Lillian Gilbreth’s Synthesist:

Harish's avatarHarish's Notebook - My notes... Lean, Cybernetics, Quality & Data Science.

Lillian Gilbreth is one of my heroes in Industrial Engineering. I have written about her here and here. In today’s post, I am looking at Gilbreth’s idea of an analyst and synthesist. The term “analyst” is in common vocabulary, whereas the term “synthesist” is not. Even Microsoft Word is identifying that the term “synthesist” is incorrect.

In any introduction class to systems thinking, we get introduced to the idea of analysis and synthesis. As Russell Ackoff, the giant in Systems Thinking, teaches us:

A system is a whole which consists of a set of two or more parts. Each part affects the behavior of the whole, depending on how it interacts with the other parts of the system. To understand a system, analysis says to take it apart. But when you take a system apart, it loses all of its essential properties. The discovery that you cannot understand the…

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Behavior (a systems definition, 2004)

daviding's avatarIn brief. David Ing.

We use the term “behavior” widely. Do we really know what we mean by that? Here’s an entry from the International Encyclopedia of Systems and Cybernetics.

— begin excerpt —

0247
BEHAVIOR 1) – 4)

1. “The system of interconnected and expedient actions carried out by an organism” (UNESCO-UNEP, 1983, p.6)

2. A repetitive sequence or pattern of actions or operations, and resulting states, characteristic of a specific system.

The second definition is more general than the first, since it can apply to non-living systems, as well as to societies of organisms.

The concept of behavior, when referring to a complex system, may be associated with an interconnected network of actions.

G. PASK gives the following examples: “The behavior of a steam engine is a recurrent cycle of steam injection and piston mouvements that remains invariant. The behavior of a cat is…

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A loop theory of wisdom – how do we respond to foolish times? Geoff Mulgan

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A loop theory of wisdom – how do we respond to foolish times?

Geoff Mulgan

  • Jul 1

A loop theory of wisdom – how do we respond to foolish times?

Is it possible for an organisation, a system or a society, to become wiser? If so, how could we make this real and not just a vague invocation – like wishing people would be kinder or more loving?

In this draft paper (a more developed version of which will be published in a couple of months) I share some answers. I suggest what might be missing in much writing about wisdom and I suggest an alternative framework that cuts across different disciplines, including philosophy, psychology, computer science and organisational design.

I argue that progress in this field is badly needed, and not just because of the very visible lack of wisdom amongst many leaders and institutions, but also because rapid progress in use of data and artificial intelligence has not led to obviously wiser actions, in part because these fields lack a coherent view of the relationship between data, knowledge and wisdom.

I also argue that wisdom, and thought about wisdom matters, because it should sit above other types of knowledge, including scientific knowledge, or the insights of particular disciplines or professions.

Wisdom depends on expertise, but sits above it – and, as I argue, this should shape how we design institutions and laws, as well as science advice and governance, the design of digital technologies, and the crucial institutions that help the world make wiser decisions about complex long-term challenges – such as the IPCC and others around climate change, or IPBES concerned with biodiversity and ecosystems.

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The paper challenges some conventional views of this topic which see wisdom as static rather than dynamic, individual rather than collective, introspective rather than involving argument and open learning, and general rather than domain specific.

All of these assumptions may be misleading. I argue that instead of thinking of wisdom as an attribute we should understand it as a series of loops – loops linking thought, action and results; loops involving feedback from others; and loops involving argument and decision.

The paper shows why attempts at definition and taxonomy have been unsatisfactory and why wisdom is not a single thing but rather a shifting assembly of elements linked by what I call integrative judgement, that is in turn guided by reflection on experience. I suggest how institutions could be designed in ways that partly mimic the sometimes competing and sometimes cooperating parts of the individual brain to come closer to a capacity for wisdom.

I present wisdom as an inherently looped concept. I question the idea that wisdom is an attribute of particular people or institutions, presenting it more in terms of processes and actions. What is wise is what in the long run turns out to be wise. We can only truly recognise wisdom in retrospect, or from a distance. Words alone cannot be wise (and putting too much weight on the declarative, verbal side of wisdom opens up greater risks of hypocrisy and error, and greater risks of taking at face value the traditional hierarchical associations of wisdom – age, status, gender etc).

