Shifting From Parts to Patterns

April 4, 2017

All our knowledge has its origins in our perceptions.” – Leonardo Da Vinci

I had the pleasure of hearing my friend Nora Bateson speak last week at The Players Club in New York City where she held a reading and conversation around her recently published book, Small Arcs of Larger Circles: Framing Through Other Patterns.

If that title slows you down a bit, well, I think that’s the point. The book is a collection of essays and poems, and the conversation with Nora included personal stories of growing up in the Bateson household (Nora’s father was the pre-eminent systems scientist and anthropologist Gregory Bateson, whose first marriage was to Margaret Mead. Nora’s grandfather William, was a biologist who coined the term genetics.)

Collectively, the passages in Nora’s book draw us into a state of heightened curiosity that leads us to question how we perceive reality, ultimately enabling us to better understand our world and the challenges accelerating all around us. She invites us to probe the profound difference between our now four-hundred-year-old reductionist way of thinking (which is rooted in the Scientific Revolution), and the demands and mystery of a more accurate, complex living systems view of the world. Critical to the understanding of this more accurate world view is Nora’s enigmatic assertion, itself an invitation to the most important conversation we could be having:

“The opposite of complexity is not simplicity; it is reductionism,” she mused.

In the context of our interconnected 21st century social, political, economic and ecological challenges, the critical distinction between complexity and reductionism is far from a trivial one. It is, in fact, a life or death insight.

It is precisely because these indivisible challenges are rooted in complexity that our continually applying reductionist thinking to them has led to disastrous consequences.  Overcoming them depends on our shedding our unconscious reliance on reductionist thinking and adopting a more holistic way of looking at our world.  In other words, our failure to comprehend complexity itself, in an increasingly complex, interconnected world that seems to be spiraling out of control, may well turn out to have life or death consequences for many of us, and even civilization itself as we’ve come to know it in the Modern Age.

Admittedly, reductionism – breaking down what is complicated into its component parts so they can be analyzed and understood – has made immeasurable contributions to the progress of human civilization. The laptop I’m typing on and the man on the moon are achievements made possible through the reductionist method.  But as Wes Jackson says, “there’s nothing wrong with the reductionist method so long as you don’t confuse the method with the way the world actually works.”

Holistic thinker Allan Savory once illuminated for me that complexity is profoundly different than what’s complicated.  An iPhone or an airplane is complicated.  With time and ingenuity, it can be perfected and then mass produced, the same every time.  We humans have become experts in making what’s complicated, thanks to our now well-honed expertise in reductionist reasoning and problem solving.

But complexity is a different animal altogether.  A nation is complex. A city is complex.  A business is complex.  A rainforest is complex.  War is complex.  So too a marriage, a family, and our human self – our physical body, as well as our collective body/mind/spirit.  The complexity of a living system is distinguished by the ever-changing context that surrounds it and affects it, with feedback loops and consequences impossible to fully comprehend in advance.  Our political economy, in the context of culture and place, is such a complex living system.

Bateson explains that living systems that survive over time are characterized by mutually supportive learning networks that continuously communicate and interact across multiple contexts and variables in the system.  Yet we pretend to believe we can manage complexity as we manage what’s merely complicated, with our rules and protocols, and our key performance indicators designed through reductionist logic.  In today’s America — a complex system if there ever was one — the danger is compounded by leaders who seem to think they can govern without reference to accurate information, better known as “facts,” without which trust-based communication is impossible.

Trust issues aside, our challenges run even deeper.  Bateson writes, “The education system that reaches around the globe is a mess… The violence of breaking the world into bits and never putting it back together again substantiates the kind of blindness in which we have separated ecology from economy, and psychology from politics.”  I would add another reductionist “violence”— the separation of what used to be called “political economy” into politics and economics.  From the professional silos in which business and finance, governance and the law operate today, we literally can’t “see” the patterns that define the interconnections of complexity accurately enough to have a chance to manage them in a way that the times demand.  In truth, our aim should be to constructively guide and flow with the complexity that defines modern reality, since complexity can’t really be “managed” in the sense of asserting control.  How many presidents, CEOs, or regulators, or any of “the people running the world” understand that?

