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Editorial (18.3-4)

Looking at the various subjects that are discussed in this latest Issue of E:CO, I am struck by the variety of topics that are under study and therefore how complexity thinking is being applied to such a wide range of subjects. Looking back, I can see how my own areas of study have ranged over (too?) many topics. Originally, as a physicist I had the good fortune to be given a Royal Society European Fellowship to continue my PhD work in physics on disequilibrium phenomena - at Brussels University with Ilya Prigogine, a founding father of complexity ideas. This was a marvellous opportunity and I was free to explore whatever topics I wanted. Indeed, when Prigogine was given some research support from the US Department of Transportation to explore the possible mathematical modelling of the spatial co-evolution of transportation and urban structures, I was the one whose task it became to develop this research. So, every three months I had to head off to Boston to present our research. Each time I went there with our slowly developing ‘complex systems’ urban model, people there would be totally preoccupied with some new potential problem in US cities (recovering from riots; building metros; what happens if Chrysler goes belly up? Etc.). And each time I replied that we were trying to build a generic model of urban system/transportation, which would potentially be applicable to almost any problem in any city. A bold statement. But this did point out the difference between our kind of ‘meta-level’ approach and that of building a specific model of one particular case, with all kinds of detailed information for the case in hand. This also brings out the difference between 1) a ‘model’ that is really just a ‘description in data’ of what has happened, with predictions given by an extrapolation of the trends within the description and 2) a model built on the interaction of different agents, each with their own knowledge and aims, leading to possible futures for the system - including perhaps some unexpected emergent features. The original connection of this work to Prigogine and his team had been made by Dave Kahn, a researcher at the Transport Systems Centre in Cambridge, Boston. Thanks to this initial support and that of the excellent team there, we had a great opportunity to try to show that Complexity was not only fun, but also was and would be of great importance. It provided an excellent opportunity to try to see how complexity ideas, and dynamical models could be applied to important areas.

Through this initial break away of my work from physics, I was able over the next decades to work on all kinds of topics involving ecological and human systems. These included an amazing variety of topics: Urban and Regional planning; National and Regional social, economic and demographic evolution (Brussels, Belgium, USA, Senegal); River Basins (Soane, Rhone, Meuse); family therapy; Canadian Fisheries, fishing fleets and fishermen; Origami; social insects; economics and market dynamics (Airline competition, Car markets, Pharmaceuticals); ecology and evolution (evolving predator-prey, Darwin’s Finches etc.); organizational evolution (the car industry, Aerospace); supply chains (Cars and Aerospace); innovations (evolution of markets); designs(aerospace); and others I have since forgotten.

I accepted System Dynamics as a sensible way of approaching any problem area (it seemed better to try to model the connected effects of different elements rather than to study the elements separately)–but to go one step further. The key step that complexity added was to recognize that the ‘system’ itself could potentially redefine itself, evolve and change–qualitatively–creating new variables, new mechanisms and new emergent features and characteristics. In all the different topics of research listed above it is the underlying Complexity that links them all. Any system at a given moment has emerged from a past in which it was not what it is now. Complexity is about evolutionary emergence of structure and form. This involves ‘learning’ and ‘forgetting’ not just functioning–recognizing changed features and elements, requiring perhaps changed values, aims and goals. Complexity admits that the ‘functional structure’ may change–and life is not just a mechanical system running forward in time! Thank goodness! Instead of just having ‘a’ system–the initial one - we are looking at possible structural instabilities in which new variables and functionalities may emerge. Complexity can reveal possible futures into which the system could evolve qualitatively over time, and can therefore suggest how we might intervene to push the system in a good direction.

We can use urban and regional models to explore how the spatial patterns, of housing, business and retail centers could develop and look at the advantages of different pathways for different players. Somehow, we need to get some social consensus over what can be considered a ‘good’ direction? The fisheries work provided an important breakthrough. Here, we found that the actual task of fishing required two different (almost opposite) activities. Firstly, that of acquiring new knowledge of where the fish were–discovery. And secondly - exploitation - using this knowledge to guide fishing trips and fleet distribution in order to catch the most fish in the most profitable way. Gradually though, it was realized that this ‘fisheries’ approach which explicitly introduced the discovery and exploitation phases as separate entities was seen to apply to all the different modelling arenas. At exactly the same time, and quite independently, a colleague in Brussels, Jean-Louis Deneubourg, discovered that ants required exactly these two kinds of behaviour (discovery through imperfect trail following and efficient exploitation by sufficiently adequate trail following) in order to find and harvest food. So, obviously, a fishing fleet needs to know where the fish shoals are if they are to plan their routes. But also, more generally, in some technology space, a designer needs to know where the underlying ‘demand’ may be. Under which product type do the (potential) shoals of avid consumers exist? So, for different types of possible product design for example, there will be different numbers of potential consumers, just waiting for the appropriate, dream design of clothes, car, vacuum cleaner etc. But of course, this will only become clear after products have been launched and bets have been placed! For markets in general, there will be different possible characteristics of products, and it is important to discover what type (qualities and cost) possible buyers will be attractive. Such an idea integrates the whole spectrum of issues from the social realities of who may buy a product, through the technical and technological realities about how the product may perform, to the qualities and styles that may attract different potential buyers.

