It is intended to offer resources and explore ideas with the potential of purposefully directing the momentum needed for communities to create their own new community paradigms.
It seeks to help those interested in becoming active participants in the governance of their local communities rather than merely passive consumers of government service output. This blog seeks to assist individuals wanting to redefine their role in producing a more direct democratic form of governance by participating both in defining the political body and establishing the policies that will have an impact their community so that new paradigms for their community can be chosen rather than imposed.
Friday, May 30, 2014
Thursday, May 29, 2014
As mentioned in the previous post, a system is always of something. It may be biological, social, or computer based, all can be understood as systems even machines are systems, just usually not complex ones. We will find ourselves facing a challenge from a specific type of system, perhaps transportation or perhaps environmental. Each challenge will have a specific occurrence. The specifics of an environmental challenge in Florida will not be the same as those in North Dakota. The specifics of how such individual systems work, how the elements making up those systems actually interact has not really been delved into to any extent. How do you begin to understand the basic dynamic interactions of systems? The most fundamental means of doing so is building models of those systems.
A model is an illustration of the interrelationship between parts or elements of a system that explains how they are related and that can also help in understanding why. A model can be anything from a 3D computer simulation to a paper napkin drawing. So the idea then is to make models.
Is there then some tool that anyone could use to build and experiment with models to test out some of the general ideas of systems thinking and apply them to specific challenges? It would need to be relatively easy to use though capable of doing more complex actions as you learn. It should also be web-based and on the ‘cloud’ rather than be a stand alone desktop program. This would help in at least three ways. One, it would make it more available. Two, there could be a repository of different models and three, it could be possible to let people copy or clone models that they found interesting. Finally, in the best of all possible worlds it would be free.
There is good news, a little bad and more good news. First, there is such a program called Insight Maker or Insightmaker.com, which does everything listed above. The little bit of bad news is that this current course is only going to give you the bare basics, though it is a good start. The final good news is that they are planning a course focused on Insight Maker in September of 2014.
Insight Maker has already been introduced through the previous articles on this course and was the means of making the models used so far. It has also been featured in this blog prior to the course. However, because those earlier posts dealt with other issues they may not have been the best means of introducing Insight Maker.
Once again using a Kumu map, you start at the green circle and move along a path, first to qualitative models which include Rich Pictures and Causal Loop Diagrams and then quantitative models with a brief visit to Stock and Flow diagrams prior to reaching a point at which you are introduced to Your First Simulation and then finishing at the red colored end circle that summarizes the segment. In general terms, the segment seeks to cover the following concepts.
• Model. A simplification of reality intended to promote understanding
• Qualitative Models. Static models depicting the relationships between elements of the model. Rich Pictures and Causal Loop Diagrams are two examples of qualitative models.
• Quantitative Models. Dynamic models allow one to experience the implications of the relationships of the elements of the model over time.
◦ Testing every element added to a dynamic model will serve you well.
• Model Development. This tends to be a recursive learning process migrating toward understanding.
• Comments. While it may feel unnecessary, or even an unnatural act, adding comments which embrace your thoughts during the model development will serve you well in the future. You will be surprised how much you forget about the thoughts behind your model in a week, a month, or a year.
The nuts and bolts of the segment though are on using Insightmaker.com. Insight Maker was designed as a simulation environment though may be used to do multiple types of models. Which type is most appropriate depends on the situation to be addressed.
It is better to jump right into Insightmaker.com and play around with it. With some basic instruction, you can start making simple models and test them out. To be fair, I also have Beyond Connecting the Dots, the book written by Gene Bellinger, the instructor for the course and Scott Fortmann-Roe, the creator of Insight Maker. The course material does though give you the basics. You just have to throw yourself into doing some trial and learning. Based on the fundamental premise that we are creating models to get a greater and deeper understanding, the common concept of trial and error never applies, it is always what Gene Bellinger calls trial and learning. You are not going to break anything or cause any systems failure simply by making models with Insight Maker and it can develop that sought after deeper understanding that systems thinking calls for.
Now I am going to say something about modeling that, although it has the potential of driving away people who crave certainty, always needs to be kept in mind. It is a fundamental premise for experienced systems thinkers, pronounced by one of the field’s major thinkers.
All models are wrong but some models are useful - George Box .
The assigned work for this segment called for creating different models. A Rich Picture model and a Causal Loop Diagram in story format were made before. What had not been attempted so fare is a Stock and Flow diagram
Following the jumping in and swimming plan of action, the course’s Your First Simulation (IM-13312), which has basic model building blocks, was cloned then copies made (using command-select, command-c and command-v on a Mac) of the three examples provided, which were expanded upon creating Simulation Model Examples (Clone from Your First Simulation Model) then using those same building blocks, stocks, flow and variables to get a better understanding of how they worked.
Stocks represent the ‘stuff’ that can be measured or counted, the inventory of products or census of a population. Stock can also be increased or decreased but not instantaneously. In some cases it may change extremely quickly but this usually occurs over extended time. Flow is the means of increasing, by flowing in, and decreasing by flowing out from stock. Variables influence the rate at which flow occurs by varying the stock or the flow in some manner. Together, these can be constructed into a graphic mathematical formula that serves as the engine for the model. To get a better understanding of how the models (and modeling) were working, I also re-created a particular model's formulas in a spreadsheet format using Numbers.