Gregory Bateson famously wrote: “Break the pattern that connects and you necessarily destroy all unity.”  Yet we don’t even see the patterns, much less honor the resulting unity as the essence of our health, even our survival.  Instead, in our ignorance, we break such patterns all the time, for example, the carbon cycle, which has resulted in the climate change that we now view as a “problem” to solve.  In reality, it is the unforeseen but direct consequence of our failure to perceive, understand, and humbly work within complexity.

We humans have evolved into problem solvers using the reductionist method, a direct outgrowth of the Scientific Revolution.  It’s now baked into our DNA, limitations included.  A Second Scientific Revolution is underway, one that integrates the reductionist method with the patterns of connection that define our integral reality.  Our life depends on it.

That’s worth slowing down a bit to ponder.

  • ProsperityForRI


  • Hi John : Very nice review of Nora Bateson’s book ! I knew her father Gregory Bateson and we once did a dialogue together at the Lindisfarne Fellowship in the 1970s !

    • John Fullerton

      Hi hazel. One of the greats I missed! But his daughter Nora is her own unique gem, an artist at the core.

  • Nam Nguyen

    Wonderful article and I could not agree with you more!

    • John Fullerton

      Good to know. Need to spread the word! Thanks-

  • Mark Phillips

    Thanks for sharing this. For those like me who can’t seem to get through a book, also good is the film/documentary Nora directed on her father, An Ecology of Mind.

    • John Fullerton

      Yes excellent. We should have mentioned. Thanks mark-

  • A very close approximation to something 😉
    And I couldn’t help grinning at the reductionist explanation of the holistic approach.

    And it seems to me to be only part of the picture.

    It seems that quantum mechanics seems to be pointing to a reality that only approximates causality, and is more of a fundamental balance between order and chaos, in having probabilistic boundaries on randomness at the lowest levels. And that is at time scales of less than 10^-40 of a second. To put that sort of number in a human context, if you take the smallest time unit that a skilled human can perceive, it is about 1/100th of a second. If you take all the time that has existed in the history of our universe (some 3 times older than than this planet), then that is only 10^20 units of human time, so you have to subdivide each of those into the same number of parts again. So from the perspective of the smallest stuff we can currently measure, in terms of the smallest time units that are meaningful to that stuff, then they have lived the age of the universe squared, in the smallest time a human can perceive. So it is not surprising that their behaviour appears to very closely approximate causal behaviour, because the probability distributions of their existence are very densely populated in the smallest time we can notice.

    It seems very likely to me that we actually live in a universe that is profoundly and permanently mysterious and unpredictable at many different levels and for many different reasons (a whole ecology of reasons), and at the same time is sufficiently approximating causality at the scales of normal human existence that the difference is not detectable by our most accurate instruments to date, and thus we can develop engineering to deliver the sorts of technologies we are both using to create, transmit and read these messages, at the same time as we have free will and eternal mystery.

    And I find Jordan Peterson’s explanations of the evolutionary embodied emergence of cognition and the mythology surrounding it to be the best I have encountered to date (though of course I have a few quibbles, he appears to be the best approximation to an understanding of that problem currently generally available).

    Another key to approximating an understanding to the puzzle that is us is the role of cooperation in evolution, and the exponentially expanding role of cooperation in the higher levels of complex systems.

    And all that leads to one of the most profound of mysteries, the very notion of freedom.

    So yeah – great post; and there doesn’t appear to be any end to the journey into complexity; and no guarantees of anything either.

    I am honoured to have met you as a fellow traveler on a path without end.

  • John Fullerton

    I’m speechless! But yes, here’s to the mystery of the journey into complexity…

  • JessieHenshaw

    John, I’m sorry I couldn’t make it to your talk last Thursday, as my brother was visiting. I trust it went well. What struck me in this post was the statement “Bateson explains that living systems that survive over time are characterized by mutually supportive learning networks that continuously communicate and interact across multiple contexts and variables in the system.”

    What’s striking to me is that anywhere you actually look, that complex weaving of learning networks is NOT “continuous”, but actually very intermittent. To me it reveals how progressions of relationships are built, with connections that are on and off, on and off, with every node not in continuous connection, but mostly in separation, as they make steps on their own with what they intermittently learn.

