Metaphors are popular cognitive and conceptual tools in the worlds of systems and complexity, and boy do we like to fight about them! Take this discussion, for example, about the limits of understanding the organisation as a human body. Even if you agree with the premise (which I do, the metaphor has its limits) the collective conclusion still strikes me as remarkable: that somehow we will find a single metaphor (meadow, estuary or octopus) that sufficiently explains the phenomena under investigation.

#43: Mixing metaphors – by Luke Craven – Pig on the Tracks

Readings for Education | The Future of Education: Edgar Morin Andrés García BarriosNovember 24, 2021 In this new installment of “Readings for Education,” Andrés García Barrios reflects on three major concepts: future, complexity, and uncertainty, through the ideas of Edgar Morin.

Readings for Education | The Future of Education: Edgar Morin — Observatory | Institute for the Future of Education

methods for systemic change by the systems school

methods for systemic change Tickets, Wed 06/04/2022 at 3:00 pm | Eventbrite

http://nthmost.net/adhdbrain_loopy.html

Thirteen dilemmas and paradoxes in complexity Published on December 3, 2021

(3) Thirteen dilemmas and paradoxes in complexity | LinkedIn

Thirteen dilemmas and paradoxes in complexity

• Published on December 3, 2021

Status is onlineMarco ValenteConsultant at Cultivating Leadership27 articles Following

As readings and reflections on complexity and its applications grew over the years, increasingly my head got spinning with apparent contradictions and paradoxes. Complexity seemed to be a land of both/ands and of polarities, where statement A and its opposite statement B seemed both true under different circumstances. This below is a list of apparent dilemmas, paradoxes, polarities in complexity, by no means exhaustive but the first that came to mind.

1. Complexity is really difficult AND it is easier at the same time. Yes, complexity seems like a hard subject to deal with, and yet as long as we drop some of our inadequate tools it can actually appear easier -but it still needs a lot of rigor (see below).

Read: Jennifer Berger’s Mindtraps, and her forthcoming papers and interviews.

2. We are hopelessly biases in our perception of complexity AND we have ancient, built-in ways to deal with it. Name me one popular psychology book or leadership book that does not run you through an account of how biased we are as humans. While this has become commonplace, it is easy to mistake being “biased” for being hopeless in the face of uncertainty. It turns out that ancient wisdom, time-tested heuristics, grandma sayings are actually very robust in the face of the unknown

Read: Taleb, Gigerenzer, and the disputes between the heuristics and biases and the naturalistic approaches.

3. We need more information to navigate uncertainty AND less is more to sort through the noise. We are blind to a worldview behind evidence-based decision making: that more information is always better, which we inherited from the Enlightenment and got a reprise with Carnap. This would work well in situations where information is reliable and where a complete understanding of our system can be achieved. In reality we need more (in certain situations) and we need discernment and better Occam’s razors in uncertainty too.

Read: Gigerenzer’s paper The Beauty of Simple Models, among other things he has written.

4. We need a clear vision of the future AND we need adaptability and flexibility for a future we cannot predict. Berger and Johnston have written cogently about strategy in complexity: we need an inspiring vision while at the same time we need to recognize the irreducible uncertainty so the vision becomes more like a set of boundaries and guardrails within which to experiment. Again, both statements are true in spite of their apparent contradiction.

Read: Berger and Johnston’s Simple Habits for Complex Times.

5. We need to rely more on rigorous scientific approaches AND we need to recognize irreducible causal opacity. How can you advocate for more and less science at the same time? I am advocating for more and better science, and yet more epistemic humility so that we can recognize how strong our predictions can be, and what to do in the face of irreducible uncertainty.

Read: a good place to start is Radical Uncertainty by King and Kay

6. We need centralized sense-making about certain key variables and weak signals AND we need to distribute the capacity to make sense and decide locally. In the book Team of Teams* this apparent dilemma found a workable solution. They devised ways to display real time information on a centralized screen while at the same time they had sensing systems that were necessarily distributed. You can centralize some structures and rituals for a system to make meaning of what is going on, while acknowledging that data is necessarily distributed, local, and contextual.

