[if anyone can explain this to me, I’d be grateful 🙂 ]
Two Lyapunov Functions for Flexible Organizations – Guiod Fioretti May 2008
Abstract
Source: Two Lyapunov Functions for Flexible Organizations – Munich Personal RePEc Archive
pdf:
Author Archives: antlerboy - Benjamin P Taylor
Strategic Analytics — NECSI: Executive course, Nov 18-19 2019 Cambridge (our fair city), MA, USA
STRATEGIC ANALYTICS
This two day course prepares leaders to think, anticipate, and respond strategically in a complex environment utilizing the latest advances and tools from the field of complexity science.
November 18-19, 2019
$2,500 corporate
$1,500 government/NGO
For two intense days this course prepares leaders to think, anticipate, and respond strategically in a complex environment. Complexity science allows us to accurately predict real world events and describe unintended consequences, dynamics, and emergent behaviors in real world social systems. Learn how to harness this framework to extract the most important information from data for advanced decision making and innovation in organizations.
The course will cover:
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Identifying the leverage points to manage instability and risk
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Strategies for framing actionable responses to achieve desired outcomes
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Prediction at the limits of uncertainty
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Understanding the implications of rapid global social and political change
More in source: Strategic Analytics — NECSI: Executive
Gregory Bateson changed the way we think about changing ourselves | Aeon Essays
Source: Gregory Bateson changed the way we think about changing ourselves | Aeon Essays
Impossible choices
Learning from his family, his animals and his work with tribal people, Gregory Bateson saw the creative potential of paradox
Gregory and Nora Bateson with pet gibbon, Hawaii, 1970. Photo courtesy the Bateson Idea Group
There are times when a dilemma that seems like agony in adolescence can not only provide the basis for a prestigious career, but also lead to a profound shift in the world of ideas. Thus it is that the predicament faced by the 17-year-old Gregory Bateson, following his brother’s suicide in 1922, turns out to be extremely relevant to us today, for it eventually led him to revolutionise the study of anthropology, bring communication theory to psychoanalysis (thus undermining the Freudian model), invent the concept of the ‘double bind’, and make one of the first coherent, scientifically and philosophically argued pleas for a holistic approach to the world’s environmental crisis. Seeking to condense Bateson’s work into one core concept, one can say that, above all, he proposed a paradigm shift in the way we think of ourselves as purposeful, decisionmaking actors in the world.
Born in 1904, Gregory was named after Gregor Mendel, the monk and botanist who opened the way to an understanding of how hereditary traits are passed on from one generation to the next. Gregory’s father, William Bateson, had championed Mendel’s theories in England, involving himself in years of violent polemics as to the nature of the evolutionary process, and coining the word ‘genetics’ in the process.
So this was a family of scientists. William’s wife Beatrice worked with him on his research, and his father had been an academic. Gregory’s eldest brother John was studying biology at the University of Cambridge when he was conscripted to fight in the First World War, and killed in 1918. His other brother Martin also went to Cambridge to study zoology. Gregory, some five years younger, was expected to do the same, like his namesake; high achievement, in the Bateson family, was the only justification for living.
Yet his father insisted that the greatest achievement of all was art. Art was sublime, science a poor second. His father collected art, in particular the work of the visionary William Blake, whose original watercolour Satan Exulting Over Eve (1795) hung on the wall in the sitting room. And he associated the special genius of the artist with the idea of the genetic leap, the kind of evolutionary change that can take the race to a higher level of development. It’s just that he did not believe his family could aim so high.
Given these conflicting messages – you must achieve, but you are not capable of the highest achievement – it was probably inevitable that one of the three sons would seek to be an artist. Belligerent and exhibitionist like his father, furious too with the British establishment that had supported the war that killed his brother, Martin gave up science for poetry and the theatre. His father opposed him. The two argued and fought. Eventually, infatuated with a young woman who did not return his affection, Martin chose his dead brother’s birthday to go to the statue of Eros in Piccadilly Circus and shoot himself in the head. He was 22.