  • Doc Hall

    Good post and good review. Can we do anything about it in the business world without blowing people out of the idea that if we have reduced (reductionism of a sort) everything to a monetized model, we know everything necessary to know about a business, a proposal, or a public policy. I noted that during the rancor over ACA and ACHA, we debated, we did not dialog, and almost all the debate was about insurance plans and taxation — money and access to sick care, not about how to improve health.

    • John Fullerton

      well said. I often struggle explaining why even if we could swap out our entire energy system to renewables overnight, we would still be screwed without a fundamental change in how we understand the source of economic health (as apposed to treating one symptom of the problem). same problem!

  • Zsolt Nyiri

    Hello John, I am so glad you reflecting on Systems Thinking to your audience by mentioning Bateson’s gift to the world. All our work at the Institute for Strategy and Complexity Management (ISCM) is based on Systems Thinking and System Dynamics Modeling to solve challenges. We are deploying these think tools to compute socio-economic scenarios for Governments and communities in Africa. Hence, we cause Governments to rethink their existing policies with policy modelling solutions.

    Because Bateson’s work is core and so eminent, I take the liberty to provide your audience a practical translation of Systems Thinking for capital investments in African rural areas. Please select second video from our charity website: .
    For more information about the ‘causal overview’ model – relating to the video – one can visit the respective link and see the Interplay of Systems by clicking on the causal loop diagram (CLD). (Web link is:

    I trust this practical example brings the message across that one can visualise the cross-impact of decisions… prior to and during investments. More importantly, to demonstrate the consequences and unintended consequences of a decision over time for next generations.

    Stay in touch,

    • John Fullerton

      Thanks for this contribution Zsolt. We will review with interest… Great work!
      warm regards

  • Nora Bateson

    Hello,…. I am happy to see this discussion brewing here. And thank you John for your insights and careful thought around these ideas. Pause is so important. We don’t have time to be in a hurry right now… the transitions now at hand determine important shifts in the evolution of humanity, at least that is how I see it. Moving forward with depth and care for the larger interdependencies that generate vitality is a good start.

    • John Fullerton

      This issue of feeling extreme urgency … to save the republic, and to save the planet, while as you say, knowing we actually need to pause in order to act wisely, is a huge challenge. One that leaves me feeling uncomfortable about. Certainly confirms we are not “in control” but at best have an opportunity to steer a little if we are really good and really lucky!

      • Nora Bateson

        Yes John, me too. It feels like we are running out of time. I wonder though if that is because of the clocks, or because we are still seeing so little shift in the epistemology. Still, the concern for most is the quarterly profit margins, the consumer experience and just getting from today to tomorrow. The larger system is hardly in the conversation. Incremental systems change has proven to be a prolongation of existing patterns. I guess the pause is the time to at least reflect on the lens we are perceiving through, and maybe catch a few of our blind spots. Making sense of our world now in a way that is not perpetuating this madness, is a recognition i suppose of how impractical current ideas of practicality are, and how insane current notions of sanity are. There is wisdom in the forest. At first it seems still and silent, but soon a wider conversation reveals itself, full of vitality, and the opening of this complexity, while beautiful, the forest interaction is anything but serene. There in the pause… a world opens.

  • Daniel Martin

    Your words – ‘A Second Scientific Revolution is underway, one that integrates the
    reductionist method with the patterns of connection that define our
    integral reality..’ remind me of Thomas Kuhn’s little classic of the Sixties: The Theory of Scientific Revolution.

    For Kuhn this scientific revolution will happen finally when the old paradigm collapses sufficiently. The foundation of a new paradigm is already here, but on the margins because resisted by the old
    thinking/assumptions, etc. As the collapse of the old paradigm continues and more and more drift to the margins where the core of a new way is growing, a new paradigm develops and emerges. In our case today, the stakes are higher than every before for we have the capacity – as no generation before – to create more destruction and confusion.

    It is critical therefore that those on the margins develop – deepen and expand – their method which will require more than simply critiquing the old way. We need a new method that can be applied to every level of our interaction with life: a new way of interacting with each other and generating wisdom for living.

    • John Fullerton

      Please say more!