But if wisdom is looped, as I suggest, this also means that it can be learned, whether by individuals or organisations, through habits that partly mirror those of Bayesian inference. Moreover it is possible to address head-on processes that run counter to wisdom –algorithms that circulate lies, media dynamics that tend to amplify attention to people with vivid but misleading ideas, or legal processes that fuel discord.

I also suggest that wisdom is to some extent collective – dependent on others and their feedback – and that it is contextual; we can only judge it from a vantage point. There is no such thing as universal wisdom and wisdom is unstable because the environment that makes up its context is fluid, meaning that what is wise at one point may not be at another point. Wisdom is also looped in another sense. To think wisely we have to learn both to go out, and then to come back: to go out in the sense of exploring other perspectives, ways of seeing and thinking; and to come back in the sense of returning to an action or decision that will always be simpler than the thoughts that guide it.

Drawing on this idea I show how it is possible to cultivate wisdom; to build it into institutions and systems, usually through a division of labour; how to embed it into physical objects and into a further evolution of knowledge management and search tools, as well as artificial intelligence. I also address how wisdom can be cultivated in making sense of new fields of science and technology, bringing with them uncertain risks and benefits.

By making the pursuit of wisdom more explicit with claims, predictions and formal processes that allow for shared reflection and learning, along with a constant iteration of questions and answers, I argue that we can improve the quality of thought not only of individuals but also of organisations and whole systems. By removing some of the mystique surrounding wisdom we can do more to promote it.

None of this would matter if the world was replete with wisdom. But it’s not. Wisdom is fragile, elusive and often undervalued. In a world where data and information have become ever more ubiquitous and cheap, wisdom may have become even rarer.

………………….

I am sharing this (quite long) paper in a draft form in the spirit of its contents – to encourage critical comment and feedback.

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A loop theory of wisdom – how do we respond to foolish times?

Demystifying modeling: How quantitative models can–and can’t–explain the world | McKinsey

not-actually-wrong from McKinsey!

source: https://www.mckinsey.com/business-functions/risk/our-insights/demystifying-modeling-how-quantitative-models-can-and-cant-explain-the-world

Demystifying modeling: How quantitative models can—and can’t—explain the world

June 25, 2020 | Article By Sarun Charumilind, Anas El Turabi, Patrick Finn, and Ophelia Usher Open interactive popup Demystifying modeling: How quantitative models can—and can’t—explain the world Open interactive popup The COVID-19 crisis has brought quantitative models to the forefront. Here are some ways that modeling helps us—as long as we avoid its pitfalls.

One of the many impacts of the COVID-19 crisis has been to highlight the role of quantitative models in our lives. Ideas associated with modeling, such as flattening the curve of disease transmission, are now regularly discussed in the media and among families and friends. Across the globe, we are trying to understand the numbers and what they mean for us.

Forward-looking models aren’t new. They have long played an important but unseen role in day-to-day life—for instance, in pricing homeowners’ insurance, anticipating the weather, and deciding how many iPhones to manufacture. However, in the COVID-19 pandemic, the scale of impact and the level of uncertainty have introduced new challenges—and notoriety—for modelers.

Used properly, models provide information that can present a framework for understanding a situation. But they aren’t crystal balls that state with certainty what will happen, and they don’t in themselves answer the difficult question of what to do. The eminent British statistician George Box summarized the point with his famous aphorism: “All models are wrong, but some are useful.” And he refined it by saying, “Since all models are wrong, the scientist must be alert to what is importantly wrong. It is inappropriate to be concerned about mice when there are tigers abroad.” Sidebar

What is a model?

This article explains how models can help us make sense of the world and why they behave the way they do (see sidebar “What is a model?”). We also discuss the most common modeling pitfalls and how to avoid them.

The power of models

Making decisions in the face of uncertainty is challenging, particularly during a pandemic. Quantitative models can help us understand systems and behaviors in a number of useful ways that help navigate this ambiguous environment.

