"There are two kinds of truth. There are superficial truths, the opposite of
which are obviously
wrong. But there are also profound truths, whose opposites are equally right." --Niels Bohr
Summary: Learning About CAS
Learning about CAS is, itself, a CAS. Learning emerges
in a group through such things as information flow,
anxiety containment, reflection, and so on. Humans inherently want to learn. If learning is not taking
place
the way you think it should, step back from your context, reflect, and see if you can begin to understand
the
dynamics in the CAS that may be getting in the way of the natural behavior of learning.
The summary box below captures some key points from this
section about learning and CAS.
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Summary of Key Points in Learning About CAS
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- Remember that learning is an emergent property
of your group.
- Emphasize information flow, diversity of
thought, connection, and good enough plans;
rather than detailed curriculum and one-way
flow of knowledge from a central figure.
- Be careful about power differential within the
group and provide safety for the anxiety always
associated with learning.
- Capitalize on paradoxes and unexpected events
that occur within your context.
- Try many approaches and let successful
learning directions emerge.
- Work from the metaphor of sowing seeds and
growing crops.
- Stress involvement and application in all your
group's learning activities.
- Create tension for change by discussing gaps
in performance and expectations.
- Build skills together.
Honor diverse learning styles, while also seeking to
expand the range of what you yourself are comfortable
with.
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- Reflect on both the learning and the learning
process within your group.
- Respect anxiety about moving on and making
change, but don't make everyone wait until
everyone is ready. Blaze new trails with those
who are ready, and reflect respectfully, lovingly,
but clearly, with those who are lagging behind.
(Note: this is an interesting application of the tit-
for-tat strategy described in principle #11.)
- Always remember that the only person you can
change is you.
- Honor minimum specifications. Avoid imposing
more specifications. Get out of the way of the
creative and emerging behavior of your learning
group.
- Talk often about expectations in the group. Talk
honestly about whether you are making the
progress you hoped for.
If you are the "teacher," be a new kind of
teacher: a co-
learner, quick to share knowledge but challenging the
group to make application, nudging people off their
current attractors but allowing them to find their own
new attractors, and always open to being challenged by
the group.
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Key Points:
-
Individual agents
- Interpretation and action is based
on mental models
- Agents can have their own or shared
mental models
- Mental models can change; i.e., learning
is possible
- Interconnections among agents
- Actions by one agent changes the
context for others
- System behavior emerges from the
interaction among agents
- The system can exhibit novel behavior
- The system is non-linear; small inputs
can lead to major outcome swings
- System behavior is fundamentally
unpredictable at the detail level
- Broad-brush prediction of system
behavior is sometimes possible
- Order is an inherent property of
the system, it need not be imposed
In a CAS, agents operate according
to their own internal strategies or mental models (the
technical term is "schemata"). In other words, each agent can have its own "rules"
for how to
respond to things in its environment; each agent can have its own interpretations of events.
These rules and interpretations need not be explicit. They do not even need to be logical when
viewed by another agent. These are clearly characteristics of humans in just about any social
system.
Agents can share mental models, or be totally individualistic. Further, agents can change their
mental models. Because agents can both change themselves and share mental models, a CAS
can learn; it's behavior can adapt over time. Again, we clearly know that human organizations
change over time and are capable of progress.
The behavior of
a CAS emerges from the interaction among the agents. A CAS can, and
usually does, exhibit novel behaviors. Because of the interaction, the behavior of the system is
also non-linear; seemingly small changes can result in major swings in system behavior. If you
reflect on this, you can probably recall many examples of these behaviors in human systems.
We are usually surprised when they happen. However, when we learn to view systems through
the lens of CAS, these behaviors become expected, not surprising.
Because of this novelty and non-linearity,
the detailed behavior of a CAS is fundamentally
unpredictable. It is not a question of better understandings of the agents, better models, or
faster computing; you simply cannot reliably predict the detailed behavior of a CAS through
analysis. You have to let the system run to see what happens. The implications of this are that
we can never hope to predict the detailed behavior of a human system. While this seems
obvious to say, note how often managers and leaders (we ourselves!) act as if we know or can
be sure about how others should act in response to our actions.
Still, despite this lack of detailed predictability, it is often possible to make generally true,
practically useful statements about the behavior of a CAS. For example, while we cannot
predict the exact temperature in Atlanta at 4:49 pm on August 4, we can say that it is pretty
likely that a traveler there will not need a heavy coat. This gives us some hope in human
systems, we just need to be careful not to over-estimate our ability to predict what will happen.
Over-estimation is the usual mistake that we all make; if you have ever been surprised by how
something has turned out, you have fallen into the trap of over- estimation.
Stuart Kauffman, Ilya Prigogine, and others have shown that a CAS is inherently self-
organizing. Order is an inherent property of the system; it does not need to be imposed from
outside. Further, in a CAS, control is dispersed throughout the interactions among agents; a
central controller is not needed. Yet, most of traditional management theory is about how to
establish order and control through the actions of a few people at the top of an organizational
hierarchy. This management instinct, one that we have all learned, may be the biggest factor
holding back progress in our organizations.
1. Thoughts
