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Generative Systems Design
Complex Adaptive Systems, Process Design, Adaptive Push Back, Antifragility, Dynamic Organization, Autopoiesis
Curated by Anne Caspari
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Understanding Is A Poor Substitute For Convexity (antifragility) | Conversation | Edge

Understanding Is A Poor Substitute For Convexity (antifragility) | Conversation | Edge | Generative Systems Design | Scoop.it

Something central, very central, is missing in historical accounts of scientific and technological discovery. The discourse and controversies focus on the role of luck as opposed to teleological programs (from telos, "aim"), that is, ones that rely on pre-set direction from formal science. This is a faux-debate: luck cannot lead to formal research policies; one cannot systematize, formalize, and program randomness. The driver is neither luck nor direction, but must be in the asymmetry (or convexity) of payoffs, a simple mathematical property that has lied hidden from the discourse, and the understanding of which can lead to precise research principles and protocols.

 

The point we will be making here is that logically, neither trial and error nor "chance" and serendipity can be behind the gains in technology and empirical science attributed to them. By definition chance cannot lead to long term gains (it would no longer be chance); trial and error cannot be unconditionally effective: errors cause planes to crash, buildings to collapse, and knowledge to regress.

 

The beneficial properties have to reside in the type of exposure, that is, the payoff function and not in the "luck" part: there needs to be a significant asymmetry between the gains (as they need to be large) and the errors (small or harmless), and it is from such asymmetry that luck and trial and error can produce results. 


Via Spaceweaver
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Anne Caspari's comment, June 17, 2013 1:22 AM
Against popular understanding of what makes the universe go round "(yin/yang") , it is ASSYMETRY in many different realms. Generative systems design can benefit hugely from understanding this and using what Taleb calls convexity in order to desgin for results and success.

And here is another take on assymetries cross posted from Bonnitta Roy, http://alderloreinsightcenter.com/insightful-ideas-blog/  pointing out the different realms where assymetry is the driver:

"That at every level or domain of existence there are exclusionary principles which are the principles which guarantee difference and generate increasing levels of uniqueness. So for example, at the quantum level there is wave-particle uncertainty, at the atomic level there is Pauli exclusion, at the level of abiotic there are things like laws that govern crystals, handedness, etc… at the level of plant there is the exclusion of space, at the level of animals there are incompatible goods, and at the level of humans there are incommensurable beliefs. "

This all makes a lot of sense.
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9 basic principles of biomimicry J. Benyus

9 basic principles of biomimicry J. Benyus | Generative Systems Design | Scoop.it
Anne Caspari's insight:

mimicking nature is a good idea in generative systems design. 

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ComplexitySol: Projects as Complex Adaptive Systems (2)

ComplexitySol: Projects as Complex Adaptive Systems (2) | Generative Systems Design | Scoop.it

Acting in a Complex Adaptive System

Each agent ideally needs to know, in ‘real time’ WHAT to do, HOW to do it, and WHO to communicate with.



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Anne Caspari's comment, April 23, 2013 1:36 AM
this is a good synopsis from someone who seems to know his project work! Practical and down to earth without flattening the complexity.
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What Is A Pattern In Nature ? | Patterns In Nature Blog

What Is A Pattern In Nature ? | Patterns In Nature Blog | Generative Systems Design | Scoop.it
The design and placement of patterns in Nature do not come from an artist’s hand but from the connected and dynamic interactions of natural objects in both space and time.
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Anne Caspari's comment, March 31, 2013 7:03 AM
“This highlights a fundamental difference between Western mental constructs of the universe, with an external Lawmaker appointing order to the natural world and enforcing it, and the Chinese construct, where order arises from the intrinsic relationship between things in the universe ….. This is the same dynamic being discovered by Western complexity theorists and systems biologists in recent decades, as they investigate the principles of self-organization in the natural world.”
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ComplexitySol: Projects as Complex Adaptive Systems

"When uncertainty levels are high we tend 2rely more on prior knowledge 2make sense... This isn’t always helpful" http://t.co/XI6YehORtq
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Anne Caspari's comment, March 19, 2013 6:32 AM
this is good, sound, bottom up and applicable.
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Embracing Emergence: How Collective Impact Addresses Complexity (SSIR)

Embracing Emergence: How Collective Impact Addresses Complexity (SSIR) | Generative Systems Design | Scoop.it

When the Process Becomes the Solution

We have found in both our research and consulting that those who hope to launch collective impact efforts often expect that the process begins by finding solutions that a collective set of actors can agree upon. In fact, developing a common agenda is not about creating solutions at all, but about achieving a common understanding of the problem, agreeing to joint goals to address the problem, and arriving at common indicators to which the collective set of involved actors will hold themselves accountable in making progress. It is the process that comes after the development of the common agenda in which solutions and resources are uncovered, agreed upon, and collectively taken up. Those solutions and resources are quite often not known in advance. They are typically emergent, arising over time through collective vigilance, learning, and action that result from careful structuring of the effort. If the structure-specific steps we have discussed here are thoughtfully implemented, we believe that there is a high likelihood that effective solutions will emerge, though the exact timing and nature cannot be predicted with any degree of certainty. This, of course, is a very uncomfortable state of being for many stakeholders.

And yet staying with this discomfort brings many rewards. 