Gregory, hitherto considered the dummy of the family, now found himself saddled with all his parents’ considerable expectations. The very day after Martin’s suicide, his father wrote to the boy in boarding school to remind him that only ‘great work’ makes life worthwhile, but, once again, that ‘art is scarcely in the reach of people like ourselves’. Martin’s death proved this. ‘Fix your mind on some impersonal definite interest,’ his mother told him in a separate letter.
Gregory was about to go to university: Cambridge, of course. ‘I was left holding a sort of bag,’ he later reflected, ‘protecting these people as if they were made of glass.’ His parents insisted he study zoology; they seemed frightened of anything wayward, psychological, unstable. Yet for Bateson the only worthy object of study appeared to be human behaviour, the kind of complex circumstances – the war, British academia, his family background – that had created the drama he was living through. What he would eventually do was to use the tools of observation and analysis that his father taught him, the zoologist’s attention to patterning and morphology, to bring a fresh approach to the study of behaviour in groups, and above all how individuals communicate and relate in groups. Rereading his two great works, Naven(1936) and Steps to an Ecology of Mind (1972), it is evident that his influence in various fields has been enormous; also, that the message he eventually formulated through the 1960s and ’70s remains as urgent as ever.
Continues in source: Gregory Bateson changed the way we think about changing ourselves | Aeon Essays
The Chemical Basis of Morphogenesis – Alan Turing (1952)
Why isn’t Alan Turing more central in systems thinking/cybernetics?
Wikipedia article below and:
pdf –
slides about Turing – http://dosequis.colorado.edu/Courses/MethodsLogic/Docs/Turing.pdf
Turing’s Theory of Morphogenesis: Where We Started, Where We Are and Where We Want to Go – Thomas E. Woolley, Ruth E. Baker, and Philip K. Main – https://people.maths.ox.ac.uk/maini/PKM%20publications/428.pdf
photos of the original paper – http://www.turingarchive.org/viewer/?id=476&title=2
Source: The Chemical Basis of Morphogenesis – Wikipedia
The Chemical Basis of Morphogenesis
Turing’s paper explained how natural patterns such as stripes, spots and spirals, like those of the giant pufferfish, may arise naturally.
“The Chemical Basis of Morphogenesis” is an article written by the English mathematician Alan Turing in 1952 describing the way in which natural patterns such as stripes, spots and spirals may arise naturally out of a homogeneous, uniform state.[1] The theory, which can be called a reaction–diffusion theory of morphogenesis, has served as a basic model in theoretical biology.[2]
Reaction–diffusion systems
Reaction–diffusion systems have attracted much interest as a prototype model for pattern formation. Patterns such as fronts, spirals, targets, hexagons, stripes and dissipative solitons are found in various types of reaction-diffusion systems in spite of large discrepancies e.g. in the local reaction terms. Such patterns have been dubbed “Turing patterns“.[3]
Reaction–diffusion processes form one class of explanation for the embryonic development of animal coats and skin pigmentation.[4][5] Another reason for the interest in reaction-diffusion systems is that although they represent nonlinear partial differential equations, there are often possibilities for an analytical treatment.[6][7][8]
About us – Centuri Living Systems
I found another systems institute!
More in source: About us – Centuri Living Systems
Presentation
The Turing Centre for Living Systems (CENTURI) is an interdisciplinary project located in Marseille (France).
CENTURI aims at developing an integrated interdisciplinary community, to decipher the complexity of biological systemsthrough the understanding of how biological function emerges from the organization and dynamics of living systems.
The project federates 15 teaching and research institutes in biology, physics, mathematics, computer science, engineering and focuses on Research, Education and Engineering, 3 missions that hold interdisciplinary as their core principle.
The research and training programmes implemented under the auspices of CENTURI will foster new collaborations, will transform practices, will attract new talents and thereby contribute to making the Luminy campus a leading site for the interdisciplinary study of biological systems.
Governance
The Turing Centre is under the scientific direction of Pr. Thomas Lecuit, Research Director (IBDM). Five committees provide the executive director with expertise and advice on the distribution of the collaborative means and management of the whole project.
