Experiments: help needed

September 19, 2006

I just posted the following request onto a couple of list serves and replicate it here

I am currently engaged in several projects in Singapore relating to networks and complexity. On the basis that this group has a set of interesting people with good ideas and problems I wondered if I could prompt for some assistance (the results of both projects, including the methods will be published under our open source approach so they will be freely available to all). I also thought I might abandon my normal list serve role as curmudgeon and custodian of purity in the use of concepts!

In both cases I am looking for any wisdom that anyone has to offer, but specifically I am looking for issues/paradoxes/dilemmas which are either theoretical or practical in nature. Apologies for the length of this posting, but you can always delete it now if you are not interested in the two subjects: Networked Government and Managing Complexity in the sense of a complex adaptive system (CAS), exhibiting properties such as emergence.

1 – Looking afresh at the issue of Networked Government and its implications. Most work here seems to focus on how to use technology to link up government silos and also to link people to government. Little work seems to have gone into what a networked model of government would look like outside of the technology issues. In particular I am looking at nodal network structures where the nodes form in practice, not by design. I am also looking at forms of knowledge sharing that do not require original material to be shared in advance of specific need and a whole range of problems relating to control mechanisms in non-hierarchical structures. At the moment this is more of a theoretical/consultative product but may move to experimentation

2 – Looking at what can be managed and monitored/measured in a complex (by which I mean a complex adaptive system) system: obviously this is related to the first. However in this case we are now mixing theory with practice. Over one week in October we will run multiple sense-making experiments with different groups of government officials to see what types of methods can be developed that can be used with minimal training without any knowledge of the theory. I did something similar here with Gary Klein a few months ago and we established that describing a situation at a higher level of abstraction than normal improves not only weak signal detection (seeing things that might otherwise not be seen until too late) but also resilience to manage change. In a sense that finding was counter intuitive, but supported by other research that shows more data and lower levels of detail do not improve sense-making. This set of experiments will see me working with Alicia Juarrero (whose book Dynamics in Action is easily one of the best around in the field of complexity in human systems) and Cynthia Kurtz (who will provide the US base 12 hours apart on time difference for processing interpretations and planning the next days experiments in what will be an intensive process).

In respect of both items we are looking at the human equivalents of eco-systems, but taking into account unique aspects of human over “natural’ systems such as multiple identities and pattern based decision making. We will be experimenting with concepts such as attractors and barriers, proximity, imitation etc. Ie we are taking the concepts of CAS and experimenting with different groups of decision makers in a controlled environment.

So what is the request – well first all ideas, suggestions & references etc are welcome (and any used will be acknowledged). Either here or by email. Secondly I am specifically looking for situations and problems that can be thrown at the experimental subjects.

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The Cynefin Company (formerly known as Cognitive Edge) was founded in 2005 by Dave Snowden. We believe in praxis and focus on building methods, tools and capability that apply the wisdom from Complex Adaptive Systems theory and other scientific disciplines in social systems. We are the world leader in developing management approaches (in society, government and industry) that empower organisations to absorb uncertainty, detect weak signals to enable sense-making in complex systems, act on the rich data, create resilience and, ultimately, thrive in a complex world.

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