A previously unnoticed evidence-based practice, movement, or resource from outside the community is identified and applied locally.Local individuals or organizations begin to work together differently than before and therefore find and adopt new solutions.A successful strategy that is already working locally, but is not systematically or broadly practiced, is identified and spread more widely.

Anne Caspari's insight:

“When you are moving towards an objective, it is very important to pay attention to the road. It is the road that teaches us the best way to get there, and the road enriches us as we walk its length.”

 

Finally an article on CAS that focuses on the right Process Design features. Good.   

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Eric Berlow: Simplifying complexity | Video on ...

Eric Berlow: Simplifying complexity | Video on ... | Generative Systems Design | Scoop.it
Ecologist Eric Berlow doesn't feel overwhelmed when faced with complex systems. He knows that more information can lead to a better, simpler solution.
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All Systems Need A Little Disorder

All Systems Need A Little Disorder | Generative Systems Design | Scoop.it

Managing complex adaptive systems (CAS) is a constant balancing act between many goals that are often in conflict with each other. Most systems need to be managed to limit resource usage i.e. they need to be efficient. The mantra of efficiency is most visible in economic systems but even other systems such as biological systems cannot typically get away with profligate wastage of resources. But efficiency is not enough. Systems also need to be robust. There is no point in achieving optimal efficiency if the first change in environmental conditions causes the system to collapse. Robustness is not just about avoiding collapse and persisting. Robustness is the ability of a system to maintain critical functionality in the face of significant stress.

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Demystifying the Pattern(s) of Change: A Common Archetype

Demystifying the Pattern(s) of Change: A Common Archetype | Generative Systems Design | Scoop.it
We are all familiar with it because we have ridden its wave many times in our lives.  Some of us have developed the wisdom to embrace it when it arises; others are still resisting it, stricken by a...
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Anne Caspari's comment, April 20, 2013 5:57 AM
this is a pretty good of synopsis different viewpoints on the same phenomenon of transformation - CAS, panarchy, U process, Hero's journey. I like it.
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Complexity: It’s Not That Simple « how to save the world

Complexity: It’s Not That Simple « how to save the world | Generative Systems Design | Scoop.it
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What are Complex Adaptive Systems?

What are Complex Adaptive Systems? | Generative Systems Design | Scoop.it

Complex adaptive systems are all around us. Most things we take for granted are complex adaptive systems, and the agents in every system exist and behave in total ignorance of the concept but that does not impede their contribution to the system. Complex Adaptive Systems are a model for thinking about the world around us not a model for predicting what will happen. I have found that in nearly all situations I can view what is happening in Complex Adaptive Systems terms and that this opens up a variety of new options which give me more choice and more freedom.

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Anne Caspari's comment, March 18, 2013 2:25 AM
good overview over some of the main properties of CAS: emergence, co-evolution, sub-optimal states, requisite variety, connectivity, simple rules, iteration, self-organization, edge of chaos, nested systems...
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Defining and Modeling Complex Adaptive Systems

Defining and Modeling Complex Adaptive Systems | Generative Systems Design | Scoop.it
Almost all the critical problems of our time are problems of control and almost all of them concern complex adaptive systems. If we want to know more about our bodies, it is not just to increase knowledge but so that we can control our health.

 

CAS are  “systems that don’t yield compact forms of representation”1. In other words a complex system cannot be described by a simple set of equations. Why would this be the case? It is the “adaptive” nature of these systems that leads to this intractability. Agents within the system respond to each set of environmental conditions within a complex adaptive system with a different set of responses and the number of such environments and their corresponding agent responses that need to be accounted for to construct an accurate model of the system is simply too large. But is this simply a problem of impracticality? Could we, at least in theory, construct a model that takes into account all possible environmental conditions and all possible agent behaviours? Although some scientists may argue that such an approach is theoretically possible, there is ample evidence that the critical “adaptive” component of some complex adaptive systems may in fact be unmodelable

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luiy's curator insight, March 18, 2013 10:12 AM
What Is A Complex Adaptive System?

The first question that then needs to be answered is: What is a complex adaptive system? David Krakauer defines complex systems as “systems that don’t yield compact forms of representation”1. In other words a complex system cannot be described by a simple set of equations. Why would this be the case? As Krakauer notes, it is the “adaptive” nature of these systems that leads to this intractability. Agents within the system respond to each set of environmental conditions within a complex adaptive system with a different set of responses and the number of such environments and their corresponding agent responses that need to be accounted for to construct an accurate model of the system is simply too large. But is this simply a problem of impracticality? Could we, at least in theory, construct a model that takes into account all possible environmental conditions and all possible agent behaviours? Although some scientists may argue that such an approach is theoretically possible, there is ample evidence that the critical “adaptive” component of some complex adaptive systems may in fact be unmodelable. There is no better example of this than the problems faced by the economist Hyman Minsky in formalising many of his most important ideas.

Luciano Lampi's curator insight, March 19, 2013 6:02 AM

Interesting to read!

Léonne Willems's curator insight, March 25, 2013 1:27 PM

Another way to think about environmental influences at the source of tensions at work (as opposed to individual lack of employee performance or motivational problems). Are these 'tensions' actually symptoms of a system out of balance? Are these tensions the real gems for organisational steering? Check out how Holacracy capitalises just on that!