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Framework(s), Part IV
Freire (1994, p. 71) wrote:
Dialogue cannot exist without humility. The naming of the world, throughwhich people constantly re-create that world, cannot be an act of arrogance.Dialogue, as the encounter of those addressed to the common task of learningand acting, is broken if the parties (or one of them) lack humility. Howcan I dialogue if I always project ignorance onto others and never perceivemy own? How can I diglogue if I regard myself as a case apart from others--mere"its" in whom I cannot recognize other "I"s?
In addition, he wrote (1970, pp. 77-78) about dialogue as the creationand re-creation of meaning and suggests that creation is an act of love."Love is at the same time the foundation of dialogue and dialogue itself."
I will try to make a modest attempt at addressing some of Shealagh'sexcellent questions, after I have had some lunch. It is a cloudy, overcastday here at Lac Maskinonge, a good day for reflection and writing.
I've been away from e-mail and the dialogue for a couple of weeks, sonow that I'm refreshed, I'm keen to jump in again. Shealagh's provocativequestions were just the motivation I needed! In the spirit of her reminderthat this is indeed a "dialogue", and following on Ann's thoughtson same, here are some thoughts of my own in response to a few of Shealagh'squestions.
>Ann asked me to comment on the idea of "plural methodologies"and >"bricoleur". Well, I looked up bricoleur in the directionaryand it >said "handyman" "putterer" and I am at aloss to make the connection.
My reading of this is that Ann used the term "bricoleur" asshort-hand, in the same sense we raised it at our June workshop. To refresh,we discussed Denzin & Lincoln's (1994) concept of the "researcheras bricoleur" (where they translate bricoleur as one who cobbles together,from the verb "bricoler"; a Jack-of-all-trades or do-it-yourselfhandyman). The point being, that in highly contexualised social research,in which people don't behave predictably, where uncertainty is pervasive,and the researcher is part of the action, problem and solution (it's self-reflexive)the researcher MUST create a mosiac of approaches; must cobble togetherand assemble context-specific methods appropriate to the problem. In sodoing, according to Denzin & Lincoln (1994), the research method isa "bricolage" or unique mosaic that is essentially an emergentconstruction specific to the problem. In Ann's research (and many of ourown no doubt), what she and we are doing is precisely that. I would alsoadd that any social research that uses a systems approach (with plural methodologiesand multiple perspectives tailored to the problem) is effectively doingthis as well.
>The question that comes to mind, having reread the postings to thedialogue >over the last month or so, is how do we reconcile or integrateor make use of >these multiple contexts, perspectives, and plural methodologies?I want to >know how to make this theory operational.
Surely the $100,000 question for all practioners... I think we startwith an explicit acknowledgement of power distribution and the power structureitself in decision-making (in whatever problam context you're working).It is, as Shealagh has illustrated in her Lands for Life example, of littleuse, certain;y not legitmate, and downright fraudulent to advertise an opendoor to decision-making with, say, a round table approach, and then to slamthe door in participants faces. Operationally, in my experience with mydoctoral research, truly plural methodologies are time consuming, epistemologicallycumbersome and ultimately frustrating (since the university itself adoptsthe opposite approach). However, the best example of a plural methodologyI've used in practice is a systems approach: e.g. in my research, whichuses overall a systems methodology, I use reductionist biology to identifyand map smaller scales of an ecosystem in question; I use mulit-stakeholderprocesses such as visioning and round table meetings to deceide on the planninggoals for that system; and I use social interview methods to question managers(among other phases of inquiry). This is of course simplified since I amone person and this is a PhD project, whcih is only part of a much morecomplex and longer term/bigger scale community ecosystem planning project.Imagine the complexity of doing so at the Federal gov't level over decadesfor SD!!!
Also, I want to add that the Ursula Franklin example is nice for demonstratingflexibility, and that is certainly part of a systems approach, which alsoadvocates adaptibility and plurality of perspectives and methods. (Beinga mother of a toddler and a researcher, teacher, consultant myself, I probablyagree that this is a better example in operation than any of the above...at least where adaptibility and emergent capacity for stress recovery andresilience are concerned! OK, come to think of it, it's also a pretty goodexample for multiple perspectives, since I tend always to find several pathsto doing a task -- the one that offers the least resistance gets chosenand it is unlikely to be the same twice!!!) A great example, SHealagh!
>Are there "learning institutions" out there that we canlearn from? Peter Senge offers quite a few drawn from corporate organisationin his book "Fifth Discipline" (1990) -- but none that even comeclose to the complexity and rigidity of government -- and none that demandthe direct dealing with issues of power and control in the face of civilsociety.
>How do we see integrating perspectives that are opposed? I thinkof >the current "Lands for Life" (the name makes me so mad)process in >which the government of Ontario has abused the round tablesystem for >all that it is worth (...)
I think this example makes the point very well that we HAVEN'T trulyintegrated opposing or conflicting perspectives at all -- in the Lands forLife example, (I also choke on that euphemism) we've simply excluded andoverridden other voices. So it's a successful example of marginalisationand silencing while maintaining the illiusion of inclusion yet practisingexclusion -- surely the worst participatory fraud yet in my books. Again,I think that truly participatory or better yet, collaborative approachesdemand an explicit addressing of power, control, domination and marginalisationissues first.
