Cybernetics Society videos – YouTube

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Cybernetics Society – YouTube

Cybernetics Society

Cybernetics Society website

London Tube Quick Cybernetics

The Uses and Abuse of Cybernetic Concept in Economics, Dr David Dewhurst

Radically Constructing Ethics. 50th Conference.

Prof Andrew Pickering on the early life and future potential of Cybernetics

Imparity, Service-Dominant Logic, and the Architecture of Enterprise: Jenkinson, CybSoc 2019

David Wood: Cybernetics Society Conference 2019

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Cybernetics Society – YouTube

Centre for Systems Studies Seminar: Re-appraising Alexander Bogdanov’s Contribution to Systems Thinking – Prof Michael Jackson – Nov 18, 2020 4:30-6:30PM GMT

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Registration

Centre for Systems Studies Seminar: Re-appraising Alexander Bogdanov’s Contribution to Systems Thinking

  • Wed, Nov 18, 2020 4:30 PM – 6:30 PM GMT

Show in My Time Zone


Alexander Bogdanov is usually referred to, in the systems community, as someone who anticipated von Bertalanffy’s development of general system theory. With his rehabilitation in Russia, the opening of the Soviet archives, and the translation of more of his writings into English, the time is right for a fuller appraisal of the range of his contributions. This preliminary review outlines some avenues that such a reappraisal might explore. In particular: – The impact of his work at the time of the Russian revolution – The philosophy behind and the systems ideas expressed in his greatest work, Tektology – His science fiction writings describing the functioning of a fully fledged communist society situated on Mars – The similarities between his ideas and those of later systems thinkers, particularly Stafford Beer and his work in Chile Michael C. Jackson is Emeritus Professor at the University of Hull, editor-in-chief of Systems Research and Behavioral Science, and MD of Systems Research Ltd. He graduated from Oxford University, gained an MA from Lancaster University and a PhD from Hull, and has worked in the civil service, in academia and as a consultant. Between 1999 and 2011, Mike was Dean of Hull University Business School, leading it to triple-crown accreditation. Mike has been President of the International Federation for Systems Research and the International Society for the Systems Sciences. He is a Companion of the Association of Business Schools, a Chartered IT Professional, and a Fellow of the British Computer Society, the Cybernetics Society, the Chartered Management Institute, the Operational Research Society and the International Academy for Systems and Cybernetic Sciences. Mike has received many awards, two honorary degrees, and has been a visiting professor at numerous international universities. In 2011 he was awarded an OBE for services to higher education and business.

book via link:

Registration

Toward a theory of schizophrenia – Bateson – 1956 – Behavioral Science – Wiley Online Library

Toward a theory of schizophrenia Gregory Bateson Don D. Jackson Jay Haley John Weakland First published: 1956

https://doi.org/10.1002/bs.3830010402Citations: 1,420 PDFTOOLS SHARE Abstract Schizophrenia—its nature, etiology, and the kind of therapy to use for it—remains one of the most puzzling of the mental illnesses. The theory of schizophrenia presented here is based on communications analysis, and specifically on the Theory of Logical Types. From this theory and from observations of schizophrenic patients is derived a description, and the necessary conditions for, a situation called the “double bind”—a situation in which no matter what a person does, he “can’t win.” It is hypothesized that a person caught in the double bind may develop schizophrenic symptoms. How and why the double bind may arise in a family situation is discussed, together with illustrations from clinical and experimental dat

Toward a theory of schizophrenia – Bateson – 1956 – Behavioral Science – Wiley Online Library

pdf link: http://www.uio.no/studier/emner/sv/sai/SOSANT2525/h14/pensumliste/bateson_toward-a-theory-of-schizophrenia.pdf

Catch-22 and the paradoxes of organisational life | Eight to Late

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Catch-22 and the paradoxes of organisational life | Eight to Late

Catch-22 and the paradoxes of organisational life

with one comment

“You mean there’s a catch?”

“Sure there’s a catch”, Doc Daneeka replied. “Catch-22. Anyone who wants to get out of combat duty isn’t really crazy.”

There was only one catch and that was Catch-22, which specified that a concern for one’s own safety in the face of dangers that were real and immediate was the process of a rational mind. Orr was crazy and could be grounded. All he had to do was ask; and as soon as he did, he would no longer be crazy and would have to fly more missions…”   Joseph Heller, Catch-22

continues in source:

Catch-22 and the paradoxes of organisational life | Eight to Late

Step into System Innovation: A festival of ideas and insights — The System Innovation Initiative by ROCKWOOL Fonden – Nov 9-13, 2020

via Systems Innovation

The System Innovation Initiative by ROCKWOOL Fonden

AboutCurrent Page:Conference 2020PodcastsNewsletterContact

Step into System Innovation
A festival of ideas and insights

November 9th – 13th, 2020 // Online & Free

Join us for a festival of inspiration and insights into the practicalities of what it takes to change a system from the inside out. We have brought together some of the boldest social innovators from around the world. With them we will dive into the work of transforming systems to tackle deep social challenges. We will share a simple framework to help anyone step into system innovation, from public sector innovators, foundations and NGOs to social entrepreneurs and mission-driven businesses.Join for free

Systems Thinking for Sustainability – Sustainability Course – FutureLearn – free

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Systems Thinking for Sustainability – Sustainability Course – FutureLearn
FutureLearn – online courses from top universities

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Systems Thinking for Sustainability: An Introduction to the Symbiosis in Development (SiD) Theory

Understand how the Symbiosis in Development (SiD) framework helps you create the foundations of a sustainable society.Join course for free

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Systems Thinking for Sustainability – Sustainability Course – FutureLearn

System Thinking 5 weeeks course | MIT xPRO – starts Oct 26, 2020 – $1,149

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System Thinking | MIT xPRO
MIT xPRO Logo

Join Professor Sterman for a live webinar on Thursday, October 15th at 12 PM ET and get your questions answered live. Reserve your seat here.

SYSTEM THINKING

A five-week online course that will make you a better problem solver and improve the performance of your projects by teaching you to apply system thinking in technical environments.

SIGN UP FOR UPDATES & YOUR WEEKLY SCHEDULE

Submit your information to receive updates about this online course and download the week-by-week schedule.

By submitting your information, you are agreeing to receive periodic information about online programs from MIT related to the content of this course.

BECOME A VITAL PART OF YOUR ORGANIZATION’S FUTURE

We are surrounded by systems. The products, processes, and projects that we work on are increasingly complex and interrelated systems. Organizations are calling on you, their technical professionals, to drive and optimize complex projects under high-pressure conditions.  

