Highlights

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# Intuition is confident abductive-inferential thinking

In a recent episode of Hello Monday, Jessi Hempel interviews Dr. Natalie Nixon on creativity and her new book, The Creativity Leap. Natalie’s PhD in Design Management—plus her work in fashion, design, and business—led her to a catchy and compelling description of creative work. We accomplish creative work, she says, “by toggling between wonder and rigour.”

In the podcast conversation, Jessi and Natalie talk about intuition—and I was struck by something. “We don’t talk about intuition,” Natalie notes at about 6 minutes in. “We don’t talk about intuition in business school, in law school, or in medical school.” And yet, she says, “I observed that really successful leaders—especially really successful startup leaders—in their origin stories, there’s always this moment where ‘Something told me not to do the deal. Something told me to work with her over him.’ […] Every successful leader really reckons with incorporating acting on their intuition to make decisions.” Jessi agrees, noting that intuition comes up often in her interviews with leaders on Hello Monday as leaders cite it as the reason for their success.

The thing is, just because we don’t name intuition doesn’t mean we aren’t talking about it. That’s because intuition is really just confident, logical thinking.

Charles Sanders Peirce was a philosopher. He investigated how we inquire into and discover new knowledge.1 Before Peirce, we generally recognized the logical processes of deduction and induction. Deductive thinking helps us identify what must be true about a situation in order to explain it. When we deduce something, we look at the general rules and principles we know of and draw specific conclusions from that evidence. Inductive thinking involves drawing general conclusions from specific, limited evidence.

Peirce argued that effective reasoning follows a pattern: we determine the specific consequences of an idea (deduction), and then we judge whether the available evidence fits that idea and its consequences (induction). But how do we develop ideas?2

Abduction is the name of the logical process Peirce described for developing ideas. To think abductively means to generate and choose ideas that fit the situation at hand. A good idea should be verifiable—we should be able to use evidence to judge its fit—and should help us resolve the situation at hand. Peirce also had criteria to help choose the best ideas to test. He suggested that we should strive to conserve resources (e.g., those that most are most efficiently verifiable and usable in the situation), identify the most valuable ideas (specifically the “uberty” of an idea, or how likely it is that a possible idea might bring about an innovation), and the most relevant ideas (e.g., those that may apply beyond our current focus, too).3

Abduction is clearly an important step in any innovative process—but it is no more important than testing and using the ideas you generate. What, then, if you don’t have enough evidence to truly test and prove your ideas?

The process Peirce described—abduction, deduction, induction—is the ideal. However, we do not always have time and energy to follow the process diligently. Instead, we quickly make creative judgements based on a few observed qualities. This requires two related processes.4 The first Peirce called “abductory induction,” and it combines the first and last step of the inquiry process. We observe the qualities of the situation, and we generate possible ideas to resolve it based on those observations. The second process is known as “inference to the best explanation” (IBE).5 IBE is exactly what it sounds like. Given a number of possible ways of resolving a problem, choose the best one. (Peirce’s criteria, noted above, apply here.)

So what does all this have to do with intuition?

Intuition is the confident application of these shorthand logical approaches to creative problem solving. As Jessi and Natalie noted, we aren’t often explicitly taught about strengthening our intuition. Yet, everything we learn supports its development. The more we have to draw on in order to pull into the processes described above, the better our intuitive decisions will be.

I say that intuition is the confident application of these processes because they only work when we follow through. In reality, we use abductory induction and IBE all the time. When we engage in creative problem solving, we’re not only using information from the evidence in front of us. We’re drawing on our lived experience and our knowledge base. Even if we don’t directly recall or reference that background information, it is drawn into the creativity of abduction and it defines the general rules and principles we use in deduction. It provides us with the heuristics we use when engaging in IBE. But if we don’t have a bias towards action and instead operate with e.g., perfectionism, we fail to actually execute on these ideas. Thus, we need to have confidence in our abductory induction and IBE processes.

All this is simply a gentle challenge of the idea that we don’t talk about intuition. I think that all knowledge management practices and forms of education are actually fundamentally about strengthening our intuition.

That said, Natalie’s work is fascinating. I recommend the episode of Hello Monday and plan on picking up her book!

1. In this article, my reading of Peirce comes from the writing of William Mcauliffe↩︎

2. Peirce was actually specifically concerned with science and hypotheses generation, selection, and testing. Here I refer to generating, selecting, testing, and using ideas to apply these concepts to problem-solving more broadly. ↩︎

3. He also cautioned not to produce ideas that stop the inquiry process—e.g., magical thinking, or by suggesting that whatever happened must be a complete mystery. ↩︎

4. Actually, the difference between these two processes is the subject of substantive, controversial debate. This is in part because the scholars who study inference to the best explanation have also used Peirce’s term “abduction” to describe it. This understandably caused extensive confusion, but also probably a lot of philosophical debates and scholarship, so maybe it was for the best. ↩︎

• Researchers detail huge hack-for-hire campaigns against environmentalists

The report concludes that the campaigns represent “a clear danger to democracy” and could allow powerful organizations to target their opponents. “The extensive targeting of American nonprofits exercising their first amendment rights is exceptionally troubling,” Citizen Lab’s report says.

We didn’t want this part of cyberpunk sci-fi…

# Why are we exceeding the Earth’s carrying capacity?

This is a quickly-sketched model created from a breakout group conversation during the MUN School of Graduate Studies’ “Earth’s Carrying Capacity” dialogue.

• Roger Martin, Bianca Andreescu, and systemic strategy

According to designer/strategist Roger Martin, a strategy is an imagined possibility with which we ask the question “What has to be true for this possibility to become real?”

In this episode IDEO U’s Creative Confidence podcast, Roger talks about how that approach helped unlock Bianca Andreescu’s success at the Grand Slam singles championship in 2019.

One of the fascinating things about this approach is that it acknowledges the need for system-wide changes. By asking “What has to be true?”, a strategist must consider all of the conditions of a system that should shift to make the imagined possibility a reality. Of course, most approaches to strategy do require some appreciation of the state of the strategic environment (e.g., the five forces model). None, however, emphasize the need to guarantee these systemic conditions quite as explicitly as asking “What must be true?”

• Systemic lessons from South Korea's Patient 31

This changed with the emergence of “Patient 31.”

Reuters’ coverage of the “Korean clusters” provided the world with a vivid glimpse of the volatility of COVID-19. One person showed poor judgement, and in turn caused cascading catastrophe in her communities.

Events like the COVID-19 pandemic are thankfully rare. Moments like these—when a lot happens all at once, and the experience is shared by a collective—shape future history like nothing else. We are learning a lot from this. Not only are epidemiologists now a famous profession, but we’re all learning exactly what it takes to provide good healthcare, what good governance looks like, how public health is community health, and more.

Patient 31 holds a simple lesson for systemics: the fragility of apparently solid social systems. South Korea seemed to do everything right. Yet, due to the volatile nature of this particular socio-health system, a single “free radical” caused immense damage.

Similar volatility is evident—but more subtle—in other social systems. Consider how memes spread. Our massive communities may seem immovable at times, but it’s clear that the wrong (or right) phenomena can spread rapidly and deeply.

Stay safe.

# Divide & conquer

I have often hesitated to draft up an idea because I’m not sure the folks reading this site want to hear it. I (aim to) publish about a few disparate subjects, really:

• Systemics, design, and social change
• Data modelling and data for social change
• Productivity and personal knowledge management
• Scripting and (personal) automation
• Leadership, innovation, and changemaking

Obviously, this is too many topics for any one blog. If you’re reading this, you probably came here for just one of the topics above, and you might be interested in another one or two. And listen, I like you, and I want any visit of yours to be a valuable one. That’s why I’ve launched a sibling blog.

I could cluster the topics above a number of ways. Here’s what I think makes the most sense: This blog, Fulcra, will focus on finding leverage for complex change, including:

• Systemics, design, and social change
• Data modelling and data for social change
• Leadership, innovation, and changemaking

The newest one, Axle, will focus on how we change ourselves, including:

• Personal development
• Design and technology for augmented cognition
• Productivity and personal knowledge management
• Scripting and (personal) automation

Moving forward, this site (Fulcra) will be a platform for writing on complex systems change. I aim to study, share, and write about how the world changes—and how we can get better at changing it.

Axle is a new site I will use to share my thoughts on how we change ourselves. After all, the better we get, the better we better get. The easy thing to write about (and what you’ll probably see the most often there) are the apps and tools I use and the designs I apply in my life and work. I also plan to share functional resources (such as scripts) as well as ask questions and debate about making progress in life and work.

This was a weird decision. After all, I barely publish here, so running two different sites seems like a terrible idea. I hope, however, that having more focused platforms for these different topics will help me publish more impulsively. Feel free to follow both, or none!

• Can Snow Clearing Be Sexist?

And so the Swedish gender equality initiative team began to explore whet her snow clearing was sexist. Sure enough, they found the routine of clearing snow typically benefited men over women. In the winter, snow was cleared first on main roads leading into the city, benefiting commuters—who were mostly men. Foot- and cycle-paths were cleared last—not so good for pedestrians and cyclists, who were very often women traveling with children in pushchairs.

There was a cost to all this: 79% of pedestrian injuries occurred in winter, of which 69% were women. The estimated cost of these falls was SKr36m per winter, about USD3.7m / £3m / €3.4m / Indian ₹279m. By clearing paths first, accidents decreased by half and saved the local government money. Great action-based response to a stupid remark (“At least snow-clearing was something those ‘gender people’ can keep their noses out of,” someone had said, prompting this investigation). • As Lambda students speak out the schools debt-swapping partnership disappears from the internet “The ISA is the business model, not education,” says Kim Crayton, a business strategist and founder of CauseAScene , an organization that’s seeking to disrupt the status quo in tech. “You cannot tell me that education is your business model when you have not registered as an institution.” For months, Crayton has been speaking about the problems with coding bootcamps on her podcast, where she’s argued that they target vulnerable communities. “You’re put in these spaces and putting in 110 percent and it’s still not working and you’re told to ‘trust the process,’” she says. Great reporting on this at The Verge. Kim Crayton makes an excellent point. The promise of many of these neo-credentials is for students to leapfrog the things everyone fears about the conventional education system. No one is more vulnerable to taking on loads of student debt than those who need it most. Those students are also going to suffer the most if their university or college fails to equip them for a career. Lambda solves both of these problems, making it extremely attractive to poor students. Sadly, there’s always a catch. • Bring It On Haters With Special Guest Ben Thompson Ben Thompson, in discussion with John Gruber: It was mindblowing. It was absolutely incredible. The way that you could just do stuff that wasn’t really possible [on a computer]. Again, it was technically possible on a computer, but the user interface and experience was just transformative on the iPad. It was absolutely incredible. And Jobs knew it. It’s one of my all-time favourites Jobs moments. It’s like fifteen seconds after the demo, and it’s just like… he’s used this. He was involved in the creation of it. They had run through the demo. He knew it. And even then, he was just astonished. He’s just like ‘I can’t believe [this]…’ […] It was, to my mind, the culmination of his life’s work. He comes on there, and he’s like, ‘Isn’t it incredible? Now anyone can make music.’ I almost want to transcribe this whole episode. John Gruber and Ben Thompson discuss the potential of the iPad—and its failure to reach it. Ben uses the term “transformative” deliberately above. They discuss how, before the iPad, no computing experience could adapt to become wholly new tools and environments for whatever the user wanted to do. But the iPad can become a piano or a canvas or a television. In this sense, they argue that the iPad has (or had) the potential for disruptive innovation (RIP Clay Christensen)—but it’s not supposed to be a Mac. These two think the iPad’s lost the chance to fulfill that potential, mostly because Apple has missed the opportunity to build a vibrant developer ecosystem due to App Store policies. I hope that isn’t the case, though I think we have to look beyond the iPad to fully appreciate what might happen next. The introduction of tablets and transformative computing experiences continues to echo throughout a variety of industries. Graphic designers and illustrators have a new suite of tools to directly interact with their creations in the iPad Pro and the Surface. Similarly, tablet or hybrid devices have transformed schools—schoolchildren now have a “homework” device for all kinds of assignments. It’s true that we still need developers to imagine ever-more revolutionary applications for these devices, but there’s no denying that disruption is taking root. Either way, the episode is well worth a listen. Enjoy from 15:50 to ~31:22 and 1:26:59 to the end of the show if you want to focus on the iPad discussion. • Starting the Decade by Giving You More Control Over Your Privacy My bank, fitness and workout apps, and food delivery services I haven’t used in months—those were some of the 30+ apps interacting with Facebook data. Ostensibly this data is used to personalize ads. As of today, our Off-Facebook Activity tool is available to people on Facebook around the world. Other businesses send us information about your activity on their sites and we use that information to show you ads that are relevant to you. Now you can see a summary of that information and clear it from your account if you want to. Off-Facebook Activity marks a new level of transparency and control. We’ve been working on this for a while because we had to rebuild some of our systems to make this possible. Now, thankfully, you can review these connections yourself and clear any history manually. Check out Facebook’s Off-Facebook Activity controls, and happy Data Privacy Day. Tech 23 notes with this tag (showing first 10 results) • As Lambda students speak out the schools debt-swapping partnership disappears from the internet “The ISA is the business model, not education,” says Kim Crayton, a business strategist and founder of CauseAScene , an organization that’s seeking to disrupt the status quo in tech. “You cannot tell me that education is your business model when you have not registered as an institution.” For months, Crayton has been speaking about the problems with coding bootcamps on her podcast, where she’s argued that they target vulnerable communities. “You’re put in these spaces and putting in 110 percent and it’s still not working and you’re told to ‘trust the process,’” she says. Great reporting on this at The Verge. Kim Crayton makes an excellent point. The promise of many of these neo-credentials is for students to leapfrog the things everyone fears about the conventional education system. No one is more vulnerable to taking on loads of student debt than those who need it most. Those students are also going to suffer the most if their university or college fails to equip them for a career. Lambda solves both of these problems, making it extremely attractive to poor students. Sadly, there’s always a catch. • Bring It On Haters With Special Guest Ben Thompson Ben Thompson, in discussion with John Gruber: It was mindblowing. It was absolutely incredible. The way that you could just do stuff that wasn’t really possible [on a computer]. Again, it was technically possible on a computer, but the user interface and experience was just transformative on the iPad. It was absolutely incredible. And Jobs knew it. It’s one of my all-time favourites Jobs moments. It’s like fifteen seconds after the demo, and it’s just like… he’s used this. He was involved in the creation of it. They had run through the demo. He knew it. And even then, he was just astonished. He’s just like ‘I can’t believe [this]…’ […] It was, to my mind, the culmination of his life’s work. He comes on there, and he’s like, ‘Isn’t it incredible? Now anyone can make music.’ I almost want to transcribe this whole episode. John Gruber and Ben Thompson discuss the potential of the iPad—and its failure to reach it. Ben uses the term “transformative” deliberately above. They discuss how, before the iPad, no computing experience could adapt to become wholly new tools and environments for whatever the user wanted to do. But the iPad can become a piano or a canvas or a television. In this sense, they argue that the iPad has (or had) the potential for disruptive innovation (RIP Clay Christensen)—but it’s not supposed to be a Mac. These two think the iPad’s lost the chance to fulfill that potential, mostly because Apple has missed the opportunity to build a vibrant developer ecosystem due to App Store policies. I hope that isn’t the case, though I think we have to look beyond the iPad to fully appreciate what might happen next. The introduction of tablets and transformative computing experiences continues to echo throughout a variety of industries. Graphic designers and illustrators have a new suite of tools to directly interact with their creations in the iPad Pro and the Surface. Similarly, tablet or hybrid devices have transformed schools—schoolchildren now have a “homework” device for all kinds of assignments. It’s true that we still need developers to imagine ever-more revolutionary applications for these devices, but there’s no denying that disruption is taking root. Either way, the episode is well worth a listen. Enjoy from 15:50 to ~31:22 and 1:26:59 to the end of the show if you want to focus on the iPad discussion. • Starting the Decade by Giving You More Control Over Your Privacy My bank, fitness and workout apps, and food delivery services I haven’t used in months—those were some of the 30+ apps interacting with Facebook data. Ostensibly this data is used to personalize ads. As of today, our Off-Facebook Activity tool is available to people on Facebook around the world. Other businesses send us information about your activity on their sites and we use that information to show you ads that are relevant to you. Now you can see a summary of that information and clear it from your account if you want to. Off-Facebook Activity marks a new level of transparency and control. We’ve been working on this for a while because we had to rebuild some of our systems to make this possible. Now, thankfully, you can review these connections yourself and clear any history manually. Check out Facebook’s Off-Facebook Activity controls, and happy Data Privacy Day. • Leaked Documents Expose the Secretive Market for Your Web If the product is free, you are the product: An antivirus program used by hundreds of millions of people around the world is selling highly sensitive web browsing data to many of the world’s biggest companies. • What part of 'viral' content makes platforms want to encourage its spread? The Twttr prototype app gave me another feedback form today. It’s been my habit to complain, at every opportunity, about the trends page you have to engage with whenever you go to the Search tab. I feel a little bad for the designers and developers, because the beta is really all about how conversations on Twitter look and feel. Still, this feedback form was no different. Here’s what I wrote in the “Dislike” section: I wish I could control the trends page. It is the absolute worst part of my Twitter experience. It just feels… unhealthy. Like going through a grocery store magazine aisle. Sure, some of the headings are instructive or inspiring, but many are gross, irrelevant, or completely malignant gossip. The experience is also invasive. Because trends are forced upon you when you intend on searching for something specific, and because they’re algorithmically-tunes to be as attention grabbing as possible, it’s easy to be distracted and forget why you even entered the search pane. I never explicitly consent to learning about celebrity gossip or US politics when I use Twitter. If I tap on some of those topics, it’s not because I want to. It’s because it’s malicious click bait. In turn, it’s corrupt to design an experience that drags the user through it repeatedly. Sure, this content is viral. But shouldn’t we be inoculating against viruses, not encouraging them to spread? • US announces AI software export restrictions for China A surprising headline, but the restriction is very specific: the new export ban is extremely narrow. It applies only to software that uses neural networks (a key component in machine learning) to discover “points of interest” in geospatial imagery; things like houses or vehicles. The ruling, posted by the Bureau of Industry and Security, notes that the restriction only applies to software with a graphical user interface — a feature that makes programs easier for non- technical users to operate. Still, this is probably a marker of change to come. It’s a little odd to think of software as something that can be “exported”, however. Surely this isn’t a ban on shipping discs across a border. Software is downloaded. So, is this a kind of firewall? • This wireless power startup says it can charge your phone using only radio waves Bohn and his co-founders are confident that, if done right, a proper system for wireless power transmission could shift not just how we think about keeping devices charged and powered on at all times, but also the types of devices we end up putting in our homes and what those devices get used for. I’d say. If this works, it’ll remove a technical limitation that is pretty built-in to our mental models of how our gadgets work. Guru is envisioning a world where you can keep all manner of battery-powered gadgets, big and small, all over your home or in every corner of an office, store, or warehouse without having to worry about where they draw power from or how long it lasts on a charge. Eliminating the “where will I plug it in?” assumption might unlock opportunities across all ways of living and working. • Segway’s newest self-balancing vehicle is an egg-shaped wheelchair Segwayʼs newest self-balancing vehicle wonʼt require you to stand up. Dubbed the S- Pod, the new egg- shaped two-wheeler from Segway-Ninebot is meant to let people sit while they effortlessly cruise around campuses, theme parks, airports, and maybe even cities. Hmm. At least with self-balancing, this won’t happen. • Report Launch - OPSI Primer on AI for the Public Sector Today, we’re excited to formally launch the final version of OPSI’s AI primer: Hello, World: Artificial Intelligence and its Use in the Public Sector Another interesting output from the OPSI. It seems usefully pragmatic: The AI primer is broken up into four chapters that seek to achieve three key aims: (1) Background and technical explainer; (2) overview of the public sector landscape; (3) implications and guidance for governments. • Microsoft wants to capture all of the carbon dioxide it’s ever emitted The most audacious commitment from Microsoft is its push to take carbon out of the atmosphere. The company is putting its faith in nascent technology, and it’s injecting a significant investment into a still controversial climate solution. Proponents of carbon capture, like Friedmann, say that the technology is mature enough to accomplish Microsoft’s aims. It’s just way too expensive right now. Microsoft’s backing — and its1 billion infusion of cash — could ultimately make the tech cheaper and more appealing to other companies looking for new ways to go green.

