This blog is part of an online learning platform which includes the Pathways to New Community Paradigms Wiki and a number of other Internet based resources to explore what is termed here 'new community paradigms' which are a transformational change brought about by members of a community.

It is intended to offer resources and explore ideas with the potential of purposefully directing the momentum needed for communities to create their own new community paradigms.

It seeks to help those interested in becoming active participants in the governance of their local communities rather than merely passive consumers of government service output. This blog seeks to assist individuals wanting to redefine their role in producing a more direct democratic form of governance by participating both in defining the political body and establishing the policies that will have an impact their community so that new paradigms for their community can be chosen rather than imposed.

Monday, December 4, 2017

Systems Practice Entwining Complexity with Rationality and Emotion

As was said in the previous post on the ongoing Systems Practice course, difficulties and messes are broad terms and the distinction between them is not clear-cut and categorical. Rather they are on opposing ends of a continuum, with many, if not most, problems lying somewhere in between.

The attributes that distinguish messes from difficulties concern their scale and the uncertainty associated with them and whether these aspects were bounded or unbounded. To describe a situation as messy implies that in some important respects it is unbounded rather than if just a difficulty which then would be bounded. In addition, there is also the issue of complexity including elements of rational and emotional aspects of complexity that need to be considered.

• Difficulties, being well-defined and more limited situations, mainly involve hard complexity. Given a particular view of the matter, what is the best that can be done?

• Messes, on the other hand, are ill-defined; they include large measures of both hard and soft complexity. Of course, this may not be obvious at first and some or all of those involved may fail to recognise the soft complexity: they may initially resent alternative viewpoints, perhaps seeing them as misguided or even wilful attempts to confuse the ‘real’ issue.

According to the current course, complexity is not just a matter of there being many different factors and interactions to bear in mind in a multitude of combinations and permutations of possible decisions and events.

Complexity is also generated by the very different constructions that can be placed on those factors, decisions and events. It is not only a matter of technical or computational issues with which engineers and operational researchers deal or of the uncertainty, even irreducible uncertainty, that must be allowed for, evaluated and selected.

‘Hard complexity’ is defined by the course as generating difficult computational problems as illustrated by the game of chess, the enormous range of possible move and counter-move sequences to be considered and assessed by each of two players. This next portion of the course's definition needs to be quoted.

It is, unquestionably, complicated. Nevertheless, the nature of the game, the moves of the pieces, the fundamental purposes of the players – all these are unproblematic.

NCP has differentiated between complexity and complicated in a number of different venues. One aspect has been to see the connections of complexity as intrinsic and of complicated as intricate. The word ‘unproblematic’ in this context seems somewhat similar to the term ‘trivial’ in more formal mathematics or at least as Richard Feynman saw it. Chess, arguably, could be seen as a hard or complicated algorithm, whether unproblematic or not, from a single-sided, checkmate in 12 moves perspective but with the counteracting feedback of another player seems to me to make it unpredictably complex.

‘Soft complexity’ doesn't arise from the ‘facts’ It arises from the variety of very different (mental) constructions, and how they can be related to alternative explanations for behavior or events. Soft complexity can also feature a high degree of emotional involvement.

The course goes on to quote John Casti (1994), a mathematical modeler and writer on complex systems who links complexity to a more vernacular understanding:

… when we speak of something being complex, what we are doing is making use of everyday language to express a feeling or impression that we dignify with the label complex.

The course sets hard and soft complexity on a graph putting the computational difficulty on the x-axis and the emotional involvement on the y axis. Messes then are situations involving high degrees of both.

Complexity, particularly soft complexity, the course asserts, as far as I can interpret it, then arises from the different perspectives and how they can be interpreted, and equally, perhaps more importantly, the degree of emotional involvement people have in the situation, especially if one has a technical or engineering background making it difficult to come to terms with it.

The current course then does not attempt to address complexity at the level of complexity science as the scientific study of complex systems. It only endeavors to note distinctions between complex situations and complex systems. More about the implications, including the more philosophical, will be covered in a future post. This post will consider more personal connections with past interactions with systems practice approaches.

Despite a hypothesis that systems thinking could serve as scaffolding for deliberative and participatory systems of democracy most past system thinking projects have been solitary explorations or solitary experiments done in parallel but not actually connected with other independent efforts.

The current course raises a number of issues relevant to the interactions with a previous Systems Practice-oriented course, as team leader, of a group of ten which attempted at least by virtual modeling to address homelessness in Portland, Oregon. This was a follow-on to a previous financial modeling course as part of someone else's still ongoing, real world, on the ground effort to address homelessness in Portland, Oregon. It was among the first experiences with a group approach to systems thinking.

My personal reason for the choice was to continue that effort believing that we need to collaborate on larger scales to develop systematic means of addressing systemic wicked problems of which homelessness is one. The systems practice group approach both significantly informed the manner in which I contributed over time inducing me to substantially change my approach in ways during that course that I would not have if I had worked solely on my own.

Systems practice may though be a weaker approach in my view for those with less exposure to systems thinking because it can overly emphasize coming to a consensus. One of the primary issues of systems thinking is the tendency of people to only look at causal factors in immediate or near-immediate approximation whether by time, distance or causal relationship.

I believe that there should have been a stronger foundation in systems thinking provided at the beginning of the course and introducing Kumu at the very start could have helped with that. The challenge was crossing over to a more holistic, systems thinking perspective through a systems practice group process.

Questions of ‘interpersonal relationships’ (i.e. personal evaluations, likes and dislikes) as a contributing factor in the situation didn't really come up as the course was online. It should be noted though that NCP sees face to face interaction as an essential factor in community governance.

The other people on the team saw the situation differently from each other, they also saw many of the Systems Practice terms differently but then sometimes those terms weren't clearly expressed. It is unclear how we saw each other but interactions were done in a positive manner.

The inclusion of ‘political concerns’ were a contributing factor in the way that we all saw the situation but were related more to means than ends. All of the political concerns attributed to the people involved were considered ‘legitimate' by the group. There was likely a pro-liberal selection bias due to the course being sponsored by Acumen. There were no homeless, or homeless advocates involved or even anybody from Portland and the direct involvement of the original social entrepreneur was lost because of conflicting schedules, though she did remain available in an advisory capacity.

The most important consideration that was not adequately represented in terms of hard information and demonstrable facts, in what is now being defined as a messy situation, was the local residential reaction to the proposed system of homeless intervention, the role of residents in deciding the fate of the proposed homeless camp food truck programs. This arose from multiple causes, and was behind some of the disagreements over focus and priorities. My usual systems approach resulted going both further back by causal degrees than my teammates and with what they felt comfortable.

The discussion of what is now being termed soft complexity helped in distinguishing difficulties from messes though we didn’t name them that. We went beyond thinking about difficulties and messes only terms of hard complexity. Others contributed to the notion of trust in our system maps to a much greater extent than I did.

But the more soft complexity there is in a situation, the messier it is likely to be. Working out what to do with a mess is no longer a matter of thinking the situation through, but of rethinking or reframing it as well.

Past Posts