Why CENTURI ?
The name “CENTURI” has been chosen to the honor of Alan Turing, famous mathematician and computer scientist, but also pioneer in theoretical biology.
In 1952, he published a seminal paper entitled “The Chemical Basis of Morphogenesis”, a landmark in theoretical biology. It triggered a whole new field of mathematical enquiry into pattern formation, deciphering reaction-diffusion mechanisms and their consequences in dynamic living systems.
CENTURI is laureate of the National call ”Instituts Convergences” of the French State in the context of the ”Investments for the Future” programme (2nd PIA). The project will recruit more than 100 people (researchers, engineers, PhD students, Post-docs) over 9 years with a budget of € 20 million co-funded by the French National Research Agency and the A*MIDEX Foundation.
Embodied robots driven by self-organized environmental feedback
Which kind of complex behavior may arise from self-organizing principles? We investigate this question for the case of snake-like robots composed of passively coupled segments, with every segment containing two wheels actuated separately by a single neuron. The robot is self-organized both on the level of the individual wheels and with respect to inter-wheel coordination, which arises exclusively from the mechanical coupling of the individual wheels and segments. For the individual wheel, the generating principle proposed results in locomotive states that correspond to self-organized limit cycles of the sensorimotor loop. Our robot interacts with the environment by monitoring the state of its actuators, that is, via propriosensation. External sensors are absent. In a structured environment the robot shows complex emergent behavior that includes pushing movable blocks around, reversing direction when hitting a wall, and turning when climbing a slope. On flat grounds the robot wiggles in a snake-like manner, when…
View original post 56 more words
A Brief History of Systems Science, Chaos and Complexity – Daniel Christian Wahl
Source: A Brief History of Systems Science, Chaos and Complexity
A Brief History of Systems Science, Chaos and Complexity
Jul 8 · 6 min read
Since the beginning in the 1950s, when people like Ludwig von Bertalanffy and Kenneth Boulding developed the field of ‘General Systems Theory’ and Norbert Wiener and Jay Forrester developed the field of ‘Cybernetics’, there have been many attempts to break free from the reductionist paradigm and develop a more holistic and systemic understanding of the complexity of the world we live in.
Early systems thinkers were still ultimately aiming to improve their ability to better predict and control the system in question. The introduction of insights from chaos theory and non-liner mathematics into systems science sparked the development of complexity theory.
Interconnectedness, unpredictability, and uncontrolability are key characteristics of all complex dynamic systems. In dealing with complexity rather than mechanisms, the aim of science shifts from improving our ability to predict and control to aiming to better understand the dynamics and relationships of the systems we participate in so that our participation can be more appropriate.
“Complexity theory is becoming a science that recognizes and celebrates the creativity of nature. Now that’s pretty extraordinary, because it opens the door to a new way of seeing the world, recognizing that these complex dynamic systems are sensitive to initial conditions and have emergent properties. We have to learn to walk carefully in relation to these complex systems on which the quality of our lives depends, from microbial ecosystems to the biosphere, because we influence them although we cannot control them. This knowledge is new to our western scientific mentality…”.
— Brian Goodwin (et al., 2001, p.27).
The sciences of complexity are a variety of process-oriented areas of research exploring non-linear dynamics within complex systems. The simplest definition for a complex system is any system with more than three interacting variables. Complexity is thus a common feature of the world we inhabit.
When we speak about chaos theory it is important to understand that chaos does not refer to a state of absolutely incoherent disorder, rather “the scientific term chaos refers to an underlying interconnectedness that exists in apparently random events.” Briggs and Peat explain: “Chaos science focuses on hidden patterns, nuance, the sensitivity of things, and the rules for how the unpredictable leads to the new”(Briggs & Peat, 1999, p.2).
Chaos theory provides a radically different framework for studying complex dynamics. It highlights the limitations that are inherent in a reductionistic and mechanistic — linear cause and effect based — analysis of complex systems.
