created for California,
warnings are sucked up from an array of sources and sent automatically
to users throughout the state. Messages are squeezed into a standard
format called the Common Alerting Protocol, designed by Botterell in
discussion with scores of other disaster experts. CAP gives precise
definitions to concepts like proximity, urgency, and certainty.
Using CAP, anyone who might respond to an emergency can choose to get
warnings for their own neighborhood, for instance, or only the most
urgent messages. Alerts can be received by machines, filtered, and
passed along. The model is simple and elegant, and because warnings can
be tagged with geographical coordinates, users can customize their cell
phones, pagers, BlackBerries, or other devices to get only those
relevant to their precise locale.”


Second item of interest
I'm sure many of you noted Dexter Filkins Pg1 lead story in the NYT on
Friday, 2 Dec. 2005.  The online version headline is “Profusion of Rebel Groups Helps Them Survive in Iraq.”  That, unfortunately, lacks the truth and insight of the print version headline:
“Loose Structure of Rebels Helps them Survive in Iraq — While Al Qaeda Gains Attention, Many Small Groups Attack on Their Own.“ 

It
seems that finally someone in the journalism community has figured out
that what's happening in Iraq — and around the world — is a
decentralize, CAS.  Too bad journalists — journalism educators, students and professionals — haven't been exposed to the
concepts and vocabulary to really present the problem in all its, ahem,
complexity.

“Positive Deviance”
Has
a nice ring to it, don't you think?  In fact, the concept has been
batted around for 14-plus years and has evolved enough to have its own
physical and virtual place in the universe at the Plexus Institute and Tufts University Positive Deviance Initiative.



“Positive
Deviance … demonstrates that isolated examples of success
can be tapped to benefit an entire community or organization.
Accomplishing this requires a radical departure from 'benchmarking' and
'best practices' strategies of change….The PD approach builds on
successful but 'deviant' (different) practices that are identified from
within a
community or organization. It is based on the observation that in every
group there are certain individuals whose uncommon, but demonstrably
successful practices or behaviors enable them to find better solutions
than their neighbors or colleagues who have access to exactly the same
resources. Its use was pioneered in developing countries and has led to
sustainable improvements in seemingly intractable organizational and
social issues.”

We also like the approach because it is an example of how the high-level concepts of complexity studies and Complex Adaptive Systems (CAS) can
move from the theoretical to the experimental and on to application
state.  Again, something that journalism, and expecially
journalism educators, should be thinking about.

The following links provide general background information on the field of Cybernetics and Systems Theory, an interdisciplinary academic domain.

“People, when initially introduced to structures, also referred
to as Archetypes, often find them a bit overwhelming. They really
aren't at all difficult once you get used to them. The following
is an introduction to structures and how to read the stories associated
with the diagrams.”

http://www.systems-thinking.org/intst/int.htm

Be sure to work upstream in the URL to see the rest of Bellinger's work.

System Dynamics Society
System dynamics is a methodology for studying and managing
complex feedback systems, such as one finds in business and other social
systems. In fact it has been used to address practically every sort of
feedback system. While the word system has been applied to all sorts of
situations, feedback is the differentiating descriptor here. Feedback
refers to the situation of X affecting Y and Y in turn affecting X perhaps
through a chain of causes and effects. One cannot study the link between
X and Y and, independently, the link between Y and X and predict how the
system will behave. Only the study of the whole system as a feedback system
will lead to correct results.

 <>The System Dynamics Group was founded in
the early 1960s by Professor Jay W. Forrester at MIT. At that time, he began
applying what he had learned about systems during his work in electrical engineering
to every day kinds of systems. What makes using system dynamics different
from other approaches to studying complex systems is the use of feedback loops.
Stocks and flows help describe how a system is connected by feedback loops
which create the nonlinearity found so frequently in modern day problems.
Computers software is used to simulate a system dynamics model of the situation
being studied. Running “what if” simulations to test certain policies
on such a model can greatly aid in understanding how the system changes over
time.
See http://web.mit.edu/sdg/www/

For a good jumpstation related to GST, see:
http://pespmc1.vub.ac.be/CYBSYSLI.html