Through this online course, MIT faculty will teach you how to think of things as systems — the process of understanding how entities influence one another within a whole. You’ll be able to then communicate that gaining insight and apply new methods, techniques, and vocabulary to your projects and processes. System thinking (or “systems thinking”) helps organizations examine complexity and simplify it; recognize patterns, and create effective solutions to challenges. Understanding and approaching problems from a systems perspective in technical environments is an essential skill for your career. 

October 26, 2020

Online

5 Weeks

$1,149

ENROLL NOW

IN THIS COURSE YOU WILL LEARN TO:

Apply systems thinking to improve the performance of your projects. Understand how systems thinking is used in diverse areas such as logistics & transportation, project management, and computation. Participate in a project management simulation to apply the concepts learned, and engage in activities to contextualize each concept.

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System Thinking | MIT xPRO

How to maximise the benefits of a system value approach | World Economic Forum

source (h/t Mikael Seppala)

How to maximise the benefits of a system value approach | World Economic Forum

How can we maximise the benefits of a system value approach?

General view of the Walney Extension offshore wind farm operated by Orsted off the coast of Blackpool, Britain September 5, 2018
All aspects of our energy networks – including transmission and distribution – must be transformedImage: REUTERS/Phil Noble

12 Oct 2020

  1. Kristen PaneraliHead of Electricity Industry, World Economic Forum
  2. Stephanie JamisonSenior Managing Director, Accenture Global Utilities Leader

The World Economic Forum COVID Action PlatformLearn moreMost PopularWhy we’re one step closer to a flu vaccine that lasts foreverAnne Trafton · MIT News 13 Oct 2020Chart of the Day: This is how the $88 trillion global economy is spread around the worldKate Whiting 13 Oct 2020WHO warns herd immunity strategy ‘unethical’ and other top COVID-19 storiesKate Whiting 13 Oct 2020More on the agendaForum in focusOur new partnership will accelerate the responsible sourcing of raw materials via blockchainRead more about this projectExplore contextFuture of EnergyExplore the latest strategic trends, research and analysis

  • The path to an integrated zero-carbon energy system needs to take into account not only cost, but also system value.
  • The journey towards a sustainable energy transition has three stages.
  • Investments in renewables, efficiency and the grid come first and remain essential throughout the path

continues in source:

How to maximise the benefits of a system value approach | World Economic Forum

“where do I put my car?” – Twitter Search / Twitter

Much as I love the folks at Strong Towns and all my other friends and inspirations in urban and environmental spaces, this is not ‘stupidity’ or ‘trolling’ – though there might be tiny percentage of trolling in there – these are real human, family, and community concerns we must address.

https://twitter.com/search?q=%22where%20do%20I%20put%20my%20car%3F%22&src=typed_query

Philosophy and complexity | Francis Heylighen (2007)

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Philosophy and complexity | Francis Heylighen – Academia.edu

Philosophy and complexity

Francis Heylighen2007, Complexity, science and society179 Views21 Pages1 File ▾Show more ▾Abstract: The science of complexity is based on a new way of thinking that stands in sharp contrast to the philosophy underlying Newtonian science, which is based on reductionism, determinism, and objective knowledge. This paper reviews the historical development of this new world view, focusing on its philosophical foundations. Determinism was challenged by quantum mechanics and chaos theory. Systems theory replaced reductionism by a scientifically based holism. Cybernetics and postmodern social science showed that …

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Philosophy and complexity | Francis Heylighen – Academia.edu

Business Modeling courses online (basic free, others paid)

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Business Modeling courses

Business Modeling Courses

… the fast, reliable path to Living Business Models

Everyone talks about “Business Models”, but most popular frameworks are little more than abstract descriptions! 

https://platform.thinkific.com/videoproxy/v1/play/btrk8r6je35bt9cgshog?autoplay=trueWe need models that work, doing what is actually happening in the real-world, and showing how the future may play out. Then we can test how our plans might improve things. 

Dynamic, “living” business models simulate reality.

They can transform the performance of any enterprise, or function, and enable you to tackle challenges with much more confidence. And because everyone can see why everything is changing, you get the “joined-up thinking” we all want.

If you are an analyst, consultant, business-student or teacher, then you should know how to build and use these models.

What will I learn?

Quite simply, how to specify, build and use working, quantified models of any business challenge or plan you choose!

  • “Getting-Started”… a free extract from the full Core course. “Follow me” demonstrations to build a complete working model in an afternoon.

    FREE : more info
  • Core concepts(Classes 1-4) … create working models of any enterprise, department or issue, following our ‘AgileSD’ process. With demo models and templates to help you start on your  challenges.

    £90/$135 .. more info
  • Extensions(classes 5-10) … more  powerful frameworks – tackling competitors; developing staff, products, customers; handling intangibles and more. Each is awesome on its own, or add them to your business model.

    £150/$225 .. more info

How will I learn?

The process is simple:

… watch screen-show videos explaining key principles and demonstrating the steps to build a model

… copy the models yourself

… adapt the models to your own needs

You work to your own schedule. Use the course discussion forum to answer questions – or contact us. 

Our master-class courses guide you through this same process, but with scheduled webinars and personal guidance. You can also gain Certification by submitting assessed work.

Teachers … you can adopt the course materials to deliver yourself. Being student-led, the learning-per-contact-hour is very high, and much more engaging than other types of learning. Contact us for more information.

“Can I do this?” … YES, you can!

If you can build spreadsheets, you can build dynamic business models

You simply start from the performance outcomes you want to improve and keep asking “What causes this?” The answer sometimes includes items you already found, so you end up capturing the real world system that drives those outcomes. 

It is easier, faster and more reliable to build dynamic business models.

But although the principles are simple enough, you cannot build dynamic business models with spreadsheets! They just cannot handle the many interdependencies, the feedback and the threshold effects that pervade real-world situations. And the Sheetless software enables anyone to build models that match the system’s structure and mimic its behaviour with uncanny realism.

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Business Modeling courses

EVALUATION IN A SYSTEMS PERSPECTIVE OF PLANNING

EVALUATION IN A SYSTEMS PERSPECTIVE OF PLANNING
Thorbjoern Mann October 2020
Note: This is a section of a larger forthcoming study on evaluation in the planning discourse, for discussion in a systems community, since it raises some questions about systems perspective.

Systems perspectives of planning

In just about any discourse about improving approaches to planning and policy-making, we find claims containing reference to systems: ‘Systems Approach’, the‘ Systems Perspective’, ‘Systems Thinking’, ‘Systems modeling and simulation’, the need to understand ‘the whole system’, the counterintuitive behavior of systems. Systems thinking as a mental framework is described as ‘humanity’s currently best tool for dealing with its problems and challenges’. By now, there are so many variations, sub-disciplines, approaches and techniques, different definitions of ‘system’ and corresponding approaches on the academic as well as the practitioners’ consulting market, that a comprehensive description of this field would become a book-length project.

