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Hi Kristina, Thank you for your input. In parts of addressing complex systems, non-rational thinking has a role. I am also very interested in non-rational thinking in this context. In the area that you discuss in your message, I think that non-rational thinking is not necessarily involved. Experience shows that non-rational thinking doesn't help in relation to complex multi-feedback loop situations. It seems to result in designers making design changes in the opposite direction to those intended. 1. 'Feedback loops' are different from ' variables' in the sense that you describe them. They are 'ways that one variable influences another in a sequence such that this eventually results in a change of the initial variable. Hence, feedback loops result in dynamically changing behaviour of a situation rather than a static solution. 2. There is already a well-tested solution to addressing complex situations involving multiple feed loops - use dynamic modelling. That way, humans look at the model to see what is going to happen. That way, there is no need to be able to understand the complexity. In the simplest sense, this is what we do with prototypes. The problem then shifts to 'how representative is the model'. There is no need to go to non-rational thinking for this. 3. Mapping a complex multi-feedback loop situation doesn't work. (though it gives us the sweet illusion that we appear to be understanding the situation). Mapping feedback loops does not resolve the problem of predicting the dynamic changes in outcomes over time. Mapping only shows the relationships between feedback loops it does not show the dynamic behaviour of the outcomes and, by observation, for 2 or more feedback loops we cannot predict the behaviour of the outcome from looking at a picture of the feedback loops. Best wishes, Terry -----Original Message----- From: Kristina Börjesson [mailto:[log in to unmask]] Sent: Thursday, 22 April 2010 1:55 AM To: Terence Love; [log in to unmask] Subject: Re: Are visual approaches to design outdated? Hi Terry and all. I will start with announcing that system theory is not where my competence lies. My research area is non-rational thinking (!) and behavior and its implications for design. The ongoing discussions has, to my understanding, mainly flowed between visualisation as a i) method to manage complex situations and ii) a way to aid and facilitate human understanding. Visualisation has always been used to enhance understanding and facilitate meaning-making: "an image says more than thousand words". The negative side of this method is of course that once visualised there is a fixed form: we are in fact manipulated to think that this is how it should be, which naturally prevents or at least makes it more difficult to recognise variables which are not accounted for in the image. Terry calls these variables feedback loops, or rather, what Terry calls feedback loops, I call variables. When I studied sociology way back in time, I learned about controllable and non-controllable variables. Researchers created laboratory tests to be able to control as many variables as possible, which with current advancement within neuroscience and cognitive science appears rather naive. But then, design researchers still apply laboratory testing within user-centered design. This was, and obviously still is, examples of a reductionist view and of efforts to manage complexity: to gain results which could be reported as almost 'scientific' and therefore plausible or even true. Reality is different. * The fewer variables involved, the simpler the situation. * With rising numbers of variables involved the situation becomes complicated. * The level of complication depends on how many of these variables can be approached by rational thinking: to what degree you can apply mathematical and other established laws within natural sciences. Laws helps you to predict and hence control [and as Terry rightly points out, is the reason why we try to introduce codes, regulations, rules and so on everywhere in society. It is an effort to mimicry a natural law situation]. * As long as we believe that we can solve a problem rationally (and our modern society is basically founded on rationality), we do not use notions like chaos and complexity. * The above notions are describing a situation where human rational thinking has reached its limits: not only has the number of variables increased but they have also to a great extend become un-controllable, they are non-rational. Most people would call them emotional or irrational. To avoid this, I keep to non-rational, which then indicates non-conscious cognition. As humans at some point are involved in all problem solving [even where i.e. computers play a dominant role], the input is the result of the rational as well as the non-rational - and so is the output: how the result of the 'solved' problem is received and handled by the human it is aimed at. This is what