“Chaos theory teaches us that we are always a part of the problem and that particular tension and dislocation always unfold from the entire system rather than from some defective “part.” Envisioning an issue as a purely mechanical problem to be solved may bring temporary relief of symptoms, but chaos suggests that in the long run it could be more effective to look at the overall context in which a particular problems manifest itself.”
— Briggs & Peat (1999, pp.160–161)
In Seven Life Lessons of CHAOS, John Briggs and F. David Peat unfold seven lessons for embracing some of the deeper insights of chaos theory in our daily lives:
- Be Creative: engage with chaos to find imaginative new solutions and live more dynamically.
- Use Butterfly Power: let chaos grow local efforts into global results
- Go with the Flow: use chaos to work collectively with others
- Explore What’s Between: discover life’s rich subtleties and avoid the traps of stereotypes
- See the Art of the World: appreciate the beauty of life’s chaos
- Live Within Time: utilize time’s hidden depths
- Rejoin the Whole: realize our fractal connectedness to each other and the world.
In my 2006 PhD thesis I wrote a chapter on ‘Understanding Complexity: A Prerequisite for Sustainable Design’. The work seems to be gaining in significance and interest with the years. I am grateful that back then the lack of post-doctoral funding for the kind of trans-disciplinary work I was doing on ‘Design for Human and Planetary Health’ invited me to leave mainstream academia and work in the fruitful and fertile intersections of the disciplines and the sectors. It has helped me hone my neo-generalist skills in education, facilitation, whole systems design, consultancy, research, communication and weaving complex alliances and partnerships for transformative innovation and change.
The for me most significant insights I gained from systems science, chaos and complexity are summarized in these articles:
Facing complexity means befriending uncertainty and ambiguity
May God us keep from single vision and Newton’s Sleep! — William Blake (1802)
medium.com
Why do we need to think and act more systemically?
The power and majesty of nature in all its aspects is lost on one who contemplates it merely in the detail of its parts…
medium.com
Donella Meadows recommendations for how to dance with and intervene in systems
Donella H.Meadows was one of the co-authors of the 1972 Club of Rome Report on Limits to Growth which contributed to…
hackernoon.com
Avoiding extinction: participation in the nested complexity of life
Designing for positive emergence and planetary health?
hackernoon.com
In preparation for a recent keynote I gave at the 6th International Conference of Reporting 3.0 I summarised some of the lessons I learned in my by now 20 year exploration of how to embrace the paradox of emergence and design. On the one hand I believe it is vital to accepts uncertainty, not-knowing, and unpredictability fully to the point of deep humility. On the other hand, I also believe that we need to choose to act from the conviction that we can design for positive emergence in complex systems even if it is not an exact science and we cannot know with certainty how our efforts will turn out to affect transformative change.
How do we design for positive emergence in complex dynamic systems?
I believe we can live partially into the answer to this questions by charting pathways based on constant feedback generated by asking ourselves the following guiding questions. They might inform a deeper understanding of how to participate appropriately in these complex systems:
Who are the participants in the systems and what is meaningful to them?
Who is connected to whom & what are the qualities of their connections?
What information flows in the system & what is the quality of the information?
Which actors/agents/participants need to be engaged more/better?
What kind of qualitative and quantitative information needs to flow between participants?
What connections in the system need to be woven and nurtured?
Are we paying enough attention to context, relationships, patterns, qualities, uniqueness of place and health/wholeness?
…
This is not a complete nor definitive list, simply reflections on the way. Asking such questions can — I believe — contribute to the emergence of diverse regenerative cultures carefully adapted to the bio-cultural uniqueness of place. It can do so everywhere, but differently and appropriately.
If you like the article, please clap AND remember that you can clap up to 50 times if you like it a lot ;-)!
Daniel Christian Wahl — Catalyzing transformative innovation in the face of converging crises, advising on regenerative whole systems design, regenerative leadership, and education for regenerative development and bioregional regeneration.
Author of the internationally acclaimed book Designing Regenerative Cultures
Mega resources on cybernetics from Monoskop – including loads of pdf books
Wiki for Collaborative Studies of Arts, Media and Humanities
Cybernetics
A bibliographical genealogy of cybernetics in the United States, France, Soviet Union, and Germany in the 1940s and 1950s, followed by a selected bibliography on its impact across the sciences.
