Understanding complexity: A prerequisite for sustainable design
From ‘Design for Human & Planetary Health’, D.C. Wahl 2006
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… (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. As I have mentioned before, 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.
[This is an excerpt from my 2006 PhD Thesis in ‘Design for Human and Planetary Health: A Holistic/Integral Approach to Complexity and Sustainability’. This research and 10 years of experience as an educator, consultant, activist, and expert generalist in whole systems design and transformative innovation have led me to publish Designing Regenerative Cultures in May 2016.]
Among the scientific disciplines that have contributed to complexity theory are: general systems theory, cybernetics, chaos theory, synergetics and computational theory, as well as evolutionary biology, the theory of autopoiesis, artificial intelligence, fractal geometry and ‘far-from-equilibrium thermodynamics’ (see J. Goldstein, 1999).
In particular, lessons from non-linear mathematics and chaos theory added the crucially important insight of the fundamental unpredictability of complex dynamic systems, which allowed theories to progress beyond the detached systems theory mindset that still aimed to increase prediction and control.
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).
The German bio-cyberneticist Frederic Vester emphasized: “simple cause and effect relationships only exist in theory, not in reality.” According to Vester, we have to face up to the fact that reality is governed by indirect causes, networks of relationships and time delays that in many cases make it absolutely impossible to clearly identify individual causes. It is this awareness that makes us fully appreciate how difficult it actually is to guess at the effects that a certain intervention will have (Vester, 2004, p.15).
Accepting such profound and permanent limits to human knowledge and our ability to predict and control, will inevitably lead to taking a more humble approach to human interaction with natural process. It forces us to recognize our role as participants in natural processes. In the face of their fundamental unpredictability — we have to adopt a more responsible mode of participation based on trans-disciplinary cooperation, careful consideration and action based on the precautionary principle. In a recent report to the Club of Rome, Professor Vester wrote:
As difficult as it may be for us to engage in a trans-disciplinary approach to the whole system, and as little we may be used to dealing with complex occurrences — it will not pay off if we try to make our decision- making easier on ourselves by simply ignoring the complexity of the world we live in. It is just as impossible to escape from this complexity than it is to escape from the complexity of our own being.
Most importantly, we need to accept that we are much more entangled with the complex systems of our environment and the biosphere, than our conventional mode of linear cause and effect thinking with its method of dividing the world into categories tries to make us believe. It is simply not a case of here humanity and there nature. We, ourselves are Nature, our billions of biological cells are a part of her — and all the technology we have ever created is included in nature (trans. Vester, 2004, p.30).
While many of our human designs and technological achievements may be thoroughly unsustainable and devastatingly destructive to the natural processes, they are nevertheless participating in these natural processes that dynamically interconnect the planetary system as a whole. As paradoxical as it may seem, human technologies are a part of nature, albeit in their current form a very destructive one.
Sustainable design can be defined as appropriate participation in natural process; and appropriateness should be judged by the extent to which a certain design maintains the overall dynamic stability, resilience, flexibility, adaptability, or health of the system as a whole.
In order to create sustainable designs we will have to learn to integrate into natural process and this will require us to consider insights from many different disciplines through trans-disciplinary co-operation and dialogue. Furthermore, designers will have to become more conscious of the way that a particular design may participate in various, interconnected scales of natural process at one and the same time.
An understanding of the insights gained through complexity theory can provide a very important contribution to appreciating nature’s scale-linking properties, as well as the the work of trans-disciplinary design teams aiming towards meeting the needs of the present and future generations of humans while attempting to participate appropriately in natural process.
For many years, the ‘Santa Fé Institute’ in New Mexico has provided a platform for scientists from many disciplines to discuss and develop complexity theory and its implications. In 1996, the ‘Santa Fé Group’ defined complexity as follows:
Complexity refers to the condition of the universe which is integrated and yet too rich and varied for us to understand in simple common mechanistic or linear ways. We can understand many parts of the universe in these ways but the larger more intricately related phenomena can only be understood by principles and patterns — not in detail. Complexity deals with the nature of emergence, innovation, learning and adaptation (in Battram, 1998, p.v).