The focus here is a much narrower issue: the relationship between the ‘systems perspective’ (for convenience, this term will be used here to refer to the entire field) and evaluation tasks in the planning process. It is triggered to some extent by an impression that many ‘systems-perspective’ approaches seem to marginalize or even entirely avoid evaluation. This study will necessarily be quite general, not doing adequate justice to many specific brands of systems theory and practice. However, even this brief look at the subject from the planning / evaluation perspective will identify some issues that call for more discussion.

Systems–related practice might even be seen as a synonym for ‘planning’ since both involve similar general aims: to develop ideas for effective action to intervene in what both call ‘context’ of perceived real situations, to change or ‘transform’ those situations. ‘Context’ is one of only a few shared terms for the same concepts; the vocabulary of the different ‘perspectives’ is full of different names for what essentially are the same things. This especially applies to the facet of evaluation. So it seems appropriate to look at the question of the role of evaluation in a systems-perspective-guided model of planning.

The role of evaluation in a systems model of planning


Would systematic approach to this question require a common, well-articulated and sufficiently detailed ‘systems model’ of planning, against which concepts and expectations of evaluation (such as those explored in other sections of this study) could be matched? There are many general definitions of ‘system’ and ‘planning’ and related concepts such as ‘rational planning’, but few if any of these are sufficiently specific for the purpose of this investigation. There are many more detailed ‘models of planning’ — not necessarily based on a well defined overall ‘systems’ perspective, but in detail aimed at specific domains. This introduces too many considerations applicable to the respective fields to constitute a useful general ‘systems model of planning’. The development of such a general model is beyond the scope of this project. As a first ‘stopgap’ approach for the purpose of this study, a few selected common ‘systems perspective’ terms, tenets, and assumptions will be examined and their implications for evaluation explored.

A common view of ‘system’ is that of a collection of elements, entities connected into a coherent ‘whole’. Thus, any such set of entities and relationships can be seen as a system. (The term ‘can be seen as…’ means that the choice of declaring something as a system is taking place in somebody’s mind, whether and how well that selection reflects ‘reality’ is a different issue – since the mind can also hold conceptions of entirely imaginary entities that ‘exist’ – that is, whose ‘reality is not anywhere out there in what we call ‘reality’, — only in someone’s mind, an entity whose ‘reality’ itself is ardently disputed by many thinkers.

To begin a discussion about what might be an appropriate set of system components and relationships for a general perspective of ‘planning’ raises a question: what kinds f ‘components’ and ‘relationships’. The frame might focus on the kinds and roles of agents involved in planning, or on procedural steps and rules, for example, or on the different forms of information exchanges between the parties. The following discussion will use a relatively common framework, that of activities related to objects — variables distinguished as belonging to phases concerned with ‘context’, ‘solution development’, ‘performance’, ‘decision’ and ‘implementation.

Diagrams of the planning system described in this way -for example Rittel’s ‘design as a system’ diagram, (figure 1) distinguish the planning or design activity from the overall ‘context’ or ‘environment’ – everything else ‘out there’. The diagram shows ‘context model’, (it is not clear whether the model refers to ‘everything out there or just those context aspects pertinent to the project ), ‘design model’ and ‘evaluation model’ as three clearly separate boxes. The ‘designer’ — shown outside of the ‘design model’– must anticipate the values of ‘context’ variables (defined as influences on the project that the designer cannot control) manipulating ‘design variables’ (the designer feel can be controlled, manipulated) in the ‘design’ box, where the ‘input’ of context and design variables generate ‘outputs’ of ‘performance variables’ that are then aggregated in the evaluation box into an ‘overall performance judgment’. The designer considers various setting of design variables, until a satisfactory value of an overall performance judgment is achieved.

Figure 1: Rittel’s systems model of design [1]

A common systems community mantra is that ‘everything is connected to everything else.’ Thus, according to the understanding of ‘system’, what we call ‘reality’ of everything – the world or universe: the ‘context’ of the design or planning activity — is a system, though we never ‘know’ more than a small part of it. It includes the entities and agents — the ‘designer, planner, systems modeling expert themselves involved in or affected by the problem the plan aims at remedying — in some way. It also includes the variables the designer has decided can be manipulated, now calling those ‘design variables’. Finding out, for example, that initial assumptions about which variables can be controlled and which cannot, are mistaken: some forces assumed to be ‘controllable’ turn out not to be, while a ‘creative’ mind may find surprising ways to manipulate ‘context’ variables so as to become ‘design variables? Already, the distinction between the boxes in a more detailed systems diagram will become fuzzy. The ‘context’ is really the background within which design and assessment and decision takes place. So should a ‘systems diagram’ of planning show the design and evaluation components as parts within that infinite background?

Designers make distinctions among the entities they are aware of. The very perception of context entities as potential candidates for consideration as relevant components of the planning system is based on properties of those entities, and the strength of different types of connections, relationships, acting on their perception and being ‘cognized’ and ‘re-cognized’ by the perceiving ‘mind’. So must the designers’ minds have something like a ‘perception record’ – a picture or ‘model’ in their own set of properties? Is it meaningful to say that a person’s knowledge is the model of the world they are aware of, in that person’s mind? (The model can then have things in it – entire worlds — that are merely ‘imagined’ but are not actually in ‘reality’ but only as the imaginations of people… This creates the ‘Santa Claus’ phenomenon – imaginary entities, for which actual ‘real’ models are manufactured which now become part of actual reality.)

We also already make judgments about properties and relationships of context entities. Whereas the properties can be observed and measured in reality, the judgments are emerging and exist only in the observers’ mind (until shared with others): ‘this item is pertinent to the project’ or “this relationship is significant, so it should be included in the model”. So far, the judgments may be generally related to whether the elements and relationships in the model are ‘true’ – that they correspond to the actual reality out there and how it works. Roughly speaking, that is the aim of ‘science’, and it is important because we recognize (via repeated experience of making assumptions about reality that turn out to be mistaken) that the model is not necessarily an accurate representation of the real world, as the systems warning ‘The map is not the territory’ tries to remind us. The task of becoming aware of and ‘understanding’ the pertinent context is challenging enough to give it a prominent position and priority in the systems perspective of planning. But it is important to recognize that it already involves judgments that are no longer ‘just the facts’, but assessments of significance related to the purpose of the project.