makes the feedback loops so difficult to predict in numbers as in nature/content. Terry won't agree, but I like Birger's pragmatic approach: we have to admit the limits of human thinking to advance and break new ground. Equipped with this humbleness, we might turn our energy to map rather than to handle multiple feedback loops, hopefully thereby refraining from applying solutions, which in fact are merely theoretical. By continuously mapping complex situations, you gain experience to use as input in next situation, but probably more importantly, you learn to better predict how much room in time and space you need to approach complexity without callous reductionism leading to false solutions [in fact creating another problem]. This said: a visual approach might be very reductive IF it singularly is used to manage complexity. BUT if it is used to map complexity, it could be motivated. All the best Kristina Kristina Börjesson PhD, Research Associate Central Saint Martins College University of the Arts London 0044 7767 215992 [log in to unmask] www.borjesson-mk.se http://thefoundobject.canalblog.com ----- Original Message ----- From: "Terence Love" <[log in to unmask]> To: <[log in to unmask]> Sent: Monday, April 19, 2010 4:56 PM Subject: Re: Are visual approaches to design outdated? Hi Birger, Thank you for bringing the discussion back to the practical. That's where it's easiest to see things. For me it's watching practical life that shows how badly we humans manage any situation with feedback loops (complexity). I understand this is the opposite to what you are suggesting. I'd like to suggest some reasons why. It seems obvious that we humans are good at situations where the causes are close in time and space We respond to situations where causes are single, direct, obvious and do not involve feedback loops. Watching people in practical situations shows we are really bad at single feedback loop situations and useless at multiple feedback loops situations. Watch two people bump into each other in a shopping mall and both go one way and then the other in a comic routine. That's a single feedback loop with a bit of a delay. People get in mess and for a short while you can see they don't know what to do. The impasse is broken when one person converts it to a zero feedback situation by making a decisive move that is different. Another example in business, watch how two people behave who meet for the first time and don't know who is the senior. There is a politeness game that happens - again another single feedback loop with delay. Watch new couple's behave before they've managed to get enough information on each other to convert their behaviour to simple stimulus and response routines - they trip over each other trying to avoid making mistakes. Another single feedback loop situation. All of us know the relatively simple feedback loops of addiction - caught in the feedback between rational thought and underlying emotional desires. We humans are so bad at even single loop feedback situations that we insist on structuring life to avoid any feedback. We use management structures, codes of behaviour, legal codes, monetary codes traffic rules..... anything to try to convert feedback loop situations to situations without feedback loops. We intuitively know that we can manage complicatedness but not complexity. I can see that it appears at first that standing back we can view the human situation as complex and that we humans seem to manage. That doesn't seem to be any proof as to whether or not humans are competent at predicting the behaviour of multi-feedback loop situations (i.e. complex situations). There are at least two epistemological fallacies with the argument. First, the relevant complexity is how each individual sees it - not the complexity as seen from a rationalist all-seeing helicopter view. It is us as individual humans that are the unit of analysis and it is the situation as seen from out individual viewpoint rather than the overall world view. The alternative you are suggesting is a bit like saying 'cars are highly complex mechanical, chemical and electronic technologies' and we drive cars therefore 'all humans are successful at designing anything that involves mechanical, chemical and electronic technologies'. It is the relative complexity of the reality that each of us sees as individuals that matters in this context. The reality from observation is that we as individuals try as much as possible to ignore anything with multiple feedback loops (complexity) and if that is not possible, we instead try to treat situations as if there are no feedback loops. If that is not possible, we complain or claim that the situation is esoterically odd (e.g. 