>Ann called for "pluralistic fora" - you've lost me there- can you >define what a pluralistic forum might look like?
I read this to mean a variety of venues/means of expression for thatmultiplicity of legitmate voices and values we've so often referred to.According to my interpretation of this, round tables in which opposing andconflicting values are really heard, considered and meaningfully factoredinto the decision-making are one venue; healing circles are another; facilitatedvisioning workshops including adversarial participants are yet another....
>Is information really a new emerging reality? Has it not been centralin >the past? Or is it that the speed at which we can process it, moveit >around, analyze it that makes it more central, more key?
This is really a great question! I think it has more to do with the volume(deluge) and type, than information in and of itself. I recall this quotewhich I think captures part of the reason why information in terms of volumeand type really is more important now than previously: "The irony ofthe Information Age is that it has given new respectability to uninformedopinion" (John Lawton). Although you can read this two ways, I wouldadd that it has simultaneously and paradoxically, also given new power anda voice to those previously kept silent, e.g. the fishers referred to byChristine, or other wise practioners of a craft, art or science who havepreviously been excluded from the "expert" model of dec-makingbecasue of their lack of (one model of) credentials. An example of the dangersLawton alludes to in his quote: in the university teaching and learningcommunity, we must be especially vigilant to establish the credibility ofinformation on many of the internet sites cited by our students; we mustdetermine which are devoted to psuedo-science, bad science, nonsense anduninformed opinion versus those with credible, traceable or accountableinformation, depending on a variety of criteria.
>Nina Marie states that "a systems approach is not a recipe foraction, >but an applied way of conceptualising a problem and a path toa >negotiated, collaborated solution (Gallopin per. comm. 1996; Lister>1998). It is neither prescriptive nor sequential in operation, but >rathermay be described as a set of guiding principles with common >elementsthat must be shaped to each unique problem context". So what >constitutesthat set of guiding principles?
Thanks for the pragmatic reminder to operationalise! As I said, usinga systems approach is never prescriptive. Indeed that is what separatesand distinguishes it as a methodology and set of methods from "normalscience" or hard science. Consequently it is impossible to say whatthe detailed and specific guiding principles are for each case or problem,since they will vary with each context (recall, the research as bricolageand the researcher as bricoleur). However, there are principles which aregeneric and dynamic -- such as those we are developing here. In effect,we are developing the guiding principles for a framework for SD, which Annwill then tailor these to context-specifc SD issues.
We can take, e.g. the principle of plural methodologies, and tailor itto Shealagh's suggested fisheries problem: we might suggest a potentialhybrid of methods for this problem would be, 1. listening and incorporatingmultiple perspectives (another principle) of the fishers and scientistsand so on; 2. using reductionist biology of species' habitat and populations*as well as* a systems approach using scaled mapping of the energy budgetsof ocean habitat (e.g. -- I don't really know); and 3. a social interviewmethod to survey the fishers, Atlantic taxpayers and whoever else is a stakeholderidentified by us and then a round table to determine our planning and managementgoals. (A rough approximation of the complexity involved!)
This concludes my off-the-cuff rambling. Please forgive all the sillytypos -- my kid is at this moment dismantling my kitchen and I haven't tijmeto proof-read this before I hit the "send" button (or he wrecksthe house)!
After a long absence and after more than one increasingly (and rightfully)pointed emails from Ann, I managed to find the time to go through the manymessages that gathered in my special folder called "Ann's dialogue".It was an exciting journey, I even discovered that I was assigned to explorethe principle on scale and subsidiarity a number of weeks ago. It is maybenot by coincidence that I will be presenting a paper at the Woodlands nearHouston this weekend on the need to harmonize the interpretation of sustainabilityacross scale and systems, in this case across the public and private domain.
Scale and subsidiarity in the context of SD are extremely rich conceptsand it is unlikely that I can attempt anything like a full definition. Butlet's start with a definition for subsidiarity that already exists. Thisis from the Winnipeg Principles on Trade and Sustainable
Subsidiarity is the implementation of environmental measures at a domesticjurisdictional level appropriate to the source and scope of the problemand appropriate to effectiveness in achieving objectives. Where there aresignificant transborder impacts, there should be international cooperativeefforts.
While the principle sounds right, I think it is based on an importantassumption. The assumption is that we are able to correctly assess the scopeof problems we are dealing with and the scope of the impact of our measuresto make sure there is a match. More often than not this is not the case,which is one of the problems. Without the appropriate system of knowledge,the individual participant in the commons has limited vision, both fromthe spatial/organizational and temporal perspective. His or her feedbackloops are short cycled, while the feedback loops in the whole system context(i.e. the entire pasture) are long. The other problem is that there aremultiple spatial and temporal scales at any given time for any given issuethat would call for matching policy and other responses on several scalesat the same time. In most cases this is, well, difficult. What seems tobe necessary that we uderstand that impacts and problems present themselveson multiple scales, that we understand the potential dangers of mismatchesbetween scale of problem and scale of reaction, and that we develop operationallyacceptable ways of scanning across scales to identify and prioritize them.This is about expading the analytic and planning horizon, though it soundstoo technical: it is in fact about the expansion of our perceptive horizon,keeping in mind that reconcentration and 'scanning' are both necessaryfromthe practical point of view.