Source: Cybernetics – Monoskop
Another example – Cybernetic Volume 1, No. 1, Summer-Fall 1985
Click to access Cybernetic_Vol_1_No_1_1985.pdf
Books books books
(click ‘previous entries’)
Digital library of arts and humanities
Source: Cybernetics — Monoskop Log
The Recurring Case of ‘Recursion’: a pattern for making sense of the world | Ideas on CBC Radio, 20 June 2019
Go to link for the podcast!
Source: The Recurring Case of ‘Recursion’: a pattern for making sense of the world | CBC Radio
The Recurring Case of ‘Recursion’: a pattern for making sense of the world
People are fascinated to see the same thing on multiple levels, says author
It runs across cultures, through science, mathematics and art. It’s as common as the branches on a tree or the layers of a Russian doll — but it’s also vital to the way humans think and communicate: it’s ‘recursion’, or what some scientists call ‘self-similarity.’
“It’s important because some people think it defines our species,” says Michael Corballis, of the University of Auckland.
“One has to be a little bit in awe of how it evolved,” Corballis adds.
He sees the recursive process as key to our journey from simple organisms to complex creatures with infinite possible thoughts.
Recursion involves nesting a structure within another structure, or embedding one sequence inside another, whether it’s a sequence of words, events, or physical objects.
It’s one way to describe how almost any type of progress or evolution occurs.
“You start with a primitive creature not much more than a molecule in a mud swamp… and you’ve invented this extraordinarily complicated organism that’s capable of bringing the world into its own head and manipulating it.”
Corballis argues the amazing results of recursion — and the difficulty understanding how it works — leads some people to attribute our existence to a deity.
Beneficent spiral
Research at Newcastle University points to a possible source for a particular recursive ability in the human mind: our skill at conceiving of the minds of others.
“What we suggest is that the hemispheres of the brain, as they become very different from one another in function, and take on different jobs … in a sense, we get the hemispheres acting as parallel mirrors,” says Rachael Bailes, a cognitive scientist who studies evolutionary linguistics.
“If my left hemisphere can represent my right hemisphere, it can also represent yours,” Bailes adds. “That’s when things take off in this beneficent spiral of representing others.”
Ideas
Recursion also shows up in how we talk: Rachel Bailes
00:00 01:06
Cognitive scientist Rachael Bailes points out how a simple desire to refer to a nearby laptop could prompt complex, recursive descriptions. 1:06
Bailes suggests the prompt for this development in our evolution might be tool use, which led to humans becoming more right-handed or left-handed, unlike other primates.
Recursive predictability
Geoffrey West is a theoretical physicist and the author of Scale: the Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies. He believes that recursion is ubiquitous across natural and human society.
He points out how details such as the length of a creature’s aorta, the number of offspring it produces, and its lifespan — and many other aspects of its internal structure — follow a set of rules with predictable results.
“Despite the fact that the whale lives in the ocean and a giraffe has a long neck and mice scurry around… they are [to a great extent] scaled versions of one another,” says West.
He explains that the networks on which living creatures are based all need to solve the same problems of filling space and using energy efficiently.
“The structure that most reflects that is in fact this recursive, self-similar structure,” West says. “It’s no accident that almost all the networks that sustain life have this self-similar property.”
Source of delight
Aside from its importance in biology, art, music, computing, and more, recursion is also important as a source of delight.
Douglas Hofstadter, author of Gödel, Escher, Bach: An Eternal Golden Braid, notes the long-standing popularity of toys such as Russian dolls, which bring joy to children by hiding smaller versions of an object inside larger ones.
“Any kind of struck or nested inside another structure is something that humans have always found amusing,” Hofstadter says.
“It’s not something that I think would amuse a dog. I don’t think a dog would be particularly amused by Russian dolls but children are. There’s something about the human makeup that finds it charming and fascinating to see the same thing on multiple levels.”