As such, complexity theory clearly explores subject areas that are fundamentally important to the creation of design solutions that are flexible and adaptive enough to facilitate the long term learning process that establishes and maintains sustainability.
In dealing with complex dynamic systems, trans-disciplinary design teams will have to face the challenges posed by fundamental interconnectedness and unpredictability as well as the physical and biological fact of humanity’s participatory involvement in natural process despite our intellectual ability to assume detached observer perspectives and temporarily create a culture regarding itself as detached from nature.
Why do I stress temporarily? I would suggest that the basic assumption that our intellectual and cultural emancipation from nature justifies a position that culture is not part of nature is a root-cause of unsustainable decision-making and design.
At the level of meta-design — the influence of basic assumptions and values on our worldview and thus our intentions and design practice — the conceptual separation of nature and culture, when taken literally, becomes thoroughly unsustainable. A civilization or culture that is built on such an understanding will ultimately destroy itself, or will be forced to adopt a more holistic and participatory understanding of its role in natural process.
The historical epistemological bias that has favoured reductionistic and mechanistic analysis based on subject-object separation will have to be overcome and these methodologies will have to be integrated into the more dynamic and holistic perspective of conscious-process-participation.
Trans-disciplinary teams will have to develop the skill to shift between reductionistic analysis and holistic contextualisation; they will have to be able to switch between detached and participatory ways of knowing, thereby integrating the wealth of analytical knowledge into a holistic understanding of the complex dynamics that characterize the natural processes in which we participate.
Frederic Vester reports the work of the German systems-psychologist Dietrich Dörner, who studied problem solving as a method of information processing. In one of Dörner’s experiments a trans-disciplinary team of twelve specialists was given the task to improve the overall systems and infrastructure design of a fictional country in the developing world and the impact of their design strategy was modelled by computer over a century of repeated cycles of system intervention and modelled system change.
Dörner’s interest was not the adequacy of the computer model but how this team of experts would approach problem solving and planning and solution design, in order to identify common mistakes in the interaction with and intervention in complex systems. The list below summarizes six common mistakes that Dörner identified.
Six Common Mistakes In Dealing With Complex Systems
(After Dietrich Dörner, in Vester 2004, pp.36–37)
Inadequate definition of goals
Instead of focussing on increasing the ability and probability of survival for the system as a whole,the team concentrated on solving individual problems. The system was analysed for inadequacies and perceived problems. Once a problem was encountered the team eliminatedit. Then they would move on to the next problem, while they were often still engaged in correcting the results of their initial interference. This could be called repair-service-behaviour.
Lack of a joined-up systems analysis
A number of the specialists in the experiment were constantly engaged in the collection of a huge amount of data, which did result in enormous lists but were never joined up into a coherent understanding of the interactions involve. There was a clear lack of organizing principles — like feedback loops and limits — and therefore the data analysis made little sense. It was omitted to look at the cybernetic character of the system and study for example its historical development. This resulted in a lack of comprehension of the dynamical nature of the system.
The creation of irreversible emphasis
There is a tendency to home in on a certain emphasis and target issues that were initially identified as being the central parameters. If there are partial successes within a particular problem theme, it can become a favourite at the neglect of others. In the experiment this resulted in unawareness of certain severe consequences of particular actions, as well as a lack of action in various areas and consequential failure to resolve problems and discrepancies at hand.
Lack of attention to side-effects
Caught-up in the habits of linear-causal thinking, the team of specialists in the experiment identified the individual measures to be taken to improve the situation in a very goal-directed manner. In other words, little consideration was given to the possible side- effects of the proposed designs and action. This was even the case after the system had been identified as being governed by complex dynamics. At no point was the set of proposed interventions subjected to a policy test to distinguish between alternatives.
The tendency to over-steer or over-react
Dörner frequently observed the following: Initially interventions aimed at problem solving were made hesitantly and usually started small. If over the short term there were no visible effects on the system, what followed was usually a large scale intervention. When faced with the first unexpected feedback from the system — as the time-delayed effects of the initially small interventions had accumulated and now amplified the effects of the large scale intervention — the reactions was usually to hit the breakes or try to reverse the interventions.