The Newtonian paradigm made its impact on our perception of scale: wethink about scale _clusters_ and organize policies and organizations aroundsuch clusters as well. In fact there is an uninterrupted continuum of scales.In "Beauty in Proportions" Illich compares two two on the basisof the Greek lyra and the piano, metaphors for continuum / wholeness andreductionism, respectively. So settig the right scale assumes a sense ofright proportions. The ancients did this on the basis of tradition and religion;we are attempting to do it on the basis of science and economics, for betteror worse.
So much for now, but I think there are many more implications here thatmay need to be discussed.
I,ve enjoyed reading through all your generic principles"here ismy vastly belated contribution; I hope it is of use.
>FROM LINEAR TO CYCLICAL PRODUCTION
To meet the basic human needs of a growing population, within the assimilativeand regenerative capacities of the planet, will require a minimum ten-foldincrease in the efficiency with which we produce goods and services. Thisis a formidable challenge.
Some of the solutions are being found by better understanding how toobserve and respect the basic laws of nature within the industrial productionsystem. Such a perspective spotlights the causes of energy and materialinefficiencies in the industrial system, which are also sources of pollutionand solid waste.
A sustainable industrial system will require, among other elements, theintegration of the laws of energy and matter into the design of industrialsystems. The second law of thermodynamics tells us that when energy is changedfrom one form to another, entropy is increased: some of the energy is alwaysdegraded into lower-quality, less useful energy. The law of conservationof matter tells us that there is no "away""we can neithercreate nor destroy matter. Thus all of our production and consumption activitieslead to some degradation of energy and some "waste" matter tothe environment. The challenge is to minimize entropy, and find new, productivefunctions for what we currently class as "waste" . Achieving thiswill require major innovations in public policy, to create the appropriateincentives to drive such changes.
The industrial model of production was designed for high energy and materialthrough-put, for a world in which the notion of natural resource and assimilativecapacity limits was foreign. Increased production has historically beenaccompanied by a proportionate increase in energy and raw material inputs,pollution, and solid wastes. This is similar to primitive ecosystems, whichrely on unlimited supplies of energy and materials, and unlimited assimilativecapacity of sinks.
In the more advanced industrial economies in the last 25 years or so,production levels have begun to decouple on a per-unit basis from inputand output levels. This has been achieved with the more efficient use ofenergy, more accurate technologies through automation, and the introductionof pollution control and more successfully pollution prevention measures.However, the overall pace of production and consumption increases, of wealthand population growth have vastly outstripped the net gains of these efficiencies.The design of the industrial system has also evolved to build in significantenvironmental inefficiencies from a life-cycle perspective: globalizationis making it increasingly transportation intense, and automation is substitutingenergy for human and animal labour.
A long term solution to environmental and resource problems will requireshifting towards an industrial system modelled on a mature ecosystem---onewhich first uses energy and materials with maximum efficiency, then completelycycles all materials and thus produces no waste, and finally is sustainableas a self-contained system with only solar energy as an external input.
What are the elements for such a model? (Note"I can,t even try tobe comprehensive here, but only hit on some key themes)
The first is to use energy and materials with maximum efficiency. Thisis where we have the most applied experience in industrial environmentalmanagement. Most efforts to date have focused on the manufacturing stageof the product life cycle only, but attention is rapidly broadening to theentire system that supports a product or service through its entire life-cycle.
Some steps in this direction are familiar ones"basic industrialenergy efficiency and following the waste management hierarchy (reduce,reuse, recycle, recover). Waste minimization/ pollution prevention/ cleanerproduction programs have targeted energy and materials use efficiency withinindividual manufacturing facilities. More recent interest has focused on"industrial ecology", which seeks to exchange waste heat and materialsbetween manufacturing facilities, thus creating a form of industrial symbiosisbetween facilities in, for example, an industrial park. More recent stepsin energy and materials efficiency are focusing on maintaining the entropyof the product/ component/ or material, once the energy, materials, andhuman resources investment has been made. This introduces a new set of "R"sand begins to move us outside of the manufacturing stage of the productlife cycle, into the end-of-life design of products. In order to minimizedowncycling, products need to be designed for repair, refurbishment, remanufacturing,reuse and recycling. In Europe, these steps are being encouraged throughwell-designed extended producer responsibility programmes, which can bedesigned to create a direct financial incentive for companies to designproducts for minimal end-of-life environmental impact.
The second element, complete cycling of materials and (virtual) eliminationof wastes, is one in which we have little experience. These newer frontiersin industrial environmental innovations are found when looking at productsand services at a system level. Are there ways of reducing the materialintensity of the entire product system, for example by re-casting the functionof a product from a physical function to a service; and to extend the lifeof products? Thus Interface Inc., a flooring company, now leases flooring"services" rather than selling floor covering. This gives thecompany maximum control over end-of-life management of their product, andmaximizes their incentive to make their product durable and upgradable,and their material resource needs self-sufficient through material cycling.This stage also forces the examination of system inefficiency issues suchas transport distances that are otherwise frequently externalized.
A next step will involve full dematerialization of some activities andproducts"by shifting from material consumption to digital consumption.We have already seen shifts towards teleworking and teleshopping; the fullrange of application of this "atoms to bits" revolution is onlyjust emerging. While it appears to hold tremendous potential, a key questionis whether it will actually substitute for existing material consumption,or will there be a rebound effect in which total consumption levels continueto increase?
