The COVID Plenary Recording is now available!This public plenary titled “Societal Containment of COVID-19” was chaired by Peter Hovmand. The presented work includes:Modeling the Transmission Dynamics of SARS-CoV-2 and the Effects of Intervention Timing on COVID-19Incidence by Jeffrey ShamanSimulation-based Estimation of the Early Spread of COVID-19 in Iran: Actual versus Confirmed Cases by Navid Ghaffarzadegan and Hazhir RahmandadHybrid Modeling with System Dynamics to Contain COVID-19 by Nathaniel OsgoodThis session was part of the Health Thread, sponsored by Homer Consulting.
This recording is now available on our Covid-19 resources page. You are welcome to watch it and avail yourselves of other collected System Dynamics works relevant to understanding and containing this pandemicWATCH THE SESSION
We will collect resources here produced by SDS members and others that provide a systems view on the COVID-19 pandemic. Please email office@systemdynamics.org to suggest additions. Disclaimer: Much of the work below has not been subjected to peer review. It is work-in-progress and may be subject to errors and omissions. We share this work in the spirit of openness and collaboration and learning and encourage you to review it with a mind open to growth and a willingness to offer constructive feedback to improve our collective knowledge.
Images are treacherous, or so René Magritte would have us believe. The surrealist painter commonly played with the themes of perception, representation, and reality. In his famous work entitled The Treachery of Images, he depicted a drawing of a pipe with the caption, Ceci n’est pas une pipe (“This is not a pipe”). Of the painting he said, “if I had written on my picture “This is a pipe”, I’d have been lying!”
The world of systems mapping is filled with this paradox. While a system map is often a useful representation of a context of phenomena, it is always fundamentally incomplete.
If you were to write on a map “This is the system,” you’d be lying.
For more experienced systems practitioners, this point may seem obvious, but it is easy to confuse a map with the system it depicts. This confusion arises because of a logical fallacy called reification or the fallacy of misplaced completeness. It arises when an abstraction – a system map or model – is treated as if it were the actual system under examination.
Understanding reification
There are several drivers of reification in the practice of systems mapping, each of which layers upon the others to limit our ability to distinguish the map from the system itself. Many of these traits are baked into our cognition but recognising them is the first step in strengthening our ability critically reflect on our system maps and their role in driving transformative change.
1. Premature closure and confirmation bias
Research has shown that people think about a situation only to the extent it is necessary to make sense – perhaps superficial sense – of it. When sense is achieved, people often feel no need to continue or to further iterate their understanding of a context or situation. In medicine this is referred to as premature closure or the tendency to stop too early in a diagnostic process, accepting a diagnosis before gathering all the necessary information or exploring all the important alternatives.
Systems mapping is often undertaken with limited resources, on tight-deadlines, and only ever captures the dynamics of the system at a point in time. But even when a system map is explicitly couched as illustrative or provisional, the temptation is to use it for diagnosis and to drive decisions about what could or should be done to change the system.
If this view of how system maps are used is correct, confirmation bias likely compounds the issue. Confirmation bias is the tendency of people to favour information that confirms or strengthens their beliefs or values and is difficult to dislodge once affirmed. Having arrived at a conclusion about the structure of the system, however prematurely, our brains are predisposed to seek evidence that supports our existing understanding and interpret new information in a way that aligns with our existing view.
Put simply, confirmation bias makes us overconfident that our system maps are an accurate depiction of reality, and to discount evidence that they are not.
2. Pattern recognition, Pareidolia and Type I errors
Our brains are pattern-detection machines that connect the dots, making it possible to uncover meaningful relationships among the barrage of sensory input we face. Pattern-recognition is crucial for human decision-making and survival, but we also make mistakes (i.e. seeing a pattern where none really exists) all the time. These mistakes are what statisticians would call a Type I error, also called a false positive.
Pareidolia, for example, is a form of pattern recognition involving the perception of images or sounds in random stimuli, such as seeing shapes in clouds, or seeing faces in inanimate objects or abstract patterns. Pareidolia happens when you convince yourself, or someone tries to convince you, that some data reveal a significant pattern when really the data are random or meaningless.
Some false positives, like seeing Jesus in a piece of toast, are largely harmless. Others, like believing a system map to be a high-fidelity capture of the system under examination are more problematic, particularly given our vulnerability to confirmation bias.