The tendency to act in an authoritarian way
The power to have the ability to change the system, along with the belief that one has understood the system, often results in dictatorial behaviour, which is absolutely inadequate when dealing with complex systems. A more appropriate and effective way to affect complex dynamic systems as a participant is to change them while going with rather than against their flow. Frequently personal aspiration’s to gain professional or political prestige are the main drivers behind large-scale changes that jeopardize systems dynamics. Individuals try to impress through the size of the project they are proposing rather than its functionality. The striving for power and respect tend to negatively influence the way we deal with complex systems.
Frederic Vester emphasizes frequently that when we are dealing with complex systems the only realistic strategy is a careful holistic approach and not a precisely planned strategy. “Since complex systems require a constant dynamism in the way we think about them and therefore a rich heuristic structure — they have to include the entire range of ways in which humans can reach insights” (trans. Vester, 2004, p.38).
This reiterates another important point: In order to create appropriate design solutions that integrate into complex dynamic systems like a community, and ecosystem or the biosphere, we have to learn to include a wide variety of viewpoints into our decision making process. This integration has to span beyond trans-disciplinarity among academic disciplines to include indigenous or traditional ways of knowing and other participatory epistemologies.
Professor Vester summarizes three root causes of the most common mistakes that we commit in dealing with complex systems. These are: i) the reductionist and piece-meal way we employ when dealing with them, which makes us ignore their interconnectedness and dynamism; ii) the tendency to ignore feedback and focus on inappropriately chosen systems parameters; and iii) inappropriately short planning horizons that leave us unaware of time- delayed feedback (Vester, 2004, p.39). All three of these mistakes are also the most common causes of unsustainable design!
One way of approaching the creation of more sustainable solutions is to be aware of the common mistakes design teams make in dealing with complex systems, and to avoid those mistakes. Another way is to aim for a better understanding and increased intelligibility of the underlying dynamics and properties that define the behaviour of complex dynamic systems.
In traditional science, if you can predict and control the behaviour of a system you have defined it and therefore have understood and explained it. This can’t be done with living things, nor can it be done with the economy or the weather: all of which are complex systems.
Instead, complexity science uses simulation: an approach which can be defined as synthetic, because it is about creating rather than analysing (as in the traditional analytic approach). This lack of traditional prediction and control is not a crucial concern, because in practice we can get a sufficient ‘handle’ on complexity and complex systems to enable us to use the concept in a practical way (Battram, 1998, p.15).
The Nobel laureate and co-founder of the Santa Fé Institute, Murray Gell-Mann explains: “One of the most important characteristics of complex adaptive systems is that they cannot, in general, be successfully analysed by determining in advance a set of properties or aspects that are studied separately and then combining those partial approaches in an attempt to form a picture of the whole.” He emphasizes: “Instead, it is necessary to look at the whole system, even if that means taking a crude look, and then allowing possible simplifications to emerge from the work” (in Battram, 1998, pp.12–13).
Reductionistic approaches try to reduce complexity by separation, analysis and decontextualisation; holistic approaches try to embrace and absorb complexity by participation, synthesis and contextualisation.
Complex adaptive systems are constantly revising and rearranging their components in response to feedback from the environment. Examples are to be found in the evolution of organisms, the brain changing connections between neurons, firms reshuffling their departmental structure, countries realigning their alliances.
At some deep, fundamental level, all these processes of learning, evolution and adaptation are the same. And one of the fundamental mechanisms of adaptation in any given system is the revision and recombination of the building blocks. … New opportunities are always being created by the system. It is therefore essentially meaningless to talk about a complex adaptive system being ‘in equilibrium’: the system can never achieve balance. It is always moving on. …
Agents in the system can never ‘optimise’ their ‘fitness’ or their utility. The space of possibilities is too vast; they have no practical way of finding the optimum. The most they can ever do is to change and improve themselves relative to what the other agents are doing. In short, a complex adaptive system is characterized by perpetual novelty (Battram, 1998, p.36).
The implications for design are considerable. The activity of design as an expression of human intention critically affects the way we revise and recombine the ‘building blocks’ or the relationships within systems. Understanding the complex dynamics of perpetual change makes us acknowledge that sustainable design solutions can never be final since they have to evolve in co-adaptation with changes in the overall system in which they participate.