  • I’m looking forward to reading this book. I already agree largely with its premise as described in the article.
    My work is in the area of human thought, behavior, actions, relationship, mental health, motivation, etc.
    I rejected many of the “labels” typically used to in that arena, for example, the DSM because they reduce the symptoms to a single label that diminishes clarity.
    In my work I find that nearly everything I talk about exists along a continuum and that when things are explained using a continuum there is greater clarity about what is necessary to get improvements. Things that those using a completely reductionist method think are hard are simple using a continuum.
    Some of my work also involves feedback loops so I was delighted to see that. Emotions have recently been re-defined as a feedback loop between thoughts and our self-actualized self. I’ve been applying that perspective of emotions in my life for a decade and teaching others to do it for almost that long. In every case life improves and seems easier.
    This is absolutely on the right track. I like that.

    • John Fullerton

      Thanks for this. Reminds me of what I am learning about mood disorders being on a spectrum rather than black and white.

  • I came back to this again this morning, and decided to try from a different perspective.

    Leonardo only had part of the picture, and was therefore, essentially wrong.

    Those of us with sufficient interest and time now have some beginnings of an understanding of how evolution works.
    Evolution is about differential survival of variants in populations across all the different contexts encountered by the members of that population over deep time.
    Thus variants that have very high survival value in very rare contexts, and minor costs the rest of the time, can be present in significant concentrations in populations.

    This process embodies systems.
    It selects patterns that survive at ever more complex levels, simultaneous across all levels.

    It is now clear beyond any shadow of reasonable doubt that this process has given rise to all the living diversity that we see around us, including ourselves.
    It has structured our bodies and brains.
    In the biophysical contexts of genetic selection, it is responsible for all the capacities and tendencies to all the feelings we have.
    In the cultural context of mimetic selection it is responsible for most of the language and wider cultural constructs that we inhabit.
    In our personal journeys within both of the contexts above it is a very complex mix of choice and survival at many different levels.

    So at many levels, our behaviour in reality is the result and the expression of embodied patterns of being, which in one sense encode systems that have been selected by differential survival of variants over vast times and wide sets of contexts.

    So yes – one must look at the many levels of systems.
    No – one cannot take a purely reductionist view of seeking certainty from lowest level systems.
    And it is more complex than either of those imply.

    It is more dimensional that a holistic/reductionist view implies.

    To my mind the disasters are not so much caused by the use of reductionism, though being overly reductionist certainly has its problems (understanding the influences of subsystems is an essential part of understanding the operating limits of emergent systems), the biggest issue seems to be an addiction to certainty.

    It seems that the hardest notion for most to give up is the idea of truth.

    The idea that uncertainty, even chaos, might be a fundamental aspect of this existence within which we find ourselves seems to be the hardest thing for many to get.

    It does seem to be what Heisenberg uncertainty is pointing to, a sort of fundamental yin/yang balance between order and chaos, that in pairs of fundamental quantities (like position and momentum) require that the more we order and confine one aspect, the more chaotic and dispersed becomes the other.

    This balance of order and chaos seems to apply at all levels of emergent systems.

    And at all levels, the limits on chaos can give very close approximations to order when aggregated over large collections. Individuals may be unpredictable in any instant, but large collections over larger times give far greater confidence to predictions in many cases (but not all – some, like weather, are essentially unpredictable at all levels).

    I love David Snowden’s Cynefin Framework for the management of complexity ( It shows clearly that classical engineering approaches to order are only applicable to the simplest of domain spaces.

    Wolfram’s ideas of maximal computational complexity are also important. The idea that there are aspects of reality that cannot be reduced, as they are already maximally computationally complex, and the easiest way to see what they will produce is to let them do it.
    A great deal about being human seems to be like that. Wolfram explains that quite beautifully in this short clip ( published in March 2017.

    So there seem to be two big picture aspects here.

    One aspect is that the reality of where we are going cannot be reliably predicted, as it is of an order of complexity that we must simply live to find out where it goes.

    The other aspect is that we must all accept the fundamental uncertainty that comes with such complexity, and be willing to relax the boundaries of our cherished truths to allow the reality of our existence to create as close a model of itself as we can manage. And that would seem to be a potentially infinitely recursive process, as the emergent complexity of such behaviour folds back into the models of itself, ongoingly.

    And there are some important lessons in this that seem to be consistent.