The physical and system design changes that are needed to achieve a moresustainable industrial system are massive. Just as extensive are the changesin public policy that will be required to support or drive those changes.Three important ones from my perspective are:
- the internalization of environmental costs;
- the systematic tracking of environmental inputs and outputs at themicro level (through EMS requirements and LCAs) and macro levels, accompaniedby mandatory and third-party audited public reporting;
- the phasing in of extended producer responsibility for most products;.there,s a lot more but ..
The above can certainly be elaborated on; please feel welcome to sendme any comments or disagreements;
Ann asked me to comment on feedback. I find it difficult to do so withoutgoing back - 'WAY back - to remind myself about fundamental principles ofholism, reductionism, and thermodynamics, and then to segue into some underlyingcharacteristics of complex systems (of which feedback is an integral part).The result, unfortunately, is a lengthy digression, probably more for myown benefit than our collective good - but here it is anyhow. I startedwith really fundamental stuff (skip it if you're bored!), then attemptedto pick up where Nina-Marie left off with her lucid comments on complexsystems. Apologies for any redundancies. For those of you with enough enduranceto read all the way through, please use this as an opportunity to commenton our congruencies or divergences of perspective - after all, this wholething is supposed to be about feedback.
Thanks to all those more expedient than myself - I have enjoyed and learnedfrom all your submissions.
FEEDBACK AND COMPLEX SYSTEMS
Nina-Marie provided a very useful generic definition of a system as '...aset of elements connected by a process that together forms a whole'. Thedemarcation points or boundaries of such systems are somewhat arbitrary,and inevitably coloured by the prejudices and perspectives of the observer.Yet the concept of systems, despite our limitations in defining their boundaries,is still a very useful one for creating a collective myth of understanding,decision making, and ultimately policy and governance.
General systems theory provides us with some accessible middle groundbetween the extremes of holism and reductionism. A holistic perspective,where the determining factors in nature are wholes, not reducible to thesum of their parts, gives us feeble-minded humans real difficulties. Ifphenomena are overly complex and multi-faceted, they become 'un-knowable'by the human mind. Similarly, a reductionistic perspective, where complexphenomena are broken down into simple components or isolated parts, presentsequivalent difficulties: if phenomena are over-simplified into chunks thatare easily understood by the human mind, they cease to resemble reality(except for the simplest of mechanistic examples - which I will use liberallyfor illustrative purposes later on). At the extremes, neither of the approacheshas any predictive value, nor do they effectively provide us with learningcontent that we can act upon.
One attempt to break this impasse in the scientific establishment comesfrom the field of cybernetics, the study of systems and controls in naturalphenomena. This approach attempts to 'reassemble' simple components intointellectually manageable systems, small enough to be understood by theaided or unaided human observer, yet large enough to generate the 'surprises'which are the hallmark of most real-world processes. One goal of such endeavouris to develop better predictive abilities about the behaviour of complexsystems. Aided by remote sensing and computer algorithms, we have becomepretty good at predicting weather patterns, for example, at least on a day-to-daybasis. Other attempts at predictive modelling have been unsuccessful - sometimesspectacularly so. But perhaps the greatest value of cybernetics to datelies in its second goal: the attempt to discern some of the 'generic characteristics'of complex systems themselves. One such generic characteristic which hasmanifested itself appears to be feedback...more on that later, after another(hopefully relevant) digression.
In purely physical terms, the functioning of the ecosphere can be describedvery simplistically yet fundamentally in terms of two flows: energy andmaterials. (A third flow, information, is in a sense an emergent phenomenonfrom the first two - more on this later). All these flows are governed bythe apparently ineluctable first and second laws of thermodynamics: 1) Energycan be neither created nor destroyed, it can only change form, and 2) theuniverse is tending towards a state of disorder (or maximum entropy). Thecorollary of this is that, over astronomical time periods, energy is beingtransformed from concentrated forms into less concentrated forms (e.g.,our sun is slowly burning out, radiating its concentrated thermonuclearenergy into the cold void of space), and materials are becoming ever moredissipated and mixed up, unless energy is applied in some way to re-concentrateand re-consolidate the materials in concentrated forms.
In systems apparently devoid of significant quantities of life, suchas the other planets in our solar system, system characteristics can bedescribed quite accurately in terms of physical phenomena: for example,concentrations of gases in the atmosphere (where present) can be describedby simple laws of chemical equilibrium, and the surface characteristicsand composition of the planets are largely consistent with our known physicallaws.
Yet even in lifeless physical systems, and despite the fact that theuniverse is tending towards chaos and oblivion, there is still ample evidenceof pattern and order that appears, apparently spontaneously, out of thechaos. Examples might include the patterns of waves in the sands on thesurface of Mars, or the exquisite crystalline regularity of a snowflake,or
the orderly patterns of bubbles which appear in water boiling in a beaker.We cannot predict the position or movement of any single grain of sand thatis moved on a shoreline by ocean waves, yet the orderly patterns of ripplesmarching across the beach are, at least to our eyes and at our temporaland physical scale, a model of regularity and organization. These patternsin purely physical systems are manifested only when there is some net lossof energy and net increase in entropy, so they are not inconsistent withthe laws of thermodynamics - yet the patterns and organization which emergefrom the systems are highly ordered, and do so in an apparently spontaneousfashion.