Any optimisation of an individual design can only be temporary and will have to be repeatedly reconsidered within the dynamic context of natural processes of change and transformation. In designing we should focus more on contributing to the dynamic flexibility, resilience and health of the overall process rather than on optimising the fit of our design to temporarily adapted cultural and economic paradigms.
In order to participate appropriately and adaptively in complex dynamic systems we need to aim to make their underlying dynamics more intelligible. This is the aim of complexity theory and the reason why it can provide an effective conceptual framework for sustainable decision-making and design.
Peter Reason and Brian Goodwin have suggested six principles of complexity: rich interconnections, iteration, emergence, holism, fluctuation, and the edge of chaos (Reason & Goodwin, 1999). The list below these principles with brief explanations.
Six Principles of Complexity
(Based on Reason & Goodwin, 1999, reproduced from MSc. in Holistic Science handout by Prof. Brian Goodwin)
Complex systems are defined in terms of rich patterns of interconnections between diverse components.
Complexity theory describes novel, emergent form and behaviour as arising through cycles of iteration in which a pattern of activity, defined by rules or regularities, is repeated over and over again. Giving rise to coherent order. The order arises as a rich network of interacting elements is built up through the iterative process and the consequences of the process emerge.
The order that emerges is not predictable from the characteristics of the interconnected components and can be discovered only by operating the iterative cycle, despite the fact that the emergent whole is in some sense contained within the dynamic relationships of the generating parts.
The emergent order is holistic in the sense that it is a consequence of the interactions between all the component parts of the system and is not coded or determined by the properties of a privileged part.
During the process of iteration and emergence there are critical phases characterized by fluctuations in state variables whose amplitude can be described by a well-defined pattern (a power-law distribution) in which most fluctuationsaresmall,afewarevery large, with characteristic pattern in between. These fluctuations presage the novel, emergent order.
Edge of Chaos
Living systems are most creative, with the greatest potential for discovering order that expresses an emerge nt property of the whole system, when they are living near the edge of chaos.
It is important to understand how all these properties relate to each other and to keep in mind that they are concepts used to create a new explanatory metaphor (complex dynamic systems) — a dynamic and fuzzy map that is less detailed and precise than that provided by reductionist analysis, but a map that captures the dynamics of the overall system and may therefore guide appropriate participation.
The properties of complex systems are simultaneously cause and effect of each other and of themselves. Stuart Kaufman defined complex systems through the rich patterns of interconnections between their diverse components. Rich interconnections enable diverse components to interact in multi-causal feed-back loops. Iteration, the repeated interaction of diverse components following relatively simple rules and definable constraints is a very important property of complex dynamic systems. It is through this cyclical pattern of iteration within dynamic networks that novel forms, behaviours and properties can emerge (Reason & Goodwin, 1999).
Emergence … refers to the arising of novel and coherent structures, patterns and properties during the process of self-organization in complex systems. Emergent phenomena are conceptualised as occurring on the macro level, in contrast to the micro-level components and processes out of which they arise (J. Goldstein, 1999, p.49).
Emergence is a key concept within the theory of complex dynamic systems. It describes the unpredictable and uncontrollable manifestation of novel properties arising out of complex interactions of diverse components. Emergence, therefore takes place at a higher explanatory level and the novel forms, behaviours and properties of the whole system “are neither predictable from, deducible from, nor reducible to the parts alone (J. Goldstein, 1999, p.50).
The use of the construct of emergence as an explanatory metaphor can lead to a pivotal change in our way of understanding dynamic systems. It is central to the perspective developed in holistic science (Wahl, 2001, p.2).
Due to the non-linear and iterative relationships that create complex multi-causal feedback between the different components, the systems self-organizing properties transcend the properties of its parts and reductionist analysis fails (Reason & Goodwin, 1999).
Accepting the fundamental unpredictability and uncontrollability of emergence, redirects our intention from control and prediction of complex systems to increasing contextual intelligibility through explaining relationships and dynamics holistically rather than predicting or controlling outcomes.
Holism could be defined as a way of understanding emergent phenomena within the dynamic context of the transforming whole and accepting that they are not predictable from the properties and interactions of any of the individual parts (Wahl, 2001, p.5).