To the extent systems ‘understanding’ is related to planning, transformation of existing conditions, yet another set of insights and assumptions is needed: The recognition that the world – the context – is changing, whether we do anything about it or not. More specifically: some entities in the context change (the ‘variables’ that describe their properties take on different values), and some appear to be constant, unchanging. The model of the planning system for the project at hand must account for that distinction: the context entities that produce the changes in the context variables for the design must be found and understood (their properties and relationships identified), to develop an adequate model pertinent to the purpose of the activity: to change an unsatisfactory condition, to create a new subsystem, to remedy a ‘problem’. All this involves not just ‘information’ but evaluation judgments.

The systems recommendation to ‘understand the system’ therefore cannot refer only to the context subsystem that relates to the problem. It tries to understand and explain how the elements of the system led to (most commonly ‘cause’) the current ‘IS-state’ of the context that somebody considers ‘Not as it OUGHT to be” (a definition of ‘problem’) and hopes to find out ‘HOW’ the condition can be changed into the OUGHT state. The ‘cause-effect’ relationship assumed in most models constitutes a paradoxical judgment challenge for approaches urging the planner to identify the ‘root cause’ of a problem since it seems obvious that removing that cause will resolve the problem. Does this not require an assumption that this root cause is not itself the product or effect of another cause – which seems to be at odds with the very concept of cause and the notion that the plan can remove (un-cause’) it? How far along the causal chain must we look to find that cause that does not have a cause? Or jump to a judgment that any causal relationships into a cause are so weak and insignificant to justify its determination as the ‘root’ of the problem relationships?

So far, all this is still a sketchy account of just the early stages of planning. Much systems work is focused on the important question of how the initial system will change over time – first, if nothing is done to change it – but then, how it will change in response to what might be done to change it: interventions, plans. ‘Understanding the system’ now means ‘understanding how the system’s behavior is changing over time’. That task has proven to become more challenging – ‘complex’, ‘nonlinear’, ‘counterintuitive’, the larger the network of relationships, and the more (forward and backward) ‘loops’ occur in the network. This is where the contribution of the systems perspective has been most significant, facilitated by the advances in computing technology.

It may be important to consider the distinctions and assumption judgments that are needed to develop a successful simulation model to predict the behavior of a given system over time: the system components, their properties, the variables and their measurement provisions for establishing ‘objective’ descriptions of the states and changes, the relationship functions expressing how the state of a given entity is influenced by the states and state changes in other components. In all these choices, model makers are making many ‘subjective’ judgments. The determination or selection of components to include in the model will be based on some consideration of the strength of relationships between components. The ‘boundary’ of the system is located at the ‘last’ or outermost components of the relationship network that a person considers significant. The boundary will therefore be different for different people. While relationship strength can perhaps be measured ‘objectively’ for past and current states, the judgment about what strength is sufficiently significant for an entity at the edge of the network to be included in the network is not objective. Likewise, the predictions of likelihood of the significance of future changes are entirely subjective judgments.

The selection of ‘initial settings’ of a simulation model run corresponds to the selection of ‘design variables’ in Rittel’s model (as well as what many similar planning or ‘rational’ decision-making models for specific domains describe as the phase of ‘generating plan alternatives’). Those decisions are based on consideration of system components judged to be able to be relatively feasibly changed by applying appropriate actions and resources: interventions. These ‘leverage points’ would still be considered ‘context’ if the designer’s knowledge model does not contain relationship representations judged to offer feasible intervention opportunity.

Simulation of model behavior over time (assumed or hoped to be sufficiently close to the behavior of the ‘real’ system) is part of the quest for ‘understanding the system’. Their ’output’ is a set of tracks of selected descriptive system variables that describe the system. The early phase runs will be based on the option of ‘doing nothing’ – to see how ‘bad’ the future system states will be. The seriousness of the ‘problem’ (that justifies ‘doing something’) is assessed by the peaks or valleys of the tracks of the system variables. These variables — selected as significant descriptors of the system – may correspond to ‘criteria’ as understood in the discussion of section [..] The point is that they are already taken as ‘performance’ variables but without making the judgment or evaluation nature of this step explicit. In simple linear planning models, evaluation is something to be done after the ‘plan’ alternatives, consisting of interventions to change some of the ‘current state’ variable values of the model, to see how the peaks and valleys change, have been articulated for decision.. But again, ‘evaluation’ activities are seen from the first attempts to ‘understand the context and system behavior’, extended seamlessly into the ‘solution generation’ phase.

A problematic aspect here would be for this to be taken as the only or even just main performance assessment needed: leading to the temptation to pick that solution alternative showing the most impressive peaks or valleys of the simulation tracks. This concern has of course led to suggestions to change the planning model from the linear sequence to a cyclical or spiral one of repeated cycling through the several stages until one solution seems to emerge as the ‘best’ one.

The concern remains that the predicted descriptive system variables become the main basis for the decision. The flaw lies in constraining the perspective to these ‘objective’ features, ignoring the possibility of differences of opinions. Not only about the probability of fact-assumptions going into the model structure, but more importantly about judgments about desirability, goodness, value of the ‘whole picture’ of the plan: comprehensive evaluation is not part of the model. Simulation track diagrams give the impression that all such differences and controversies have somehow been ‘settled’, when they simply have been omitted from consideration. When attempts of more comprehensive evaluation – e.g. ‘Benefit-Cost Analysis’ — are included, the differences of opinion of different parties being affected by the problem and the proposed solutions are made to disappear by being aggregated into ‘common good’ type measures, for example Gross Social Product, growth rates, or polling results.

Briefly, what this means, — even for the simple assumption of a single designer working on a personal planning issue, — already the ‘perspective’ of the first stage of ‘understanding the system’ will include considerations of context, design (leverage point) and performance: so should a ‘model’ of the planning system more visibly and explicitly account for all of this, to meet both systems and evaluation expectations?

Acknowledging the roles of the many parties involved in planning projects

As the perspective of planning activities here has become more complex, aspects such as ‘differences of opinion’ have crept into the discussion. But the diagrams still look like the ‘perspective’ of a single person – initiator of the process by raising a problem or issue, designer, developer of the model, ‘client’ of the investigation effort, decision-maker — all in one. In actual planning projects all these roles will be real people or parties. And they will all have different ‘perspectives’ of the problem, the project, and plan proposals. Must the overall model not acknowledge that each party involved in a planning project will come to the table with a different perspective: view of the situation, assessment of components and relationships and their significance, and, above all, different views and judgments regarding what is a ‘good’ plan and outcome? Obviously, a realistic model of the planning system (not only the system to be planned but the planning process itself), must take all these roles into account. If there is to be a collective decision ‘on behalf of all affected parties’ or for entire communities, society as a whole: shouldn’t the question or task of how that decision can be forged from all those perspectives into one justifiable story be a distinct part of the systems model of planning?