'it's a wicked problem', or ' not my problem' or we make a guess and try to bluff it out). From observation, we humans handle complicatedness relatively well, and those with an enthusiasm for relationships can understand situations with single feedback loops. Again by observation, as soon as situations with relationships have two or more feedback loops, people quickly come up with phrases such as 'it could go either way' or 'it's in the lap of the gods' or something similar that indicates that they can no longer predict the outcome. So the first fallacy is that to suggest that everything is complex is epistemologically the wrong context for the subject of study. The second problem with claiming humans are successful at complexity is also epistemological. The problem is the viewpoint on 'successful' in the claim 'humans are successful at dealing with complexity because the world looked at objectively is complex'. The underlying key to the fallacy is in defining 'success' as 'what people define as success'. This is claiming an objective definition on the basis of a subjective judgment. It is like saying success is simply people doing what they do. Intrinsically, there is no means of inferring from it whether we are good or bad at complexity. To recap, from observation of practical situations, we humans ignore complexity and deal with it as complicatedness or as simple situations. It is with this behaviour and these limitations that we define what is success in dealing with life. That doesn't give any information about whether or not we are naturally able to understand and predict the behaviour of a situation determined by multiple feedback loops. The definition of success is independent of competence in a specific task unless there is much more carefully defined links with competence. I'm suggesting that simply by sitting at a café or observing people at work, when we look at how humans behave in both everyday and highly skilled situations, we find we as humans avoid multiple feedback situations. When we do deal with them we deal with them as if they are to single feedback loop 'complicated' situations or even as if they are 'simple' situations. Also by observation, when the situations are important and the feedback loops dominate the outcomes then we get problems . Observing how people deal with these confirms the same findings. Commonly, those reviewing a failure situation try to interpret it without feedback loops. Often this problem situation can continue indefinitely. A classic case was the several decades of failures in IT and Information systems. The combination of feedback loops and delays was a key component of the outcome being the wrong solution for the wrong users. Recent design methods such as Agile and Scrum address and partially resolve some of the single feedback loop feedback issues. Again it needs a method/code etc. Again, I'll suggest that the issues stand and that visualisation only helps with complicated situations. Please send me any example of a visually-based method that enables humans to predict the dynamic behaviour of a multi-feedback complex situation. I haven't found one yet. Best wishes, Terry ____________________ Dr. Terence Love, FDRS, AMIMechE, PMACM School of Design and Art Director Design-focused Research Group, Design Out Crime Research Group Researcher, Digital Ecosystems and Business Intelligence Institute Associate, Planning and Transport Research Centre Curtin University, PO Box U1987, Perth, Western Australia 6845 Mob: 0434 975 848, Fax +61(0)8 9305 7629, [log in to unmask] Visiting Professor, Member of Scientific Council UNIDCOM/ IADE, Lisbon, Portugal Honorary Fellow, Institute of Entrepreneurship and Enterprise Development Management School, Lancaster University, Lancaster, UK ____________________ -----Original Message----- From: Birger Sevaldson [mailto:[log in to unmask]] Sent: Saturday, 17 April 2010 1:33 AM To: Terence Love Subject: SV: Are visual approaches to design outdated? Dear Terry Thanks for challenging the ideas of visualisation being helpful in dealing with complexity. Its clearly justified to do so. To my experience it is very difficult to impose the old systems model with well defined boundaries, hierarchies of sub systems, well defined inn and output and well defined feed back loops. Even quite simple real life systems are to my mind hard to squeeze into this model. e.g. a car is today built according to integrale principles where an increasing number of parts are designed to performe according to multiple criteria and functions. This makes it very challenging to subdivide an automobile into its subsystems, because the multiple performance blurres the boundaries. Maybe this difference in systems approaches is at the heart of the different possitions in this discussion? As an example: you say that "'Complex' situations are different. Human cognitive and emotional biology is not well suited to understanding or predicting the outcomes of 'complex'situations." I totally disagree with this: To my mind are humans very well equiped cognitively and biologically to understand and to a certain degree predict the outcomes of very complex situations. We do this every day from morning to the evening. If we were not we would not survive for