Fantastic news. Carbon capture is a key opportunity for decelerating climate change. Hopefully more companies follow suit.

Systemics

17 notes with this tag (showing first 10 results)

• Roger Martin, Bianca Andreescu, and systemic strategy

According to designer/strategist Roger Martin, a strategy is an imagined possibility with which we ask the question “What has to be true for this possibility to become real?”

In this episode IDEO U’s Creative Confidence podcast, Roger talks about how that approach helped unlock Bianca Andreescu’s success at the Grand Slam singles championship in 2019.

One of the fascinating things about this approach is that it acknowledges the need for system-wide changes. By asking “What has to be true?”, a strategist must consider all of the conditions of a system that should shift to make the imagined possibility a reality. Of course, most approaches to strategy do require some appreciation of the state of the strategic environment (e.g., the five forces model). None, however, emphasize the need to guarantee these systemic conditions quite as explicitly as asking “What must be true?”

• Can Snow Clearing Be Sexist?

And so the Swedish gender equality initiative team began to explore whet her snow clearing was sexist. Sure enough, they found the routine of clearing snow typically benefited men over women. In the winter, snow was cleared first on main roads leading into the city, benefiting commuters—who were mostly men. Foot- and cycle-paths were cleared last—not so good for pedestrians and cyclists, who were very often women traveling with children in pushchairs.