Is the assumption that there ‘is’ an achievable single valid general perspective even for the ‘objective’ aspects requiring due consideration an unlikely, wishful-thinking one? Many approaches seem to make it appear that the eventual decision will be ‘rationally’ based on such a common perspective. Can we reasonably expect that the ‘approach’ of a planning process will result in all participants sharing the same perspective? Does the slogan ‘planning decisions should be based on the facts’ express the position that a commonly shared perspective can be achieved only for the ‘factual’ aspects of the information involved – and that these – only these – should determine the decision?

Looking at another common slogan that begins to acknowledge differences of opinion: “Planning decision should be based on the merit of arguments”. (The ‘pros and cons’ about a proposal). Does this expectation or demand assume that the issues about the pro and con arguments can be ‘settled’ to determine the decision? (If ‘settling’ means everybody adopting a common perspective). Information systems (e.g. IBIS: Issue Based Information Systems, and APIS: ‘Argumentative Planning Information Systems) based on the Argumentative Model of planning, as well as the procedural recommendations for collective planning processes drawn from the model, aim at inviting and bringing all the information that could become part of solution designs and arguments about them to the attention of the designers and decision-makers. The attempt to devise procedures for the evaluation of the arguments we routinely use in planning will quickly show that those ‘planning arguments’ [4] contain not only factual but also deontic (OUGHT) premises. Logic asserts that their deontic conclusions (‘Plan A ought to be adopted’) cannot be derived from facts alone: ’Planning arguments’ are not ‘deductively valid’, from a formal logic point of view – though they are used in various disguised forms – all the time in planning and policy-making. And planning decisions do not rest on single ‘clinching’ arguments but on ‘weighing’ of the whole set of ‘pro’ and ‘con arguments. So should the systems planning model include all these, including the plausibility, quality, significance assessments (perspectives) of all the parties involved? And how should it describe the way all these considerations will or should guide the decisions? Most of these issues still need to be investigated and discussed more thoroughly, before they can become general accepted ‘practice’.

The role of creativity and imagination in a systems model of planning

As if the difficulties discussed so far are not challenging enough, there is an underlying sense of ‘something missing’ in the picture of systems model of planning: the issue of creativity. If the systems models of the solution generation phase (whether in a linear or cyclical version) are built from the ‘objective fact’ information in the context, does creative activity merely consist of inventing new combinations of knowledge items (as some definitions of design actually are suggesting, and techniques such as Brainstorming are based upon?) Where do truly surprising, innovative ideas come from, how do they fit into the systems model of design and planning?

Going back to the ‘perspective’ image of context knowledge, a person’s ‘model’ of a situation was describing context information as coming to a perceiving entity through a ‘screen’ (like the glass panes the Renaissance painters who invented perspective used to trace the image of a scene: the very term ‘perspective’ means ‘seen through’). The emerging picture of points and connections seen through the glass began to look like the real scene.

But then the artists added new items to the pictures — figures of people they may have studied and drawn on different ‘screens’ — but also entirely ‘imagined’ entities: angels, fairytale heroes, villains, sorcerers, monsters, and imagined sceneries and landscapes. Just harmless, ‘not real’ fairytale illustrations? When communicated, shown to others, these stories and sceneries come to viewers and listeners as ‘real’ context items. This created ‘Santa Claus’ problems of understanding the difference between ‘real reality’ and its models, and models of imagined reality, which now were communicated to others and began to have very real effects in the real world. So description of the IS/OUGHT discrepancy of a perceived problem as the difference between the variable value of an ‘objective’ property of a context entity and the perceivers opinion that a different value of that variable would be ‘better’ or more desirable does not capture the phenomenon of imagination of entities not (yet) found in objective reality. Doesn’t true designers’ creativity lie in just this kind of imagination?

Without going into the question of how such creative imagery comes about in designers (and other people’s) minds, can we say that a person’s ‘perspective’ should the seen as the combined picture of ‘real context’ representation a n d all the creatures populating the persons’ imagination? To the extent imagination plays a significant role in creative solution development, it would seem necessary. The question here is then about how systems or other models of planning should accommodate the phenomenon. Taking the call for understanding the ‘whole’ system seriously, does this now mean that the planning process must consider all perspectives of all affected and involved parties in a planning project?

Do the difficulties of answering these questions explain the tendency of many ‘brands’ of systems approaches to marginalize or entirely avoid the task of explicit, thorough evaluation? For a comprehensive model of planning to at least account for the presence of these problems, it may be useful to examine the different patterns of this tendency on some detail.

Tendencies to marginalize evaluation in systems practice

The general part of some planning approaches may seem to give due recognition of the different phases including evaluation, and assign equal attention to each phase. For example, the list of phases of the ‘Rational Planning Model’ [2] which adds two more practical stages to the three boxes of Rittel’s model, (I would suggest adding at least ‘decision to implement’ to the list) appears to consider each of the phases as equally deserving attention:

“Definition of the problems and/or goals;
Identification of alternative plans/policies;
Evaluation of alternative plans/policies;
Implementation of plans/policies;
Monitoring of effects of plans/policies.”

However, many accounts of consultant brands of planning on social media give a different impression: their ‘systems models‘ of planning focus on ‘early’ phases (understanding the system’ and ‘developing solutions’) while marginalizing or entirely avoiding engagement in thorough ‘systematic’ evaluation procedures. The reasons may range from practical concerns about their burdensome complexity, to aims of avoiding the impression of substantial differences of opinions, a general need to produce ‘positive’ success stories ideally resulting in consensus-supported decision recommendations (leaving the responsibility for actual decision to the ‘clients’ of the project). Even Rittel, who sought to develop a better ‘second generation planning approach with his ‘Argumentative Model of Planning’ [1] guiding his proposals for ‘Argumentative Planning Information Systems’ that pointedly focused on the aspects of differences of opinion and perspectives – issues – did not have time before his untimely early death, to offer a more coherent model of evaluation of the merit of arguments in the planning discourse.


This tendency should be seen as different from a traditional practice that also avoids elaborate evaluation: that of starting from an existing ‘solution’ that is recognized as the ‘current best’ response to a known planning task – for example a house or a car. Such a design or planning project is not seen as a new, unprecedented problem, but to add an improvement to the precedent solution. The improvement involves only one or a few parts or aspects, (sometimes just an aesthetic one) and the project is considered successful if the difference is actually perceived by the public or client as an improvement, so no comprehensive evaluation effort is needed. While this is a quite common and respected practice – all automobile manufacturers offer new, ‘improved’ models every year; architecture students are required to start every new design assignment with a study of precedents, — it is usually not claimed to be a ‘systems’ approach since that would require looking at all parts of the ‘whole system’.


