An Award for NAFCM + Conflict Mapping and Other Tools for Understanding Complex Problems
Newsletter 114 - May11, 2023
by Heidi Burgess and Guy Burgess
Follow Up and Good News about D. G. Mawn and the National Association for Community Mediation
On May 4, 2023 we shared a conversation we had with D.G. Mawn, the President of NAFCM, about the work of NAFCM. One day later, on May 5, the Alliance for Peacebuilding announced that D.G. was awarded the Melanie Greenberg U.S. Peacebuilding Award of Excellence.
The award, named after and presented by Humanity United’s Managing Director, Peacebuilding, Melanie Greenberg, was established in 2018 to highlight individuals and organizations working to address increasing dynamics of conflict and instability in the United States, signifying the need for and importance of peacebuilding efforts at the community and national level.
. . .
As Greenberg said when presenting the award, "I am deeply honored that D.G. Mawn has been chosen as the recipient of the 2023 Melanie Greenberg award. Drawing on NAFCM's roots in the Civil Rights Movement, D.G. has ensured that peace and justice never walk far apart during a time of deep polarization and upheaval in the United States. D.G. has been a brilliant, patient, creative force for change in communities across every region of the country, and has started to build a compelling and inclusive national vision and infrastructure for peace. D.G. embodies all that it means to be a peacebuilder, in the most courageous and visionary senses of the word."
Congratulations to D.G.!
Graphical Conflict Mapping to "See" Complexity
by Heidi Burgess and Guy Burgess
May 9, 2023
Following on our earlier post and newsletter about how "Our Problem Isn't 'Them,'" we want to share one strategy for quickly understanding at least some of the complexity of any situation, and develop a better understanding of what responses might be helpful and which not. This is a strategy we call graphical conflict mapping, to differentiate it from text-based conflict mapping, which was developed by Paul Wehr and others and is still used in some university classes. Graphical conflict mapping involves drawing diagrams of what influences what, as I originally learned from Peter Coleman in his book The Five Percent and Robert Ricigliano in his book Making Peace Last. While I used this strategy in classes, it also is very useful for disputants themselves to do, either alone, with their own group, or with a facilitator, drawing maps with people on "the other side." This latter approach can be challenging, but it is extremely valuable for helping people understand how the other side sees the problem everyone is concerned about, and moving all sides away from the overly simplistic "us-versus-them" framing of that situation.
Graphical conflict mapping can be a pretty involved process (I have my students spend several weeks working on their maps), but it can also be done fairly quickly and easily if you get a few people together to unpack a thorny problem. All you need is a big piece of paper or a white board (we tell our students to go out and get a roll of brown wrapping paper if they don't have a white board available), post-it notes, pens, and markers. Then you set to work mapping the conflict of your concern.
For illustration, let's consider the conflict over police violence in the U.S. Put a post-it note in the center of the big piece of paper or white board and on it write "police violence." Then ask yourself and your co-mappers, what factors contribute to police violence? "Racial stereotyping" might be one answer. Write that on a post it note, put it to the left of the center note and put an arrow between them, with the point going toward police violence.
What else contributes to the problem? "Inadequate police training" might be another answer. Put that on a note and put an arrow toward the center. "Police fear" might be a third. Put an arrow going from police fear to police violence, but also, perhaps, from stereotyping to fear because stereotyping of blacks as violent likely increases police's fear of blacks in their encounters with them. Inadequate training might also lead to fear. Put in another arrow. What leads to stereotyping? Hateful stories on social media might be one answer. Put that on the map. What leads to inadequate police training? Inadequate funding might be one answer. Ah-ha! That suggests that defunding the police might contribute to police violence, not deter it.
Keep going like this until you have listed all the factors that you can think of that might lead to police violence, the things that lead to those things, and, if you have time and space, the things that lead to those things. Then start putting in arrows showing the interrelationships between these factors.
You can already see, this isn't a simple "us versus them" problem. The more you understand what is creating the problem, the more you will be able to see what might be done to try to fix it. And you might see that policies you are advocating, such as "defunding the police," might be counterproductive. This is what is meant by the phrase "complicate the narrative" a phrase coined by Amanda Ripley, a journalist who is leading the way in the United States towards more constructive journalism.
Complex Versus Complicated Systems
Another aspect of avoiding over-simplification of conflict narratives is understanding the nature of complex systems, which characterize most intractable conflicts. Most people understand complex to mean "complicated" or "hard to understand." They are hard to understand, but systems theorists (and a growing number of conflict theorists) make an important distinction between "complex," and "complicated."