    Complexity requires boundaries.
    Without boundaries everything becomes amorphous goo.
    We require boundaries at every level – physical, individual, social.
    And those boundaries need to be both flexible and selectively permiable, and both of those need to be context sensitive.

    So liberty in such a context cannot mean existence without boundaries, as that must, by definition, lead to non existence.

    Liberty, in a context of complex systems, must mean accepting those boundaries that are necessary for survival, and no more. Morality is essential to survival.
    And it seems that there cannot be any sort of absolute certainty about what those boundaries are, and there can be degrees of confidence in particular contexts.

    The real problem comes with novelty.
    Novelty, if real, has no historical precedent.
    If something is truly novel, then by definition it has not existed previously.
    That has two profound issues.
    1 – most people are unlikely to see it for what it is, and are likely to classify it as something that is similar in some aspect to something from their previous experience (and in doing so miss the novelty that is present).
    2 – there is no historical proven precedent for how to most effectively treat the new thing.

    We already know enough to know that we face many levels of existential threat that we have no effective risk mitigation strategies for, so we have to keep on exploring new stuff, to solve the old problems, and along the way, we are bound to both encounter and create new problems. So long as we are alert for that, open to those possibilities, we are probably on the safest possible path.

    And Wolfram in the short clip above points to our exponentially expanding ability to automate things.

    This exponentially expanding ability to automate is now the single greatest driver of change.

    Markets can only put a positive value on things that are scarce.

    If you doubt that think of air. Fresh clean air is arguably the single most valuable commodity for any human being, yet of no value in any market where it is universally abundant (which is most places).

    What few people have yet grasped, is that the need for scarcity to deliver market value is now directly in opposition to our technical ability to fully automate the production and delivery of a large and exponentially expanding set of goods and services.

    Our social systems are currently largely driven by profit, and profit demands scarcity.
    So while our existing systems can deliver radical abundance to some, they must always fall short of delivering such abundance universally, even if doing so is technically possible.

    That is why something like Universal Basic Income (UBI) is required as a transition strategy, to take us from our existing markets based systems (which arguably worked in times of genuine scarcity) to whatever evolves as our abundance based systems going forward.

    And one of the attributes of complexity that is clear from a study of evolution from a systemic view, is that new levels of emergent complexity are always characterised by new levels of cooperation, and cooperation requires attendant strategies to prevent invasion by cheating strategies. Arguably most of our existing financial and political systems can be characterised as cheating strategies. That doesn’t mean that we need to get rid of any people necessarily, we just need to change the strategic environments within which those people exist, and their awareness and self interest will respond accordingly.

    And it seems that security will always demand an element of massive redundancy and diversity in our systems, so it seems that within the broadest possible context of cooperation, we can see massive variability in instantiated sets of social and technical systems, each within their own sets of boundaries, and each interacting within wider sets of boundary conditions.

    And the idea that we can use hard rules to define such conditions is not sustainable.
    Those higher order boundaries must have flexibility in dimensions many will not even be able to distinguish. And that will require active communication systems and openness like never before.

    And Jordan Peterson has the best development I have encountered of the levels of complexity embodied in many of our deep cultural constructs (he misses a few things, but gets far more than most – is as good a place to start as any).

    I am clear, beyond any shadow of reasonable doubt, that our survival demands that we go beyond markets as a dominant force in our social planning infrastructure. The context has now changed sufficiently that market values can no longer be used in a planning context, though they can retain utility in a delivery context for some time to come. Our existing debt based money creation system must change, is changing.

    We have much to do.

  • John Fullerton

    This is a critical insight, thank you for adding it to the discussion. In my work with holistic management on the world’s grasslands with Allan Savory and crew, they have a simple approach.

    1. Create a holistic goal (context specific).
    2. Create a plan to deliver the goal.
    3. Assume plan is wrong (because it will be as soon as the context changes)
    4. Monitor to see where plan is wrong and adapt as required.
    5. Do step 4 again and again.