Read: Team of Teams by Gen Mac Chrystal. (*The US aggression in the Middle East in the early 2000’s was a bad mistake in my view, but the book contains useful ideas).

7. We need more, better coherence AND we need to acknowledge the generative importance of lack of coherence. We need better ways of aligning on our sense of coherence around certain hypothesis about what is going on in the system at any given time, and at the same time we need to take the opportunity that lies in the moments of confusion: they can be times of proving us wrong, of innovation in the scientific field (why does this drug work in spite of our expectations?) and so on.

Read: Dave Snowden’s blog posts that mention aporia, and the notion of coherence by Thagard.

8. We need to rely on sound models more AND less at the same time. It is hard to make sense of this, but models are more important in complexity to project potential scenarios (see projections of infections, etc.) and we need to bring more epistemic humility to their predictive powers as well, especially in fat tailed distributions where small errors in the input of our models make them horribly wrong. What does this mean in practice? Use them for exploring the space of possibilities without taking any of them as the final ‘truth’ (unless they have a track record of sound predictions or a controllable environment).

Read: softly pro-models, The Model Thinkers, by Scott Page. Against models: Taleb.

9. Leadership in complexity should be often more decisive AND more accepting of uncertainty and ambiguity too. Our systems incentivize leaders who have the answers and promise us some future outcomes with a degree of certainty. But we should rather be inspired by the values that they stand by, while it is hard to make promises about certain future outcomes that nobody can know about. Leaders can still commit to radical learning in conditions of ambiguity though.

10. We need more specialized knowledge in certain fields AND we need more generalists. Dave Snowden is exactly right on this point. Silos of expertise are not bad per se -they are essential, in fact. We need them desperately while we also need to bridge across context and tend to the interrelationships between ideas, departments, and worldviews.

Read: for inspiration, Range by David Epstein.

11. We need more experimentation at the edges AND we need rigorous hypothesis testing alongside our experimental approach. You learn about a complex system by ‘poking’ it first. You pinch a blob of jelly with a fork and see how it wobbles. You can not hypothesize what will happen without touching the jelly. But this should not translate into an ‘anything goes’ reminiscent of Feyerabend. We need rigorous testing of what hypothesis is behind each intervention as a way to reliably learn from our experience.

12. Complexity is a highly specialized field AND it is not a “field” but a worldview that permeates other disciplines. It is possible that in two or three decades from now complexity will become a highly specialized field with degrees and university curricula. But complexity is also a lens through which we can look at the world, not a “thing” that can be studied in isolation.

13. Complexity science is novel and unique AND it is rooted in ancient wisdom that did not survive against the Cartesian/Newtonian consensus. Jean Boulton and Peter Allen in their great book Embracing Complexity retrace some of the story of how complexity ideas were permeating ancient traditions in both the East and the West. You can just as easily argue that the modern understanding of reality as a set of linear causes is the outlier that took prominence over the last four / five centuries since Decartes and Newton, and that our culture has been used to complexity more than it has been familiar with the mechanistic understanding of the world.

Read: Embracing Complexity.

What would you add?

https://www.linkedin.com/pulse/thirteen-dilemmas-paradoxes-complexity-marco-valente/

BACK SHARE   Moving From Transactional To Relational: Volume 1, Issue 2 Nov 30, 2021 Journal of Awareness-Based Systems Change – Issue #2

Moving From Transactional To Relational: Volume 1, Issue 2 – News – Presencing Institute

link https://www.nfi.edu/kuleshov-effect/

https://en.wikipedia.org/wiki/Kuleshov_effect

Some things I’ve learned about change (1)

Some things I’ve learned about change (1) – Escaping the invisible asylum

Russell Ackoff

FROM MECHANISTIC TO SYSTEMIC THINKING

November 1993

Presented at the Systems Thinking in Action conference, Ackoff states that humanity is in the early stage of a transition from the Machine Age to the Systems Age. The Machine Age was characterized by belief in complete understandability of the universe, analysis as a method of inquiry, and cause and effect as a sufficient relationship to explain all. The dilemma that disrupted such beliefs was systems thinking. The Machine Age began to die when humanity gave up the principle of understandability. Gradually, it’s become accepted that there can be no complete understanding of the universe because nothing can be understood independently of its environment—all is environmentally relative. While analysis produces knowledge, it is synthesis that produces understanding. Furthermore, the Systems Age recognizes that cause and effect is just one way of looking at reality among an infinite number.