The important point is that the design and success/failure of a product depends not only on the existing customers and producers that are in the ‘game’, but also potential players and buyers who are not yet participating. Clearly, the number of potential customers depends on how the market develops–are some firms obtaining considerable economies of scale, or are others acquiring ‘prestige’? Firms might be wary of who has not yet entered the market, and potential customers may be trying to assess the cost/benefits of buying the product which will depend both on what they consider important, and who they see buying the product. In other words, we have ‘reflexivity’, where the market (and its model) are affected not only by what is present and rational, but also by what is not present but might happen–particularly in the light of what the model is currently indicating. So, not only is the market affected by what potential players think might happen, but also by what a model of this appears to indicate will happen. I first came across this idea when I read ‘the Alchemy of Finance’ by George Soros in 1987. He particularly focused on financial markets as being under the influence of the beliefs about values, partly at least, affected by what any model was indicating. But really this idea is completely general and applies to almost all human systems. Many people don’t buy cars on the basis of a rational analysis of the material cost/benefits of speed, comfort, economy. In reality, they are very concerned by - how do I look in this car’? Or what does my shopping basket/clothes/jewellery say about me?

Because of this remarkable interaction between what people think and what people think other people think, and a model trying to capture what is going to happen, there is a remarkable fluidity. And this situation has given rise to the enormous advertising industry which is about shaping what people think about a product, and what they think other people will think about it. For the UK the advertising spend is more than £20 billion, (internet £8Billion, TV £5Billion…). Clearly, it is really big business to influence how people perceive products and the way the product may enhance or reduce how a buyer may be perceived by others! This seems a little far from what is often called a ‘free market’!

It is in fact a measure of the real complexity of all things human.

It is this fundamentally competitive view of human beings that introduces ‘competitive’ envisioning of possible actions, and how each action is judged on how ‘good’ or ‘bad’ it makes us look. The only way out is community. If we look at systems form the point of view of a community with genuine concerns for each citizen on the part of the others, then a model, or an action might be conceived by an agent in terms of what it does for the community, including the less fortunate.

Reflexive agents within systems can invalidate the assumptions that underlie the systemic projections and changes. Instead of just having the interactions of the agents within a system we now must include their reflexivity and motivations. But how much do they weight their own gains against that of the community? This is particularly important when we note that the current political philosophy is one that says that in ‘free’ markets, selfish actions lead to the ‘best’ outcome for all–that is, it supposedly leads to maximum profits for companies and maximum utility for consumers. But that would only be true in the absence of reflexivity, of worries about self-image and of appearances. Because of this we will find that people, organizations and societies may behave in ways that we cannot anticipate even with the help of complexity science. So, the message that arises out of this is that complexity leads to the recognition of an irreducible element of uncertainty in human systems and a real limit to knowledge about the future. Instead of simply finding that we move from answers based on a mechanistic view of the world, to answers based on a complexity view, we find that there may not be answers! We therefore need to adopt an exploratory and opportunistic attitude where we shall continually need to reflect on what we thought would happen and what is actually happening. Surprisingly perhaps, instead of saying that there is no point in modelling complex systems, it really makes modelling and reflection more vital than before. Reality can break away from any predicted trajectory. This means that instead of building models in order to predict the future, we need to model in order to detect emergence and creativity within the system when our current interpretive framework fails.

The complexity of the world leads to compulsive ‘post-hoc’- ery in many people’s attempts to assign causality to what seems to have happened. Now, suddenly, people say they can ‘explain’ the BREXIT referendum result and the Trump win, in terms of people that felt they had been ‘left behind’. But the people involved in the vote are many and various, and possibly simply wanted to ‘send a sign’ of disaffection to the world in general. The voters that caused the ‘upset’ probably have no coherent visions of what needs fixing or how! Probably this UK and US experimental jump into the unknown will be messy, and will have unforeseen consequences for both voters and those who organized it. In some of my early work on social evolution I often used ‘ignorance’ as a ‘mechanism’ that lead to novel explorations. I think we are about to witness a massive experiment of this kind. Let us hope that we survive our coming ‘learning’ experience. The application of Complexity to human systems, gives us new ways of exploring possible futures, and a range of evolutionary paths that could occur. However, it is also correct in warning us that unpredictable occurrences, can and will occur.