Guests in this episode:
- Rachael Bailes teaches cognition and evolutionary linguistics at Newcastle University. Her work includes studying mirror neurons and ‘meta-representation’ in human brains.
- Michael Corballis researches language and the brain at the University of Auckland. He is the author of The Recursive Mind: The Origins of Human Language, Thought, and Civilization.
- Douglas Hofstadter directs the Center for Research on Concepts and Cognition at at Indiana University. His first book was Gödel, Escher, Bach: an Eternal Golden Braid, published in 1979. More recent work includes I Am a Strange Loop.
- Geoffrey West is the author of Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies. He is a former president of the Santa Fe Institute.
**The episode was produced by Mark Dance, with help from Tom Howell.
Brains, selves and spirituality in the history of cybernetics – Andy Pickering, 2008 (revised from 2007)
“This what I like about cybernetics: it was and is nowhere in the Cartesian space of human exceptionalism. It reminds us that we are performative stuff in a performative world—and then elaborates fascinatingly on that.”
Source: https://ore.exeter.ac.uk/repository/bitstream/handle/10036/81576/ASU-spirit.pdf?sequence=2&isAllowed=y
BRAINS, SELVES AND SPIRITUALITY IN THE HISTORY OF CYBERNETICS
andy pickering
sociology & philosophy
university of exeter
a.r.pickering@exeter.ac.uk
templeton workshop, ‘transhumanism and the meanings of progress,’ arizona state university, 24-25 april 2008
this essay is a revised version of a paper presented at the max planck institute for history of science, berlin, 3 november 2007—my presentation at ASU will frame it more precisely in relation to the theme of the templeton workshop
My research in the history of cybernetics in Britain has taken me to strange and unexpected
places. Grey Walter’s 1953 popular book, The Living Brain, is, on the one hand, a down-to-earth,
materialist and evolutionary story of how the brain functions. I know how to deal with that. But it
is also full of references to dreams, visions, ESP, nirvana and the magical powers of Eastern yogi,
such as suspending the breath and the heartbeat—siddhis as they are called. I never knew what to
make of this, except to note how strange it is and that respectable scientists don’t write about such
things now. But then I realised that I should pay attention to it. Walter was by no means alone on
the wild side. All of the other cyberneticians were there with him. In his private notebooks Ross
Ashby, the other great first-generation cybernetician in Britain, announced that intellectual
honesty required him to be a spiritualist, that he despised the Christian image of God and that
instead he had become a ‘time worshipper.’ Gordon Pask wrote supernatural detective stories.
Stafford Beer was deeply absorbed by mystical number-systems and geometries, happily sketched
out his version of the great chain of being, taught Tantric yoga and attributed magical powers like
ASU-spirit.doc
p. 2
11/8/09
levitation to his fictional alter ego, the Wizard Prang. Echoing Aldous Huxley on mescaline,
Gregory Bateson and R D Laing triangulated between Zen enlightenment, madness and ecstacy.
Strange and wonderful, surprising stuff. What is going on here? I want to try to sort this out, and
tie it back to a distinctive conception of the human brain.1
Meditating on the history of cybernetics has helped me see just how deeply modern thought is
enmeshed in an endlessly repetitive discourse on how special we are, how different human beings
are from animals and brute matter. It is, of course, traditional to blame Descartes for this human
exceptionalism, as we might call it.2 But while we may no longer believe we have immortal and
immaterial souls, the human sciences seem always to have been predicated on some immaterial
equivalent that sets us apart: language, reason, emotions, culture, the social, the dreaded
knowledge or information society in which are now said to live. This sort of master-narrative is
so pervasive and taken for granted that it is hard to see, let alone to shake off and imagine our
way out of. This is why we might learn from cybernetics. It stages a non-dualist vision of brains,
selves and the world that might help us put the dualist human and physical sciences in their place
and, more importantly, to see ourselves differently and to act differently. Let me talk about how
this goes.
We should start with the brain. The modern brain, as staged since the 1950s by AI for example, is
cognitive, representational, deliberative—the locus of a certain version of human specialness.