With this knowledge, my first Stock and Flow diagram was finally finished. Well, completed but not finalized as I still have other ideas. There was a good deal of trial and learning involved, more than I expected, with numerous redesigns and a few restarts. There is the issue of not only making sure your model is actually modeling the real world circumstances that you are considering to the extent needed but also making sure that the internal workings of your model are also consistent with that endeavor. In early versions the external numbers looked good but a closer examination indicated that it was not calculating what I thought it was. I checked by putting the numbers into a spreadsheet to see if the presumed equations generated by the model could be regenerated there.
Below the model’s description are sliders that you can use to change the number of homes, businesses and other traffic. Pressing the ‘Run Simulation’ button at the top of the page shows the effects based on the numbers over a 20 year time period. My model ostensibly calculates road wear and tear on community roads due to increased traffic particularly through new development. What it actually considers is the relation between elements within the modeled system.
My model is wrong, remember George Box. It only examines a slice of the world, ignoring other aspects. Its knowledge of the world is not accurate and what it does examine is not realistically portrayed with any precision. I tried to make its limitations clear in the model. Hopefully though it could be useful, or be the basis for something, if only as a practice run, for something that could become useful.
In writing about the real world understanding mistakes made by Watson, the IBM computer that defeated the greatest champions of the television quiz show Jeopardy at their own game, to explain the difference between knowledge and understanding. Michael Strevens wrote:
“Watson and you both answer questions by seeing connections between things. But they are different kinds of connections. Watson picks up from things it reads that there is a correlation between a sphere’s rotating and a fixed point on its surface having a constantly changing view of the rest of the world. You grasp why this correlation exists, seeing the connection between the opacity of the Earth, light’s traveling in straight lines, and geometry of the sphere itself. For you the statistics are a byproduct of what really matters, the physical and causal relations between things and people and what they do and say. Grasping those relations is what understanding consists in. Watson lives in a world where there are no such relations: all it sees are statistics. It can predict a lot and so it can know a lot, but what it never grasps is why its predictions come true.”
Systems thinking and modeling can help you to understand why.
Saturday, May 17, 2014
Tuesday, May 6, 2014
This is the first time the course has been offered. It is closed but if all goes well I suspect it will be offered again. It is being guided by Gene Bellinger, who has been cited on these pages most recently in, “How Do I Make Use of this Systems Thinking Stuff?” in Creating New Community Paradigms”. The medium for presenting the lessons is Kumu, a web-based data visualization tool for tracking and visualizing relationships.
The intention is to write about what is taken out of the class and how it evolves my perspective. What it won’t do is to detail or repeat the teachings of the class. Others will have to take the class for themselves to understand how to walk the path. Many of these lessons can also be found in Beyond Connecting the Dots. The difference is that with the class lines up differently than the book in terms of presentation and the interaction with the class is more two-way.
Kumu lays out the course content, usually presented through YouTube videos or InsightMaker models, as points on a visual map which link together the twelve topics making up the course. This allows a visual overview of the entire course or any one of the segments making up the course. My plan is to serve more as a chronicler than as a cartographer as to how systems thinking could be integrated with new community paradigms. Though mind maps such as Kumu don’t really have a time component to them as one is free to start, proceed and jump to whatever path one chooses. The worth of the journey is dependent in part on what the creator provides and links together, and in part on what you put into it.
The first section does not begin with systems thinking in its own right. Instead, it asks you to shift your perspective of the world from how it is usually presented as a machine subject to being broken down into smaller pieces and therefore controllable with the right levers. It asks you to look at your world as an interrelated system or a series of systems. The emphasis, at this point, is not on whether the world is a single system or multiple systems, rather it is how we approach the nature of such a system.
Such an approach looks to the world and discerns that even before seeking the interconnections making up the world that some of its basic ‘elements’ have common characteristics. They are quantifiable or countable and can be increased or decreased over time. In aggregate, these elements make up complex systems such as communities and how they impact those communities in different ways can be modeled.
The class makes a point of the common forms of models based in large part on the nature of the elements making up the systems being studied. There are Three Types of Models (IM-8932), Rich Picture, Causal Loop Diagram and Stock and Flow that endeavor at different levels to mirror the essential reality of real world systems through Three Recurring Structures (IM-5138), Independent Growth, Reinforcing Exponential Growth and Balancing Goal Seeking that are ubiquitous within systems.
Whether it is a matter of funds in the city budget or the number of cars on the road, how that occurs can help determine if communities are worthwhile places to live or not. These elements can have the additional characteristic of being subject to increase or decrease on an exponential basis. Interest rates on loans can be exponential while revenue from the financed asset could be linear.
Finally, they can be considered to have optimal levels. Idealistically, city budgets endeavor to reach optimal levels of expenditures to fund the programs which are beneficial to the community. They fund road improvements to increase the capacity of the streets to allow an optimal number of vehicles (The community question is what is that optimal number?) These three properties can interact together in a variety of different way. Built roads in a community can be increased but not easily and not indefinitely. Traffic, particularly if it originates outside of the community, could increase exponentially overtaxing the community’s circulation system. The community could try to find some means of balancing these conflicting influences but its actions might feedback in unintended ways.