There was a cost to all this: 79% of pedestrian injuries occurred in winter, of which 69% were women. The estimated cost of these falls was SKr36m per winter, about USD3.7m / £3m / €3.4m / Indian ₹279m. By clearing paths first, accidents decreased by half and saved the local government money. Great action-based response to a stupid remark (“At least snow-clearing was something those ‘gender people’ can keep their noses out of,” someone had said, prompting this investigation). • Systemics and design principles in support of Tiago Forte's PARA framework • Applied Systems Thinking # Applied Systems Thinking Based on the Applied Systems Thinking workshop, I’ve collected a variety of resources to help you map complex problems below. The buttons link directly to files to save you some trouble. Be mindful that most of these files are published documents or books, so if you really like them, you should buy a copy and support the authors! If you have questions or if you’re looking for more resources, never hesitate to reach out to me via ryan@fulcra.design. # Introduction What are systems? Interconnected sets of elements whose interactions lead to emergent, “purposeful” behaviour. (A system’s purpose is not necessarily what someone intends of it, though, nor can it be derived from rhetoric about the system. A system’s purpose can only be defined by examining its actual behaviour.) Systems—and the actors within them—do exactly what they are “designed” to do. That is, systems act perfectly in tune with the structures and incentives that they have. Only by understanding these complex structures and incentives can we begin to make real progress on the challenges we’re addressing. # Key Things To Remember 1. The most important thing about mapping is not the map itself. It is the conversations that the map (and the mapping process!) can spark. 2. Stay focused on answering complex questions. Mapping is not an end in itself. You are “finished” mapping when you’ve answered your focusing questions (more below). # Case Studies • Remember the story of the development worker trying to support water access in rural Malawi. (37.4 kb) By identifying someone else who was working on a similar problem (community health workers), the development worker was able to gain substantial leverage over their problem with minimal effort. Systems work helps is to identify leverage points. • Remember the story of The After Prison Initiative (TAPI). (37.4 kb) By helping changemakers working on the same issue see the whole system, each was able to recognize the problems with the system that they were responsible for. Systems help us recognize that every participant in a system has responsibility for the whole system, not just their part. • Remember the story of the spruce budworm. (37.4 kb) The Atlantic Canadian lumber industry made itself addicted to insecticide by beginning and sustaining insecticide sprays before they understood the long-term forest ecosystem. Systemic innovation is often counterintuitive; the wrong fix in the wrong place can make matters worse. • Remember the story of the well-intended conference organizers. (37.4 kb) This story teaches two lessons. First, systemic problems are rarely shifted by simple solutions. If you account for only one part of the problem, your fix may fail. Second, it is difficult to understand a systemic problem without involving all of the key stakeholders, particularly the beneficiaries you aim to serve. Involve them in order to see the whole system. # Developing A Focusing Question # Why Are “How Might We..?” Questions Useful? • “How” invokes a sense of opportunity. Therefore, “How might we..?” questions are appreciative. • “Might” invokes a sense of pluralism. Therefore, “How might we..?” questions are open-ended: there is more than one possible solution. • “We” invokes togetherness. Therefore, “How might we..?” questions are pursued collaboratively, particularly by asking and answering questions with stakeholders. However, “How might we..?” questions aim to provide solutions. Before we can “solve” systemic issues, however, we must understand them. And unfortunately for us, these are usually wicked problems. To understand a problem, we must begin to explore causality. Systemic designers seek to understand complexity by searching for the patterns that cause our problems—and finding the underlying structure of those patterns that enable their persistence. To that end, David Stroh suggests developing a “focusing question” in systems work. The purpose of systems mapping, he says, is not to map a system; it is to answer the focusing question A focusing question has the form “Why does this problem persist?” or “Why, despite our best efforts, intentions, and resources, have we been unable to achieve a certain goal or solve a particular problem?” # FOUR TYPES OF SYSTEMS MAPPING # Rich Pictures Rich pictures come from Checkland’s Soft Systems Methodology (SSM). Akin to a sketchy infographic, these maps are illustrated and make heavy use of labels and symbols to help the mapper or the reader understand a messy situation. # Actor Maps Actor maps graph the relationships in a social system. Who (or what organizations) influence who? Who funds who? How is the vision of the system determined? By identifying different stakeholders, including who are the most important beneficiaries and victims of a system, systemic designers might catch gaps, missed connections, or other issues. # Causal Loop Diagrams Also known as influence diagrams and effect maps, Causal Loop Diagrams graph the phenomena of a system. What are we trying to stop from happening (or what do we want to happen more often)? What encourages or limits those phenomena? Then, what encourages or limits _those_causes or limits? By drawing causal connections between the phenomena of the system, we can recognize the complex interactions that lead to the (frequently counterintuitive) emergent patterns of behaviour normally invisible. # Stock And Flow Diagrams How much of what quantities flow at what rates? Stock and flow diagrams make explicit the system’s stores (e.g., the heat in a cup of coffee) and its rates of change (e.g., how quickly heat escapes from the cup). These diagrams also recognize what controls these rates of change. # Applied Systems Thinking # Dimensions Of A System: Add detail to your systems maps by exploring the different dimensions along which influence might flow: wealth, power, values, knowledge, or beauty. Different types of obstructions—poverty, maldistribution, and insecurity—can cause different types of problems in each of these dimensions. # Leverage Points: Leverage points are places within a system with which a little effort yields great reward. Likewise, bottlenecks are places within a system which resistance could cause significant problems. # Leverage Points: Leverage points are places within a system with which a little effort yields great reward. Likewise, bottlenecks are places within a system which resistance could cause significant problems. # Systems Archetypes: Systems archetypes are common patterns identified in causal loop diagrams or stock-and-flow diagrams. Archetypes exhibit similar behaviours and can be resolved by similar solutions. # The Systems “Business Idea”: Do you need a particular actor or phenomena to receive resources/power/etc.? Where would that resource come from? What influences how much of the resource gets distributed? How can you increase those influencing forces? The business idea uses a causal loop diagram to map the systemic structure of an organization’s strategic sustainability. It makes explicit the phenomena that generate resources for the system to reinvest—and the strategic competencies that the organization can use to enhance those phenomena. # Systemic Theories Of Change: What is the change strategy you’re adopting? Similar to the business idea, a systemic theory of change plots a theory of change model in systemic form, identifying the goal phenomena to enhance (or limit), the key activities that can support that enhancement (or limitation), and the inputs required to sustain and scale those activities. # Systems Stories: Never explain a systems map in a pitch or to a general audience. Instead, follow the iceberg model to distill a systems story 1. Describe what happened (an example of the event or phenomena the systemic designer seeks to address); 2. Describe what has been happening (the pattern of events that lead to the problem or issue); and 3. Describe why (the underlying causal structure that enforces the persistence of these problematic patterns). # Technology For Systems Mapping Mural Mural.co is a collaborative tool for design sprints. As such, it provides features for collaborative whiteboarding and sticky noting, voting via dotmocracy, and a variety of other neat and helpful tools. It is very free-form (and as such has no features specifically made for systemic design) but that open-endedness may be useful. Loopy Nicky Case’s Loopy is a simple tool that allows you to simulate systemic behaviours. It is very unsophisticated (e.g., it is challenging to provide precise system settings) but it is extremely gestural and is therefore fun to use to illustrate and explore ideas. Plectica Plectica is a “visual mapping software”. It allows you to nest and draw connections between cards representing anything. The goal of the app is to provide a simple interface for complex ideas. Kumu Kumu is a web app built specifically for systems mapping. It features extensive features and documentation and a lively support community full of fellow systems mappers who like to help one another. The developers/founders are active participants in that community and regularly provide customer support, too. Develop actor maps, systems maps, and all kinds of other interesting interactive visuals with Kumu. # ADDITIONAL RESOURCES I’ve collected and described resources on related topics at https://systemic.design/resources. In particular, you may want to check out the items on organizational change (e.g., the “Notes on Leadership and Language in Regenerating Organizations” paper and the article on organizational learning). • Leverage analysis in systemic design • Finding the Emic in Systemic Design # Finding the Emic in Systemic Design A paper presented at RSD7 in Turin, Italy. # ABSTRACT I argue that an under-emphasized but crucial variable of success in systemic design is the perspective through which systemic design processes are implemented and executed. While rooted in design (a consciously empathetic discipline, especially in recent years; cf. Kimbell, 2011), it is easy for systemic designers to conduct the research required for their projects in externalized ways. These approaches risk misrepresenting the stakeholders who contribute to projects and, in turn, they are a danger to the potential impact of these misresearched problem systems. I propose to advance a theoretical argument for this danger, the development of an assessment framework to check whether an internalized perspective has been effectively achieved, and provide a proof of concept of this framework through hermeneutic case study analysis. As I will show, systemic design processes that are not executed with the direct and explicit engagement of stakeholders – to the extent of achieving an emic (or from within) understanding of the system – may be flawed at their foundation. By fostering recognition of the importance of an emic perspective, and by providing a framework of principles, practices, and process to accomplish systemic design with this perspective, I hope to ensure that systemic design processes are as accurate and valid as possible with respect to the stakeholders of the system. This is not to suggest that systemic design practice is “too etic”. In fact, with roots in design, systemic design is often deliberately emic. Systemic designers make use of designerly tools that help the researcher to build empathy with system stakeholders (e.g., soft systems methodology, critical systems heuristics, appreciative inquiry; Jones, 2014). They often seek to engage stakeholders in the systemic design process and include reflective analysis of what has been learned in order to assess where deeper engagement with the system is required (Ryan, 2014). That said, with the advent of crowdsourcing (the facilitated involvement of the general public in problem solving, usually using online tools; Lukyanenko & Parsons, 2012) and data science (the use of computational tools to analyze and understand large quantities of data; cf. Scepanovic, 2018), it is likely that data-driven methods will increasingly influence systemic design practice. One recent example sought input from hundreds of people to identify opportunities for change in Canadian post-secondary systems through an iterative online survey (cf. Second Muse, Intel, & Vibrant Data, 2016). This data-driven direction is a powerful opportunity, of course, but it underscores the need to develop principles and best practices for assessing and supporting emic understanding as we gain more data from these tools. This proposal consists of two steps. First, I will look to the principles and theorists of ethnography to develop a framework for assessing the emic/etic perspective of a given research project. Namely, Geertz’ “Thick Description: Toward an Interpretive Theory of Culture” (found in The Interpretation of Cultures, 1973, chapter 1) provides a foundation for the process of emic research, while Creswell and Miller (2000) provide a set of procedural principles for emic validity. Taken together, we generate a critical research framework with which we may assess a given research project’s emic perspective. Second, I will provide a proof-of-concept of this framework (and its theoretical underpinnings) via a casebased assessment of three systemic design projects. Case studies provide an effective venue for learning about the context-dependent manifestations of the phenomena being studied (Flyvbjerg, 2006). One of these case studies is one I have developed through my experience in participating and contributing to the development of the Canadian National Youth Leadership and Innovation Strategy framework, which convened hundreds of youth and youth-serving organizations in order to understand the youth leadership and innovation system in Canada (cf. MaRS Studio Y, 2017). The second and third case studies are those profiled by Ryan and Leung (2014). In order to interpret and analyze the chosen case studies, I turn to the methodology of phenomenological hermeneutics (Eberle, 2014, p. 196; cf. Wernet, 2014). Phenomenological hermeneutics are appropriate as I have access to the described phenomena of the systemic design projects captured by the chosen cases, but these phenomena are not explicitly captured with reference to emic or etic perspectives – thus some construction of the inherent emic or etic data is necessary in order to make judgments about the perspectives found in the projects. In each case, I will use identify phenomena representing the practice of emic (or etic) understanding in the research orientation of the work, as acknowledged by the above framework. In each case, I will examine the step-by-step procedure and any associated notes about the experience of the researchers and participants involved. In each step or experience, I will look for evidence of the four steps of emic understanding or the six techniques of emic validation reported above. # References Creswell, J. W., & Miller, D. L. (2000). Determining Validity in Qualitative Inquiry. Theory Into Practice, 39(3), 124–130. https://doi.org/10.1207/s15430421tip3903_2 Eberle, T. S. (2014). Phenomenology as a Research Method. In U. Flick (Ed.), The SAGE Handbook of Qualitative Data Analysis (pp. 184–202). Los Angeles, Calif. [u.a.]: Sage. Retrieved from https://www.alexandria.unisg.ch/228374/ Flyvbjerg, B. (2006). Five Misunderstandings About Case-Study Research. Qualitative Inquiry, 12(2), 219245. https://doi.org/10.1177/1077800405284363 Geertz, C. (1973). The interpretation of cultures: Selected essays (Vol. 5019). Basic books. Jones, P. (2015). Design Research Methods for Systemic Design: Perspectives from Design Education and Practice. Proceedings of the 58th Annual Meeting of the ISSS - 2014 United States, 1(1). Retrieved from http://journals.isss.org/index.php/proceedings58th/article/view/2353 Kimbell, L. (2011). Rethinking Design Thinking: Part I. Design and Culture, 3(3), 285–306. https://doi.org/10.2752/175470811X13071166525216 Lukyanenko, R., & Parsons, J. (2012). Conceptual modeling principles for crowdsourcing (pp. 3–6). ACM. https://doi.org/10.1145/2390034.2390038 MaRS Studio Y. (2017). A strategic framework for youth leadership & innovation in Canada: Insights from the 2016 National Youth Leadership and Innovation Strategy Summit. Toronto, ON. Retrieved from http://www.studioy.marsdd.com/wp-content/uploads/2016/12/MaRS_NYLISstrategic_framework_Final.pdf Ryan, A. (2014). A Framework for Systemic Design. FORMakademisk–research Journal for Design and Design Education, 7(4). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/787 Ryan, A., & Leung, M. (2014). Systemic Design: Two Canadian Case Studies. FormAkademisk - Research Journal of Design and Design Education, 7(3). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/794 Scepanovic, S. (2018). Data science for sociotechnical systems - from computational sociolinguistics to the smart grid. Aalto University. Retrieved from https://aaltodoc.aalto.fi:443/handle/123456789/30187 Second Muse, Intel, & Vibrant Data. (2016, May 11). What Your Data Says: Post-Secondary Education Mapping Survey Highlights. RECODE. Retrieved from http://re-code.ca/whats_happening/watch-recodewebinar-what-your-data-says/ Wernet, A. (2014). Hermeneutics and Objective Hermeneutics. In U. Flick, The SAGE Handbook of Qualitative Data Analysis (pp. 234–246). SAGE Publications, Inc. https://doi.org/10.4135/9781446282243.n16 • Global Steering Group for Impact Investment systemic theory of change # The Global Steering Group for Impact Investment’s (2018) systemic theory of change A systems model I helped visualize for the Global Steering Group on Impact Investment in 2018: • Procrastination Station # Procrastination Station Procrastination is itself a systems trap. That balancing loop sucks you in. You take on sneaky little actions as dopaminergic relief to the burden you’re escaping from, while the burden only grows heavier. (A form of Fixes that Fail.) • Creative Education Futures # Creative Education Futures What are the futures of art and design schools in Canada? In 2015, I supported Kinetic Café in developing OCAD University’s latest Vision and Mission statements. As part of that work, I helped scan for signals, trends, and drivers in art and design school futures. Our scan revealed five important drivers of change: reforming education, creative economies and cultures, new geographies, empowering technologies, and conscious collective. A walkthrough of this work is visualized and embedded below. If it doesn’t display, you can visit it directly here. • Leadership is # Leadership is… Lessons learned from Memorial Student Leadership Conference (MSLC) 2017. These thoughts were spurred by Director of Student Life Dr. Jennie Massey’s opening remarks for the conference, and were reinforced by the keynote speaker, Mr. Seamus O’Regan, MP. Jennie and Seamus both talked about the oft-haphazard decision making that led to their achievements. The truth about this reinforcing loop is that no matter where you are in the process, you can do something to make it to the next step. No, not every moment will be virtuous – the cycle is not _that_virtuous. It is a cycle nonetheless, and that’s the thing about cycles: they do not stop. Systems 16 notes with this tag (showing first 10 results) • Systemic Strategy # Systemic Strategy: Systemic Design Methods for Complex Systems Change A presentation from Peter Jones and I at RSD9, virtually in Ahmedabad, India. • Conversations, cybernetics, and Theory of Mind • A quick sketch of an interdisciplinary systems model # Why are we exceeding the Earth’s carrying capacity? This is a quickly-sketched model created from a breakout group conversation during the MUN School of Graduate Studies’ “Earth’s Carrying Capacity” dialogue. Download the model • Systemic lessons from South Korea's Patient 31 This changed with the emergence of “Patient 31.” Reuters’ coverage of the “Korean clusters” provided the world with a vivid glimpse of the volatility of COVID-19. One person showed poor judgement, and in turn caused cascading catastrophe in her communities. Events like the COVID-19 pandemic are thankfully rare. Moments like these—when a lot happens all at once, and the experience is shared by a collective—shape future history like nothing else. We are learning a lot from this. Not only are epidemiologists now a famous profession, but we’re all learning exactly what it takes to provide good healthcare, what good governance looks like, how public health is community health, and more. Patient 31 holds a simple lesson for systemics: the fragility of apparently solid social systems. South Korea seemed to do everything right. Yet, due to the volatile nature of this particular socio-health system, a single “free radical” caused immense damage. Similar volatility is evident—but more subtle—in other social systems. Consider how memes spread. Our massive communities may seem immovable at times, but it’s clear that the wrong (or right) phenomena can spread rapidly and deeply. Stay safe. • What part of 'viral' content makes platforms want to encourage its spread? The Twttr prototype app gave me another feedback form today. It’s been my habit to complain, at every opportunity, about the trends page you have to engage with whenever you go to the Search tab. I feel a little bad for the designers and developers, because the beta is really all about how conversations on Twitter look and feel. Still, this feedback form was no different. Here’s what I wrote in the “Dislike” section: I wish I could control the trends page. It is the absolute worst part of my Twitter experience. It just feels… unhealthy. Like going through a grocery store magazine aisle. Sure, some of the headings are instructive or inspiring, but many are gross, irrelevant, or completely malignant gossip. The experience is also invasive. Because trends are forced upon you when you intend on searching for something specific, and because they’re algorithmically-tunes to be as attention grabbing as possible, it’s easy to be distracted and forget why you even entered the search pane. I never explicitly consent to learning about celebrity gossip or US politics when I use Twitter. If I tap on some of those topics, it’s not because I want to. It’s because it’s malicious click bait. In turn, it’s corrupt to design an experience that drags the user through it repeatedly. Sure, this content is viral. But shouldn’t we be inoculating against viruses, not encouraging them to spread? • The Demon Haunted World I have a foreboding of an America in my children’s or grandchildren’s time—when the United States is a service and information economy; when nearly all the manufacturing industries have slipped away to other countries; when awesome technological powers are in the hands of a very few, and no one representing the public interest can even grasp the issues; when the people have lost the ability to set their own agendas or knowledgeably question those in authority; when, clutching our crystals and nervously consulting our horoscopes, our critical faculties in decline, unable to distinguish between