Systems which generate such 'emergent phenomena' - the apparently unpredictableand spontaneous patterns of self-organization - are referred to alternativelyas 'complex systems', 'SOHOES', 'adaptive systems', or 'resilient systems'.(The terms are congruent enough, I believe, to be viewed as functional synonyms).The behaviour of complex systems is not predictable based upon our knowledgeof the properties of the individual components of the system. Emergent phenomenamanifest themselves even in what appear to be relatively simple, deterministicphysical systems. Such systems become more stable and resilient when additionalsystem components are added (James Lovelock's Daisyworld model is a goodexample), as long as these components are 'connected' in some sort of redundantand parallel fashion, not in a rigid, linear, or obligate sequential fashion(like John Middleton's watch example).
Complex systems are comprised of many parts, and the detailed 'struture'of the individual parts does not affect the details of the other parts.However, unpredictable system properties, or emergent phenomena, are derivedfrom the interaction of the parts.
There are a few concepts emerging from the ongoing study of complex systems:hierarchy, metastability, and (I told you I'd get to it eventually!) -feedback.
Hierarchy exists (or, rather, can be discerned - or perhaps imposed?)within all complex systems. Our perception of the properties of the systemare profoundly influenced by the level of the hierarchy we are using asa frame of reference, as well as the criteria we use for establishing ordefining the hierarchy. For example, let's consider a hierarchical spectrumwhich ranges from subatomic particles to the global ecosystem. We can rankthe
subcomponents of the global ecosystem hierarchically in a number of ways.I'll choose two: physical and temporal.
"Subsystem" Interaction time
Quarks 10 to the minus 20 seconds
Neutrons/Protons 10 to the minus 12 seconds
Atoms 10 to the minus 8 seconds
Molecules 10 to the minus 5 seconds
Macromolecules 10 to the minus 3 seconds
Cells 10 to the minus 1 seconds
Populations | seconds -> hours -> days->
Communities | weeks -> months -> years...
The physical ranking is based not only upon size, but upon aggregationof subsystems: as we go down the list, we see a general trend of increasingsize, but more precisely of increasing aggregation, where subsystems higheron the list become subsumed as components of subsystems lower on the list.We also see a trend of increasing complexity, since the aggregate numberof subsystems increases as we go down the list.
We also can roughly measure the interaction times within such subsystems- for, example, the period of time it takes for an atom to combine withanother atom is somewhere in the realm of 10 to the minus 8 seconds. Ateach level of complexity, subsystem components interact with one anotheron about the same time scale. At lower levels of complexity, interactionsoccur too quickly to be 'perceived', and tend to average out and not benoticed - yet they are fundamental to the operation of the system. At higherlevels of complexity, interactions occur much more slowly, and they areeither used as 'parameters' for lower levels (e.g., the changing seasons),or they occur too slowly to be noticed at all.
(Speculatively - could the following be viewed as 'parameters' at higherlevels of complexity...John Robinson's indicators? Ice ages? El Nino? Therise and fall of civilizations? The cycles of bear and bull markets on thestock exchange? I'm sure there are lots of examples. Just freewheeling here...).
To anthropomorphosize, quoting George Cowan of the Santa Fe Institute(1989): "On every level of complexity, you're living on a common timescale horizontally, looking at something that operates much faster belowyou, and at something that operates much slower above you".
Thus, you're aware of the flirtatious glance of the attractive individualacross the room, but not of the macromolecular mechanisms which cause yourheart to speed up and your tissues to react, or of the role of your increasedexhalations of carbon dioxide in patterns of global warming.
Hierarchy can be discerned in physical phenomena (see list above), insocial aggregations (individuals, families, communities, nations, strategicalliances...), in corporate systems (offices, branches, districts, administrativeregions, head offices, corporations, corporate alliegences, the WTO, theglobal economy...), and so on. Recognition of the relationships amongstlevels in a hierarchy, and amongst different levels in different hierarchies,is key to understanding complex system interactions. by choosing differentclassification criteria to construct hierarchies, we get different resultsand different potential interactions.
Related to the concept of hierarchy is the concept of metastability -that complex systems may appear to be stable at some scale or level, butmay in fact be far from stable at another. Consider the arc of water emergingin a precise, lovely, mathematically perfect parabola from a Renaissancefountain. It appears to be stable from a distance; we can describe its shape,trajectory, and velocity very accurately - in fact, the fountain's architectsrely upon its predictability for its formal aesthetic appeal. But if welook closer, within the column of moving water, we see a chaotic braid ofgushings; if we look closer still, the motion of any single water moleculewithin the arc's boundaries is, for al practical purposes, completely unpredictable.
Complex systems are always far from static balance - I cringe when peoplerefer to 'the balance of nature', because the imagery evoked is not of adynamic living system but rather of some dead and mechanistic Newtoniangadget. Systems in static balance are no longer complex; they are stableand have simple properties which can be easily described and predicted -and they are usually devoid of life or its influence. Complex systems existin states of dynamic equilibrium on varying time scales. They may exhibitgradual, incremental changes, or be punctuated by rapid, transformative'flips' to other states of dynamic equilibrium. Since these systems operate'out of balance', their characteristics cannot be understood by lookingfor steady states. Instead, we have to look at system transitions, and thepatterns which govern or accompany these transitions.
