Complexity Theory, Development and IKMemergent.

I was at an IDS seminar last Friday – “Knowledges, Capacities and Learning for Development: Insights from Complexity approaches”.  If the title is alarming then this ODI paper is an excellent primer, “Exploring the science of complexity Ideas and implications for development and humanitarian efforts”. An even shorter introduction comes from this post by Duncan Green, Head of Research at Oxfam who wrote a summary introduction to the ODI paper.

Ideas from complexity theory have permeated everyday discourse – see the butterfly’s wing and the hurricane – but so far I have never made the time to understand more. This is a two part blog entry. This post captures some first reactions – mine to Dave Snowden (who introduced and led the morning session) along with three short video reactions from participants.

I’ve read Dave Snowden’s work but this was the first time I have seen him perform. He has a rock-star style, as befits his KM guru status, full of anecdotes and one liners: the guru comes through in the principles, axiom-like, with which he peppers his delivery (if you tire, you can spot them because most of the audience start writing quickly: people stop taking voluminous notes quite early – he is very fast and the content is dense). He is also intensely human, which is why I chose this picture of him. He lodges his slides on his site, and like most of us, I suspect, has a set that evolve slowly over several events. This one seems to be close to the version we heard at IDS.  The slides are interesting in themselves, and capture a lot of his ideas, but not the performance of the day.

He has developed a body of work that I think is exceptionally broad and deep: his politics (I declare an interest here) are old left  but he works for British and US intelligence, military and business clients (“development consultants are those prepared to live with low margins”); he is a convergent academic, whose first degree was in Physics and Philosophy, and whose work now ranges across natural science, informatics, IT, social science and development – to name those I can distinguish; he has developed, with colleagues, methodologies for introducing to organisations and groups the ideas and implications of complexity (some of which we experimented with at the seminar); he has spawned a sophisticated software tool – sensemaker – that crunches and displays patterns derived from analysis of metadata associated with narrative fragments of sense making (signified – tagged – by the providers). These patterns display – numerically and, far more impressively, graphically, correlations that – it is claimed – illustrate culturally specific clusters of meaning, value and judgement. He is also sharing much of his materials and ideas at a site designed to be an Open Source, collaboratively developed resource. 

While I reflect on implications for IKMemergent, here are three interviews with seminar participants all involved in KM4Dev. These are provided in the spirit of the Snowden style – as narrative fragments to aid sense making. They are, typically, lightly constrained by a simple common framework – the question, “what does this mean to KS (and in one case, to KS and Oxfam)”. 

Ewan Leborgne, from the IRC, talks about the Cynefin framework, which is summarised here:

 

[blip.tv ?posts_id=1335247&dest=-1]

 

[blip.tv ?posts_id=1335397&dest=-1]

 

[blip.tv ?posts_id=1338456&dest=-1]

Snowden’s work is driven by the principle that the sense making must be participative, that providers of content must be engaged in the generation of the analytical frameworks with which we – the audience – can be helped to make our own sense of their contributions. So I invite Ben, Ewan and Jo to help us by providing some tags – filters, with which to interpret what they are saying here.

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10 Responses

  1. Thanks for sharing the event and the impressions of some of the participants. As the Consultative Group on International Agricultural Research is in the middle of a change process, we (KS project of the CGIAR) ask very similar questions: http://ictkm.wordpress.com/2008/10/08/how-to-choose-ks-and-management-approaches-for-enabling-change/

  2. Hi thanks for sharing this. It is very much in line with my interview with Alan Fowler who also works with the complexity school of thinking. My question is whether is it useful to see for instance a community of practice as a complex adaptive system. Or doesn’t that give you any handles to work with?

  3. Nice posting Pete.

    Just as IKME is interested in multiple knowledges, so it would be true to say that complexity is taken up multiply.

    Simplistically I think there are three broad groups of writers and thinkers on complexity as it applies to social phenomena.

    In the first camp are writers who are still trying to bend complexity to a predictive scientific model: the idea, then, is that it might be possible to develop a framework or a tool to apply to social phenomena such as organisations to achieve predictable, ie better, results. Authors like Meg Wheately, Peter Senge, and the recent ODI paper have all taken up complexity in this way. I recently came across an article by Alan Fowler on The Broker where he is also taking up complexity theory (although I would argue there are theories rather than ‘a’ theory) in this way.. These authors sometimes imply that is possible for managers to ‘unleash complexity’ in the organisation, or after Wheatley, to follow a few simple rules and ‘utilise’ complexity.

    In many ways this way of understanding insights from the complexity sciences as tools which can somehow be ‘applied’ directly to organisations never really escapes from the way that scientific method is commonly understood.