what feels good and what’s true, we slide, almost without noticing, back into superstition and darkness… The thread discusses the growth of anti-intellectualism and conspiracy theories. I’m reminded of this timeless Medium post about how hating Ross in Friends became a meme in and of itself, reinforcing the persecution of science in the ’90s. From David Hopkins: I want to discuss a popular TV show my wife and I have been binge-watching on Netflix. It’s the story of a family man, a man of science, a genius who fell in with the wrong crowd. He slowly descends into madness and desperation, led by his own egotism. With one mishap after another, he becomes a monster. I’m talking, of course, about Friends and its tragic hero, Ross Geller. […] If you remember the 1990s and early 2000s, and you lived near a television set, then you remember Friends. Friends was the Thursday night primetime, “must-see-TV” event that featured the most likable ensemble ever assembled by a casting agent: all young, all middle class, all white, all straight, all attractive (but approachable), all morally and politically bland, and all equipped with easily digestible personas. Joey is the goofball. Chandler is the sarcastic one. Monica is obsessive-compulsive. Phoebe is the hippie. Rachel, hell, I don’t know, Rachel likes to shop. Then there was Ross. Ross was the intellectual and the romantic. Eventually, the Friends audience — roughly 52.5 million people — turned on Ross. But the characters of the show were pitted against him from the beginning (consider episode 1, when Joey says of Ross: “This guy says hello, I wanna kill myself.”) In fact, any time Ross would say anything — about his interests, his studies, his ideas — whenever he was mid-sentence, one of his “friends” was sure to groan and say how boring Ross was, how stupid it is to be smart, and that nobody cares. Cue the laughter of the live studio audience. This gag went on, pretty much every episode, for 10 seasons. Can you blame Ross for going crazy? People in the Reddit thread point out that these seemingly recent trends have been taking root for a long time. While this is true, it’s also true that (just like seemingly everything else) these phenomena have been moving much faster and growing much larger in recent years. Which leads to a curious tangent: how do accelerated scales of change play on our biases? Does the interaction between these biases and our accelerated experiences change our perception of the world? • The ‘Amazon effect’ is flooding a struggling recycling system with cardboard Chinaʼs 2017 decision to turn away Americaʼs trash has left the recycling industry reeling as it figures out what to do with all the packaging online shoppers leave behind. Recycling is a funny thing. For me, it’s almost a guilt-free act. “Sure, I’m using all of these boxes, but they’re recycled, so who cares?” But increasingly recycling and the trash bin seem like equivalent destinations. It’s even imaginable that recycling is worse, because recycled objects might travel farther before being dumped into a landfill anyway. “Itʼs very difficult for American material recovery facilities to satisfy that standard because Americans put plastic bags and chewing gum and bowling balls and dirty diapers and everything else you can imagine into the recycling containers,” Biderman says. The strict rules also apply to plastic and other recyclables, but cardboard and mixed paper have seen the sharpest drops in prices. I’m tempted to blame people: “It’s too bad we can’t be more considerate. Have you ever looked in the recycling bins in public receptacles?” Et cetera. But really, we should be designing systems that make this easy—or incentivize good behaviours somehow. Either way, the current situation is insufficient: There has also been a noticeable shift in the source of the cardboard, says Coupland: itʼs coming from peoplesʼ homes instead of brick-and-mortar businesses. Thatʼs bad news, since retailers are less likely to generate cardboard thatʼs too filthy to be recycled. Consumersʼ cardboard boxes are often mixed with other, dirty recyclables like ketchup bottles or soda cans that spill their contents over the cardboard. On average, about 25 to 30 percent of the materials picked up by a recycling truck are too contaminated to go anywhere but a landfill or incinerator, Coupland says. • TED and YouTube launch global climate initiative Anyone, anywhere can propose an idea. YouTube creators will help spread the word, and the best proposals could be put into motion with the help of businesses, policymakers, and and celebrities supporting the initiative. The initiative will culminate in a summit in Bergen, Norway next October to share the solutions that came out of the effort. Countdown will work with a panel of experts and scientists to vet proposals, and the strongest will be turned into TED talks. The talks will be filmed at the summit in Norway, in front of “a hand-picked audience capable of turning those ideas into action,” according to a press release. An interesting partnership, and yet another example of “crowdsolving”: trying to find solutions to wicked problems via the mobilizing power of the Internet. • Systems Practice, Abridged # Systems Practice, Abridged For serious system mapping work, spending [significant] time studying, thinking about, and mapping your system helps ensure you are addressing root causes rather than instituting quick fixes. In the long term, the time and resources you invest in Systems Practice will pay dividends. But what if youʼre not quite sold on the Systems Practice methodology yet? What if you havenʼt encountered systems thinking before and just want to dip your toes in? Or what if youʼre an expert or an educator with only a few hours to introduce Systems Practice to a fresh new group of systems thinkers? I have been in the latter situation, and it’s a challenge. In my experience, people who are wholly new to systems thinking can take a lot of time to acclimate to the mindset. But! If, as a teacher, you can’t illustrate the benefits quickly, it’s easy to disengage. So, I’m glad this exists. This is a wonderful new resource from Kumu’s Alex Vipond that helps walk you through systems and Kumu’s tools at the same time. • Piret Tõnurist & Systems Change: how to get started and keep going? This is a great talk from Piret Tönurist of the Observatory on Public Sector Innovation. One of the core issues of the talk is innovation doubt—the “if it ain’t broke, don’t fix it” mentality. To paraphrase Piret: […] why are we doing innovation at all? Maybe sometimes things are working fine, why do we think about innovation at all? We start off with four questions: 1. Do you want to do things better? 2. Do you have goals and purposes to fulfill? 3. Do you want to address the needs of your stakeholders? 4. Do you want to prepare for the risks and uncertainties that the future holds? If you answered “yes” to at least one of those questions, then your job is to do innovation—your job is to be a changemaker. Also, the talk includes a neat model for different varieties of innovation, image courtesy of this post by Adrian M. Senn over on Medium: https://miro.medium.com/max/1210/1*AaPZeqAVLoo85RfY7Dxspw.png Change 12 notes with this tag (showing first 10 results) • Researchers detail huge hack-for-hire campaigns against environmentalists The report concludes that the campaigns represent “a clear danger to democracy” and could allow powerful organizations to target their opponents. “The extensive targeting of American nonprofits exercising their first amendment rights is exceptionally troubling,” Citizen Lab’s report says. We didn’t want this part of cyberpunk sci-fi… • The Demon Haunted World I have a foreboding of an America in my children’s or grandchildren’s time—when the United States is a service and information economy; when nearly all the manufacturing industries have slipped away to other countries; when awesome technological powers are in the hands of a very few, and no one representing the public interest can even grasp the issues; when the people have lost the ability to set their own agendas or knowledgeably question those in authority; when, clutching our crystals and nervously consulting our horoscopes, our critical faculties in decline, unable to distinguish between what feels good and what’s true, we slide, almost without noticing, back into superstition and darkness… The thread discusses the growth of anti-intellectualism and conspiracy theories. I’m reminded of this timeless Medium post about how hating Ross in Friends became a meme in and of itself, reinforcing the persecution of science in the ’90s. From David Hopkins: I want to discuss a popular TV show my wife and I have been binge-watching on Netflix. It’s the story of a family man, a man of science, a genius who fell in with the wrong crowd. He slowly descends into madness and desperation, led by his own egotism. With one mishap after another, he becomes a monster. I’m talking, of course, about Friends and its tragic hero, Ross Geller. […] If you remember the 1990s and early 2000s, and you lived near a television set, then you remember Friends. Friends was the Thursday night primetime, “must-see-TV” event that featured the most likable ensemble ever assembled by a casting agent: all young, all middle class, all white, all straight, all attractive (but approachable), all morally and politically bland, and all equipped with easily digestible personas. Joey is the goofball. Chandler is the sarcastic one. Monica is obsessive-compulsive. Phoebe is the hippie. Rachel, hell, I don’t know, Rachel likes to shop. Then there was Ross. Ross was the intellectual and the romantic. Eventually, the Friends audience — roughly 52.5 million people — turned on Ross. But the characters of the show were pitted against him from the beginning (consider episode 1, when Joey says of Ross: “This guy says hello, I wanna kill myself.”) In fact, any time Ross would say anything — about his interests, his studies, his ideas — whenever he was mid-sentence, one of his “friends” was sure to groan and say how boring Ross was, how stupid it is to be smart, and that nobody cares. Cue the laughter of the live studio audience. This gag went on, pretty much every episode, for 10 seasons. Can you blame Ross for going crazy? People in the Reddit thread point out that these seemingly recent trends have been taking root for a long time. While this is true, it’s also true that (just like seemingly everything else) these phenomena have been moving much faster and growing much larger in recent years. Which leads to a curious tangent: how do accelerated scales of change play on our biases? Does the interaction between these biases and our accelerated experiences change our perception of the world? • The ‘Amazon effect’ is flooding a struggling recycling system with cardboard Chinaʼs 2017 decision to turn away Americaʼs trash has left the recycling industry reeling as it figures out what to do with all the packaging online shoppers leave behind. Recycling is a funny thing. For me, it’s almost a guilt-free act. “Sure, I’m using all of these boxes, but they’re recycled, so who cares?” But increasingly recycling and the trash bin seem like equivalent destinations. It’s even imaginable that recycling is worse, because recycled objects might travel farther before being dumped into a landfill anyway. “Itʼs very difficult for American material recovery facilities to satisfy that standard because Americans put plastic bags and chewing gum and bowling balls and dirty diapers and everything else you can imagine into the recycling containers,” Biderman says. The strict rules also apply to plastic and other recyclables, but cardboard and mixed paper have seen the sharpest drops in prices. I’m tempted to blame people: “It’s too bad we can’t be more considerate. Have you ever looked in the recycling bins in public receptacles?” Et cetera. But really, we should be designing systems that make this easy—or incentivize good behaviours somehow. Either way, the current situation is insufficient: There has also been a noticeable shift in the source of the cardboard, says Coupland: itʼs coming from peoplesʼ homes instead of brick-and-mortar businesses. Thatʼs bad news, since retailers are less likely to generate cardboard thatʼs too filthy to be recycled. Consumersʼ cardboard boxes are often mixed with other, dirty recyclables like ketchup bottles or soda cans that spill their contents over the cardboard. On average, about 25 to 30 percent of the materials picked up by a recycling truck are too contaminated to go anywhere but a landfill or incinerator, Coupland says. • TED and YouTube launch global climate initiative Anyone, anywhere can propose an idea. YouTube creators will help spread the word, and the best proposals could be put into motion with the help of businesses, policymakers, and and celebrities supporting the initiative. The initiative will culminate in a summit in Bergen, Norway next October to share the solutions that came out of the effort. Countdown will work with a panel of experts and scientists to vet proposals, and the strongest will be turned into TED talks. The talks will be filmed at the summit in Norway, in front of “a hand-picked audience capable of turning those ideas into action,” according to a press release. An interesting partnership, and yet another example of “crowdsolving”: trying to find solutions to wicked problems via the mobilizing power of the Internet. • MTA floods NYC subway entrance because ‘climate change is real’ An incredible story out of New York today, as reported by The Verge: A flooded subway entrance stopped Brooklyn commuters in their tracks yesterday. For four hours on Wednesday, the staircase leading down to Broadway Station in Williamsburg was blocked off and completely submerged. The sight was even stranger since it hadnʼt rained in New York City that day. The Transit Authority was testing adaptations they’d installed in case of real flooding. Still, I’m sure that the social/informational impact was felt, too. Also, the MTA’s sarcastic explanation is gold. From Twitter: We’re pivoting to submarines. ^JLP • Medical Crowdsourcing: Harnessing the 'Wisdom of the Crowd' to Solve Medical Mysteries Medical crowdsourcing offers hope to patients who suffer from complex health conditions that are difficult to diagnose. Such crowdsourcing platforms empower patients to harness the “wisdom of the crowd” by providing access to a vast pool of diverse medical knowledge. An interesting application of crowdsourcing. What’s the incentive for healthcare providers to participate, though? I’m not sure doctors can bill for participation in Figure 1. I think the main reason they engage at all is curiosity, and that would likely degrade if, as the authors of the linked study discuss, there was a lot of “noise” from uninteresting posts by patients who aren’t medically literate. • John Kerry, Arnold Schwarzenegger wage ‘World War Zero’ on climate change Today former Secretary of State John Kerry and former California governor Arnold Schwarzenegger declared war on climate change. The two led an all-star cast of lawmakers and celebrities to launch an initiative called World War Zero, which aims to get individuals, businesses, and governments to drastically slash greenhouse gas emissions. The initiative, for now, boasts a lot of glitzy names without many details on how it will achieve its goal. Its bipartisan founding members — which include Bill and Hillary Clinton, Richard Branson, Jimmy Fallon, Cindy McCain, and Al Sharpton, and more than 70 other notable names — plan to hold 10 million “climate conversations” in 2020, The New York Times reported over the weekend. Seems like an incredible effort. And it’s an excellent angle. “War”—when declared by major public figures—certainly catches the public attention. Kerry compared the urgency of climate change to the challenges facing America during World War II. “When America was attacked in World War II we set aside our differences, united and mobilized to face down our common enemy,” Kerry said in a statement. “We are launching World War Zero to bring that spirit of unity, common purpose, and urgency back to the world today to fight the great threat of our time.” Of course, actually waging war doesn’t always garner the unity or have the results we aim for, especially when it’s a war against a social issue. • Introducing Into the Dataverse, the article series # README.txt: Introducing Into the Dataverse, the article series There is a significant gap in research about Canadian data collection activities on a granular scale. This lack of knowledge regarding data collection practices within Canada hinders the ability of policymakers, civil society organizations, and the private sector to respond appropriately to the challenges and harness unrealized benefits. So true. This looks like an interesting series from the great team at Brookfield. • How Tesla's first gigafactory is changing Reno, Nevada “In the five years that weʼve had to asses the effect [the Gigafactory has] had on the workforce, on the community, I think there have been these ramifications that we talk about in the episode that nobody was really prepared for,” Damon said in an interview with The Verge. “Like, we knew there was going to be an issue with housing, which other cities are experiencing, too. But thatʼs become super critical.” Side-effects of growth are not a new problem, but the massive initiatives we’re seeing recently might spark new varieties of old issues. • Former Go champion beaten by DeepMind retires after declaring AI invincible The South Korean Go champion Lee Se-dol has retired from professional play, telling Yonhap news agency that his decision was motivated by the ascendancy of AI. “With the debut of AI in Go games, Iʼve realized that Iʼm not at the top even if I become the number one through frantic efforts,” Lee told Yonhap. “Even if I become the number one, there is an entity that cannot be defeated.” Wow. Perhaps the first real example of “AI took my job?” Design 12 notes with this tag (showing first 10 results) • Why the grass is greener: Making sure that shiny new alternative tool is actually going to help you “The grass is always greener on the other side.” The popular idiom discourages whoever’s listening from seeking out alternatives, suggesting that other options always look better from wherever we’re currently standing. But it has a funny problem: nobody ever explains why the grass is greener on the other side. That’s because it isn’t. The truth is that your side is just yellower/trampled on/eaten… and that’s because you’re on it. Moving to a different place will be fine at first. Then you’ll use it, too, and eventually it’ll look the same as where you started. (In this metaphor, you’re a goat. 🐐) In workflow design, in addition to the novelty of “shiny new object,” new and alternative tools are great simply because they don’t have the cruft you’ve built up in the old tool. That cruft might be noisy notes, a lifetime of guilt-inducing task management, or even just bad habits and behaviours. The problem isn’t the tool. It isn’t you, either. It’s you and the tool. So, after switching, the problems seem to go away… only to re-emerge (possibly in a new form) later because the issues are generated by your usage, not by the tool. The solution is to fall in love with the problem, not the (shiny, potential) solutions. 1. Determine what your issues actually are, and try to figure out why they’re happening. 2. Then, abstractly identify how you might be able to mitigate the problems. • Don’t say “I’ll use Bunch,” say “If I standardize certain work spaces on my computer, I can develop muscle memory for using those workspaces, reducing distraction and allowing me to spend less cognitive energy on finding everything I need to get engaged.” 3. Last, identify some tests or success conditions that will tell you whether the solution is actually working. This’ll help minimize irrational perspectives on how well the honeymoon stage is going. Only after taking those three steps should you choose a tool. Find something that can implement the abstract principles you’ve articulated, and be sure to follow-through on the tests. In doing this, you’re actually creating and implementing a rough design theory. You’re using design science to make your work as easy and engaging as it can be! High-five for that. • Systemic Strategy # Systemic Strategy: Systemic Design Methods for Complex Systems Change A presentation from Peter Jones and I at RSD9, virtually in Ahmedabad, India. • Systemics and design principles in support of Tiago Forte's PARA framework • Keeping the buzz in buzzwords A thought-terminating cliché limits conversation by capturing a complex (but potentially debatable) subject within a reductive term or phrase. Merlin Mann references this idea in episode 164 of Back to Work when discussing curiosity and buzzwords. Thought-terminating clichés can be used to avoid discourse on a subject: by never unpacking the components of an idea that are debatable, those components go unexplored. They can also be exploited to veil ignorance or illogic—the speaker can state the complex term and allow the implication to have impact without contextualizing/explaining it while the intimidated audience shies away from critique or questioning. This explanation makes the phenomena seem villainous, but many of us are prone to committing these crimes—through buzzwords! Buzzwords are terms that catch on because they represent something exciting to a discourse. Then, because they’re popular, they get used frequently, by many people. Because they are somewhat novel, these different uses attach slightly different meanings to the same word. Eventually the buzzword’s overused (reducing the novelty, and therefore the impact of its meaning) and/or overloaded with meaning. Most of our buzzwords were real things at one point (and sometimes they still are). When buzzwords are used effectively they allow a good conversation to move faster between speakers who have the same mental models about the buzzwords.1 Sometimes, however, buzzwords are said to represent concepts that aren’t fully understood by everyone in the conversation. When my meaning of the word “design thinking” differs from yours, but we both refer to design thinking in conversation nonetheless, we can run into trouble. In these situations, buzzwords obfuscate the ideas we’re actually talking about. In my experience, we also know when we’re using buzzwords. We can guess at when others are using them, too. As a result, the conversation loses meaning, and we lose trust in the conversation. # Dealing with buzzwords So what can we do? Well, the easy thing to do is to clarify. When you use a phrase with many potential interpretations, try to clarify how you’re using the phrase. When others use words that may have multiple meanings, ask specific questions about what they actually mean. This clarification might seem like extra work, but it only needs to happen when terms are first invoked—and it’ll prevent lost time and energy due to the consequences of thought-termination later on. More importantly, though, we should try to avoid thought-terminating clichés altogether. Take time to break down the concepts you’re talking about in concrete terms. Explain them in ways you haven’t heard before to avoid relying on trite metaphors and anecdotes. If you can really get at what you mean, your language will be minimally re-interpretable: that is, it should be near-impossible to understand your explanations differently from how you intended. As a result, your