One key to the interaction of components of complex systems is feedback.In the physical world, every transformation of materials or energy (let'scall it an 'event') has a detectable effect, not only on the material orenergy source itself, but on the environment surrounding that material orenergy source as well. Events will always be manifested in the surrounding
environment in some way, often in the form of generalized emanations(like the movement of air and particulates and the release of heat and lightthat accompanies the explosion of a firecracker in midair, for example).But in some cases, by accident or design, when the constellation of surroundingsubsystems is right, an event will induce a particular type of system-mediatedchange that will either amplify or damp the original event. If the system-mediatedchange accompanying an event serves to enhance, amplify, or replicate theoriginal event, directly or indirectly, then we have a system of positivefeedback. If the system-mediated changes accompanying an event serve toreduce, damp, or cancel out the original event, directly or indirectly,then we have a system of negative feedback.
But instead of continuing with such ponderous generic verbiage, let'suse some common examples. We're all familiar with the horrific squeal whichresults when a microphone is placed in front of an amplified speaker (no,not the horrible noise which results when some of our colleagues are handeda microphone at a conference - that's another form of emergent phenomenonentirely). A tiny sound is picked up by the microphone, amplified, sentout of the speaker, picked up again by the microphone, amplified yet again,sent back out through the speaker, and so on, escalating repeatedly in volumein a classic example of positive feedback. The results are an obnoxiousshriek, perhaps the destruction of the equipment, and possibly (if othersubsystem components are correct), bestselling heavy metal music.
Another example of positive feedback from physics is a nuclear chainreaction. Fission of a radioactive atom releases a proton, which in turncollides with another radioactive atom, inducing fission and releasing yetanother proton, and so on...and an escalating chain reaction results - butonly under rare natural circumstances, or the highly contrived anthropogeniccircumstances (e.g., a nuclear weapon) where the system conditions permitsuch unchecked positive feedback to occur.
A familiar mechanistic example of negative feedback system is a roomthermostat connected to an electrically controlled heater. In warm ambienttemperatures, the bimetallic electrical switch in the thermostat is open,and the heater is turned off. If the ambient temperature drops below a predeterminedthreshold, the bimetallic switch closes, the heater is turned on, and theambient temperature in the room rises. Eventually, when temperatures riseabove a certain point, the bimetallic switch will open again, and the heateris turned off. Of course, control of temperature in this system is unidirectional:the room can be heated if it drops below a certain temperature, but nothingcan be done to control the upper limit of the room's temperature if it continuesto rise due to external ambient conditions. (Canadians who live in conventional,non-air conditioned houses are reminded of this for a few weeks every summer).
The interaction of feedback loops in complex systems can result in conditionsof dynamic equilibrium and metastability. Let's expand the thermostat andheater system to include another subsystem: a thermostatically controlledair conditioner. Now we see a system which is capable of regulating temperaturein the room to within a very precisely controlled range. If temperaturesdrop below a certain threshold, the heater kicks in and warms the room up.If temperatures rise above a certain threshold, the air conditioner startsup and the room gets cooled. We can set the thermostat of the air conditionerjust a degree or two higher than that of the heater, and a metastable systemwill result. From the frame of reference of the room, and looking only atthe parameter of temperature, we have effectively reached equilibrium. Thisequilibrium is far from static, though - it is maintained through the constantthermostatic monitoring of ever-changing ambient temperatures, the perpetualcycling of the heating and cooling equipment, the constant provision ofenergy in the form of electricity, and the constant discharge of waste energyto the environment external to the room. Though it is a metastable system,it is too simple and linear to be resilient: a power outage, an equipmentmalfunction, or the simple act of opening a few windows can cause the systemto behave inappropriately or break down entirely. But it is useful for understandingthe phenomena surrounding the interactions of subsystems in complex systems.
The simple, mechanistic example above can introduce another key conceptapplicable to the interaction of complex systems: information. In a purposefuldesign like a climate-controlled room, we need to track or monitor an environmentalparameter (temperature) with system components (bimetallic thermostats).The thermostats translate the results of that monitoring into feedback whichgoverns the behaviour of the system (in this case, the negative feedbackwhich controls the cycling of the heater and air conditioner). In such apurposeful and mechanistic design, the thermostats are clearly informationdevices. But exactly which environmental or system parameter can be construedas 'information' in any given system is context dependent. Our example isof a system that only regulates temperature, so temperature is the onlypertinent information variable. Other environmental parameters like theoxygen concentration in the room, or the pattern on the wallpaper, wouldbe incidental to the successful operation of the system. It is a simpleand overtly purposeful system, so we can easily determine where the 'informationcontent' can be found.
However, in emergent, self-organizing, spontaneous complex natural systems,we tend to identify pertinent 'information content' retroactively and reductionistically,after we have attempted to describe and understand the functioning of thesubsystems. This is useful, and we should continue to do so, but it obviouslyposes a problem, as we already know that attempts to use reductionism aloneto understand complex systems (even purely physical ones) are inadequate.