It is with these insights that we endeavor to understand the world. The potential to change how we understand the world arises because these insights caution us that we cannot stop at the superficially apparent aspects of the world and need to look deeper at the interconnections defining the nature of these properties. It encourages us to question our assumptions as to why traffic is increasing and not default to past knowledge that may no long apply. This allows for entirely new considerations such as perhaps a new factory has not only provided employment but also the financial ability and the need for private vehicles to get to work because there is inadequate public transportation.
What the real configuration of interrelationships is must be determined empirically. These depend in very large part on what configuration one seeks for the system or community. Not everyone in a community will be seeking the same configuration as some will seek far less traffic as it hinders their travel while others will seek more because it brings customers to their businesses. Each though could be negatively impacted if they attained what they were seeking to an excessive degree through the detrimental impact it would have on the other group. Too many vehicles would jam the streets turning people away to different routes and too few could result in the community’s downtown dying. Understanding how these all interrelate helps the community come up with viable strategies for finding a balance rather than continually doubling down on a pursuit of increasing growth.
Through this approach one, in collaboration with others, can devise a far more likely means of creating a future in which the strategies implemented serve to be of benefit rather than leading to unintended consequences making matters worse or create new problems. It allows one to navigate to such a future even with the challenges of a both complex and complicated world with cause and effect separated by both time and space. The building of a freeway along the edge of a community can impact roads within the community if commuters use those roads to bypass traffic jams or as means of ingress or egress. A new road might take traffic away from one business district to another but the impact might not be felt immediately until the stores started going vacant.
This newly acquired insight into the workings of the world allows one to then to acquire and apply the attained knowledge in a new way. More important is that this new way leads to further understanding and knowledge. This new methodology involves the creation of models which will be discussed in far greater detail as the course proceeds.
Two types of models had been attempted previously. The first, a Causal Loop Diagram model featured in the post, Better Deliberative and Participatory Democratic Community Based Governance through Systems Thinking. The second was a Rich Picture model that served as a pictorial back of the napkin explanation of the detrimental relationships resulting in troubling situations in which we find so many of our communities. The third, more recent, was a Causal Loop Diagram Complexity Assailing Our Communities an extension of one set of relationships set forth in the Rich Picture model. None of the models are viewed as being finalized. Instead, they are seen as means of inspiring further inquiry.
The course initiates an introduction and provides guidelines for model construction that ties into a very important concept related to the 'Essence of And'. This is not only a central concept but it is also a means of defending the utility of systems thinking. The rationale for why pursue systems thinking and take this class is addressed through the video, “Unleashing Understanding, the Essence of And”.
The class also offers additional resources through a link to the Model Thinking Course by Scott E. Page, which has been referenced previously on these pages in Systems Thinking as a disciplined process for Community Governance.
"More often than not it seems that models that people build are like Cathedrals. In the process of construction they employ a substantial amount of labor, material and staging as they work through the process. Once the Cathedral is completed all that was used to build it is removed and it remains as a structure for others to behold, though more often than not others just find them confusing because of the supporting developmental understanding is missing.
The thought that came to mind was to think of a model like a stage play. I can give the audience a sense of what the play is about so they are interested in coming to the play. Then once they arrive the play actually unfolds one act at a time and some of the actors are in multiple acts.
As such might it be advantageous to consider a model like a play where I provide the audience an overview of the model to develop interest, and then each loop in the model is presented as an act in the play with the elements of the loops being the actors, with relations between them, some of which appear in multiple loops? As such a person’s understanding of the model is developed in a piece-wise coherent manner which attempts to avoid overwhelming the audience.
It was a thought of the moment.”
This segment of the class offers three different ‘plays’ demonstrating different aspects of systems. The reality that since everything in the web of systems making up the world is connected that it is exceedingly difficult to have only one effect from any action Bird Feeder Dilemma (IM-8872). That the interaction of elements can feedback to their point of origination into a loop changing the nature of those interactions over time Moose and Wolves (IM-8590) and Sustaining the Forest Model (IM-8889). The course uses theses ‘plays’ as scaffolding for the other concepts raised in this segment, putting the participant in the role or protagonist and narrator.
It is realized that this is a hodgepodge of information, overloaded because it comes from so many different levels and different directions, introducing unfamiliar concepts. How all of this is related is endeavored to be illustrated with the model, Elements, Relationships, Models, and Plays. Hopefully, it will begin to be untangled and be more sensible as the course progresses.
All of this is seen as creating a Web of Wonder, serving as the port from which the next part of the journey will be taken, an Overview of System Thinking.
“We live in a world much like a giant spider web, where everything is connected to everything else. When something changes in one part of the web it ripples though the entire web. We tend to live in the moment, not realizing how our actions ripple over time through distant parts of the web. When we don't understand the web, things around us seem extremely complicated, confusing, and overwhelming. We feel caught in the web. What we need is a web of understanding for this web of extended interactions.
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