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Peter,I may have run across your work via David Ing in the past. I found your post exploring Michael Lissack Society of American Cybernetic meeting Feb 18th and exploring a NSF grant at the meeting. I am not an academic researcher and have been involved with experimental business design applied prototype projects since 1984. I fell in love with the experimental concept of autopoiesis (Baetson, Maturana, Verela, Beer and Flores) For the past 15 years I have been engaged in collaborative learning between the Lakota Oyate (people), Oglala Tribe over 10,000 years old, situated on Pine Ridge Reservation US Prison Camp #334, South Dakota USA. The Oglala Lakota Nation represents an ancient nobel oral scientific life ways and a primitive genius in humanness struggling to be conserved within a new emergent order, we(i)sdom continuum and useful fruitfulness in leadership. The recent XL Keystone New CIA and Standing Rock Oceti Sakowin "Water Is Life" are indicators of the Lakota green shoot breaking through the concretization of patriarchal culture's political economics hell bent on a manner of appropriation, domination and submission, mistrust and control, sexual and racial discrimination and mercantile competition justifying a rational for war as the central organizing principle of governance. Javier Livas in 2013 visited the Lakota territory and we are committed to caring, feeding and nurturing American Indian's viewpoint by entering global orbit as cyberneticians in 2017. I agree that the UK US experimental jump into the unknown. In the Lakota creation story there is Iktomni, trickster, a character who violates social manners of wolakota as a teaching of what not to do in maintaining a generative ecological knowing manner of living. Some stories are funny and children laugh. Other stories are frightening chaotic terror teaching children that the world is also dangerous. My assessment is this "ignorance" is the end of democracy as a valid western discourse and opening a novel exploration into "Autopoietic Epistocracy WE(i)SDOM Continuum." This tragedy of the commons is just getting started. The metaphor I use as an observer is watching western patriarchal political economic bullet train, operating with no conductor, engineer, brakeman fly off a precipice destined to hit the ocean floor on earth. The central reflexive learning experience is "we did it it to ourselves and there is no transcendent authority responsible for the human suffering in the wake of the crash created." I am an optimist rooted in the biological concept of autopoiesis. I live in moments and observe the evolutionary drift as star dust to star knowledge. All cultures are star dust belonging to one loving universe. Unfortunately man loves shadows and thinks his monkey mind belongs to the chimpanzee community manner of living. What a shame and waste of attention on too many beautiful days living on earth?I have no expectations of complexity professors valuing my autopoietic learning and experience with the Lakota. This is a hunting party in the wilderness creating a new game with canopy of stars as our blanket and warmth in designing a future world together. We tell stories, laugh, sing, dance and enjoy the drumbeat in the human heart spirit-sense of wolakota: a P2P covenant of peace and friendship moment to moment beyond power, control, expectations and greed. Wolakota is a manner of living capable of surviving genocidal attitudes, behaviors and activities. The Oglala Lakota have proved it!Happy New Year!Best regards Mushin

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Happy New Year to E:CO! Your closing statement, “we need to model in order to detect emergence and creativity within the system when our interpretive framework fails.” One potential modeling framework, Lewicki, Mcallister, and Bies, (1998) provided their notion of a Simultaneous Multidimensional Trust and Distrust Framework as a foundation to research the role of trust and distrust in our adaptation to change. It is being researched in the ongoing debate regarding whether trust and distrust is a single continuum or are they separate? I am finding the research very useful in exploring the function of a person’s neural sensory fusion perception system of trust and distrust. It provides people immediate awareness alerts in adapting their behavior to the potential emergence of beneficial and/or dangerous changes occurring in the social environment. The question is, does this sensory fusion of trust and distrust carry over to other people’s perceptions as well?

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Your closing statement, “we need to model in order to detect emergence and creativity within the system when our interpretive framework fails.” Could the model your mention might be one where the fusion between trust and distrust is contagious among members of a social group work in trust and distrust fusion for both social good and bad creativity? As you have probably figured out that I am working on a paper on that idea. I have been invited to present a paper for a university department celebration of their 50th anniversary on that subject. The abstract is as follows:This paper proposes an organization development theory on how the function of a person’s trust and distrust perceptions influence the development of person’s self-governance as a participant in complex social interaction behaviors for emergent social change. The first half of this article examines the trust and distrust debate as to whether trust and distrust form the extremes of a single unified perception or they are two separate perception functions. However, the first argument hinges on showing it is not an error of false dichotomy. However, if they are separate perceptions, the argument hinges on showing they are not a fallacy of the excluded middle. In an effort to resolve the debate Lewicki, Mcallister, and Bies, (1998) provided their notion of a Simultaneous Multidimensional Trust and Distrust Framework as a foundation for seeking what the excluded middle might actually appear to be. Angelika Dimoka’s (2010) fMRI research demonstrated that trust and distrust activate separate correlate places in the brain. Wu, Siege, Stiefelhagen, and Yang (2002) architected a AI model of the human neural process, showing that neural sensory fusion may be a strong candidate to be the Lewicki, et al, excluded middle of their simultaneous multidimensional framework that links trust and distrust perceptions in the human neural system. In the second half, the article combines their research to create a template to trace the “trust-sensory fusion-distrust” version of human perceptions as they flow through the human sensory fusion system. This sensory fission approach is applied the trust and distrust sensory fusion influence on people’s self-governance behavior in social interactions with others, namely as a child, a family, various informal and formal social groupings, and as trust and distrust sensory fusion shared among citizens and stewards of their political government.