Clarifying which drivers matter

Models structure data in support of reasoned decision making by restricting variables to those that matter for a particular question. For example, when developing a demographic model to help civic leaders plan future community needs, key drivers could be birth rates, death rates, and new-job creation. Models can help users understand what is known about each element and identify the areas of continuing uncertainty. https://view.ceros.com/mckinsey/coronavirus-promo-video-desktop

Determining how much an input can matter

Models are well suited to exposing sensitivities: they show how even small changes in key assumptions can produce large variations in outcomes, helping decision makers establish priorities. An obvious case in point related to the COVID-19 pandemic is the massive impact of even small adjustments in the transmission rate of infection. By establishing sensitivities, models pinpoint areas for investment of effort or money to reduce uncertainty.

Facilitating discussions about the future

Models expose how different assumptions lead to different outcomes. Through discussion of modeling results, decision makers can form a collective judgement on scenarios to plan for, based on the multiple variables considered, and thus reach practical decisions (see sidebar “Building a quantitative model while using it”). For example, models were used to enable policy makers to weigh the benefits of requiring seatbelts against the moral hazard of encouraging people to drive faster. Not only do models trigger discussion, but they may force a more nuanced and evidence-based approach to decision making. In many cases, that is more important than the specific output itself. Sidebar

Building a quantitative model while using it

Pitfalls to avoid when using models

Overlooking the fact that a model can’t fix bad data

Taking assumptions and simplifications for granted

The risks of bias in modeling

Expecting too much certainty

Modeling philosophy for the COVID-19 pandemic

continues in source: https://www.mckinsey.com/business-functions/risk/our-insights/demystifying-modeling-how-quantitative-models-can-and-cant-explain-the-world

COVID-19 – A Complexity Leadership Response, Diane Ketley

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COVID-19 – A Complexity Leadership Response, Diane Ketley


COVID-19 – A Complexity Leadership Response

7 July, 202053Post contributor:Diane Ketley, NHS HorizonsDiane Ketley

The current COVID-19 situation is an example of complexity – and an opportunity for reflection on how systems respond to the challenges it is causing.

We need to understand that complex, adaptive systems such as healthcare are dynamic, have multiple interacting elements, are unpredictable and have the following characteristics:A complex adaptive system has the capability to self-organise, accommodate to behaviours and events, learn from experience and dynamically evolve but not necessarily in predictable ways. The system’s performance and behaviour changes over time and cannot be completely understood simply by knowing about the individual components. Read more in Adaptive Spaces, Networks…. and a Challenge Called Spread and Braithwaite 2018.

Mary Uhl-Bien recently joined Matthew Mezey from the Q community and me for a virtual conversation to share her insights on the current complex challenges COVID-19 brings, and illustrate these insights with examples of responses seen in USA and UK.

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COVID-19 – A Complexity Leadership Response, Diane Ketley

How Can We Apply Physics to Biology?

Why Physics Is Not a Discipline Physics is not just what happens in the Department of Physics. BY PHILIP BALL APRIL 21, 2016

How Can We Apply Physics to Biology?

Systems design and the front line | Seth’s Blog

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Systems design and the front line | Seth’s Blog

Systems design and the front line

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Systems design and the front line | Seth’s Blog

Ecosystems thinking for design in government and non-profit sectors — the basics (1/2) | by ksenia cheinman | Jul, 2020 | Medium

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Ecosystems thinking for design in government and non-profit sectors — the basics (1/2) | by ksenia cheinman | Jul, 2020 | Medium

Ecosystems thinking for design in government and non-profit sectors — the basics (1/2)

ksenia cheinman

ksenia cheinmanFollowingJul 7 · 12 min read

A tiled collage of 9 black and white images showing every-day life from different angles and perspectives.
Images from Unsplash; Sean BeneshCharles DeluvioGeran de KlerkDave MichudaArtem MaltsevLaura ConnellyTony SebastianJessica DelpKeisuke Higashio.