From Mechanistic to Systemic Thinking – Russell Ackoff

Frame Control by Aella 27th Nov 2021

Frame Control – LessWrong

Frame Control

by Aella27th Nov 2021

Social & Cultural DynamicsSocial RealityFramesWorld ModelingPersonal Blog

Crossposted from my blog

When I mention my dad’s abuse, I mention salient things – physical pain, insults, and controlling behavior. These are “clearly bad” – if I tell you that he often told me I was lazy and would fail horribly at life once I left home, you know it’s bad, because it’s concrete, easy to imagine and obviously unkind. But this wasn’t the worst of the abuse; the most terrible parts were extraordinarily hard to understand or describe.

In his world, I felt insane – I couldn’t tell what was real, who was at fault, or why my heart hurt so much. My sense of clarity around my own intentions crumbled; everything I thought or did might have seemed good on the surface, but that goodness became just a disguise for my true, darker intentions – all helpfully revealed to me by my dad. And none of it was salient or concrete or easily understandable; I remember my mom once telling me, “I can’t describe what this is like to other people. The individual things seem so silly, I can’t put the important thing into words.” 

I’m going to try to put it into words, and the words I personally use for “the important thing” are frame control. 

Continues in source

https://www.lesswrong.com/posts/bQ6zpf6buWgP939ov/frame-control

and

https://knowingless.com/

What Is Memory that It May Have Hindsight and Foresight as well

What Is Memory that It May Have Hindsight and Foresight as well | Semantic Scholar

What Is Memory that It May Have Hindsight and Foresight as well

• H. Foerster
• Published 1969
• Psychology

“What is Time?” According to Legend, Augustine’s reply to this question was: “If no one asks me, I know: but if I wish to explain it to one that asketh, I know not.” Memory has a similar quality, for if not asked, we all know what memory is, but when asked, we have to call for an International Conference on the Future of Brain Sciences. However, with a minimal change of the question, we could have made it much easier for Augustine. If asked “What’s the time?” he may have observed the position of the sun and replied: “Since it grazes the horizon in the west, it is about the sixth hour after noon.”

When meaning loses its meaning, with Nora Bateson & Dave Snowden

Meeting Registration – Zoom

As the theory and application of complexity and systems thinking translates into new epistemological worlds and emerging ontological possibilities, there is an ever-growing need for rigour, attention and creative understanding of the language and metaphors that circulate.

We invite you to a series of conversations between Nora Bateson and Dave Snowden to explore the uses and shifting meanings of some of the key concepts and ideas in the fields of complexity and systems theory. We will dive into the origins and histories of concepts like abduction and ecology to explore how meanings stretch, transform and sometimes wear out across ecosystems of communication.

This journey with Nora and Dave offers unique perspectives – tracing the roots of ideas and discerning subtle differences – towards a shared curiosity in the integrity of cultural dialogue and tending vital connections across understandings.

EMERGENCE An International Transdisciplinary Journal of Complex Social System

Home Page – Emergence: Complexity & Organization

Collected Works of Warren S. McCulloch Edited by Rook McCulloch

– Emergence: Complexity & Organization

Warren Sturgis McCulloch Interview Canadian Broadcasting 1969 – Warren speaks of brains and thinking machines, science and his legacy, and the need to be ‘completely humble to the facts and completely haughty to man…’

Warren Sturgis McCulloch Interview on Vimeo

Warren Sturgis McCulloch Interview

Canadian Broadcasting 1969 – Warren speaks of brains and thinking machines, science and his legacy, and the need to be ‘completely humble to the facts and completely haughty to man…’