communication will become more impactful. The conversations you participate in will have more novelty, too, making it more exciting to discuss the ideas you’re sharing. This may result in more buzzwords emerging, but that’s okay—use the same approach to break those down, too. • Beautiful is good and good is reputable # Beautiful is Good and Good is Reputable: Multiple-Attribute Charity Website Evaluation and Initial Perceptions of Reputation Under the Halo Effect The halo effect is essentially how positive—but irrelevant—traits influence our perception of what the thing with the halo actually says or does. These authors explored how charities manifest the halo effect on their websites, and find evidence for four varieties of halo effect. this study employs charity websites as a multi-attribute donation channel consisting of three attributes of information content quality (mission information, financial information, and donation information) and four attributes of system quality (navigability, download speed, visual aesthetics, and security). Based on the proposed framework, this study proposes four types of halos that are relevant to charity website evaluation —collective halo (attribute-to-attribute), aesthetics halo (attribute-to- dimension), reciprocal-quality halo (dimension-to-dimension), and quality halo (dimension-to-dimension) • Level Up: Leveraging Skill and Engagement to Maximize Player Gameplay # “Level Up”: Leveraging Skill and Engagement to Maximize Player Gameplay We find that high-, medium-, and low-engagement-state gamers respond differently to motivations, such as feelings of effectance and need for challenge. In the second stage, we use the results from the first stage to develop a matching algorithm that learns (infers) the gamer’s current engagement state “on the fly” and exploits that learning to match the gamer to a round to maximize game-play. Our algorithm increases gamer game-play volume and frequency by 4%–8% conservatively, leading to economically significant revenue gains for the company. As ever with this kind of mechanism, are we sure we want this to exist..? The potential is no doubt powerful. Imagine interactive TV shows that modulate what they’re presenting based on readings of the viewer… Hrm. • Resources # Resources Updated Nov 14, 2019 Below I’m collecting a set of resources dealing with a variety of topics for shareable reference—a sort of living, semi-public annotated bibliography. Many of these readings should be accessible via a library or a good Internet search, but if you find something here that shouldn’t be this easy to download, feel free to contact me and I’ll remove it. Or, if you come across any broken links, please let me know! # Getting Started with Systemic Innovation Kudoz’ Where Are You Scaling? Placemat (2017) KudozWhere Are You Scaling? “placemat” is an explorable tool to help think through what scaling really means in a given venture. It builds upon Riddell & Moore’s (2015) Scaling Out, Scaling Up, and Scaling Deep in expanding our notion of scaling. When you hear the word “scale” in a conventional conversation, the meaning is likely synonymous with scaling out: reaching more people (stakeholders or customers) with the product, service, program, or policy at the heart of the conversation. Yet there are other underappreciated aspects of scaling: some are required in order to successfully scale out, while others are different ways of achieving impact—maybe scaling out isn’t the best route to take after all! Scaling up, for instance, refers to reaching higher in power hierarchies in order to implement higher-level solutions to the problem you’re addressing. Scaling deep means to reach the same people you’re already reaching more deeply, or with greater impact. Kudoz introduces two more concepts: scaling infrastructure, or building out more tools and supports to make the work more effective and sustainable; and scaling scree, or lending support and legitimacy to other, different actors and initiatives addressing the same issues you are. Mulgan & Leadbeater’s Systemic Innovation (2013) While the above concepts help make concrete the different ways an intervention might change a system, Mulgan and Leadbeater’s (2013) discussion paper on systemic innovation dives a bit deeper into theory. They link the practice of systems thinking to approaches to innovation, providing a framework for “joining up” a set of innovations in order to achieve systemic change. # Getting Started with Social Innovation Mulgan’s Social Innovation: What It Is, Why It Matters, And How It Can Be Accelerated (2007) Geoff Mulgan offers a comprehensive yet down-to-Earth guide to social innovation. The reading really helps communicate what the differences are between social innovation and conventional innovation with practical examples. Phills Et Al.‘S Rediscovering Social Innovation (2008) The Stanford Social Innovation Review has been one of the preeminent publishers on social innovation since its inception in the early 2000’s. In this review Phills et al. summarize a brief history on social innovation itself while paving a way forward in research and practice. # Getting Started with Design What is “design”, really? It’s easy to think that design is the layout of graphics or illustrations—perhaps even making decisions about layouts, as in architecture. These disciplines—graphic design and architecture—certainly leverage design, and many people employed in these industries are designers. Yet these disciplines do not fully capture what design is, thus we should not limit the understanding and application of design to these industries. The term design shares latin roots with designation. To design is therefore to mark; to frame. Framing means to view a given problem or system from different perspectives in order to deeply understand it and, in turn, to develop novel ways of doing something about it or with it. To become a better designer, you must get better at both analyzing and creating frames. # Getting Started with Systems Thinking Systems thinking is most useful when applied to complex, chronic issues: “wicked problems” that resist taming through conventional approaches. David Stroh, who wrote Systems Thinking for Social Change, argues that effective systems initiatives begin with a focusing question: a question that bounds the project (so that you don’t spend forever debating about where the problem system really ends) and anchors your systems-understanding work in a framing that you can return to if you get lost. This is a question of the form “Why, despite our best efforts and intentions, does [x] persist?” or “…have we not reached our goal of [y]?”—where [x] and [y] are phenomena that remain unassailable through conventional initiatives. Goodman, Kemeny & Roberts’ The Language Of Systems Thinking (2000) The Language of Systems Thinking introduces the reader to reinforcing and balancing loops using simple examples. Braun’s The Systems Archetypes (2002) Systems archetypes extend the links and loops of basic systems thinking into more complicated structures – and in doing so, begin to share with the reader deeper insights into the counterintuitive behaviour of the systems we work with. Donella Meadows’ Leverage Points: Places To Intervene In A System (1997) With robust systemic models, we can begin to identify leverage points: key phenomena that have great potential for change throughout the system. # Getting Started with Futures Thinking Jim Dator’s What Futures Studies Is, And Is Not (1995) What Futures Studies Is, and Is Not is a wonderful introductory and reader-friendly summary of futures thinking. Choo’s The Art Of Scanning The Environment (1999) Chun Wei Choo’s The Art of Scanning the Environment offers a walkthrough of scanning practices. Bishop, Hines & Collins’ The Current State Of Scenario Development (2007) The Current State of Scenario Development provides a comprehensive review of scenario development approaches and techniques. # Deeper Reading: Organizational Change Dubberly Et Al.‘S Notes On The Role Of Leadership & Language In Regenerating Organizations (2002) Hugh Dubberly and a suite of colleagues provide an elegant—poetic, even—walkthrough of how change happens to organizations through their language. They reframe an organization as a continuous set of conversations between people, in turn showing the power of changing the language those people use in order to change the nature of the organization itself. Weick & Westley’s Organizational Learning: Affirming An Oxymoron (1999) Karl Weick and Frances Westley attack the very idea of organizational learning by showing how “organizing” and “learning” are, in fact, opposing processes. To organize is to order; to learn is to disrupt. Success in organizational change is therefore rooted in a leader’s ability to handle the tension between organizing and learning. Too much organizing and the organization will miss opportunity in change—but too much learning and the organization might not be stable enough to survive. Gawde’s Learning From Systems Thinking (2017) How can systems thinking help with changemaking in an organization? Writing for People Matters, Sanjay Gawde provides a succinct argument and explanation linking systems approaches to organizational change. • Applied Systems Thinking # Applied Systems Thinking Based on the Applied Systems Thinking workshop, I’ve collected a variety of resources to help you map complex problems below. The buttons link directly to files to save you some trouble. Be mindful that most of these files are published documents or books, so if you really like them, you should buy a copy and support the authors! If you have questions or if you’re looking for more resources, never hesitate to reach out to me via ryan@fulcra.design. # Introduction What are systems? Interconnected sets of elements whose interactions lead to emergent, “purposeful” behaviour. (A system’s purpose is not necessarily what someone intends of it, though, nor can it be derived from rhetoric about the system. A system’s purpose can only be defined by examining its actual behaviour.) Systems—and the actors within them—do exactly what they are “designed” to do. That is, systems act perfectly in tune with the structures and incentives that they have. Only by understanding these complex structures and incentives can we begin to make real progress on the challenges we’re addressing. # Key Things To Remember 1. The most important thing about mapping is not the map itself. It is the conversations that the map (and the mapping process!) can spark. 2. Stay focused on answering complex questions. Mapping is not an end in itself. You are “finished” mapping when you’ve answered your focusing questions (more below). # Case Studies • Remember the story of the development worker trying to support water access in rural Malawi. (37.4 kb) By identifying someone else who was working on a similar problem (community health workers), the development worker was able to gain substantial leverage over their problem with minimal effort. Systems work helps is to identify leverage points. • Remember the story of The After Prison Initiative (TAPI). (37.4 kb) By helping changemakers working on the same issue see the whole system, each was able to recognize the problems with the system that they were responsible for. Systems help us recognize that every participant in a system has responsibility for the whole system, not just their part. • Remember the story of the spruce budworm. (37.4 kb) The Atlantic Canadian lumber industry made itself addicted to insecticide by beginning and sustaining insecticide sprays before they understood the long-term forest ecosystem. Systemic innovation is often counterintuitive; the wrong fix in the wrong place can make matters worse. • Remember the story of the well-intended conference organizers. (37.4 kb) This story teaches two lessons. First, systemic problems are rarely shifted by simple solutions. If you account for only one part of the problem, your fix may fail. Second, it is difficult to understand a systemic problem without involving all of the key stakeholders, particularly the beneficiaries you aim to serve. Involve them in order to see the whole system. # Developing A Focusing Question # Why Are “How Might We..?” Questions Useful? • “How” invokes a sense of opportunity. Therefore, “How might we..?” questions are appreciative. • “Might” invokes a sense of pluralism. Therefore, “How might we..?” questions are open-ended: there is more than one possible solution. • “We” invokes togetherness. Therefore, “How might we..?” questions are pursued collaboratively, particularly by asking and answering questions with stakeholders. However, “How might we..?” questions aim to provide solutions. Before we can “solve” systemic issues, however, we must understand them. And unfortunately for us, these are usually wicked problems. To understand a problem, we must begin to explore causality. Systemic designers seek to understand complexity by searching for the patterns that cause our problems—and finding the underlying structure of those patterns that enable their persistence. To that end, David Stroh suggests developing a “focusing question” in systems work. The purpose of systems mapping, he says, is not to map a system; it is to answer the focusing question A focusing question has the form “Why does this problem persist?” or “Why, despite our best efforts, intentions, and resources, have we been unable to achieve a certain goal or solve a particular problem?” # FOUR TYPES OF SYSTEMS MAPPING # Rich Pictures Rich pictures come from Checkland’s Soft Systems Methodology (SSM). Akin to a sketchy infographic, these maps are illustrated and make heavy use of labels and symbols to help the mapper or the reader understand a messy situation. # Actor Maps Actor maps graph the relationships in a social system. Who (or what organizations) influence who? Who funds who? How is the vision of the system determined? By identifying different stakeholders, including who are the most important beneficiaries and victims of a system, systemic designers might catch gaps, missed connections, or other issues. # Causal Loop Diagrams Also known as influence diagrams and effect maps, Causal Loop Diagrams graph the phenomena of a system. What are we trying to stop from happening (or what do we want to happen more often)? What encourages or limits those phenomena? Then, what encourages or limits _those_causes or limits? By drawing causal connections between the phenomena of the system, we can recognize the complex interactions that lead to the (frequently counterintuitive) emergent patterns of behaviour normally invisible. # Stock And Flow Diagrams How much of what quantities flow at what rates? Stock and flow diagrams make explicit the system’s stores (e.g., the heat in a cup of coffee) and its rates of change (e.g., how quickly heat escapes from the cup). These diagrams also recognize what controls these rates of change. # Applied Systems Thinking # Dimensions Of A System: Add detail to your systems maps by exploring the different dimensions along which influence might flow: wealth, power, values, knowledge, or beauty. Different types of obstructions—poverty, maldistribution, and insecurity—can cause different types of problems in each of these dimensions. # Leverage Points: Leverage points are places within a system with which a little effort yields great reward. Likewise, bottlenecks are places within a system which resistance could cause significant problems. # Leverage Points: Leverage points are places within a system with which a little effort yields great reward. Likewise, bottlenecks are places within a system which resistance could cause significant problems. # Systems Archetypes: Systems archetypes are common patterns identified in causal loop diagrams or stock-and-flow diagrams. Archetypes exhibit similar behaviours and can be resolved by similar solutions. # The Systems “Business Idea”: Do you need a particular actor or phenomena to receive resources/power/etc.? Where would that resource come from? What influences how much of the resource gets distributed? How can you increase those influencing forces? The business idea uses a causal loop diagram to map the systemic structure of an organization’s strategic sustainability. It makes explicit the phenomena that generate resources for the system to reinvest—and the strategic competencies that the organization can use to enhance those phenomena. # Systemic Theories Of Change: What is the change strategy you’re adopting? Similar to the business idea, a systemic theory of change plots a theory of change model in systemic form, identifying the goal phenomena to enhance (or limit), the key activities that can support that enhancement (or limitation), and the inputs required to sustain and scale those activities. # Systems Stories: Never explain a systems map in a pitch or to a general audience. Instead, follow the iceberg model to distill a systems story 1. Describe what happened (an example of the event or phenomena the systemic designer seeks to address); 2. Describe what has been happening (the pattern of events that lead to the problem or issue); and 3. Describe why (the underlying causal structure that enforces the persistence of these problematic patterns). # Technology For Systems Mapping Mural Mural.co is a collaborative tool for design sprints. As such, it provides features for collaborative whiteboarding and sticky noting, voting via dotmocracy, and a variety of other neat and helpful tools. It is very free-form (and as such has no features specifically made for systemic design) but that open-endedness may be useful. Loopy Nicky Case’s Loopy is a simple tool that allows you to simulate systemic behaviours. It is very unsophisticated (e.g., it is challenging to provide precise system settings) but it is extremely gestural and is therefore fun to use to illustrate and explore ideas. Plectica Plectica is a “visual mapping software”. It allows you to nest and draw connections between cards representing anything. The goal of the app is to provide a simple interface for complex ideas. Kumu Kumu is a web app built specifically for systems mapping. It features extensive features and documentation and a lively support community full of fellow systems mappers who like to help one another. The developers/founders are active participants in that community and regularly provide customer support, too. Develop actor maps, systems maps, and all kinds of other interesting interactive visuals with Kumu. # ADDITIONAL RESOURCES I’ve collected and described resources on related topics at https://systemic.design/resources. In particular, you may want to check out the items on organizational change (e.g., the “Notes on Leadership and Language in Regenerating Organizations” paper and the article on organizational learning). • Leverage analysis in systemic design • Finding the Emic in Systemic Design # Finding the Emic in Systemic Design A paper presented at RSD7 in Turin, Italy. # ABSTRACT I argue that an under-emphasized but crucial variable of success in systemic design is the perspective through which systemic design processes are implemented and executed. While rooted in design (a consciously empathetic discipline, especially in recent years; cf. Kimbell, 2011), it is easy for systemic designers to conduct the research required for their projects in externalized ways. These approaches risk misrepresenting the stakeholders who contribute to projects and, in turn, they are a danger to the potential impact of these misresearched problem systems. I propose to advance a theoretical argument for this danger, the development of an assessment framework to check whether an internalized perspective has been effectively achieved, and provide a proof of concept of this framework through hermeneutic case study analysis. As I will show, systemic design processes that are not executed with the direct and explicit engagement of stakeholders – to the extent of achieving an emic (or from within) understanding of the system – may be flawed at their foundation. By fostering recognition of the importance of an emic perspective, and by providing a framework of principles, practices, and process to accomplish systemic design with this perspective, I hope to ensure that systemic design processes are as accurate and valid as possible with respect to the stakeholders of the system. This is not to suggest that systemic design practice is “too etic”. In fact, with roots in design, systemic design is often deliberately emic. Systemic designers make use of designerly tools that help the researcher to build empathy with system stakeholders (e.g., soft systems methodology, critical systems heuristics, appreciative inquiry; Jones, 2014). They often seek to engage stakeholders in the systemic design process and include reflective analysis of what has been learned in order to assess where deeper engagement with the system is required (Ryan, 2014). That said, with the advent of crowdsourcing (the facilitated involvement of the general public in problem solving, usually using online tools; Lukyanenko & Parsons, 2012) and data science (the use of computational tools to analyze and understand large quantities of data; cf. Scepanovic, 2018), it is likely that data-driven methods will increasingly influence systemic design practice. One recent example sought input from hundreds of people to identify opportunities for change in Canadian post-secondary systems through an iterative online survey (cf. Second Muse, Intel, & Vibrant Data, 2016). This data-driven direction is a powerful opportunity, of course, but it underscores the need to develop principles and best practices for assessing and supporting emic understanding as we gain more data from these tools. This proposal consists of two steps. First, I will look to the principles and theorists of ethnography to develop a framework for assessing the emic/etic perspective of a given research project. Namely, Geertz’ “Thick Description: Toward an Interpretive Theory of Culture” (found in The Interpretation of Cultures, 1973, chapter 1) provides a foundation for the process of emic research, while Creswell and Miller (2000) provide a set of procedural principles for emic validity. Taken together, we generate a critical research framework with which we may assess a given research project’s emic perspective. Second, I will provide a proof-of-concept of this framework (and its theoretical underpinnings) via a casebased assessment of three systemic design projects. Case studies provide an effective venue for learning about the context-dependent manifestations of the phenomena being studied (Flyvbjerg, 2006). One of these case studies is one I have developed through my experience in participating and contributing to the development of the Canadian National Youth Leadership and Innovation Strategy framework, which convened hundreds of youth and youth-serving organizations in order to understand the youth leadership and innovation system in Canada (cf. MaRS Studio Y, 2017). The second and third case studies are those profiled by Ryan and Leung (2014). In order to interpret and analyze the chosen case studies, I turn to the methodology of phenomenological hermeneutics (Eberle, 2014, p. 196; cf. Wernet, 2014). Phenomenological hermeneutics are appropriate as I have access to the described phenomena of the systemic design projects captured by the chosen cases, but these phenomena are not explicitly captured with reference to emic or etic perspectives – thus some construction of the inherent emic or etic data is necessary in order to make judgments about the perspectives found in the projects. In each case, I will use identify phenomena representing the practice of emic (or etic) understanding in the research orientation of the work, as acknowledged by the above framework. In each case, I will examine the step-by-step procedure and any associated notes about the experience of the researchers and participants involved. In each step or experience, I will look for evidence of the four steps of emic understanding or the six techniques of emic validation reported above. # References Creswell, J. W., & Miller, D. L. (2000). Determining Validity in Qualitative Inquiry. Theory Into Practice, 39(3), 124–130. https://doi.org/10.1207/s15430421tip3903_2 Eberle, T. S. (2014). Phenomenology as a Research Method. In U. Flick (Ed.), The SAGE Handbook of Qualitative Data Analysis (pp. 184–202). Los Angeles, Calif. [u.a.]: Sage. Retrieved from https://www.alexandria.unisg.ch/228374/ Flyvbjerg, B. (2006). Five Misunderstandings About Case-Study Research. Qualitative Inquiry, 12(2), 219245. https://doi.org/10.1177/1077800405284363 Geertz, C. (1973). The interpretation of cultures: Selected essays (Vol. 5019). Basic books. Jones, P. (2015). Design Research Methods for Systemic Design: Perspectives from Design Education and Practice. Proceedings of the 58th Annual Meeting of the ISSS - 2014 United States, 1(1). Retrieved from http://journals.isss.org/index.php/proceedings58th/article/view/2353 Kimbell, L. (2011). Rethinking Design Thinking: Part I. Design and Culture, 3(3), 285–306. https://doi.org/10.2752/175470811X13071166525216 Lukyanenko, R., & Parsons, J. (2012). Conceptual modeling principles for crowdsourcing (pp. 3–6). ACM. https://doi.org/10.1145/2390034.2390038 MaRS Studio Y. (2017). A strategic framework for youth leadership & innovation in Canada: Insights from the 2016 National Youth Leadership and Innovation Strategy Summit. Toronto, ON. Retrieved from http://www.studioy.marsdd.com/wp-content/uploads/2016/12/MaRS_NYLISstrategic_framework_Final.pdf Ryan, A. (2014). A Framework for Systemic Design. FORMakademisk–research Journal for Design and Design Education, 7(4). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/787 Ryan, A., & Leung, M. (2014). Systemic Design: Two Canadian Case Studies. FormAkademisk - Research Journal of Design and Design Education, 7(3). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/794 Scepanovic, S. (2018). Data science for sociotechnical systems - from computational sociolinguistics to the smart grid. Aalto University. Retrieved from https://aaltodoc.aalto.fi:443/handle/123456789/30187 Second Muse, Intel, & Vibrant Data. (2016, May 11). What Your Data Says: Post-Secondary Education Mapping Survey Highlights. RECODE. Retrieved from http://re-code.ca/whats_happening/watch-recodewebinar-what-your-data-says/ Wernet, A. (2014). Hermeneutics and Objective Hermeneutics. In U. Flick, The SAGE Handbook of Qualitative Data Analysis (pp. 234–246). SAGE Publications, Inc. https://doi.org/10.4135/9781446282243.n16 Projects 11 notes with this tag (showing first 10 results) • Your Notes are an Information System • Systemic Strategy # Systemic Strategy: Systemic Design Methods for Complex Systems Change A presentation from Peter Jones and I at RSD9, virtually in Ahmedabad, India. • Leverage analysis in systemic design • Finding the Emic in Systemic Design # Finding the Emic in Systemic Design A paper presented at RSD7 in Turin, Italy. # ABSTRACT I argue that an under-emphasized but crucial variable of success in systemic design is the perspective through which systemic design processes are implemented and executed. While rooted in design (a consciously empathetic discipline, especially in recent years; cf. Kimbell, 2011), it is easy for systemic designers to conduct the research required for their projects in externalized ways. These approaches risk misrepresenting the stakeholders who contribute to projects and, in turn, they are a danger to the potential impact of these misresearched problem systems. I propose to advance a theoretical argument for this danger, the development of an assessment framework to check whether an internalized perspective has been effectively achieved, and provide a proof of concept of this framework through hermeneutic case study analysis. As I will show, systemic design processes that are not executed with the direct and explicit engagement of stakeholders – to the extent of achieving an emic (or from within) understanding of the system – may be flawed at their foundation. By fostering recognition of the importance of an emic perspective, and by providing a framework of principles, practices, and process to accomplish systemic design with this perspective, I hope to ensure that systemic design processes are as accurate and valid as possible with respect to the stakeholders of the system. This is not to suggest that systemic design practice is “too etic”. In fact, with roots in design, systemic design is often deliberately emic. Systemic designers make use of designerly tools that help the researcher to build empathy with system stakeholders (e.g., soft systems methodology, critical systems heuristics, appreciative inquiry; Jones, 2014). They often seek to engage stakeholders in the systemic design process and include reflective analysis of what has been learned in order to assess where deeper engagement with the system is required (Ryan, 2014). That said, with the advent of crowdsourcing (the facilitated involvement of the general public in problem solving, usually using online tools; Lukyanenko & Parsons, 2012) and data science (the use of computational tools to analyze and understand large quantities of data; cf. Scepanovic, 2018), it is likely that data-driven methods will increasingly influence systemic design practice. One recent example sought input from hundreds of people to identify opportunities for change in Canadian post-secondary systems through an iterative online survey (cf. Second Muse, Intel, & Vibrant Data, 2016). This data-driven direction is a powerful opportunity, of course, but it underscores the need to develop principles and best practices for assessing and supporting emic understanding as we gain more data from these tools. This proposal consists of two steps. First, I will look to the principles and theorists of ethnography to develop a framework for assessing the emic/etic perspective of a given research project. Namely, Geertz’ “Thick Description: Toward an Interpretive Theory of Culture” (found in The Interpretation of Cultures, 1973, chapter 1) provides a foundation for the process of emic research, while Creswell and Miller (2000) provide a set of procedural principles for emic validity. Taken together, we generate a critical research framework with which we may assess a given research project’s emic perspective. Second, I will provide a proof-of-concept of this framework (and its theoretical underpinnings) via a casebased assessment of three systemic design projects. Case studies provide an effective venue for learning about the context-dependent manifestations of the phenomena being studied (Flyvbjerg, 2006). One of these case studies is one I have developed through my experience in participating and contributing to the development of the Canadian National Youth Leadership and Innovation Strategy framework, which convened hundreds of youth and youth-serving organizations in order to understand the youth leadership and innovation system in Canada (cf. MaRS Studio Y, 2017). The second and third case studies are those profiled by Ryan and Leung (2014). In order to interpret and analyze the chosen case studies, I turn to the methodology of phenomenological hermeneutics (Eberle, 2014, p. 196; cf. Wernet, 2014). Phenomenological hermeneutics are appropriate as I have access to the described phenomena of the systemic design projects captured by the chosen cases, but these phenomena are not explicitly captured with reference to emic or etic perspectives – thus some construction of the inherent emic or etic data is necessary in order to make judgments about the perspectives found in the projects. In each case, I will use identify phenomena representing the practice of emic (or etic) understanding in the research orientation of the work, as acknowledged by the above framework. In each case, I will examine the step-by-step procedure and any associated notes about the experience of the researchers and participants involved. In each step or experience, I will look for evidence of the four steps of emic understanding or the six techniques of emic validation reported above. # References Creswell, J. W., & Miller, D. L. (2000). Determining Validity in Qualitative Inquiry. Theory Into Practice, 39(3), 124–130. https://doi.org/10.1207/s15430421tip3903_2 Eberle, T. S. (2014). Phenomenology as a Research Method. In U. Flick (Ed.), The SAGE Handbook of Qualitative Data Analysis (pp. 184–202). Los Angeles, Calif. [u.a.]: Sage. Retrieved from https://www.alexandria.unisg.ch/228374/ Flyvbjerg, B. (2006). Five Misunderstandings About Case-Study Research. Qualitative Inquiry, 12(2), 219245. https://doi.org/10.1177/1077800405284363 Geertz, C. (1973). The interpretation of cultures: Selected essays (Vol. 5019). Basic books. Jones, P. (2015). Design Research Methods for Systemic Design: Perspectives from Design Education and Practice. Proceedings of the 58th Annual Meeting of the ISSS - 2014 United States, 1(1). Retrieved from http://journals.isss.org/index.php/proceedings58th/article/view/2353 Kimbell, L. (2011). Rethinking Design Thinking: Part I. Design and Culture, 3(3), 285–306. https://doi.org/10.2752/175470811X13071166525216 Lukyanenko, R., & Parsons, J. (2012). Conceptual modeling principles for crowdsourcing (pp. 3–6). ACM. https://doi.org/10.1145/2390034.2390038 MaRS Studio Y. (2017). A strategic framework for youth leadership & innovation in Canada: Insights from the 2016 National Youth Leadership and Innovation Strategy Summit. Toronto, ON. Retrieved from http://www.studioy.marsdd.com/wp-content/uploads/2016/12/MaRS_NYLISstrategic_framework_Final.pdf Ryan, A. (2014). A Framework for Systemic Design. FORMakademisk–research Journal for Design and Design Education, 7(4). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/787 Ryan, A., & Leung, M. (2014). Systemic Design: Two Canadian Case Studies. FormAkademisk - Research Journal of Design and Design Education, 7(3). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/794 Scepanovic, S. (2018). Data science for sociotechnical systems - from computational sociolinguistics to the smart grid. Aalto University. Retrieved from https://aaltodoc.aalto.fi:443/handle/123456789/30187 Second Muse, Intel, & Vibrant Data. (2016, May 11). What Your Data Says: Post-Secondary Education Mapping Survey Highlights. RECODE. Retrieved from http://re-code.ca/whats_happening/watch-recodewebinar-what-your-data-says/ Wernet, A. (2014). Hermeneutics and Objective Hermeneutics. In U. Flick, The SAGE Handbook of Qualitative Data Analysis (pp. 234–246). SAGE Publications, Inc. https://doi.org/10.4135/9781446282243.n16 • Global Steering Group for Impact Investment systemic theory of change # The Global Steering Group for Impact Investment’s (2018) systemic theory of change A systems model I helped visualize for the Global Steering Group on Impact Investment in 2018: • Innovation is a buzzword Notes, slides, and the Innovation Auditing guide presented at the talk are found below. # The research The research presented during the talk is discussed on the following pages: # Slides Find a PDF of the slides I presented at the link below. Beware: the animations don’t translate well to print, so some of the pages have graphical issues. # Innovation Auditing Innovation Auditing is a simple procedure that individuals, organizations, and governments can use to detect the gaps in the innovation process they seek to support. See the PDF guide by clicking the link below. • Creative Education Futures # Creative Education Futures What are the futures of art and design schools in Canada? In 2015, I supported Kinetic Café in developing OCAD University’s latest Vision and Mission statements. As part of that work, I helped scan for signals, trends, and drivers in art and design school futures. Our scan revealed five important drivers of change: reforming education, creative economies and cultures, new geographies, empowering technologies, and conscious collective. A walkthrough of this work is visualized and embedded below. If it doesn’t display, you can visit it directly here. • Innovation Education # Innovation Education What is innovation? How do we define innovation, its outputs and processes, and what are the skills and competencies necessary to practice and excel in innovation? Read the full paper. Many strategies and policies, both federal and provincial, have attempted to improve Canada’s innovation capacity in the last few decades. Universities and colleges are often discussed in these strategies for their role in facilitating new partnerships and in developing (potentially) actionable research. It is rare, however, for these strategies to recognize education plays in the creation of innovators. This is counterintuitive: education is an obvious mechanism with which to develop the knowledge and abilities of a population. Yet we lack a holistic understanding of what it takes to practice innovation, let alone the kinds of curricula that might provide those skills and competencies. Moreover, we are inconsistent in the definitions and language we use to define innovation—often obsessing over technology and commercialization. We tend to assume innovation comes from research and development processes, and that innovators are simply highly skilled people. Presented here is the result of an intensive review of reports, strategies, policy, and theory on innovation in the Canadian context. This literature was scanned and coded—inspired by the ethnographic methods of grounded field theory—in order to synthesize a holistic theory of innovation. This theory includes a universal definition of the innovation process, a recasting of different focuses of innovation as innovation orientations, a comprehensive model of the innovation process, and a synthesis of innovation skills and competencies into 13 learning domains, 47 learning constructs, and 227 learning outcomes. These tools provide utility for policymakers and educators in pursuit of understanding and improving innovation capacity. In particular, the model of innovation education is the most comprehensive of its kind, providing an extensive set of concepts with which to understand education gaps and build curricula. Perhaps the most important contribution of this research, however, is the recognition that our conversations about innovation strategies and education reform must be aligned. **How exactly do people learn to be innovative, and how are our education systems currently facilitating that process? **With this study we have begun to seek answers to these questions, but there is much more work to do. If you use these ideas and learn something from your experience, or if you have thoughts on how to improve them, don’t hesitate to make suggestions and to share your work. Find resources on this page that detail the definitions and models of innovation developed through this research and how these concepts may be applied in innovation education programming. # Explore the Model Across dozens of perspectives on innovation, a set of 13 domains of skills and competencies emerged. These domains have been interactively visualized using Kumu.io. You can play with the work yourself by clicking the button. Use the controls in the bottom corners to focus on specific components of the model, to surface the innovation process so that you can explore both simultaneously, and more. Note that the visualization is best explored on a desktop! # Learn more about the skills and competencies of innovation This document provides an executive summary of the insights and models on innovation education uncovered through this research and guides educators to put these concepts and tools to use. # Read the Research Education reform presents an opportunity to improve innovation education and, in turn, advance innovation capacity. I synthesize the framing and strategy of resources from provincial, national, international, and theoretical perspectives on innovation in order to develop a holistic model of innovation and a curricula for innovation education. Then, I use systemic design to model Newfoundland and Labrador’s current education system and to suggest strategies for reform to enable improvement in Newfoundland and Labrador’s innovation education. Finally, I explore how systemic reform in Newfoundland and Labrador may serve as a systems laboratory for reform efforts in other jurisdictions. Innovation Education is a major research project presented to OCAD University in partial fulfillment of the requirements for the degree of Master of Design in Strategic Foresight & Innovation. This work was supported by the Social Sciences and Humanities Research Council of Canada. • Education Systemics # Education Systemics What are the mechanisms of education systems change? How might we use systemic design to power a reform movement? What does systems thinking teach us about opportunities and barriers for education reform in Newfoundland and Labrador? Education reform is not a new idea. Many organizations and initiatives have reimagined the schools, universities, and colleges that are the backbone of our economy and society—yet, to many, it seems like little has changed in recent decades. As Jal Mehta, Robert Schwartz, and Frederick Hess began their book on the subject, “if we keep doing what we’re doing, we’re never going to get there.” Traditional education reform approaches have depended on a best practices approach in what is glibly called a “silver bullet culture”. A single idea, found successful in a specific institution or district, becomes hailed as the be-all-end-all solution. This solution is then celebrated and championed across contexts until actors realize that expected results have not materialized, and reformers move on to the next silver bullet solution. This approach to education reform has not worked. According to Mehta, Schwartz, and Hess: “If we are to deliver transformative improvement, it is not enough to wedge new practices into familiar schools and districts; we must reimagine the system itself”. In other words, education systems change has been found to be more than difficult. It is a wicked problem: ill-defined, constantly fluxing, with many conflicting stakeholders and no true solutions. How can we provoke change in wicked problems? I argue that reforming education is a sociotechnical problem, involving human psychology; social, political, and economic factors; and complex interactivity–what Don Norman and Pieter Stappers have called a “DesignX” problem. These authors suggested that DesignX problems can only be solved through a process of muddling through, developing incremental sub-solutions through deep analysis. This deep analysis means partitioning the problem into modules and recognizing the intersecting dimensions of the problem. Peter Jones provides further advice for this kind of problem solving, defining an approach called systemic design. Systemic design integrates systems thinking and systemic methods–ways of understanding complex problems through the relationships of the phenomena and actors involved–with design thinking and design methods, applying human-centred design to these seemingly intractable, large-scale problems. With systemic design, Peter says, we use “known design [tools]—form and process reasoning, social and generative research methods, and sketching and visualization practices—to describe, map, propose, and reconfigure complex services and systems”. # Approach & Findings With this in mind, I turned to several types of modelling in order to use systemic design on the complex problem of education reform: process modelling, actor mapping, and causal loop mapping. In this modelling, I focused on Newfoundland and Labrador—my home province—and the education of innovation, examining how our system currently provides innovation learning and how we might do better. Finally, I applied centrality analysis – a quantitative approach to assessing leverage points and bottlenecks in networks and systems maps—in order to surface potential opportunities and challenges in the system. I examined four types of centrality analytics: • Reach efficiency takes an element’s reach (the proportion of the network within two steps of that element) and divides it by the number of neighbouring elements it has. Elements that score the most on this metric tend to be less connected but have high exposure to the rest of the system, making them low-hanging fruit for change efforts. • Betweenness assesses the number of times an element lies on the shortest path between two other elements. Elements high on the betweenness metric are bridges throughout the map, controlling the flow of phenomena throughout the system. This means that these elements may be bottlenecks or single points of failure. • Eigenvector centrality measures an element’s connectedness to other well-connected elements, computing an overall value that is an indicator of the element’s influence over the whole system. • Torque calculates each element’s reach efficiency weighted by its eigenvector centrality (e.g., how influential that element is). Elements with high torque should be relatively easy to impact (as they are not densely influenced by other phenomena in the map), but will impact the rest of the map substantially. These are key leverage points of change. The detailed methods and findings from each of these approaches are discussed in turn in the links below. # Process Modelling, Actor Mapping, And Causal Loop Mapping # Conclusions I aimed to see the education system for what it is in order to describe strategies for the transformative reform that Mehta, Schwartz, and Hess called for. The education system is therefore composed of a number of interrelated components, organized in a hierarchy, whose emergent phenomena lead to its own dynamics. Yet, many might say that this systemic chaos implies a system of constant change, while education is hallmarked for its derelict stagnancy in the 21st century. How is it that such a system has not evolved? Well, perhaps the system is not actually that broken. As eloquently argued by Ryan Burwell, an instructional designer at the MaRS Discovery District: The school system is not broken. It is perfectly aligned to provide equitable access to a canon of high-quality, standardized content with greater rigour and organization than any other knowledge delivery system we currently have. However, it is not designed to foster the problem-solvers, innovators and entrepreneurs that are becoming an increasingly significant part of the global economy. Incorrectly identifying this misalignment as a broken system has created a culture of fear and failure around education, leading to top-down reforms and increased numbers of mandatory programs. I return to Mehta, Schwartz, and Hess’ depiction of school reform’s silver bullet culture. Many stakeholders with competing interests and different priorities are invested in every debate on education systems change. Thus, there are many potential silver bullets–and many advocates for them. The misunderstanding of the problem described by Burwell and the complexities of education reform described by Mehta, Schwartz, and Hess perfectly capture the need for a systemic