This article is Part 1/2 . Part 2 shows what ecosystems thinking could look like in action. Part I covers the basics:

  • What is an ecosystem
  • Why is ecosystems thinking important
  • How to map ecosystems
  • What to do with ecosystems
  • Ecosystem resources

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Ecosystems thinking for design in government and non-profit sectors — the basics (1/2) | by ksenia cheinman | Jul, 2020 | Medium

How To Hack The Epistemic Crisis, with Audrey Tang – STEAL THIS SHOW

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How To Hack The Epistemic Crisis, with Audrey Tang – STEAL THIS SHOW

How To Hack The Epistemic Crisis, with Audrey Tang

Friday 26 June 2020

https://stealthisshow.com

39:07

In this episode, we meet up with Audrey Tang, Taiwan’s Digital Minister, to discuss how Taiwan eliminated Covid-19 with only 7 deaths. Find out how information technology was instrumental in Taiwan’s success, from helping source and distribute masks, to enabling citizen engagement through direct democracy. And finally, we dig into how this ongoing experiment with direct democracy in Taiwan has helped avoid the deadly plague of conspiracy theories, social polarization, and what some people are now calling the ‘epistemic crisis’ we’re experiencing in the West.

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How To Hack The Epistemic Crisis, with Audrey Tang – STEAL THIS SHOW

Life begets life: The diversity of species on Earth is generating itself | Roberto Cazzolla Gatti

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Life begets life: The diversity of species on Earth is generating itself | Roberto Cazzolla Gatti

Roberto Cazzolla Gatti

Life begets life: The diversity of species on Earth is generating itself

RCG / 14 febbraio 2017

A new research hypothesis suggests that biodiversity is autocatalytic

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If competition is the main evolutionary driver, why can so many species coexist within the same ecosystem instead to have a few that dominate? This a long and central question in ecology. Many ideas have been suggested in an attempt to explain this evolutionary paradox. Most of them are based on the importance of ecological niches for the maintenance of differentiated against dominated environments.fractal_tree_by_tararoys

A fractal tree, as that hypothesized in the BNDT by Dr. Roberto Cazzolla Gatti, for the differentiation of niches (as growing branches of the tree) biodiversity-related (the more species, the more branches=the more niches)

In 2011, Dr. Roberto Cazzolla Gatti, associate professor in Ecology and Biodiversity at the Tomsk State University (Russia) proposed the “Biodiversity-related Niches Differentiation Theory” (BNDT), arguing that species themselves are the architects of biodiversity, by proportionally increasing the number of potentially available niches in a given ecosystem. Along similar lines, but independently, the idea of viewing economics, biology and ecology as emergent autocatalytic sets (self-sustaining network of mutually “catalytic” entities) was suggested by Dr. Wim Hordjik, researcher at the Konrad Lorenz Institute for Evolution and Cognition Research, Klosterneuburg (Austria) and the famous McArthur Fellowship winner, Prof. Stuart Kauffman from the Institute for Systems Biology, Seattle (USA).

Now, in a paper published in Ecological Modelling (Volume 346, 24 February 2017, Pages 70-76) with the title “Biodiversity is autocatalytic” the three scientist merged their ideas in a new hypothesis to explain why and how a so great amount of species could live together in the same environment. The research paper suggests that one group of species enables the existence of (i.e., creates niches for) other species. This means — the authors say — that “biodiversity can indeed be considered a system of autocatalytic sets, and that this view offers a possible answer to the fundamental question of why so many species can coexist in the same ecosystem”.

simple_autocatalysis

The variability among living organisms in terrestrial, marine and other aquatic ecosystems, and the ecological complexes of which they are a part, have been defined with the term “biodiversity”. Apart from the formal definitions and the different ways to measure it, the central question about biological diversity on Earth is how so many species can coexist within the same ecosystem.

However, the idea that interactions between species are important catalysts of the evolutionary processes that generate the remarkable diversity of life is gaining interest among ecologists. For instance, it has been shown that symbiosis between gall-inducing insects and fungi catalysed both the expansion in resource use (niche expansion) and diversification. Indeed, facilitation (a process that allows the colonization and presence of new species taking advantage of the presence of other ones by expanding the ecosystem hypervolume) plays a major role in species coexistence, strongly increasing the biodiversity of an area. A species emerges from this environment and is an expression, in fact a historically contingent expression, of those interactions. In other words, species are expressed and maintained by a complex interacting ecological network.

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Life begets life: The diversity of species on Earth is generating itself | Roberto Cazzolla Gatti

Lean Management: A Socio-Technical Systems Approach to Change – STS Roundtable

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Lean Management: A Socio-Technical Systems Approach to Change – STS Roundtable

Lean Management: A Socio-Technical Systems Approach to Change

Let it be said that there are multiple paths to the same truth. Ancient tribes possessed knowledge of the environment and man’s place in the natural world that we are just now confirming through science.