The periodical emergence of radical novelty that characterises the behaviour of complex dynamic systems arises through the amplification of random events in far from equilibrium conditions. Iteration drives this amplification of random events that makes emergent properties so radically unpredictable (J. Goldstein, 1999).
By simulating the behaviour of complex systems through computer models it has become apparent that a second source for radical unpredictability in complex dynamic systems is their sensitivity to initial conditions, since the smallest differences are amplified by each successive iteration. “The long term trajectory of the system is highly sensitive to the starting point” (Stacey et al., 2000). Chaos theory refers to this amplification through iteration as the butterfly effect, often used to illustrate how localized changes within complex dynamic systems can ultimately cascade up to result in global change.
Reason and Goodwin emphasize that there is no privileged set of components that code for the emergence of holistic order, “it is a consequence of the interactions between the component elements of the system” (Reason & Goodwin, 1999, p.285). The distinctive pattern of fluctuation in the variables, that defines deterministic chaos, changes as the system emerges out of chaos into novel, emergent order. A mixture of nascent order and chaotic dynamics are preconditions for the emergence of novel properties.
This region of the dynamic spectrum, where outdated order dissolves into a creative and responsive chaos from which novel order can emerge, is often referred to as “the edge of chaos.” Stuart Kaufman suggested: “The best place for a system to be, in order to respond appropriately to a constantly changing world, is at the edge of chaos.” He explains: “Here order and disorder are combined in such a way that the system can readily dissolve inappropriate order and discover patterns that are appropriate for changing circumstances” (in Reason & Goodwin, 1999, p.286).
Brian Goodwin concludes: “Life exists at the edge of chaos, moving from chaos into order and back again in a perpetual exploration of emergent order” (Goodwin, 1994). In an essay written during the Masters in Holistic Science programme I summarized the relationships between the six principles of complexity proposed by Reason and Goodwin as follows:
Thus, the aim of holism is to make the emergence of novel phenomena out of iterated interactions among richly interconnected components in a complex system more intelligible by relating their emergent properties to the dynamic process of a perpetually transforming whole.
Emergence occurs in a dynamic region, called the edge of chaos that is characterized by a change in the distinctive patterns of fluctuation in the system’s variables. The emergence of order out of chaos is not due to a deterministic, previously existing blueprint, but due to the intrinsic dynamics or repeated interactions among the diverse components [participants] of a complex whole (Wahl, 2001, p.5).
According to Goodwin, emergent properties can be recognized “by their qualities, which are expressions of the coherence of the whole.” Brian Goodwin explains: “Emergent properties are unexpected types of order that arise from interactions between components whose separate behaviour is understood. Something new emerges from the collective — another source of unpredictability in nature.” He continues: “The complex systems on which our lives depend — ecological systems, communities, economic systems, our bodies — all have emergent properties, a primary one being health and well-being” (Goodwin et al., 2001, p.27).
One of the central propositions made in this doctoral thesis is that design can only be sustainable if it participates appropriately in natural process. To achieve this goal, design should aim to facilitate the emergence of health and well-being throughout the whole system. Chapter three will address to what extent complexity theory can help to inform this kind of salutogenic design. The important point here is that complexity theory shifts the underlying intention of both science and design from control, manipulation and prediction to appropriate participation in natural process.
The sciences of complexity suggest why we cannot control the processes that underlie the health of organisms, eco-systems, organizations, and communities. They are governed by subtle principles in which causality is not linear but cyclic, cause and effect are not separable and therefore manipulable.
Those systems are the cause and effect of themselves, involving ever increasing loops of mutual dependence … there is dependent co-arising between human action and the context within which it is entangled … (Goodwin, 1999a).
Equally there is dependent co-arising between design and the context within which it is entangled. Many past design decisions created the context of today’s design decisions. Many of the designs of the last two centuries have been created mainly with their economic and cultural context in mind. Environmental and cultural disintegration and climate change are the effects of disregarding the ecological and social contexts within which design is entangled.
Emergent properties are distinct behaviours or attributes of complex dynamic systems, that are characteristic to “each level of biological organization from molecules to ecosystems” and function synergistically at each level to give that level a life of its own which is greater than the sum of its parts” (Marten, 2001, p.43).