Take the human brain, for example. At one level, our maps of the brain are exceptionally accurate. We know what parts are where, how large they are, and what their purpose is. But in terms of really understanding all the functional relationships and the ways that the regions of the brain are communicating with each other, our understanding is limited. We don’t know whether regions are communicating through photonic or acoustic pathways, for example, but scientists infer, identify, and map patterns of communication regardless.
The mistake is believing a map to be a complete or accurate depiction of reality, which is why researchers typically conduct multiple studies to examine their research questions and continue to iterate different maps at different levels of detail and granularity. Having multiple maps and recognising that every map is incomplete helps avoid Type I errors and the reification of one view of a system over others.
3. System maps as silver bullets
This raises yet another paradox: if having multiple maps helps us build a more accurate picture of the actual situation or phenomenon under investigation, why do so many systems projects produce a single map?
There are countless examples. From the Foresight Obesity Map to single outputs of group model building exercises the message is the same: you only need one map to understand the dynamics of this system. This message plays into our cognitive biases and contributes to reification of certain view of the world.
This drive towards one map per project or problemis possibly driven by our desire for dominant monocausal explanations. Humans are energy-minimising cognitive systems, and probably for good evolutionary reasons. Monocausal explanations require less brain power to execute than complex explanations, even though that biases us towards solutions that look or feel as if they are single silver bullet.
We don’t recognise this bias in the practice of systems mapping, but producing one map for a particular system is the same prescribing one treatment for a particular illness.
In both cases, there is no silver bullet. Multicausal explanations are necessary if we are going to properly engage with and map complex systems, even if using them is not our default cognitive setting.
Overcoming our biases
Almost every moment throughout the day, we are making decisions. However, most of us are unaware of the thoughts, buried beliefs, prejudices and biases that influence our decisions, and therefore, most people are unconscious of how they impact our decisions.
Systems practitioners are probably better than most at being aware of the more common cognitive biases, but ultimately, we are all human and our brains are very good at playing tricks on us. The world of systems mapping is not immune to the challenges of confirmation bias, nor to our desire to understand the world through monocausal goggles.
While many biases are universal, the way they impact different areas of practice is divergent and unpredictable ways. Identifying these biases and their impact on how we map the systems around us will help to bring more consciousness and humility into the work of systems practice.
A new type of educational paradigm for a complex world
Complexity University is part of 10-in-10; a cross between a foundation, a marketplace and a university. It has been designed on the basis of two decades of disciplined practice tackling complex challenges.
We see ourselves as a new breed of organisation.
Rather than being daunted by complexity, we are at home in complex situations, seeing them as opportunities for changing systems no longer fit for purpose.
The paradigm underpinning our work, developed by reflecting on decades of practice, is relentlessly pragmatic. We are interested in effectively tackling society’s most complex challenge in practice.
Modernity and postmodernity have given rise to a particularly difficult and novel snarl of problems. While we can look at ancient lifestyles and cosmologies as models of sustainable living when compared to our own, we cannot necessarily turn to them to figure out what to do about the situation we find ourselves in.
The long march of ideologies that characterised the twentieth century is over. This news has yet to filter through to the last desperate holdouts, still clinging to a fiction that one ideology might win over another. Ideological responses, that is, responses espousing normative choices regardless of context are no longer fit for purpose.
Our fight then, is with the high modernist paradigm of strategic planning, with its associated “best practices,” and cultures of response. We believe that this paradigm is a zombie paradigm, dead but still lurching around biting and infecting people.
Here are a set of Rules of Thumb, Practices and Orthodoxies underpinning our work. Click each to learn more.
Anokhin Petr Kuzmich PRINCIPAL ISSUES OF THE GENERAL THEORY OF FUNCTIONAL SYSTEMS 1973
FIRST PART-
GENERAL BACKGROUND It is difficult to find a moment in the history of civilization that could be said that it was then that the idea of integrity, of the unity of the world, arose. Probably, already at the first attempt to understand the world, a thinking person was faced with an amazing harmony between the whole, the “universe”, and separate details, parts.