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Lean Management: A Socio-Technical Systems Approach to Change – STS Roundtable

Whole systems approach needed to tackle housing issues – Claire Smith, New Civil Engineer

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Whole systems approach needed to tackle housing issues – New Civil Engineer

Whole systems approach needed to tackle housing issues

02 JUL, 2020 BY CLAIRE SMITH

Poor outcomes and unintended consequences could be avoided by using a systems approach to planning housing, according to new research by the National Engineering Policy Centre.

The Sustainable Living Places report, which was led by the Royal Academy of Engineering, is calling for national and local planning policies to be aligned around a common sustainability agenda for both housing and infrastructure.

The report, which was delivered in partnership with the Infrastructure and Projects Authority, says that the planning system must be demystified and stakeholders empowered in order to unlock the potential benefits for society.

According to the report, the current housing crisis provides a real opportunity for change in both the quality of living places and the scale of housing delivery in the UK. However, the complexity of the housing problem demands a systemic approach with 300,000 new properties needed a year to meet demand plus the target to reach carbon net zero by 2050.

The findings suggest that applying a systems approach to a complex policy challenge offers insights on how those perspectives interact to shape the development of a place.

The project focused on applying the systems approach used for infrastructure to the housing market in order to create sustainable living places, which the group defines as happy, healthy, low carbon, adaptive places where people desire to live.

Sustainable Living Places working group chair Tim Chapman said: “As engineers providing independent advice, we wanted to apply our engineering expertise to make life in the UK better. In particular, we had a strong wish to apply the engineering principle of whole-systems thinking into other arenas, where clearly things did not work as well as they could or should.

“We set up a working group of experts, to explore how this thinking might be applied to housing in the UK, a complex challenge, with social, environmental and governance issues.”

Using a participatory systems approach, engineers and professionals representing the multiple disciplines across the system of housing, planning and infrastructure, worked together to develop a shared understanding of the current system of the process. Engineers worked in collaboration with economists, planners, sociologists and community leaders to provide an independent, big picture view of the whole process. Together they created a detailed map that captured challenges and identified opportunities for change. The report identifies key elements of the system and how they impact and interconnect with one another, and pinpoints areas where change can be most effective.

“The first stage of the work has resulted in maps that offer different and exciting opportunities for change in the system,” said Chapman. “More interestingly, it shows that the discipline of whole systems thinking is much more broadly applicable and it can shed new light to traditional problems, where the policy issues are far wider and complex than the engineering ones alone. It also proves that the discipline of engineering in partnership with other professional disciplines can bring a new clarity to policymaking, presenting a high-level and accessible summary of a complex problem involving a panoply of issues.”

The key leverage points for positive change…

continues in source

Whole systems approach needed to tackle housing issues – New Civil Engineer

Traditions of ‘Complexity and Systems Science’?

jamorell's avatarEvaluation Uncertainty

Martin Reynolds (The Open University). Applied Systems Thinking in Practice (ASTiP) Group. School of Engineering and Innovation. The Open University, Walton Hall, Milton Keynes MK7 6AA, United Kingdom +44 (0) 1908 654894 | martin.reynolds@open.ac.uk |  Profile | Publications

From a systems thinking in practice (STiP) tradition I would first like to change the formulation from ‘complexity and systems science’ to complexity scienceand systems thinking (cf. Reynolds et al., 2016). The revised formulation is important for two reasons in appreciating respective lineages. First, contemporary ideas on complexity including the ‘butterfly effect’ and ‘complex adaptive systems’ are very much rooted in the scientific tradition dating from Warren Weaver’s 1947 paper ‘science and complexity’. Second, contemporary systems thinking should be regarded as a transdisciplinary endeavour inclusive of systems science and complexity science, but far beyond the confines of a scientific discipline (Reynolds and Howell, 2020). Note that…