And the key point to grasp is that the cybernetic brain was not like that. It was just another organ
of the body, an organ that happens to be especially engaged with bodily performance in the
world. In this sense, the human brain is no different from the animal brain except in mundane
specifics: Ashby, for example, noted that we have more neurons and more neuronal
interconnections than other species, making possible more nuanced forms of adaptation to the
environment. And, of course, the defining activity of first-generation cybernetics was building
little electromechanical models of the performative brain—Walter’s tortoises and Ashby’s
homeostats—thus completing the effacement of difference between humans on the one side and
1 A much fuller treatment of the topics to follow (and much else) complete with citations to sources is to be
found in my forthcoming book: Sketches of Another Future: The Cybernetic Brain, 1940-2000 (Chicago:
University of Chicago Press, forthcoming).
2 The canonical transhumanist dream of downloading consciousness to a computer is, of course, a species
of human exceptionalism writ very large. My idea here is to explore a different mode of being in the world
and where it might lead us, especially across spiritual terrain.
animals, machines and brute matter on the other. This what I like about cybernetics: it was and is
nowhere in the Cartesian space of human exceptionalism. It reminds us that we are performative
stuff in a performative world—and then elaborates fascinatingly on that. Now I want to try to
make sense of some of these elaborations as they bear on non-Cartesian understandings of minds,
selves and spirit.
Continues in source: https://ore.exeter.ac.uk/repository/bitstream/handle/10036/81576/ASU-spirit.pdf?sequence=2&isAllowed=y
What is Management Cybernetics? – Barry Clemson (including 22 laws published 1984)
includes the 22 ‘laws’ of which he says:
Allenna Leonard and I articulated these 22 “laws” in 1982 or 1983. I hope we can think about this again in the near future and perhaps add a few more.
Source: What is Management Cybernetics? – Barry Clemson
What is Management Cybernetics?
Big Organizations, Management Cybernetics, Systems (How things really work)
Cybernetics, according to Stafford Beer, is the science of effective organization. Clear as mud, you say!
For example, a bacterium that was not effectively organized would quickly die. An ecosystem that was not effectively organized would very shortly be something else. A poorly organized human nervous system would not be able to regulate breathing, heart rate, speech, vision, etc. etc. etc. A poorly organized computer operating system would frequently crash and might have lots of security issues (sounds sort of like Windows, doesn’t it … sorry, as a devoted Mac user I couldn’t resist that one. I’ll try to behave from now on).
Effective organization is the basic requirement for the survival of a complex system.
What makes something a “complex system”?
“Complex system” is hard to define precisely but a common sense definition will do for now. A complex system has many parts which interact in ways that produce results that none of the parts alone can produce. Examples of complex systems include personal computers, a dog, a human being, an organization, and an eco-system.
Restating our original definition we might say that cybernetics is the science of effective organization for complex systems. When you apply the laws of cybernetics to the management of organizations you get management cybernetics. Stafford Beer spent about 60 years working out the implications of cybernetics for management. He wrote about eight books and hundreds of papers on the subject.
In my 1984 introductory book on management cybernetics I said that most books with the words “science” and “management” in the title are neither scientific nor good management. I claimed that management cybernetics, on the other hand, is good science and teaches us how to co-operate with the natural order of things rather than continuously bloodying our heads on stone walls. In that 1984 book, Allenna Leonard and I listed 22 laws, principles, and theorems of management cybernetics. Ern Reynolds then suggested a very useful exercise: paste the name of your organization in place of the word “system” in the 22 laws, principles and theorems. You will then have a useful cybernetic description of your organization.
Here are the 22 laws, principles and theorems.
1. System Holism Principle: A system has holistic properties possessed by none of its parts. Each of the system parts has properties not possessed by the system as a whole.
2. Darkness Principle: no system can be known completely.
3. Eighty-Twenty Principle: In any large, complex system, eighty percent of the output will be produced by only twenty percent of the system.
4. Complementarity Law: Any two different perspectives (or models) about a system will reveal truths about that system that are neither entirely independent nor entirely compatible.