While the attitudes of systems consulting are understandable – given the pressures of competition in securing project contracts, financial and time constraints – these trends are arguably not living up to systems-perspective claims of superiority over other approaches, nor the evaluation expectations sketched out in this study. Especially the connection between evaluation results and the eventual decision often remains unresolved: too many decisions end up being made by decision modes and practices that blatantly ignore the evaluation insights or avoid evaluation altogether. A brief indication of some of the tactics used for this may be useful to guide more research and development on this problem.

Several kinds of ‘tactics’ for this ‘evaluation evasion tendency’ can be distinguished: One is the tendency discussed above: to consider the performance variable tracks of simulation models with highly aggregated data into ‘common good’ measures as already sufficient to support decisions. This may eliminate many other evaluation aspects from consideration, and hide any opinion differences from sight. The ‘Root Cause’ approach is a variation of this tactic: focusing the effort on identifying the ‘root cause’ of a problem, for which there are few or only one way to ‘remove’ it, will greatly simplify the work.

The approach of sequential narrowing down the ‘solution space’, by eliminating all solutions that seem unsatisfactory on some significant evaluation aspect, to only one remaining solution for which there then is ‘no alternative’ is a more general variation of this tactic.

Reliance on traditional ‘best practice rules’ is another tactic, one that may be labeled as ‘generating single solutions by following rules’. Original trade guilds’ manuals and secrets became elaborate systems of government regulations: designing a plan by systematically observing and following all the regulations at least would ensure the plan getting a permit – a statement of ‘good enough’ but arguably far from helping the resulting plans or buildings to become desirable, good, or beautiful. Regulations typically prescribe ‘minimal’ conditions for permitting and so tend to generate barely tolerable results – a criticism often heard about the environments of architectural and modern urban design.

Theories about ‘good design and planning can play a similar role: In architectural and urban design, theories (such as the Pattern Language) prescribe or recommend the generation of plans by combining ‘valid’ components and rules into single solutions whose validity and quality is guaranteed by the method of generating them – no additional evaluation effort is needed.

The same result can be achieved by procedural means. Small planning teams, even with variations of user or citizen participation, facilitated by a moderator of the consulting firm hired for the project, and working under tight resource and time constraints as well as psychological pressure – competition, the fact that team members are employees of the ‘client’ company and/or the consultant firm, emphasis on achieving consensus, rewarding ‘cooperation’ and subtly penalizing critical comments (‘attitude’) about flaws in emerging group solutions all aim at generating single solution products. If dissenting discussion persists, or when the assembled team shows signs of fatigue, procedural moderation tools such as the “Any more objections? – so decided!” statement by the facilitator can produce ‘consent’ presented as ‘consensus.

Finally, the increasing calls must be mentioned for planning to pay attention to ‘crowd wisdom’ or ‘swarm behavior’ as approaches generating ‘single’ solutions whose validity is guaranteed by the crowd or swarm, and therefore does not require any systematic evaluation efforts. The obvious questions for investigating the validity of such approaches as serious replacement for more thorough and ‘systematic’ planning and policy-making seem to run afoul of the very principle assumptions of such approaches: that this would be tantamount to ‘evaluation’ to which crowd wisdom is inherently superior and thus makes it unnecessary, even detrimental. Some serious discussion and perhaps comparative experiments seem appropriate to find a meaningful answer to these questions.

Wrong question?”

The reasons for evaluation avoidance may superficially look like somewhat illegitimate ‘shortcuts’ or ‘excuses’ not to have to engage in cumbersome evaluation procedures. But they might also be based on some underlying concerns that should be looked at, in the spirit of both the systems mantra to consider the ‘whole picture’ as well as the ‘wrong question?’ advice to question the basic assumptions of any project.

Some such concerns might be related to the role of large complex planning projects, given the inevitable power relations in society: Can the very sophistication and complexity of the systems perspective, and especially the evaluation procedures relayed to it, be used as tools of domination and oppression, even as their proponents embrace ‘participation’ and the aim of giving due consideration to ‘all’ expressed opinions and concerns? Or can their apparent inclusiveness of all opinions serve as legitimization devices for avoiding responsibility for making decisions (and facing ‘accountability’ questions for questionable results? Phenomena like the ‘plausibility paradox’ finding of argument evaluation efforts that seem to tend towards the center point of zero (on a +pl/-pl plausibility scale the more arguments are assessed and honest plausibility/probability estimates are applied [section … of the study] seem to support such skepticism.

The very examination of the evaluation task itself can lead to impressions of futility of the effort: Are the opinions and judgments that must be made and aggregated into decision guides so subjectively individual, mired in temporal situation conditions and based on incomplete, insufficiently reliable ‘evidence’ support, (support coming in ‘inconclusive’ argument patterns) — that they never should be used as the basis for plans for large projects that will have consequences way beyond individual’s ‘planning horizons’ and ability to correct mistakes? Is it more meaningful to look for more timeless, universal, general principles tested by experience in many applications over time? There are several theories trying to offer such timeless truths, whose support ranges from personal preferences of the theorist and their followers, to connections (e.g. in architecture) to mathematics and geometry. (Of course, even such theories have been accused of becoming tools of cultural dominance and oppression.)

Theories drawing on insights from evolution studies and complexity theories suggesting that valid solutions can ’emerge’ from many small acts coalescing into ‘crowd’ behavior based on ‘crowd wisdom’ — instead of being based on grandiose plans implemented by power entities in hierarchical organizational structures. Groups investigating these issues should be encouraged but seem to resist considerations of questions such as what to do about different crowds behaving very differently and thus getting in each others’ ways (lemmings seem to get in their own self-destructive way… which might be a warning to keep in mind.)

These few examples must suffice to convey the need for taking such attitudes seriously and establish a constructive discourse about their applicability to the different forms of plans and responses to challenges.

Summary and suggestions from the investigation.

This brief exploration raised many questions and exposed areas about systems and evaluation that arguably need more work: thinking, research and experiments. But there may be some findings and perhaps lessons that could guide immediate change of perspectives and application patterns.

Does the insight that evaluation judgments are made in all phases’ of systems-guided planning suggest some revisions, even reconstruction, in some prevailing systems models of planning? For example, should systems perspective promotions consider and include the following aspects more clearly?

* Systems models are not reality — a well-known mantra – but representations of people’s selective and incomplete perspectives of parts of ‘reality’. Especially different people and parties in the planning process will have significantly different models in their minds. That is, the single systems model of a project gives a misleading impression that a common understanding of the problem, situation, solution has been achieved?