    The stunning implication of this is that the “scientific method” does not work, since “holding all else constant” means that the plan will fail (due to the changing context as you point out). Savory has been ridiculed by the “scientific community” who have tried to test his method using such the scientific method. Allan would say they are not testing holistic management by definition, so what is failing is a reductionist failed imitation. But this is a profound paradigm shift awaiting to happen and very confusing to our established way of thinking. The changing context on a ranch is likely to be rainfall vs expected rainfall, but also invasive weeds, or one year we had an invasion of grasshoppers! But in a human economy, the possibilities for changing context are endless! Making economic management even with the right framework and measures to monitor, highly complex!

    • Hi John,

      If you look at Snowden’s Cynefin framework for managing complexity (which is a very simplified framework for getting a feel for the types of complexity present and the sorts of management responses appropriate ), then you will understand that what most call the “scientific method” of holding all else steady and varying a single aspect to test the effect of that single aspect, is only appropriate to the simplest of Snowden’s 4 classes.

      Any scientist with a reasonable understanding of complexity and statistics will understand that – and unfortunately that is a small subset of those who call themselves scientists.

      So scientists come is a vast spectrum of understandings and methodologies – much like human beings generally and cultures generally. Most scientists are every bit as dogmatic as most adherents of any religious system – just a different set of dogmas.

      The only thing that should be common to all scientists is a willingness to let the evidence from well formed experiment be the determinant of questions. And there is always room for argument about how well formed an experiment is, and conceptual bias from particular modes of interpretation can be a major factor (dogma).

      What we “see” is very much a function of what we expect to see, modulated by what is actually there. Human beings are very adept at subconsciously pushing whatever shaped observational peg is present into the nearest shaped conceptual hole that it will fit in, and using that as evidence for “truth”.
      Becoming aware of the many levels at which we have a strong subconscious tendencies to such things is a big part of the process (Yudkowski’s “Rationality from AI to Zombies” is a reasonable catalogue of many of those, and at the same time it mostly ignores the fact that rationality is only ever the tiny tip of human behaviour, most of which is and must always be, subconsciously heuristic). Reality is far too complex to ever be able to handle consciously. Everyone, at all levels, has to make vast sets of subconscious and conscious simplifying assumptions and take heuristic shortcuts to be able to make any sort of sense of anything.

      Part 1 of understanding science is getting that our conscious experience is never of reality itself, but can only ever be of a subconsciously created model of reality. Once that sinks in, it demands a certain level of humility from us.

      Uncertainty is fundamental.
      Simplistic assumptions occur at every level, always.

      Building a reasonably useful approximation to the levels of complexity present in reality takes many thousands of hours of work. One has to train and retrain neural networks over and over. There simply is no substitute for experience in doing such things.

      And we each need to be able to use the tools of science to inform our models, without being blinded by the dogma of any particular set of scientific paradigms.
      Building more accurate models demands that we be prepared to try out things that do not seem at all sensible from our current models (that is the definition of novelty in a very real sense).
      Being willing to trust intuition and feelings enough to design tests, and then having the stamina to keep on testing modes of communication until one finds one that has a reasonable probability of success, of weakening the bounds of dogma at some level to allow new possibilities to emerge in a new mind, that is part of the process. It can be a very lonely journey.

      When the core concept of economy – the market – encounters an exponentially expanding set of conditions (fully automated systems) that fundamentally undermine it, and turn it from something beneficial to something that is an existential risk to humanity, that can be very difficult for people to see.

      When one has been taught that evolution is all about competition, it can be difficult to see that actually evolution is exponentially more about cooperation as successive levels of complexity emerge.

      Understanding that morality is one of the necessary boundary conditions for complex systems like ourselves to exist was not clearly visible to Nietzsche or the Post Modernists, yet to those with a sufficient depth of understanding of evolution and complexity and strategy it stands out like the proverbial.

      So I just caution you, yes, certainly, acknowledge that the simplistic term “scientific method” as applied to holding all but one variable constant, is appropriate to only a tiny subset of the systems in reality, and do not make that mean that the wider methods of science, statistics and complexity are not appropriate more widely.

      And certainly, acknowledge that many systems are genuinely chaotic, and do not have any significant predictable attributes, and trying to predict them is a waste of time. Learn to identify them and avoid them to the greatest degree that is possible.

      And many other systems are complex, and require an iterative approach of probe, sense, evaluate, amplify or dampen aspects as appropriate, and repeat. That’s life. Accept it. Enjoy it.

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