In essence, this problem is relevant not only for biologists, but also for physicists, economists, and other specialists. It is enough to follow the extremely interesting discussion between Niels Bohr and Albert Einstein to understand what a burning problem is the development of these new principles of a holistic approach to the object under study. In this discussion, two approaches to the question of how to ensure the level of a specific whole in scientific research, for example, an organism, collided, and at the same time not lose the huge advantages of the level of the finest analysis.
As you know, Niels Bohr expressed his point of view in a concept known as the “principle of complementarity.” According to this concept, a whole and holistic approach should give the researcher the opportunity to find additional characteristics of the studied object, more or less expressing the specific features of the whole. He believes that the observation conditions, i.e. the perspective in which we observe the object under study can change in the course of research and this provides additional support points for a comprehensive knowledge of the object. At its core, this approach, expanding the possibilities of studying a holistic object, puts the researcher in the position of an observer who determines how the observed phenomena develop.
Albert Einstein, on the contrary, sought to find an approach that would replace Bohr’s phenomenological approach with a dynamic approach that allows one to penetrate into the nature of internal interaction in some complex integral phenomenon.
While with the help of the phenomenological approach to the whole process it is possible to determine how the objects under study are arranged, Enshtein’s approach is to present the empirically found regularity as a logical necessity.
It is now important for us to emphasize that the discussion between the two greatest scientists of our time takes as something definite and obligatory the search for the transitional principle of a holistic approach to phenomena. The point is only in what form this principle could be most effective for a specific research work, since a holistic approach in general, while remaining a researcher’s dream, did not provide any constructive solutions at the same time for formulating the tasks of everyday research. “Whole” and analytical experimentation still coexisted in two parallel planes, without enriching each other.
The emergence of a systems approach gave scientists some hope that, finally, the “whole” from a diffuse and non-constructive form will take on a clear outline of an operational research principle. However, before analyzing the reasons why this principle was not found, we want to give a brief assessment of the development of a systems approach in various physiological schools.
The term “system” has a very ancient origin, and there is hardly any scientific direction that did not use it. It is enough to recall the “circulatory system”, “digestive system”, etc., which are still accepted by some researchers as expressing a systematic approach. For the most part, the term “system” is used when it is about something brought together, ordered, organized, but, as a rule, the criterion by which the components are assembled, ordered, organized is not mentioned.
These common disadvantages are natural. We must not forget that the consistent application of the systemic principle to phenomena of various classes (organism, machines, society) is not a simple change of terminology, a rearrangement of only the order of research methods. The systematic approach to research is a direct consequence of the change in the theoretical approach to understanding the objects under study, i.e. to some extent, a consequence of a change in the very form of thinking of the experimenter. Naturally, such a process cannot be instantaneous.
As will be shown below, the most characteristic feature of the systems approach is that in research work there cannot be an analytical study of some partial object without an accurate identification of this particular in a large system. Thus, from a strategic and practical point of view, the researcher should first of all have a specific concept of the system, which should satisfy the basic requirements of the very concept of the system, and only then formulate the point of the system that is subject to specific research.
In the field of physiological research, I.P. Pavlov was perhaps the first to use the expression “system” for some special cases of his experimental work. It is primarily about the formation of a dynamic stereotype. As you know, this system is created by the fact that the stereotyped order of the same conditioned stimuli is repeated from day to day. As a result of a long training session, this order of stimuli, detected by the amount of saliva specific for a given stimulus, manifests itself even when the same stimulus is used.
Direct electroencephalographic studies of the brain at the time of creating such a dynamic stereotype, carried out in our laboratory by A.D. Semenenko, showed very interesting properties of the brain as a whole. Thus, for example, it turned out that to each forthcoming stimulus in the case of a strengthened dynamic stereotype, the brain automatically, i.e. only on the basis of previous training and regardless of a real external stimulus, prepares a state that qualitatively reflects exactly the stimulus that was used in this place many times in previous trainings. Of course, the stereotypical states of the brain created in this way, reflecting the complex of conditioned stimuli of a given experimental day, are far from their physiological sense from that systematic approach, which is booming recently. Nevertheless, these experiments showed that the brain, on the basis of the acquired experience, can create some integral states that combine the stimuli of a whole experimental day and open up independently of the actual experimental situation.
continues in source:
Anokhin Petr Kuzmich PRINCIPAL ISSUES OF THE GENERAL THEORY OF FUNCTIONAL SYSTEMS 1973
Stafford Beer achieved the hardest of all pedagogic tasks: he changed the way people think. His protean influence stretches from generations of inspired students, through Salvador Allende’s Chile, to the collective brain of openDemocracy. A huge, life-affirming figure has passed, but his work will long survive, says our international editor.