* Encouraging efforts to coordinate the vocabulary and focus of evaluation judgments made at different ‘stages’ of the process – early judgments (often not really acknowledged and stated explicitly as such) can eliminate important concerns from subsequent work?

* Should visual representations of both the process and the system being worked on – systems diagrams – be expanded to more explicitly include evaluation and the agents making evaluation judgments?

* Should systems models of planning that inadvertently or intentionally represent the process as a linear sequence be replaced by recursive or ‘parallel processing’ representations?

* Are efforts to provide a clearer understanding of distinctions between ‘descriptive’ plan features and ‘evaluative’ judgments? Specifically, should the practice of showing ‘optimal’ behavior of a system over time with descriptive measures as the suggested basis for decisions be changed to complement the ‘objective’ measures with corresponding evaluation judgments, admittedly on the risk that this will reveal significant differences of opinion?

* Should the tendency of deliberately or inadvertently encouraging ‘single-aspect’ decisions be resisted in favor of considering the ‘whole picture of evaluation concerns?

* When addressing social issues, should systems practitioners stop claiming that their ‘brand’ approach will ‘optimize’ consensus solutions, and offer ‘data- or ‘fact-based’, ‘science based’ solutions, and solve ‘wicked problems’? (There are always winners and losers in those problems, all ‘solutions have costs as well as benefits, which inevitably will be unequally distributed.)

* Should ‘reminders’ or suggestions for coherent and thorough evaluation techniques be ‘posted’ repeatedly (just like systems mantras such as ‘understand the context’ or ‘look for relationship loops’, or ‘are we looking at the wrong question/problem?’

* Should examples of more thorough evaluation techniques (among others) be offered in a ‘tool kit’ for participants in planning projects to apply as necessary? No specific procedures can be recommended as mandatory ‘universal’ parts of planning approaches for all types of projects and situations.

* Should ‘templates’ of standard evaluation-related contributions (like template suggestions for planning arguments and their assessment) be offered at critical decision points?

* Should AI efforts be developed to assist evaluation in planning, to focus on such tasks as ‘translating’ verbal comments into templates for systematic evaluation, or the task of aggregating evaluation results into decision guides?

* Should aggregation tools that aim at ‘averages’ of evaluation results (prematurely aiming at ‘consensus’ outcomes) be accompanied by aggregation formats that reveal potential conflicts or differences of opinion? At a minimum, for example: Churchman’s ‘counter-planning’ suggestion based on radically different starting premises and goal statements (e.g. turning an aspect preference ranking list upside down…).

* Should shortcut steps such as (‘root cause’, system ‘boundary’ judgments be acknowledged as participant (modeler’s) judgments, not ‘reality-based constraints’?

* Should process provisions allow, even encourage, participants to change initial ‘default’ agreements as appropriate to insights obtained during the process? “The process design is part of the plan’ but collective ‘consensus’ pressures should be resisted?

* Is research about the reliability of evaluation-avoiding approaches needed: The possibility of approaches to lead participants to ignore aspects? Forgetting things? Bias towards theory-based criteria rather than project-related concerns? ‘Star designer’ decisions as responsibility-avoidance tactics?

* Should increased efforts be encouraged to improve transparent connections between evaluation results and decision? How should these provisions be addressed in more evolved systems models of planning?

Notes

[1] Rittel’s systems model of design: H.W. Rittel: Design methods lectures at U.C. Berkeley.
[2] Rational Planning Model: https://en.wikipedia.org/wiki/Rational_planning_model
[3] Theory of Change: https://en.wikipedia.org/wiki/Theory_of_change
[4] The distinction of ‘planning arguments’ (initially ‘design arguments’) was first introduced, to my knowledge, In my dissertation ‘The Evaluation of Design Arguments’ (U.C. Berkeley, 1977). See also: “The Structure and evaluation of Planning Arguments” T. Mann, in ‘INFORMAL LOGIC, Dec. 2010. Or “The Fog Island Argument” XLIBRIS 2009

Figure 2 — Evaluation in a systems perspective of planning — overview

#planning-discourse, #systems-perspective-of-planning

Fig. A1. The relation between abduction, deduction and induction…. | Kleinhans et al, 2010

Fig. A1. The relation between abduction, deduction and induction…. | Download Scientific Diagram
Fig. A1. The relation between abduction, deduction and induction. Several alternative terms encountered in literature are given. Each has its own weakness (see text) (from Kleinhans et al., 2010).

Fig. A1. The relation between abduction, deduction and induction. Several alternative terms encountered in literature are given. Each has its own weakness (see text) (from Kleinhans et al., 2010).

Source publication

Fig. A1. The relation between abduction, deduction and induction. Several alternative terms encountered in literature are given. Each has its own weakness (see text) (from Kleinhans et al., 2010). Source publication

Fig. A1. The relation between abduction, deduction and induction…. | Download Scientific Diagram

systems changes – Theoretical Grounds, Pragmatic Grounds: Methods, Systems Changes Learning Registration, Mon, Oct 19, 2020 at 6:30 PM Toronto time

source:

Theoretical Grounds, Pragmatic Grounds: Methods, Systems Changes Learning Registration, Mon, Oct 19, 2020 at 6:30 PM | Eventbrite

OCT 19

Theoretical Grounds, Pragmatic Grounds: Methods, Systems Changes Learning

by David Ing Free

Event Information

Progressing methods with a dualistic approach: (i) the scholarly team, on theoretical grounds, and (ii) the field team, on pragmatic grounds

About this Event

In October, members of the Systems Changes Learning Circle have been leading workshops at RSD9 (Oct. 14) and Global Change Days Beacon Events (Oct. 22). We are collectively evolving a core knowledge set under Creative Commons licensing, being deployed in different styles for different audiences.

Methods development has progressed with two interacting teams with contrasting emphases:

  • the scholarly team, focused on correctness, validating on theoretical grounds; and
  • the field team, focused on understandability, validating on pragmatic grounds.

For this Systems Thinking Ontario meeting, David Ing will review the introductory framing on which the circle has converged, and outline the sequence of activities expected ahead.

Please see: https://wiki.st-on.org/2020-10-19 for more details

Open-minded novices and learners are always welcomed. We’ll try to keep the conversations understandable by the layman, and entertain questions for clarification.

To be notified of future sessions, please join the Google Group: http://bit.ly/st-on

book at:

Theoretical Grounds, Pragmatic Grounds: Methods, Systems Changes Learning Registration, Mon, Oct 19, 2020 at 6:30 PM | Eventbrite

More from https://wiki.st-on.org/2020-10-19

2020-10-19

October 19 (the third Monday of the month, due to Thanksgiving) is the 84th meeting for Systems Thinking Ontario. The registration will be on Eventbrite at https://www.eventbrite.ca/e/theoretical-grounds-pragmatic-grounds-methods-systems-changes-learning-registration-125102505963.