5. Hierarchy Principle: Complex natural phenomena are organized in hierarchies with each level made up of several integral systems.
6. Godel’s Incompleteness Theorem: All consistent axiomatic foundations of number theory include undecidable propositions.
7. Entropy – the Second Law of Thermodynamics: In any closed system the differences in energy can only stay the same or decrease over time; or, in any closed system the amount of order (or organization) can never increase and must eventually decrease.
8. Redundancy of Information Theorem: Errors in information transmission can be protected against (to any level of confidence required) by increasing the redundancy in the messages.
9. Redundancy of Resources Principle: Maintenance of stability under conditions of disturbance requires redundancy of critical resources.
10. Redundancy of Potential Command Principle: In any complex decision network, the potential to act effectively is conferred by an adequate concatenation of information.
11. Relaxation time Principle: System stability is possible only if the system’s relaxation time is shorter than the mean time between disturbances.
12. Circular Causality Principle One: Given positive feedback (i.e., a two-part system in which each stimulates any initial change in the other), radically different end states are possible from the same initial conditions.
13. Circular Causality Principle Two: Given negative feedback (i.e., a two-part system in which each part tends to offset any change in the other), the equiibrial state is invariant over a wide range of initial conditions.
14. Feedback dominance theorem: For high gain amplifiers, the feedback dominates the output over wide variations in input.
15. Homeostasis Principle: A system survives only so long as all essential variables are maintained within their physiological limits.
16. Steady State Principle: If a system is in a state of equilibrium (a steady state), then all sub-systems must be in equilibrium. If all sub-systems are in a state of equilibrium, then the system must be in equilibrium.
17. Requisite Variety Law: The control achievable by a given regulatory sub-system over a given system is limited by 1) the variety of the regulator, and 2) the channel capacity between the regulator and the system.
18. Conant-Ashby theorem: Every good regulator of a system must be a model of that system.
19. Self-Organizing Systems Principle: Complex systems organize themselves; the characteristic structural and behavioral patterns in a complex system are primarily a result of the interactions among the system parts.
20. Basins of Stability Principle: Complex systems have basins of stability separated by thresholds of instability. A system “parked” on a ridge will “roll downhill”.
21. Viability Principle: Viability is a function of the balance maintained along two dimensions: 1) autonomy of sub-systems versus integration of the system as a whole, and 2) stability versus adaptation.
22. Recursive System Theorem: If a viable system contains a viable system, then the organizational structure must be recursive; or, in a recursive organizational structure, any viable system contains, and is contained in, a viable system.
Allenna Leonard and I articulated these 22 “laws” in 1982 or 1983. I hope we can think about this again in the near future and perhaps add a few more.
Chapter eight of my cybernetics book elaborates on these laws and provides lots of examples. My short essay on “Systems Thinking” is a companion piece to this one.
Contact me: I love to hear from readers. Email me at cyberneticapress at gmail dot com. Thanks, Barry Clemson
Coming Concepts: The Cybernetic Glossary for new management – Allenna Leonard (1990/revised 2004)
Source: https://i2s.anu.edu.au/wp-content/uploads/2009/10/cybernetic_glossary.pdf
Marco Valente on LinkedIn sparked another big discussion on ‘Complexity theories and Systems Thinking: parallels and differences’…
This was over a year ago, but in a recent discussion with Dave Snowden on twitter, it got resumed… I can’t recommend the article per se (though it seems entirely honestly and constructively meant) but the comments are Quite Interesting:
https://www.linkedin.com/feed/update/urn:li:article:8370213503392053397/?commentUrn=urn%3Ali%3Acomment%3A(article%3A8370213503392053397%2C6323841743901036544)&replyUrn=urn%3Ali%3Acomment%3A(article%3A8370213503392053397%2C6553869821061267456)
Autopoiesis Today – Milan Zeleny – and whole of Cybernetics Forum from the American Society for Cybernetics 1981 special autopoeisis issue
https://www.univie.ac.at/aoc/asc/Periodica/X_2_3_1981.pdf#page=9
Systems Community of Inquiry 