When systems are understood as integral and whole systems in a process of constant transformation, we begin to understand that their overall survival depends on the interactions and relationships of their parts and how they fit together. Analysis of the parts in isolation fails to account for the complexity and non-linear relationships that characterize the system as a whole. “Because the parts are interconnected, the behaviour of every part is shaped by feedback loops through the rest of the system” (Marten, 2001, p.43).
The self-organization of complex biological wholes, from cells to ecosystems and the biosphere as a whole can be made more intelligible through the theory of complex dynamic systems. For example, Marten provides the following description of self-organization and emergence in ecosystems:
The core of ecosystems organization resides in an ecosystem’s biological community — all the plants, animals, and microorganisms living in an ecosystem. The particular species in the biological community at a particular place are drawn from a larger pool of species living in the surrounding area. Selection of those species, and their organization into a food web, happens by a process known as community assembly. … The community assembly process is an emergent property of the ecosystem (Marten, 2001, p.47).
Marten suggests: “Ecosystems and social systems are complex adaptive systems.” He explains: “Complex because they have many parts and many connections between the parts; adaptive because their feedback structures give them the ability to change in ways that promote survival in a fluctuating environment” (Marten, 2001, p.42).
Design, planning and decision-making are obvious ways in which a social system can adapt to feedback from its environment. The fundamental re-design of humanity’s interaction with and integration into natural process will be best guided by notions such as complex adaptive systems, participatory responsibility, and salutogenic (health-generating) design adapted to multiple scales.
John Tillman Lyle spoke of a new era of design, which he referred to as the “emerging era of predictive adaptation”, but not in the sense of the predictive power based on the deterministic abstractions of reductionist science. Lyle acknowledged the unpredictability that comes with the complexity of understanding things in their multiple scales of context. He pointed out that “it is unlikely that prediction in design, occurring as it does in the infinitely variable world of reality, will ever be entirely deterministic. … The intangible and the ineffable always enter in” (Lyle, 1985, p.264).
Lyle proclaimed a spirited vision for a new era of design, which is now beginning to unfold through an urgently needed sustainability revolution empowered by a much larger and more integrative and holistic concept of design as an expression of a change in human intentionality and the dominant worldview. Lyle’s vision reads:
Even though the possibilities are infinite, we need to be willing to explore them. The exploring involves both halves of the brain: imagining future landscapes and analysing their behaviour. I believe it is one of the promising achievements of our times that so many people are taking part in the imagining and predicting. Genuinely participatory processes are beginning to take place, in design if not in government, but these do not simplify or clarify design process. Rather they add layer upon layer of varied values and perceptions.
It is important to recognize that, however sophisticated our tools and techniques, the unexpected can always occur. With prediction goes uncertainty. Recognizing the inevitability of uncertainty and having done all we can to shape a system that will behave as predicted, we need to minimize the possibility of catastrophe when it does not. We need to be as sure as humanly possible that when the unexpected does occur, it does not bring about disaster. This means checks, balances, feedback, complexity, sometimes a conservative stance. In ecosystem design, the whole stake should never ride on the role of the dice (Lyle, 1985, p.264).
Natural design aims to create expressions of appropriate participation in natural process. As such it does not suggest final nor universal solutions, rather, as a process natural design aims to integrate appropriately into the conditions of the local environment through expressing the continuous, community based, learning process that reflects sustainability as a process of co-evolution and co-adaptation of culture and nature in place.
Complexity theory provides an adequate and useful conceptual framework and explanatory metaphor for a new design theory based on appropriate participation in natural process and salutogenesis as the guiding principles behind sustainable design (see chapter two). Complexity theory also provides the conceptual framework for the idea of scale-linking sustainable design solutions across a wide range of scales from product to settlement to bioregion to biosphere (see chapter four and five).
The “complexity revolution” (Goodwin 2005, personal comment) coincides with the emergence of a more widespread participatory consciousness and a more ecological worldview. In chapter three, I will describe what I call the emergence of the natural design movement as a manifestation of this change towards a participatory worldview.