Theoretical Grounds, Pragmatic Grounds: Methods for Reordering our Priorities through Systems Changes Learning

In October, members of the Systems Changes Learning Circle have been leading workshops at RSD9 (Oct. 14) and Global Change Days Beacon Events (Oct. 22). We are collectively evolving a core knowledge set under Creative Commons licensing, being deployed in different styles for different audiences.

Methods development has progressed with two interacting teams with contrasting emphases:

  • the scholarly team, focused on correctness, validating on theoretical grounds; and
  • the field team, focused on understandability, validating on pragmatic grounds.

For this Systems Thinking Ontario meeting, David Ing will review the introductory framing on which the circle has converged, and outline the sequence of activities expected ahead.

Here’s a description of the abstract for the RSD9 workshop:

— begin paste —

The idea of “systems change” has risen in popularity over the past few years. To make this more than just another buzzword, how might we approach it? In what ways does “systems change” mean more than just “change”? Does “systems change” build on the large legacy of “systems thinking”?

The Systems Changes Learning Circle is now in year 2 of 10 year journey. Our aim is to reify systems changes as a first-class concept. This extends prior published research on social and organizational change, based in the systems sciences. At RSD8, the Khan and Ing (2019) presentation reflected the early explorations coming from the core group. For 2020, at RSD9, we propose a workshop to share some methods in early stages of development for initiating deeper deliberations into systems changes.

Systems changes may involve:

  • shifting adaptively;
  • shifting behaviorally; and/or
  • shifting ecologically.

Living systems may respond through:

  • systematic changes;
  • systemic changes; and/or
  • timescape-landscape changes.

Degrees of systems changes may be judged as:

  • unfolding nature;
  • fixing problems; or
  • history making.

The multi-day, iterative workshop still under development takes a multi-paradigm approach based on learnings grounded in five philosophies:

  • (i) learning which, as phenomenology;
  • (ii) learning what, as ontology;
  • (iii) learning why, as epistemology;
  • (iv) learning whom+when+where, as phronesis; and
  • (v) learning how, as techne.

To convene working groups in advance of iterations on the five learnings, we now propose a Question Zero conversation for orientation, on Reordering Priorities. This workshop on Reordering Priorities can be conducted within 90 minutes, in-person or online, with parallel breakout groups.

The workshop will be structured as multiple steps:

  • Step 0: Participants will introduce themselves briefly. To encourage discussion, participants will be encouraged to cluster into small groups with others whom they do not know well.
  • Step 1: As individuals, participants will each quickly jot down three top three systems changes in which they are interested. These systems changes may be ones that they would like to come faster, or ones they would like to not happen.
  • Step 2: A two-dimensional map will be presented. Individuals will be asked to place their top three systems changes with axes along:
    • urgent to important; and
    • local to distant (Pepper, 1934; Tolman and Brunswik, 1935).
  • Step 3: In groups, each individual will be asked to show their mappings, and provide background for having prioritized those interests.
  • Step 4: Authentic systems thinking orders synthesis (putting thing together) before analysis (taking things apart). Each group will be encouraged to attempt to synthesize its priorities across its participants.
  • Step 5: One reporter from each group will reflect on their collective experience on reordering priorities.

Artifacts and comments from the group reports will be collected for summarization, possibly for publication in the proceedings. This knowledge-creating exercise will be used to refine methods for groups engaging in action learning.

The Systems Changes Learning Circle (founded 2019) is a group convening at the Centre for Social Innovation (Toronto) emerging from Systems Thinking Ontario (founded 2012). We include postgraduates and instructors from the Strategic Foresight and Innovation Program at OCADU in Toronto. Our content at licensed as Creative Commons at http://systemschanges.com . We cooperate with the Open Learning Commons at http://openlearning.cc , and the Digital Life Collective at http://diglife.com .

— end paste —

The scholarly team has been David Ing and Zaid Khan. The field team is Dan Eng, Kelly Okamura and Zemina Meghji.

Venue:

Suggested pre-reading:

Pre-reading is not required. A list of references includes:

  • Emery, Fred E., and Eric L. Trist. 1965. “The Causal Texture of Organizational Environments.” Human Relations 18 (1): 21–32. https://doi.org/10.1177/001872676501800103.
  • Ing, David. 2013. “Rethinking Systems Thinking: Learning and Coevolving with the World.” Systems Research and Behavioral Science 30 (5): 527–47. https://doi.org/10.1002/sres.2229.
  • Ing, David. 2017. Open Innovation Learning: Theory Building on Open Sourcing While Private Sourcing. Toronto, Canada: Coevolving Innovations Inc. https://doi.org/10.20850/9781775167211.
  • Khan, Zaid, and David Ing. 2019. “Paying Attention to Where Attention Is Placed in the Rise of System(s) Change(s).” In Proceedings of the RSD8 Symposium. IIT – Institute of Design, Chicago, Illinois: Systems Design Association. https://systemic-design.net/rsd-symposia/rsd8-2019/systems-change/.
  • Pepper, Stephen C. 1934. “The Conceptual Framework of Tolman’s Purposive Behaviorism.” Psychological Review 41 (2): 108–33. https://doi.org/10.1037/h0075220.
  • Ramírez, Rafael, John W Selsky, and Kees van der Heijden. 2008. “Conceptual and Historical Overview.” In Business Planning for Turbulent Times: New Methods for Applying Scenarios, edited by Rafael Ramírez, John W. Selsky, and Kees van der Heijden, 17–30. Earthscan. http://doi.org/10.4324/9781849774703.
  • Tolman, Edward C., and Egon Brunswik. 1935. “The Organism and the Causal Texture of the Environment.” Psychological Review 42 (1): 43. https://doi.org/10.1037/h0062156.

Agenda

https://www.gstatic.com/atari/embeds/5de913a2354e93acf4d43c4db53928e5/intermediate-frame-minified.html?jsh=m%3B%2F_%2Fscs%2Fapps-static%2F_%2Fjs%2Fk%3Doz.gapi.en_GB.rfCVHjX22yM.O%2Fam%3DwQE%2Fd%3D1%2Fct%3Dzgms%2Frs%3DAGLTcCP711OA6KJNspWsqcliNYUXjRiXzw%2Fm%3D__features__&r=473560388

Post-meeting artifacts

Bloggers are encouraged to write about their learning and experiences at the meeting. Links will be added to this page.

Complex Systems Leadership Program – various training courses from WICKED LAB in Australia

Address wicked problems by ​ embracing complexity and creating systemic change 

Complex Systems Leadership Program – WICKED LAB