Complicated systems have many parts, but the parts are connected in determined, predictable ways. Cars are complicated, computers and cell phones are complicated. But they were designed by people, who understand how they work, how the parts work, and how the parts are connected. When a part breaks, they can find it, fix it, and make the machine work again. In addition, in complicated systems, the relationship between inputs and outputs is determined and linear. This means small inputs will create small, determined outputs, and large inputs will create large determined outputs. So when you push gently on the accelerator in a car, the car will move forward slowly. If you floor it, the car will speed ahead as fast as it is able. How much the car speeds with different levels of pressure on the accelerator is predictable, at least if one is driving on flat ground.
Complex systems have many interconnected parts, but they are not connected in known or determined or linear ways. Rather, they are adaptive--each element in the system responds (adapts) to its environment in a (sometimes) predictable way. But the system, as a whole, is not determined or predictable —it can produce novel and unexpected outcomes. That means the behavior of the whole cannot be explained by the behavior of the parts, and you cannot fix complex adaptive systems by taking out the broken piece, fixing it, and putting it back in its place. It won't work the same way it did before. You have to be much more experimental when you try to intervene in complex adaptive systems--trying something, watching the effects, adapting, and trying again.
As Wendell Jones points out in his BI essay on Complex Adaptive Systems, each human, in an of themselves, is a complex adaptive system.
The human brain is the most complex system known to us, in the universe, with one hundred billion (1011) neurons and ten thousand trillion (1016) connections (synapses) among those neurons. At each of these synapses, complex interactions occur among electrical charges and over 100 chemicals. Much work is currently under way to examine aspects of the emergent property of the brain that we know of as consciousness. From the earlier discussion, one can see that an individual's actions might be generally predictable, but those actions can never be precisely predictable. In addition, our human self-awareness (an emergent characteristic) generally allows us to choose how we interact with one another or a group.
So we can't predict how, exactly, any human will respond when presented with a particular situation. And when you get many humans interacting with each other, the situation becomes even less predictable. That means that we can't "fix" complex adaptive systems as if they were simple or even complicated systems. There are not cause-and-effect relationships, where a broken piece can be replaced and the system will work again. Outcomes aren't linear. We might push hard in one place and nothing will happen. Push a little elsewhere, and the entire system will rearrange itself.
Jones went on to explain:
The attribute of complex systems that provides direction for intervention is the nonlinear self-organizing property. In these systems, whether a jazz ensemble or an ant colony, agents in the system adjust to every stimulus in ways that are not linear. That is, small input changes can produce large output changes. This is actually very encouraging, for it suggests that small inputs into a protracted or intractable conflict can conceivably produce large effects.
People working the field of dispute resolution need to be willing to embark on "enlightened experiments." That is to say, change something and work with the system while it adjusts to the change. If a positive result is not immediately apparent, wait awhile. It may yet be coming. Many times, these initial changes will not produce a significant reorganization of the system, but there can be changes that will result in reorganization within the system that will be beneficial. Such "enlightened experiments" could include altering aspects of the negotiations, such as changing the venue, changing the negotiation teams, adding culture-specific features to the negotiation, etc. Although it is impossible to tell which change will make the biggest difference, small changes in complex adaptive systems can lead to significant changes and potential negotiation breakthroughs.
In summary, making a difference in the midst of intractable conflict will not come from a reductionistic analysis of the system, conducted in hopes of designing and deploying a "definitive" intervention. Instead, evolutionary progress toward resolution can be possible through mindful experiments from within the conflict and then moving with the self-organization that follows.
The impossibility of predicting and controlling conflict need not result in a sense of hopelessness or resignation. It can, instead, propel us to a deeper exploration of the nature of complex adaptive systems and the amazing possibilities that reside within such self-organizing systems for constructive change.
So, bottom line, we need to see the conflicts we care about not as simple "us-versus-them", "good-guys-versus-bad-guys" situations, but rather as what they are--complex adaptive systems. Once we see that, we can learn as much as we can about how the system is "put together," and how it works, (using graphical conflict mapping, for example) and then we can begin to experiment with inputs we can make into the system in the hopes of changing it in the way we would wish. If an input doesn't seem to work, wait awhile. Watch. It may bring about the desired change, just more slowly than we expect. Or it might not--it might actually lead to further problems. If so, figure out what went wrong, and try something else. Success is by no means certain, but it is much more probable if we understand the nature of the problem we are dealing with and respond accordingly, rather than simply continuing to escalate an escalated conflict further and try to "win" an unwinnable game.
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