Stafford Beer, scientist, poet, painter, founder of Management Cybernetics and world leader in operational research, who has died at the age of 75, was much larger than life. The handsome photograph that one accompanied the Guardian obituary is entitled ‘Subversive Showman’. If he fitted neatly into neither the British establishment, nor the academic nor indeed the business world, it was partly because of the sheer impact of the man – but also because of what he had to say.
His self-appointed task was to bring an often unwelcome message to whoever would listen, including the twenty-two governments who hired him as a consultant over the years, about the need for ‘effective organisation’ in companies, social services, great institutions, whole countries, and international communities, if they were not to be left behind by technological advance, threats to economic survival, and loss of faith in established authority – by, in short, complexity and change.
Some people ‘got it’: they joined the band of friends and followers from around the world, and were rewarded by Stafford’s patient and loyal interest in their own efforts to apply what they had learnt. They were inspired by his various favourite dicta, such as ‘Don’t bite my finger: look where it’s pointing’, or ‘You accuse me of using big words that you find hard to understand. But you need big words for big ideas. And you should find it hard to understand.’
Many more, who were nevertheless profoundly influenced by his work, found these admonitions unfashionable and irritating, and his many books unreadable. They often failed to see the indefatigable energy which he devoted to trying to make himself better understood: Stafford’s ideas in Latin, in thirteen languages, in poetry, in a summary for business schools, as applied to car engines, hospitals, prisoners or stars.
There are 12 design principles in permaculture. I think they can be applied to daily life, work and play which will allow us to live happier and healthier, to work more effectively and to create a more sustainable world.
Here are the 12 principles:
Observe and interact.
Catch and store energy.
Obtain a yield.
Apply self-regulation and accept feedback.
Use and value renewable resources and services.
Produce no waste.
Design from patterns to details.
Integrate rather than segregate.
Use small and slow solutions.
Use and value diversity.
Use edges and value the marginal.
Creatively use and respond to change.
How can we use these principles to guide our life or our work?
COVID‐19 – how a pandemic reveals that everything is connected to everything else
Joachim P. Sturmberg MBBS, MFM, PhD, DORACOG, FRACGP Carmel M. Martin MBBS, MSc, PhD, MRCGP, FRACGP, FAFPHM
First published: 06 July 2020 https://doi.org/10.1111/jep.13419
Shannon, father of information theory + titan of 20th c. science combined rigor, playfulness + insatiable curiosity (to?) invent a powerful but simple formalism linking thermodynamic entropy to information content. Jaynes' 1957 paper on that connection https://t.co/I23qjDlXOPpic.twitter.com/FuLbRZlZBQ
I’m a systems engineer at heart but also passionate about design. Systems thinking has grown on me over many years of practice and research and I now do all that I can to promote it.
I’m often asked to define a ‘systems approach’ and where to get started with systems thinking.
Forget the textbooks. Don’t worry too much about the theory. I’m not saying these things aren’t valuable. I’m simply saying that they can wait.
This website is deeply grounded in the work of Humberto Maturana, with further elements from the work of others in Matriztica and elsewhere, and of course my own ideas. I would like to be clear that what I have presented, and indeed all that I can present to you, is only what I know, I have to claim responsibility for that. Further the world I live and understand has arisen through all of the many encounters I have experienced. Over my lifetime I have encountered many people, some as individuals, others known only through some of their works. I can and do thank them all for their intentional or unintentional contribution to me. Hence this website, although based on the biological, epistemological, ethical and daily life-based understanding that I have gained from Maturana’s deep work, I will be also present many other sources throughout this site.
Seized by Agreement, Swamped by Understandingedited by L. Fell, D. Russell & A.StewartA collection of papers to celebrate the visit to Australia in August 1994 by Humberto MaturanaISBN 0-646-20084-4 Hawkesbury Printing, University of Western Sydney.This book is now out of print, though it is available in major Australian libraries.
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