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Free SDS Conference Plenary session on “Societal Containment of COVID-19”, Monday, July 20, 2020, 13:00 Central European Summer Time

lifted from Rob Young’s post at

https://www.facebook.com/groups/SCA.COVID19

Free SDS Conference Plenary session on “Societal Containment of COVID-19”, Monday, July 20th, 13:00 Central European Summer Time

https://sds.memberclicks.net/

Monday, July 20th, 13:00 Central European Summer Time

Societal Containment of COVID-19, chaired by Peter Hovmand

As part of our 2020 virtual conference, there will be one plenary session related to COVID-19. The Society has made the decision to open this session up to anyone who would like to attend free of charge. Papers in this session will highlight work in the field that serves to inform public health policy to contain the COVID-19 pandemic and provide learning opportunities that improve mental models for policy-makers, modelers, and the general public.

The following papers will be presented:

· Modeling the Transmission Dynamics of SARS-CoV-2 and the Effects of Intervention Timing on COVID-19 Incidence, by Jeffrey Shaman

· Simulation-based Estimation of the Early Spread of COVID-19 in Iran: Actual versus Confirmed Cases, by Navid Ghaffarzadegan, Hazhir Rahmandad

· Hybrid Modeling with System Dynamics to Contain COVID-19, by Nathaniel Osgood

(part of the System Dynamics Society annual conference: SDS 2020, virtual, July 20-22, and Summer School, Colloquium and Workshops on other dates)

 This online session is FREE and open to all! Monday, July 20th, 13:00 Central European Summer Time Societal Containment of COVID-19, chaired by Peter Hovmand All conference attendees are already registered for this session. Additional participants will be accepted until we reach our limit of 1000 participants. To reserve your spot, register below. If we exceed our limit, we will add you to a waiting list.

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Systems Thinking Ontario – 2020-07-13, 6:30pm Ontario time

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Systems Thinking Ontario – 2020-07-13

Systems Thinking Ontario – booking at https://www.eventbrite.com/e/synthesis-mapping-2020-sfi-2-systems-thinking-ontario-registration-108793075016

2020-07-13

July 13 (the second Monday of the month) is the 81th meeting for Systems Thinking Ontario. The registration is on Eventbrite at https://synthesis-mapping-2020-2.eventbrite.com.

Synthesis Mapping (#2), 2020 Strategic Foresight and Innovation program

Every year Systems Thinking Ontario hosts a series of summer evening events for presentations of synthesis maps (complex systems maps) created in systemic design courses in OCAD University graduate programs.

  • The previous evening, June 8, we had three presentations.
  • This second evening, July 13, we’re looking to have up to three presentations.

Synthesis maps are rich visualizations that illustrate the real-world complexity of systemic challenges, and typically used to not only “map system problems” but to propose design recommendations for systems change and policies (from health to public policy, from service experiences to social change) from evidence gathered in stakeholder research. Policymakers and organizational stakeholders use synthesis maps for strategic advising, long-term planning, and considering interventions for social and systemic challenges (wicked problems).

While we are still sorting out the final slate of presenters, we have confirmed:

  • “The Canadian Loonshot: The hewers of pixels and the drawers of data in service of the world”, with Trevor Bell, Geoffrey Evany Hill, Nam Hoang, Ali Milad
  • “Putting the Dating in Online Dating”, with Ireena Haque, Gulnar Joshi, Aneesha Kotti, Grayce Slobodian
  • [more to come]

Venue:

  • The link for a Zoom conference will be sent upon registration on Eventbrite.
    • It’s really too bad that we can’t use the OCADU Visual Analytics Lab to meet in person!

Suggested pre-reading:

What are Synthesis Maps and Gigamaps? at https://slab.ocadu.ca/project/synthesis-maps-gigamaps

Agenda

https://www.gstatic.com/atari/embeds/913211048dfa67f4be7864f4505a4b63/intermediate-frame-minified.html?jsh=m%3B%2F_%2Fscs%2Fapps-static%2F_%2Fjs%2Fk%3Doz.gapi.en_GB.iWyQuFdbWzA.O%2Fam%3DwQc%2Fd%3D1%2Fct%3Dzgms%2Frs%3DAGLTcCOyhlEmBby7qWoiftyYszJcOof1oQ%2Fm%3D__features__&r=411151227

Post-meeting artifacts

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

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Systems Thinking Ontario – 2020-07-13