very long. So humans are amazingly well equiped to navigate through multiple hyper complex systems e.g. walking down a crowded street while having a conversation with another person, navigating in different layers of different overlapping and interacting systems being traffic flows, social spaces, visual symbols, micro climates. How more complex can it get? We use skills and perseption , visual thinking, interpretation of patterns, filters, to a large degree tacitly. I think these skills are what is activated when we work visually with complexity in design. I refere to soft systems methodology (Checkland was quoted in this discussion earlier) and e.g. Systems Architecting as described by Mayer and Rechtin. I think this soft end of systems thinking is more relevant and closer related to design thinking, than some of the more traditional systems approaches. Maybe we come from different world views and the discussion needs to clarify this first? Here a selection of references i found interresting, (please feel free to suggest additional sources): Checkland, P. (2000). Soft Systems Methodology: a 30-year retrospective. Systems Thinking, Systems Practice. P. Checkland. Chichester, John Wiley & Sons LTD. Checkland, P. and J. Poulter (2006). Learning for Action: A Short Definitive Account of Soft Systems Methodology and its use for Practitioners, Teachers and Students. Chichester, John Wiley & Sons, Ltd. Csikszentmihalyi, M. (1999). Implications of a Systems Perspecive for the Study of Creativity. Creativity Handbook. R. J. Sternberg. Cambridge, Cambridge University Press. Glanville Ranulph, A Ship without a Rudder CybernEthics Research, Southsea, UK 1994 Gordon Dyer, Y3K: Beyond Systems Design as we know it, in: Res-Systemica, Vol. 2, 2002. Refering to Béla H. Banathy Frostell, B., Å. Danielsson, et al., Eds. (2008). Sciene for Sustainable Development: The Social Challenge with Emphasis on the Conditions for Change. Uppsala, VHU. Frostell, B. (2009). Industrial Ecology and Environmental Systems Analysis- Systems Approaches for Increased Complexity. Stockholm, KTH Royal Institute of Technology. Gharajedaghi, J. (2006). Systems Thinking: Managing Chaos and Complexity: A Platform for Designing Business Architecture. London, Elsevier. Gigch, J. P. and J. McIntyre-Mills, Eds. (2006). Wisdom. Knowledge and Management: A Critique and Analyses of Churchman's Systems Approach. New York, Springer. Gruber, H. E. (1988). "The evolving systems approach to creative work." Creativity Research Journal 1. Gruber, H. E. and D. B. Wallace (1999). The Case Study Method and Evolving Systems Approach for Understanding Unique Creative People at Work. Handbook of creativity. Cambridge, Cambridge University Press. Gunderson, L. H. and C. S. Holling, Eds. (2002). Panarchy: Understanding Transformations in Human and Natural Systems. Washington DC, Island Press. Gunderson, L. H. and L. P. Jr., Eds. (2002). Resilience and Behavior of Large-Scale Systems. Washington, Island Press. Jonas, W. (1996). Systems Thinking in Industrial Design. Systems Dynamics, Cambridge Massachusets, MIT. Jonas, W. (2005). Designing in the real world is complex anyway-so what? Systemic and evolutionary process models in design. European Conference on Complex Systems Satellite Workshop: Embracing Complexity in Design, Paris. Maier, M. W. and E. Rechtin (2000). The Art of Systems Architecture. Boca Raton, CRC Press. Mariussen, Å. and Å. Uhlin, Eds. (2006). Trans-national Practices, Systems Thinking in Policy Making. Stockholm, Nordregio. Meadows, D. (1999). "Leverage Points: Places to intervene in a System." The Sustainable Institute, Hartland. Meadows, D. H. (2008). Thinking in Systems. White River Junction, Chelsea Green Publishing. Midgley, G. (2000). Systems Intervention: Rhilosophy, Methodology, and Practice. New York, Kluver Academic / Plenum Publishers. Miller, J. H. and S. E. Page (2007). Complex Adaptiv Systems: An Introduction to Computational Models of Social Life. Princeton, Princeton University Press. Olsson, M.-O. and G. Sjöstedt, Eds. (2004). Systems Approaches and Their Applicaitons: Examples from Sweden. Dordrecht, Kluwer Academisc Publishers. Rechtin, E. (1999). Systems Architecting of Organisations: Why Eagles Can't Swim. Boca Raton, Florida, CRC Press LLC. Sage, A. P. and J. E. J. Armstrong (2000). Introduction to Systems Engineering. New York, John Wiley & Son. Senge, P. M., B. Smith, et al. (2008). The Necessary Revolution: How individuals and organizations are working together to create a sustainable world. New York, Doubleday. Svedin, U. (2006). Introduction to Systems Approaches and Their Aplications. Systems Approaches and Their Aplications: Examples from Sweden. M.-O. Olsson and G. Sjöstedt. Dortrecht, Kluwer. Ulrich, W. (2000). "Reflective Practice in the Civil Society: the contribution of critical systemic thinking." Reflective Practice 1(2): 247-268. Walker, B. and D. Salt (2006). Resilience Thinking. Washington, Island Press Best regards Birger