Feedback and complex systems are obviously not confined to the physicalor abiotic realm. Emergent phenomena spring forth with glorious abandonwhen living organisms interact with their biophysical environments. Throughtheir life processes, living creatures are able to channel energy and materialsin a fashion which imposes order on themselves and their biophysical environment,to a degree which far outstrips anything we can see in purely physical systems.It is also a characteristic of systems with a living component that theyare able to exist in metastable states that are far out of whack from whatwould be expected by the laws of simple physical equilibrium. Perhaps thebest example of this is the earth's atmosphere, a volatile mixture of reactivegases that could not be maintained in its present form if not for the collectiveactivities of living organisms. The predictable annual cycling of carboninto and out of the atmosphere, concomitant with the seasonal increasesand decreases in primary productivity in temperate regions, is another exampleof a predictable, emergent, metastable phenomenon.
It is also somewhat easier to identify 'information content' in systemswith a living component. Information flows result when living organismsinteract with their biophysical environment, either as receivers (by activelyor passively monitoring or tracking certain flows of energy or materials,the 'signals' which carry information), or as transmitters (by modifyingcertain flows of energy or materials in a coded fashion, intentionally orotherwise). Most living organisms do all of the above, and moreover, areable to react to actively or passively received information in a multiplicityof ways, some intentional and under the organism's control (e.g., an animalmoving out of bright sunshine to avoid its damaging effects), and othersnot (e.g., an animal secreting skin pigments to protect itself against brightsunshine). The adaptability and behavioural plasticity of living organismsas we interact with our biophysical environments greatly increases the complexityand resilience of the subsystems which constitute the global ecosystem,though we are all of course bounded by our ecological niches, limits oftolerance, and rates of evolutionary adaptation.
Another form of feedback is unique to living organisms: memory. Manyliving organisms remember the past. If they believe the future is goingto be like the past, they will behave according to successful patterns intheir past history (a form of positive feedback). If they believe that thefuture is going to be different from the past, then they will change theirbehaviour (a form of negative feedback), 'experimenting' with a number ofbehavioral alternatives until the most successful new behavioural strategyis hit upon. The old patterns, and the results of the 'experiments', successfuland unsuccessful, are remembered, so that it is unnecessary for the organismto go through a new round of the same 'experiments' every time change isencountered.
IMPLICATIONS OF FEEDBACK AND COMPLEXITY FOR ANTHROPOGENIC SYSTEMS
There seem to be a few speculative implications arising from all of theabove. Before we got to them, though, I'd like paraphrase John Middleton'scontention that insight into the functioning of complex systems does notallow us to escape value judgements about our decisions. If we wish to usethe concepts of complexity, hierarchy, feedback, and resilience, we mustbe explicit about the criteria we value and think are important to maintain.I
also caution against any misty-eyed search for morality in natural systems,which I believe to be awe-inspiring, vastly instructive, amazing in theirbeauty and terror, but inherently amoral. We certainly don't want to bemodelling our social structures on elephant seal societies or our institutionson ant colonies. The insights gained from natural systems are invaluable,and we are complete fools if we think we can outsmart or outperform theexquisite and marvellous functioning of the ecosphere with our ham-fistedattempts at management...but we will nonetheless be forced into making anthropocentricdecisions each and every time, not necessarily because we want to, but becausewe HAVE to. It's the only frame of reference we've got. We can, and should,try to get outside the box of our own circumscribed human existence, butwe must be realistic about the degree to which we can do so. Our ineptness,though, as Caterina alluded, should at least be compensated for by an awarenessof our arrogance and audacity, which I think should translate into a concertedattempt to protect and preserve that which we do not understand...whichmeans most of the known ecosphere.
On with the speculation:
- Hierarchy, metastability, and feedback in complex biophysical systemsappear to have exact analogues in complex behavioural systems of anthropogenicorigin. In human systems, there are additional hierarchical levels of learningand memory beyond the individual, provided by our cultural systems, communitystructures, institutions, economies, and systems of governance. Technology,in the form of books, mass communications, data storage, computers, andinformation retrieval systems, 'artificially' extend the learning and memoryfeedback components of anthropogenic systems even further. All of theseare complex systems unto themselves, internally hierarchical, metastable,and reliant upon feedback loops to function. Restricting access to informationto certain segments of humanity cripples individuals and institutions bynot allowing them to take advantage of this collective learning and memoryfeedback, and inhibits the emergence of new forms of problem solving.
- We know that we are unable to successfully predict the behaviour ofcomplex systems through reductionistic means, though we have made some progressin modelling approximations of complex systems through cybernetics and othersimilar approaches. We also know that we cannot fully comprehend the functioningof whole systems in any meaningful way, but that we can look at, chart,and monitor the parameters which emerge from whole systems.
Does this imply that there is (or perhaps should be) an upper limit tothe size and complexity of anthopogenic structures (say, for example, thesize of institutions or the complexity of governments)? Should we attemptto anticipate or predict that maximum size and design the structures accordingly,or should we let the 'break points' or 'subsystem boundaries' emerge spontaneously(as they inevitably will anyway)?