    In the second camp are academics who have tried to analyse complex social phenomena by using sophisticated computer models. In this group I would include Peter Allen at Cranfield and Peter Hedstrom at Oxford University. Neither would claim that there models are in any way predictive, or in the latter’s case, even of necessarily being an accurate picture of reality. Rather they claim that their models offer us a better way of understanding how social phenomena may arise. Hedstrom concludes the following:

    1 there is no necessary proportionality between the size of the cause and
    the effect

    2 the structure of social interaction is of considerable explanatory
    importance in its own right for the social outcomes that emerge

    3 the effect a given action has on the social can be highly contingent upon
    the structural configuration in which the actor is embedded.

    4 Aggregate patterns say very little about the micro-level processes that
    brought them about.

    To a certain extent, then, Allen and Hedstrom are partially leaving behind the notion that science is only science if it can produce causal, predictive results which are universally applicable. However, they still believe that reality still needs to be modelled using the universal language of mathematics before we can be properly sure that we understand what is going on. The linear equations used in these computer models have no mathematical solution, they only have retrospective explanatory power.

    In the third camp you will find authors like Ralph Stacey, Robert Chia and Hari Tsoukas, who understand complexity in interpretive terms and would deny that it is directly applicable to social phenomena. Nonetheless they would argue that insights from theories of complexity offer similar explanations to those forged by a generation of philosophers and sociologists such as Norbert Elias, Pierre Bourdieu and the American pragmatists to name the most prominent. Stacey, Chia and Tsoukas, whom Fowler does not call on, suggest that insights from the complexity theories and from these prominent sociologists and thinkers, pose a radical challenge to the way we understand social phenomena. So, for example, Stacey calls on Elias to show how he has a theory of social emergence very close to the central insight from complex adaptive systems theory (CAS), that complex social patterning arises purely from the interactions of agents organising locally. There is no overall plan and no single agent is in charge. This is how Elias describes it:

    “As the moves of interdependent players intertwine, no single player nor any
    group of players acting alone can determine the course of the game no matter
    how powerful they may be. … It involves a partly self-regulating change in
    a partly self-organizing and self-reproducing figuration of interdependent
    people, whole processes tending in a certain direction.”

    You can see how this understanding of insights from the complexity sciences implies a fundamental challenge to writers in the first group, who still think that complexity is something they can harness or control. As managers and workers in organisations we can never ‘use complexity’ because we ourselves are part of the patterning that we presume to change. We may, through our greater power, be able to have greater influence events, but our influence will always be modified and affected by the power of everyone else we seek to influence. In effect social patterning arises from the interplay of power relations.

    It is hard to place Snowden in these three groupings. On the one hand, since he had developed computer software it would be tempting to put him in the second group. However, he also has tendencies towards the first group, implying that you can use his software to manage complexity, or even tell the difference between simple, complicated, complex and chaotic. How would you know? In the end you might conclude that if you think the social phenomenon you are dealing with is simple or complicated, then you haven’t heard the news. Again, it’s another grid which implies an outside perspective that the writers in the third group would say is impossible.

    Snowden denies he is in the third group because that poses a challenge to his belief in predictability and control. He is right in the sense that if things really are complex and we form part of that complexity in a way that makes it difficult for us to stand outside of ourselves, it is a pretty profound challenge.

    It takes all sorts though!
    Chris Mowles

  4. […] Complexity Theory, Development and IKMemergent. « The giraffe […]

  5. […] more and watch video clips of participants perspectives on Pete’s blog Possibly related posts: (automatically generated)Innovation dialogue: How to be strategic in the […]

  6. […] Read more and watch video clips of participants perspectives on Pete’s blog […]

  7. I appreciate Chris’s comments for the way it ‘frames’ the perspectives. It gives me one opportunity to look at the field from that lens to ‘see’ what I ‘see’.

    And now I can choose to disagree with it somewhat…at least from my current perspective : )

    I would contend that the first group isn’t in pursuit of “predictive scientific model”, but instead suggests that complexity science is a ‘view’ that helps us to better understand, describe and effectively react to the world around us.

    Say we have a friend in some sort of trouble. They talk to us. We try to ‘see’ their challenges and offer advice. Such advice is never ideal for we can never see all the things that are necessary and we’re being given a ‘report’ from just one perspective. All we can do is provide some ‘influence’ to guide further action. That’s the real focus of the group 1 camp.

    • And this is totally bogus “who still think that complexity is something they can harness or control” Do surfers believe they can harness or control a wave? Group 1 recognize the natural potential, the kinetic energy of complexity. Like a surfer they look for ways to ‘ride the crest of the wave’ and leverage its power [what books have you been reading?]

  8. […] Comments Rotkapchen on Complexity Theory, Development…Rotkapchen on Complexity Theory, Development…jasmin live on Not the Semantic Web, […]

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