The new science keeps reminding us that in this participative universe, nothing lives alone. Everything comes into form because of relationship. We are constantly called into relationship — to information, people, events, ideas, life. Even reality is created through our participation in relationships. We chose what we notice; we relate to certain things and ignore others. Through these chosen relationships we co- create our world. If we are interested in affecting change, it is crucial to remember that we are working within webs of relations, not with machines (Wheatley, 1999, p.145).
One of the most effective ways to catalyse the transformation towards sustainable human participation in natural processes is to facilitate the availability of appropriate information to the diverse agents within the complex dynamic system of human society.
The emerging global to local network culture which links responsible and engaged citizens in communities and NGOs worldwide is the medium through which appropriate information can spread and affect the system as a whole. Education as a means of inter-and intra-generational spread of appropriate information clearly plays and important role in the transformation towards sustainability (see chapter five).
How we classify knowledge and information as reliable critically affects our worldview and thus how we design and make decisions. I refer to these up-stream regions of design as meta-design (see later in this chapter, and chapter six). The intention of appropriate participation in natural process and the aim for long term sustainability are the logical consequences of a worldview that integrates culture and nature. In order to meet human needs while expressing this fundamental intention and aim, natural design will have to integrate into natural process by learning from natural process (see chapter three).
The adaptive learning process that expresses sustainability can be coherently structured based on an understanding of complex dynamic systems as self-organizing and self-making networks within networks, systems within systems, or processes within processes.
The Buddhist Monk and poet Thich Naht Hanh beautifully expresses such an interconnected process-oriented, participatory way of relating to natural complexity and emergence in his description of a sheet of paper and the notion of inter-being. From within a more holistic worldview and consciousness a sheet of paper turns into dynamic relationships and interdependences:
If you are a poet, you will see clearly that there is a cloud floating in this sheet of paper. Without a cloud, there will be no rain; without rain, the trees cannot grow; and without trees, we cannot make paper. The cloud is essential for the paper to exist. If the cloud is not here the sheet of paper cannot be here either. So we can say that the cloud and the paper inter-are. “Interbeing” is a word that is not in the dictionary yet, but if we combine the prefix “inter” with the verb “to be,” we have a new verb, inter-be.
If we look into this sheet of paper even more deeply, we can see the sunshine in it. Without sunshine, the forest cannot grow. In fact, nothing can grow without sunshine. And so, we know that the sunshine is also in this sheet of paper. The paper and the sunshine inter-are. And if we continue to look we can see the logger who cut the tree and brought it to the mill to be transformed into paper. And we see wheat. We know that the logger cannot exist without his daily bread, and therefore the wheat that became his bread is also in the sheet of paper. The logger’s father and mother are in it too. When we look in this way, we see that without all these things, this sheet of paper cannot exist.
Looking even more deeply, we can see ourselves in this sheet of paper too. This is not difficult to see, because when we look at a sheet of paper, it is part of our perception. Your mind is in here and mine is also. So we can see that everything is in here with this sheet of paper. We cannot point out one thing that is not here — time, space, the earth, the rain, the minerals in the soil, the sunshine, the cloud, the river, the heat. Everything co-exists with this paper. That is why I think the word inter-be should be in the dictionary. “To be” is to inter-be- we cannot just be by ourselves alone. We have to inter-be with every other thing. This sheet of paper is, because everything else is.
Suppose we try to return one of the elements to its source. Suppose we return the sunshine to the sun. Do you think that this sheet of paper would be possible? No, without sunshine nothing can be. And if we return the logger to its mother, then we have no sheet of paper either. The fact is that this sheet of paper is made up only of “non-paper” elements. And if we return these non-paper elements to their sources, then there can be no paper at all. Without non-paper elements, like mind, logger, sunshine and so on, there will be no paper. As thin as this sheet of paper is, it contains everything in the universe in it (Thich Naht Hanh, 1991, pp.95–96).
[This is an excerpt from my 2006 PhD Thesis in ‘Design for Human and Planetary Health: A Holistic/Integral Approach to Complexity and Sustainability’. This research and 11 years of experience as an educator, consultant, activist, and expert generalist in whole systems design and transformative innovation have led me to publish Designing Regenerative Cultures in May 2016.]
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