- As others have noted, diversity, multiple pathways, and a plethoraof possible feedback loops in complex systems makes them resilient. Thatresilience is manifested in metastability - in essence, the predictabilitythat emerges from a multiplicity of complex, individually unpredictableinteractions in dynamic systems - but it also makes those same metastablesystems resistant to change. David Sims' stubborn university administration,it seems to me, is a prime (and frustratingly familiar) illustration. Theuniversity administrative system may not be sustainable in the long run,or optimal even in the short run - but it is functioning 'adequately' (i.e.,not in immediate danger of critical failure) when judged by the the limited,short-term parameters that the administrators choose to track (or are instructedto track, or are capable of tracking). Only by expanding their awarenessof temporal, physical, and information elements above and below them inthe complexity hierarchy will they be able to discern threats and opportunitiespertaining to their goals, and make more appropriate decisions. This maypossibly require more information, but more likely it requires differentways of synthesizing and viewing the plethora of information that alreadyexists. It also implies a shift in focus from preserving institutions toachieving goals.
Perhaps if our attempts at decisionmaking were to become more modularand goal-oriented, just as our attempts at problem-solving have to becomemore interdisciplinary and task-oriented, then our institutional structuresand systems of governance would arise as emergent phenomena, better adaptedto meeting our objectives than rigid bureaucracies. (Ann and her colleagueswere definitely onto something with the round-table processes they explored,creating dynamic, productive virtual institutions within existing ossifiedbureaucracies). There could be a great deal of flexibility in these kindsof adaptive institutional structures, as long as several criteria were respected.
Ann, you said we should speculate and be spontaneous. I'm going to goWAY out on a limb and propose a preliminary list of characteristics requiredfor adaptive and resilient collaborative S.D. decisionmaking structuresthat recognize the existence of complexity. This list is idealistic, buthopefully contains some seeds of implementable reality:
i) There has to be an acknowedgement of the limits of the earth's ecosystems.(Wait -don't groan at the vagueness and idealism of this motherhood statementjust yet). Every human endeavour must be judged against explicit, unambiguousprinciples of sustainability that must be disarticulated, as much as possible,from the short-term vagaries of the political process. We have already managedto effectively disarticulate several issues of key concern to the Canadianpopulace from the electoral cycle: medicare and unemployment insurance aresacred cows, have been for decades, and will continue to be, at least forthe forseeable medium to long term. Though they are tinkered with by ourelected officials, it is usually with an eye to ensuring their persistencerather than tampering with their existence.
ii) A consultative mechanism would have to be put in place to allow peopleto provide input in defining goals and objectives (issue-based participatorydemocracy, or some analogue?);
iii) These goals and objectives would have to be stated as clearly andunambiguously as possible;
iv) Multiple approaches to achieving goals and objectives would be encouraged,and interdisciplinary task forces democratically constituted based uponexpertise and espoused positions on key issues of governance, rather thanadherence to a broad slate of party politics;
v) Accountability of people, groups, and processes would have to be ensured,and success rewarded. Monitoring is an indispensable element of every adaptivemanagement process, and only through this form of feedback can we adjustour approaches to meet goals and objectives;
vi) Access to information, and to methods of sharing, disseminating,and adding to that information, would have to be ensured.
A few final thoughts about complexity. Since complex systems have nonatural boundaries, it's conceivable that we could badly misjudge whichare the pertinent components or parameters to consider in our decisionmakingprocesses. I don't think that there is any way out of this; we can onlydo our collective best, with the best available information.
Another thing which I have avoided entirely is the contention that the'emergent phenomena' we observe are not spontaneous at all, but rather theresult of external intervention of some form - call it divine, call it paranormal,call it what you like. The perspective of divine intervention is one thatI am extremely uncomfortable with, but it bears mentioning as another setof unexplored possibilities.
I'm going to wrap things up rather inelegantly right here, as even Ican percieve that I have exceeded my own system boundary. I look forwardto your further submissions and comments.
Sawasdee from Thailand,
Thank you everyone for a most informed and lively discussion on sustainabledevelopment principles. We are still missing two submissions, one from GlenNewton on Integrity and Else on Values. If you are unable to make thesecontributions, I would appreciate if you would notify me?
Could I now ask everyone to re-visit their draft principles and editto a few succinct lines that convey the message? Don't forget that our audienceis decision-makers, at both the political and bureaucratic level, thus,we should avoid overly jargonistic language, and simplify wherever possible.As per David Sims' email dated March 18, 1998, don't forget our need toapply our work to the real world. In other words, if the framework we developisn't 'doable' and 'realistic', then we remain in the realm of theory andhave lost praxis.
COULD I IMPOSE AN ARBITRARY, BUT PERHAPS NECESSARY, LIMIT OF NO LONGERTHAN TEN LINES PER PRINCIPLE, AND IN THE BEST SCENARIO, AN AVERAGE OF FIVELINES. THIS WILL BE DIFFICULT, BUT I AM REMINDED OF WHEN I AM TRYING TOPAINT LANDSCAPE WATERCOLOURS, AND MY PROFESSOR ALWAYS TAUGHT US THAT THESIMPLER WE COULD RENDER THE SUBJECT, THE MORE POWERFUL OUR PAINTING WOULDBE.
I WOULD APPRECIATE IF YOU COULD SUBMIT YOUR REVISED PRINCIPLES BY APRIL26,
For your information, in my dissertation, I will be directly citing eachof you throughout the text, and each principle will be referenced to theauthor. In addition, with respect to the principles, however, I will includethem verbatim as an appendix to illustrate the "robustness" ofthe electronic dialogue.