design-based approach to change. # Process Mapping From process modelling, it is clear that while NL’s education system currently offers some opportunities to learn certain constructs of innovation, the availability of these opportunities is not densely packed throughout their study. It is easy to recognize a dearth of access to the domains of Foresight and Scanning, Vision and Purpose, and Adaptability and Resilience. Further, the degree to students learn the domains and constructs of innovation skills from the public system remains unclear. Ultimately, now that these models exist, further analysis will be able to examine these constructs more closely as students progress through the system. This is especially true for many of the “optional” components of the broader education system. After school programs, hobbies, sports and recreation, volunteer and extra-curricular roles, self-directed learning, and employer training could each be vital sources of innovation education, but it was impossible to study these aspects of the system in any meaningful way in the present study. A dedicated effort should examine the availability of these sources and assess their utility for innovation learning. One research approach would be to survey learners along the learning journey, testing their abilities in the different constructs I’ve outlined. This ethnographic approach could reveal hidden truths: perhaps, for instance, certain regional cultures in the province actually provide powerful learning in design through a community culture alone. # Actor Mapping Systemic modelling reveals the power and wealth subsystems active amongst the actors of the education system. Centrality analysis of the power subsystem illustrates that parents and the provincial government have efficient influence on the system, and change that can mobilize those bodies of actors will quickly take shape. Meanwhile schools, the School Board, and educators have substantial global influence over the system–change efforts that engage these actors may be slow but momentous. Finally, power bottlenecks are educators; schools and school councils; and the Department of Education and Early Childhood Development. This suggests that these actors will ultimately need to be involved if any reform effort were to achieve success. Reach efficiency analysis of the wealth subsystem shows that the federal government, parents and students, and the provincial Department of Advanced Education and Skills each strongly influence the distribution of wealth. The Federal and Provincial Governments have powerful incentives with which to motivate and control reform efforts. Betweenness centrality revealed that the whole system is tightly linked, making it potentially volatile: economic issues in one component of the system may ripple out and impact the others. # Causal Loop Mapping Finally, these maps intimated a causal loop diagram illustrating how innovation education reform might happen in the public education system. Several loops and one archetype demonstrate significant effect over the system. The Low Definition loop describes an acceleration of the impact of ill-defined innovation on our ability to educate on it. The We Teach What We Know loop shows how a lack of innovation education leads to a lack of people capable of teaching it and vice-versa. The New Economy loop shows how economic shocks driven by drops in commodities pricing has raised our awareness of the importance of the innovation economy. The Innovation-driven Growth loop shows how innovation capacity will accelerate jobs in the knowledge economy, which will in turn drive our ability to create more innovators through education. The Limited Resources loop balances our ability to reform education for innovation due to a lack of funding for the reform effort due to austerity budgets, driven by drops in the price of oil. Finally, the R&D, Not Innovation archetype is an instance of the Fixes that Fail systems archetype, showing how a conflation of innovation with R&D efforts fails to improve our innovation capacity while also distracting from true innovation education. The result of centrality analysis on these causally-linked phenomena is rich with pragmatic insight. Three phenomena with efficient reach over the whole system are innovation learning from outside of the public education system, lack of emphasis on innovation education, and low price of oil. The former points to an accessible lever of change: introduce innovation education through extra- and co-curricular programs, volunteer and leadership roles, sports and recreation, or self-directed learning, and the system may catch up by offering its own programming to match. The leverage of a lack of emphasis on innovation education offers another route: increase awareness on innovation education in order to encourage the system to improve on it. Finally, low price of oil retains leverage as a dampener on the system: if the economy continues in recession, the system is less able to offer resources for reform efforts. Other calls for reform is one force with substantial torque over the system, indicating that reformers must be co-opetitive with other education change efforts, else all reform efforts might fail due to competition with one another. The availability of accessible and practical models for innovation education is another high-torque element, however, elevating the potential of the present research to create change in the system. A third element with high torque is the generational shift in work, evidence that a substantial source of impetus for innovation education reform could come from changes in work and careers. Finally, betweenness centrality offers a picture of the bottlenecks and points of failure within the system. Innovation capacity and innovation education are two forces semiotically central to the system, and thus it is intuitive that they will be slow to change, no matter what else is happening within the system. On the other hand, recognition of innovation deficiency, the perceived innovation gap, and the search for solutions to the innovation gap are three phenomena that are clear points of fragility in any systemic change effort. If the system does not recognize its deficiencies, perceive the gap in innovation capacity, or opt to search for solutions, reform efforts are liable to be frustrated. # Limitations Despite these clarion recommendations for systemic design, several limitations prevent wholesale adoption. One key limitation of the presented results of systems modelling is that the connections defined in these models are unquantified. In the refined actor map, for instance, it may be that educators have little power over their school councils, or perhaps the NL Federation of School Councils has far less lobbying capacity than the NL Federation of Teachers. Evaluating the strength of these connections and including these evaluations in our analytics would improve the acuity of those metrics substantially. As previously mentioned, if innovation learning is not coming from the public education system, it must be coming from somewhere else. Yet, these potential sources arguably include the whole of the human experience—as we have, after all, been learning to innovate since pre-history. Future research might take on an ethnographic approach to understanding the system, investigating different student-innovators and where they learned their innovation skills, or a longitudinal approach, following students as they become innovators through their years in the education system. These exercises fell outside the limits of the present research, unfortunately. Another limitation is that, while the scope and approach to mapping were designed to increase the variety of the system as much as possible, the mapping was still completed with the perspective of only this author. The representativeness of the systems models would therefore be strengthened considerably with Delphi-inspired methods as seen in previous research, bringing the mapping process to others in order to iteratively refine and the map from alternative stakeholders’ points-of-view. Another potential future study is to “bring the whole system into the room”. This would mean convening a group of stakeholders who were holistically representative of the actors of the system, engaging them in a systems modelling process to develop a map with their collective perspectives. # ACTIONS AND TAKEAWAYS # In The Short Term A few immediate actions stem from this research. # 1. Adopt A Model First, we must adopt a model of innovation skills and competencies. Regardless of whether the adopted model is the one developed through this project or another alternative, it is imperative that we begin to recognize the skills and competencies used by successful innovators. By identifying these skills, we will be capable of examining our weaknesses and, in turn, developing ways of resolving those weaknesses. To spur this discussion, I plan on sharing the models developed here widely. # 2. Consider The Role Of Education In The Creation Of Canadian Innovators Second and in tandem, we must include the role of the education system in nurturing innovators in our provincial and national innovation strategies. Many approaches to innovation policy discuss the post-secondary education system with respect to its role in public-private partnerships and the commercialization of research. We must expand this role to include the development of innovation skills and competencies as well. In the near future I hope to meet with policymakers involved in the development of Newfoundland and Labrador’s innovation strategies to advocate for this approach there. # 3. Unite Education Reform Movements Education reform movements must be united in their calls for change. A host of movements relate to the notion of innovation education, from code.org (a non-profit urging computer science and programming education in K-12) to the 21st century learning movement (a pedagogical framework for the skills and knowledge necessary for the 21st century; cf. http://www.p21.org). The present research shows that these reform efforts may conflict, however, if they are brought forward asynchronously by their champions. It is therefore crucial that these efforts learn to “co-opete” (as in “co-opetition”) and engage educators and policymakers with aligned advocacy. I hope to work with the education systems change movements I already have relationships with in the immediate future in order to begin this dialogue. # In The Long Term As explored by David Stroh in Systems Thinking for Social Change, systems change is only possible when the actors of the system collectively recognize the tension between where the system is and where they want it to be. That realization isn’t possible, however, before the actors have even talked to one another—let alone come to consensus about a shared vision for the future. We realize that Canada’s future prosperity is predicated on our ability to leverage the boons of our resource economy and evolve it into an “innovation rich” leader in the knowledge economy. Yet, as discussed at the beginning of this paper, the danger is that education’s role in this transformation has yet to be recognized in full. We are not talking about how to create innovators, let alone what strategies we should employ in doing so, or how the system is stuck in becoming better at innovation education. Worse, there are many simultaneously conversations happening in both education reform and innovation—conversations that compete with one another, threatening the potential of the whole. This research offers a model of the education system in Newfoundland and Labrador. Yet these models are untested, and as I have noted, the research is sorely lacking a futures perspective that observes both threats and strategic opportunities in our changing environment. **How might we spark a collective, integrative discourse on innovation and innovation education? **Then, how might we elevate its importance such that collective action is taken—before we’ve missed the opportunities of the knowledge economy? How might we refine the systemic models, and how might we augment this work with a futures perspective, using environmental scanning to develop and integrate changing trends for strategic leverage? These questions point toward a need for a powerful, strategic theory of change, and the willingness to muddle through. In other words, **this change will not come about through the efforts of ad hoc standalone initiatives like this one. ** We need a sustained effort. We need a lab that brings together design science and systemic design, creating and testing designs of the system itself, making sure they are valid constructs of the concepts they are intended to represent, all while obeying the principles of systemic design. This is not a new idea. Many have articulated the notion of social labs, design or change labs, or social innovation labs. In fact, the OECD’s Centre for Educational Research and Innovation seems to operate such an approach for systemic innovation in global education. I argue that Canada–or at least, Newfoundland and Labrador–needs to take a lab-based approach to navigating complex education reform in education. This lab must unite the perspectives, strategies, and actors currently engaged in similar pursuits; build, maintain, and refine models of the systemic change taking place; be engaged in environmental scanning and strategic foresight to monitor for both threats and opportunities; and prototype change initiatives, taking lessons back to these models and strategies. Only a dedicated, intelligent effort will help us build the education systems that will develop the skills and knowledge we need to answer the 21st century. Innovation Education is a major research project presented to OCAD University in partial fulfillment of the requirements for the degree of Master of Design in Strategic Foresight & Innovation. This work was supported by the Social Sciences and Humanities Research Council of Canada. • Innovation systemics # Innovation Systemics # Takeaways # Problem 1: Canada Struggles To Understand How It Can Fit The ‘Idea Economy’ Into The Broader Economic Context (I.e. Other Sectors). Thus, Canada should take steps to foster the idea economy. The world is changing, and Canada needs to understand how the tenets of the idea and knowledge economy will best flourish across the primary sectors that drive the broader Canadian economy. Building regional collectives (like the Waterloo-Kitchener corridor) to advance innovation is only one step, whereas our findings suggest the need to take a collective leap and author a White Paper that will activate a national approach on the new, ideas-based economy. In doing so, the Government of Canada will engage a collective of stakeholders, thought leaders and businesses both large and small to lead a national dialogue on how innovation ought to play out across Canada’s diverse communities, companies and campuses. # Problem 2: Canadians Do Not Recognize The Unique Strengths Of The Economy As It Is, And Neglect Recognition Of The Innovations Already Taking Place. Canada should change the narrative. Innovation is happening, but it is taking place in sectors and industries different than the ones we tend to pay attention to. Increasing awareness about the need for, and impact of, innovation within advanced manufacturing, natural resources and agriculture will help cross pollinate the economy with more robust, productive approaches and solutions. This will also help to shift the culture of entrepreneurship by empowering a generation of Canadians to create sustainable value and ensure they and their communities prosper. # Problem 3: Canada Currently Allocates A Disproportionate Amount Of Resources (Talent And Capital) To “Tech Solutionism”, At The Cost Of Others. Canada should redirect the pipeline. The ultimate step is to increase the carrying capacity of the system to generate value for entrepreneurs from outside the technology sector. Drawing sectors and industries together with the innovation ecosystem will build deeper and more diverse connections. Diverting the flow of resources—talent and capital—and binding it with existing infrastructure and institutional support will build a depth that will support a more robust Canadian economy. Furthermore, investing in improving the structures that nurture prosperity—incubators, accelerators, entrepreneurship, and innovation programs—and bringing them together with campuses and companies already making an impact, will propel Canada forward. # The Context “Innovation drives an economy’s ability to create more economic value from an hour of work, thereby increasing economic output per capita. The resulting productivity growth creates potential for rising wages and incomes, and thus for a higher standard of living.” (University of Lethbridge Research Services, 2015) A robust innovation ecosystem has the ability to improve productivity, economic growth, and job creation metrics in countries adequately supporting this process. In these countries, there also tend to be more resources available to support spending in education, health, and infrastructure, to name a few (“Innovation details and analysis”, 2013). Accordingly, the importance of a healthy innovation system is tied closely to that of a healthy national economy, along with its people, communities and institutions. In Canada, however, economic discourse around innovation and entrepreneurship has recently pointed towards a decline in productive returns from startup investment. Although an improvement from previous years, in 2015 Canada was ranked 9th out of 16 peer countries in innovation by the Conference Board of Canada, receiving a letter grade of “C” on its Innovation Report Card (“Innovation details and analysis”, 2013). This ranking points to a persistent weakness in the Canadian innovation system, commonly referred to as the “innovation gap”. This phenomenon is being reported by some of the country’s top journalists, startup CEOs, established investors, think-tanks, and members of various levels of government across the country. While these reports highlight culture, politics, economics, and education as the cause of this gap, and underlining the need for reform, policy changes, and new programs, few of these calls to action are gaining traction. There is no easy answer to this wicked problem. With the above in mind, we initially sought to answer the question “Why are investments in innovation resulting in diminishing returns in productivity?” through our research, but we quickly realized that in order to address this issue, we would first need develop a thorough understanding of the innovation ecosystem in Canada and thus we broadened our research questions to “How might we understand the Canadian innovation system?” all the while still focusing on this oft reported, elusive innovation gap. Innovation details and analysis. (2013). The Conference Board of Canada. Retrieved from http://www.conferenceboard.ca/hcp/details/innovation.aspx University of Lethbridge Research Services. (2015). Putting Innovation in Context. Lethbridge, Alberta, Canada: University of Lethbridge. Retrieved from http://www.agility-ulethbridge. ca/2015/09/11/putting-innovation-in-context/ # Research Synthesis Map This synthesis map summarizes our research on Canada’s systemic innovation challenges this past term. # Leverage Analysis We used centrality analysis to examine our map of the system for potential leverage points. The elements that surface from this analysis offer opportunities (or, in some cases, roadblocks) for policy and program interventions. # The Paper # The Researchers This work was completed by a team of Master of Design students in OCAD U’s Strategic Foresight & Innovation program. Michael Berman Robyn McCallum David Fascinato Ryan J. A. Murphy Innovation 8 notes with this tag • Intuition is confident abduction # Intuition is confident abductive-inferential thinking In a recent episode of Hello Monday, Jessi Hempel interviews Dr. Natalie Nixon on creativity and her new book, The Creativity Leap. Natalie’s PhD in Design Management—plus her work in fashion, design, and business—led her to a catchy and compelling description of creative work. We accomplish creative work, she says, “by toggling between wonder and rigour.” In the podcast conversation, Jessi and Natalie talk about intuition—and I was struck by something. “We don’t talk about intuition,” Natalie notes at about 6 minutes in. “We don’t talk about intuition in business school, in law school, or in medical school.” And yet, she says, “I observed that really successful leaders—especially really successful startup leaders—in their origin stories, there’s always this moment where ‘Something told me not to do the deal. Something told me to work with her over him.’ […] Every successful leader really reckons with incorporating acting on their intuition to make decisions.” Jessi agrees, noting that intuition comes up often in her interviews with leaders on Hello Monday as leaders cite it as the reason for their success. The thing is, just because we don’t name intuition doesn’t mean we aren’t talking about it. That’s because intuition is really just confident, logical thinking. Charles Sanders Peirce was a philosopher. He investigated how we inquire into and discover new knowledge.1 Before Peirce, we generally recognized the logical processes of deduction and induction. Deductive thinking helps us identify what must be true about a situation in order to explain it. When we deduce something, we look at the general rules and principles we know of and draw specific conclusions from that evidence. Inductive thinking involves drawing general conclusions from specific, limited evidence. Peirce argued that effective reasoning follows a pattern: we determine the specific consequences of an idea (deduction), and then we judge whether the available evidence fits that idea and its consequences (induction). But how do we develop ideas?2 Abduction is the name of the logical process Peirce described for developing ideas. To think abductively means to generate and choose ideas that fit the situation at hand. A good idea should be verifiable—we should be able to use evidence to judge its fit—and should help us resolve the situation at hand. Peirce also had criteria to help choose the best ideas to test. He suggested that we should strive to conserve resources (e.g., those that most are most efficiently verifiable and usable in the situation), identify the most valuable ideas (specifically the “uberty” of an idea, or how likely it is that a possible idea might bring about an innovation), and the most relevant ideas (e.g., those that may apply beyond our current focus, too).3 Abduction is clearly an important step in any innovative process—but it is no more important than testing and using the ideas you generate. What, then, if you don’t have enough evidence to truly test and prove your ideas? The process Peirce described—abduction, deduction, induction—is the ideal. However, we do not always have time and energy to follow the process diligently. Instead, we quickly make creative judgements based on a few observed qualities. This requires two related processes.4 The first Peirce called “abductory induction,” and it combines the first and last step of the inquiry process. We observe the qualities of the situation, and we generate possible ideas to resolve it based on those observations. The second process is known as “inference to the best explanation” (IBE).5 IBE is exactly what it sounds like. Given a number of possible ways of resolving a problem, choose the best one. (Peirce’s criteria, noted above, apply here.) So what does all this have to do with intuition? Intuition is the confident application of these shorthand logical approaches to creative problem solving. As Jessi and Natalie noted, we aren’t often explicitly taught about strengthening our intuition. Yet, everything we learn supports its development. The more we have to draw on in order to pull into the processes described above, the better our intuitive decisions will be. I say that intuition is the confident application of these processes because they only work when we follow through. In reality, we use abductory induction and IBE all the time. When we engage in creative problem solving, we’re not only using information from the evidence in front of us. We’re drawing on our lived experience and our knowledge base. Even if we don’t directly recall or reference that background information, it is drawn into the creativity of abduction and it defines the general rules and principles we use in deduction. It provides us with the heuristics we use when engaging in IBE. But if we don’t have a bias towards action and instead operate with e.g., perfectionism, we fail to actually execute on these ideas. Thus, we need to have confidence in our abductory induction and IBE processes. All this is simply a gentle challenge of the idea that we don’t talk about intuition. I think that all knowledge management practices and forms of education are actually fundamentally about strengthening our intuition. That said, Natalie’s work is fascinating. I recommend the episode of Hello Monday and plan on picking up her book! 1. In this article, my reading of Peirce comes from the writing of William Mcauliffe↩︎ 2. Peirce was actually specifically concerned with science and hypotheses generation, selection, and testing. Here I refer to generating, selecting, testing, and using ideas to apply these concepts to problem-solving more broadly. ↩︎ 3. He also cautioned not to produce ideas that stop the inquiry process—e.g., magical thinking, or by suggesting that whatever happened must be a complete mystery. ↩︎ 4. Actually, the difference between these two processes is the subject of substantive, controversial debate. This is in part because the scholars who study inference to the best explanation have also used Peirce’s term “abduction” to describe it. This understandably caused extensive confusion, but also probably a lot of philosophical debates and scholarship, so maybe it was for the best. ↩︎ • The changing work of innovation for public value and social impact In two senses, the work of innovation for public value and social impact is changing in Australia and around the world. What we expect public innovation to do and what we need it to achieve, and how that work should be done, are both changing. And they are changing together while they are changing each other. It’s true. It’s hard to keep up with the discipline of changemaking, but it’s even harder to keep up with the change that needs to be made. Therefore Martin Stewart-Weeks calls for optimism: Despite some of the uncomfortable and unsettled conditions, there is real energy in the search for more effective ways to solve the big problems we face in common – managing our complex cities, rewiring large and complex health and social care systems, tackling climate change, searching for better ways to integrate the human and technology capabilities of the digital age and making our communities healthy and resilient. The speed, intensity and sheer connectedness of these and many other complex, public challenges are giving rise to new methods and tools that can help to tackle them with purpose and skill. • Piret Tõnurist & Systems Change: how to get started and keep going? This is a great talk from Piret Tönurist of the Observatory on Public Sector Innovation. One of the core issues of the talk is innovation doubt—the “if it ain’t broke, don’t fix it” mentality. To paraphrase Piret: […] why are we doing innovation at all? Maybe sometimes things are working fine, why do we think about innovation at all? We start off with four questions: 1. Do you want to do things better? 2. Do you have goals and purposes to fulfill? 3. Do you want to address the needs of your stakeholders? 4. Do you want to prepare for the risks and uncertainties that the future holds? If you answered “yes” to at least one of those questions, then your job is to do innovation—your job is to be a changemaker. Also, the talk includes a neat model for different varieties of innovation, image courtesy of this post by Adrian M. Senn over on Medium: https://miro.medium.com/max/1210/1*AaPZeqAVLoo85RfY7Dxspw.png • Paul Jarvis on Hurry Slowly: Small is Beautiful The ever-refreshing Paul Jarvis shares some uncommon thoughts on productivity in Jocelyn K. Glei’s Hurry Slowly podcast. In particular, Paul and Jocelyn discuss the importance of resilience. Citing research and his own experience, Paul points out that resilience is a more important factor in success than many others. Obviously, though, enabling resilience is not as easy as simply pointing out how important it is. As they discuss, resilience isn’t something innate—which means that it can only be developed through experience. And this is where things get tricky: who gets to have resilience-building experiences? In my research on innovation skills, I discovered that resilience was one of three key domains that wasn’t an important outcome for our public education systems. This means that resilience training isn’t necessarily a public good. Only if you’re lucky (or privileged) will you have the chance to build up your resilience muscle. • IBM expert Tamreem El Tohamy on bridging the skills gap in Africa In the next three years, as many as 120 million workers in the world’s 12 largest economies may need to be retrained or reskilled as a result of Artificial Intelligence (AI) and intelligent automation. cf. Lee Se-Dol. This is according to the latest IBM Institute for Business Value (IBV) study, titled The Enterprise Guide to Closing the Skills Gap. Seems like an interesting guide. This metric surprised me: In 2014, it took three days on average to close a capability gap through training in the enterprise. In 2018, it took 36 days. I didn’t know this measure existed, but I can see the utility. As knowledge work grows ever more specialized, this time-to-capability can only grow. • Innovation is a buzzword Notes, slides, and the Innovation Auditing guide presented at the talk are found below. # The research The research presented during the talk is discussed on the following pages: # Slides Find a PDF of the slides I presented at the link below. Beware: the animations don’t translate well to print, so some of the pages have graphical issues. # Innovation Auditing Innovation Auditing is a simple procedure that individuals, organizations, and governments can use to detect the gaps in the innovation process they seek to support. See the PDF guide by clicking the link below. • Innovation Education # Innovation Education What is innovation? How do we define innovation, its outputs and processes, and what are the skills and competencies necessary to practice and excel in innovation? Read the full paper. Many strategies and policies, both federal and provincial, have attempted to improve Canada’s innovation capacity in the last few decades. Universities and colleges are often discussed in these strategies for their role in facilitating new partnerships and in developing (potentially) actionable research. It is rare, however, for these strategies to recognize education plays in the creation of innovators. This is counterintuitive: education is an obvious mechanism with which to develop the knowledge and abilities of a population. Yet we lack a holistic understanding of what it takes to practice innovation, let alone the kinds of curricula that might provide those skills and competencies. Moreover, we are inconsistent in the definitions and language we use to define innovation—often obsessing over technology and commercialization. We tend to assume innovation comes from research and development processes, and that innovators are simply highly skilled people. Presented here is the result of an intensive review of reports, strategies, policy, and theory on innovation in the Canadian context. This literature was scanned and coded—inspired by the ethnographic methods of grounded field theory—in order to synthesize a holistic theory of innovation. This theory includes a universal definition of the innovation process, a recasting of different focuses of innovation as innovation orientations, a comprehensive model of the innovation process, and a synthesis of innovation skills and competencies into 13 learning domains, 47 learning constructs, and 227 learning outcomes. These tools provide utility for policymakers and educators in pursuit of understanding and improving innovation capacity. In particular, the model of innovation education is the most comprehensive of its kind, providing an extensive set of concepts with which to understand education gaps and build curricula. Perhaps the most important contribution of this research, however, is the recognition that our conversations about innovation strategies and education reform must be aligned. **How exactly do people learn to be innovative, and how are our education systems currently facilitating that process? **With this study we have begun to seek answers to these questions, but there is much more work to do. If you use these ideas and learn something from your experience, or if you have thoughts on how to improve them, don’t hesitate to make suggestions and to share your work. Find resources on this page that detail the definitions and models of innovation developed through this research and how these concepts may be applied in innovation education programming. # Explore the Model Across dozens of perspectives on innovation, a set of 13 domains of skills and competencies emerged. These domains have been interactively visualized using Kumu.io. You can play with the work yourself by clicking the button. Use the controls in the bottom corners to focus on specific components of the model, to surface the innovation process so that you can explore both simultaneously, and more. Note that the visualization is best explored on a desktop! # Learn more about the skills and competencies of innovation This document provides an executive summary of the insights and models on innovation education uncovered through this research and guides educators to put these concepts and tools to use. # Read the Research Education reform presents an opportunity to improve innovation education and, in turn, advance innovation capacity. I synthesize the framing and strategy of resources from provincial, national, international, and theoretical perspectives on innovation in order to develop a holistic model of innovation and a curricula for innovation education. Then, I use systemic design to model Newfoundland and Labrador’s current education system and to suggest strategies for reform to enable improvement in Newfoundland and Labrador’s innovation education. Finally, I explore how systemic reform in Newfoundland and Labrador may serve as a systems laboratory for reform efforts in other jurisdictions. Innovation Education is a major research project presented to OCAD University in partial fulfillment of the requirements for the degree of Master of Design in Strategic Foresight & Innovation. This work was supported by the Social Sciences and Humanities Research Council of Canada. • Innovation systemics # Innovation Systemics # Takeaways # Problem 1: Canada Struggles To Understand How It Can Fit The ‘Idea Economy’ Into The Broader Economic Context (I.e. Other Sectors). Thus, Canada should take steps to foster the idea economy. The world is changing, and Canada needs to understand how the tenets of the idea and knowledge economy will best flourish across the primary sectors that drive the broader Canadian economy. Building regional collectives (like the Waterloo-Kitchener corridor) to advance innovation is only one step, whereas our findings suggest the need to take a collective leap and author a White Paper that will activate a national approach on the new, ideas-based economy. In doing so, the Government of Canada will engage a collective of stakeholders, thought leaders and businesses both large and small to lead a national dialogue on how innovation ought to play out across Canada’s diverse communities, companies and campuses. # Problem 2: Canadians Do Not Recognize The Unique Strengths Of The Economy As It Is, And Neglect Recognition Of The Innovations Already Taking Place. Canada should change the narrative. Innovation is happening, but it is taking place in sectors and industries different than the ones we tend to pay attention to. Increasing awareness about the need for, and impact of, innovation within advanced manufacturing, natural resources and agriculture will help cross pollinate the economy with more robust, productive approaches and solutions. This will also help to shift the culture of entrepreneurship by empowering a generation of Canadians to create sustainable value and ensure they and their communities prosper. # Problem 3: Canada Currently Allocates A Disproportionate Amount Of Resources (Talent And Capital) To “Tech Solutionism”, At The Cost Of Others. Canada should redirect the pipeline. The ultimate step is to increase the carrying capacity of the system to generate value for entrepreneurs from outside the technology sector. Drawing sectors and industries together with the innovation ecosystem will build deeper and more diverse connections. Diverting the flow of resources—talent and capital—and binding it with existing infrastructure and institutional support will build a depth that will support a more robust Canadian economy. Furthermore, investing in improving the structures that nurture prosperity—incubators, accelerators, entrepreneurship, and innovation programs—and bringing them together with campuses and companies already making an impact, will propel Canada forward. # The Context “Innovation drives an economy’s ability to create more economic value from an hour of work, thereby increasing economic output per capita. The resulting productivity growth creates potential for rising wages and incomes, and thus for a higher standard of living.” (University of Lethbridge Research Services, 2015) A robust innovation ecosystem has the ability to improve productivity, economic growth, and job creation metrics in countries adequately supporting this process. In these countries, there also tend to be more resources available to support spending in education, health, and infrastructure, to name a few (“Innovation details and analysis”, 2013). Accordingly, the importance of a healthy innovation system is tied closely to that of a healthy national economy, along with its people, communities and institutions. In Canada, however, economic discourse around innovation and entrepreneurship has recently pointed towards a decline in productive returns from startup investment. Although an improvement from previous years, in 2015 Canada was ranked 9th out of 16 peer countries in innovation by the Conference Board of Canada, receiving a letter grade of “C” on its Innovation Report Card (“Innovation details and analysis”, 2013). This ranking points to a persistent weakness in the Canadian innovation system, commonly referred to as the “innovation gap”. This phenomenon is being reported by some of the country’s top journalists, startup CEOs, established investors, think-tanks, and members of various levels of government across the country. While these reports highlight culture, politics, economics, and education as the cause of this gap, and underlining the need for reform, policy changes, and new programs, few of these calls to action are gaining traction. There is no easy answer to this wicked problem. With the above in mind, we initially sought to answer the question “Why are investments in innovation resulting in diminishing returns in productivity?” through our research, but we quickly realized that in order to address this issue, we would first need develop a thorough understanding of the innovation ecosystem in Canada and thus we broadened our research questions to “How might we understand the Canadian innovation system?” all the while still focusing on this oft reported, elusive innovation gap. Innovation details and analysis. (2013). The Conference Board of Canada. Retrieved from http://www.conferenceboard.ca/hcp/details/innovation.aspx University of Lethbridge Research Services. (2015). Putting Innovation in Context. Lethbridge, Alberta, Canada: University of Lethbridge. Retrieved from http://www.agility-ulethbridge. ca/2015/09/11/putting-innovation-in-context/ # Research Synthesis Map This synthesis map summarizes our research on Canada’s systemic innovation challenges this past term. # Leverage Analysis We used centrality analysis to examine our map of the system for potential leverage points. The elements that surface from this analysis offer opportunities (or, in some cases, roadblocks) for policy and program interventions. # The Paper # The Researchers This work was completed by a team of Master of Design students in OCAD U’s Strategic Foresight & Innovation program. Michael Berman Robyn McCallum David Fascinato Ryan J. A. Murphy Obsidian 7 notes with this tag • When and how to publish notes: Publishing thinking effectively and efficiently • A Templater script for updating file titles and dates in YAML This Templater script gives the current Obsidian note a proper YAML title, date, and lastmod field. This facilitates integration with Quartz/Hugo. It requires MetaEdit (as well as Templater, obviously). Update file titles and dates with this Templater script   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60  <%* let file = tp.file.find_tfile(tp.file.title) const {update} = app.plugins.plugins["metaedit"].api const {getPropertyValue} = app.plugins.plugins["metaedit"].api const {position, ...rest} = tp.frontmatter; let content = tp.file.content; let newFileContent = content.split("\n"); let isYamlEmpty = Object.keys(tp.frontmatter).length === 0 && !content.match(/^-{3}\s*\n*\r*-{3}/); /* reset selection to the top of the document to make sure the action doesn't clear any text */ let editor = this.app.workspace.activeLeaf.view.editor; if (editor.getSelection === "") { // no text is selected } else { editor.setCursor(editor.getCursor()); } async function updateCurrentFile(someContent, someFile) { someContent = someContent.join("\n"); await app.vault.modify(someFile, someContent); } let propNameForLastModified = "lastmod"; let fileLastModifiedDate = "\"" + tp.file.last_modified_date("YYYY-MM-DD\THH:mm:ss") +"\""; if (isYamlEmpty) { // No YAML yet newFileContent.unshift("---"); newFileContent.unshift({propNameForLastModified}: ${fileLastModifiedDate}); newFileContent.unshift("---"); await updateCurrentFile(newFileContent, file); } else if (rest.lastmod === undefined) { // YAML exists but no date field newFileContent.splice(1,0, ${propNameForLastModified}: ${fileLastModifiedDate}); await updateCurrentFile(newFileContent, file); } else { // YAML exists and a date property exists await update(propNameForLastModified, fileLastModifiedDate, file); } /* Now we can assume YAML exists, so let's add the rest of the metadata */ let propNameForDate = "date"; let fileCreatedDate = "\"" + tp.file.creation_date("YYYY-MM-DD\THH:mm:ss") + "\""; if (rest.date === undefined) { // YAML exists but no date field newFileContent.splice(1,0, ${propNameForDate}: ${fileCreatedDate}); await updateCurrentFile(newFileContent, file); } else { // YAML exists and a date property exists await update(propNameForDate, fileCreatedDate, file); } let propNameForTitle = "title"; let fileTitle = "\"" + tp.file.title + "\""; if (rest.title === undefined) { // YAML exists but no title property exists newFileContent.splice(1,0, ${propNameForTitle}: {fileTitle}); await updateCurrentFile(newFileContent, file); } else { // YAML exists and a title property exists await update(propNameForTitle, fileTitle, file); } new Notice (tp.file.title + "'s title is now " + fileTitle + ". Last modified date metadata updated to " + fileLastModifiedDate + ".", 2000); _%>  • Automatically download Reminders into your Obsidian notes with Shortcuts Want a quick, hands-free, one-step method to capture reminders and tasks into Obsidian? Take advantage of Reminders, Shortcuts, and Shortcuts’s automations feature. This Shortcut will extract all reminders currently incomplete in a given list and append them to your daily note. Here’s a screenshot of the full Shortcut Download it and set it up (i.e., answer all of the configuration questions). Then, create Shortcuts automations (via the Automations tab in Shortcuts) that run on whatever triggers you want (e.g., “Whenever the Obsidian app is opened” and “9am”). Add a “Run Shortcut” action to that automation, then select the shortcut you’ve just configured. 🎉! Whenever the shortcut is triggered, the reminders in the designated list will be added to your daily note. You can now say e.g., “Hey Siri, add ‘Pick up milk’ to my Obsidian list,” and that item will (eventually) be added to your daily note. • Use Metadata Menu and Dataview to tag your notes from a selection of existing tags only • A Keyboard Maestro macro for quickly and easily opening published notes in Obsidian Similar to Notes/A Shortcut for quickly and easily opening published notes in Obsidian, this macro makes it easy to jump from viewing a published note on the web to editing it in Obsidian. Don’t forget to switch Mainframe to your vault’s name! I have it tied to a Stream Deck button, but you can configure it to trigger however you’d like. See a screenshot of the macro • A Shortcut for quickly and easily opening published notes in Obsidian If you publish your notes to the web in any way and you are on iOS/macOS, here’s a simple shortcut that lets you quickly and easily open a note from your website in Obsidian: See the shortcut in action • Publishing my notes Research 7 notes with this tag • ∎ Data Science and Prediction - Dhar - 2013 - Reading Session 202301271312 In situations where we are able to design randomized trials, big data makes it feasible to uncover the causal models generating the data. The author doesn’t make this point very big but it is actually quite important. There are many cases in which it is unethical to undertake a conventional scientific study of certain phenomena… Even though we know that those phenomena are happening anyway. If the data is collected “naturally,” however, we may be able to trace and track patterns in these data without putting ourselves in precarious ethical situations • When and how to publish notes: Publishing thinking effectively and efficiently Articles 6 notes with this tag • Design Management for Wicked Problems - talk at ADMC 2020 # Design management for wicked problems - ADMC 2020 Our toughest problems resist conventional strategies for change. In this talk from Peter Jones and I, we show how designerly approaches—namely methods from systemic design—can help create and implement systemic theories of change. Those theories may then be used to develop effective strategies for wicked problems. We presented this talk at the Academic Design Management Conference in 2020, and it led to a follow-up paper. • Your Notes are an Information System • Systemics and design principles in support of Tiago Forte's PARA framework • Student Acquisition, Engagement, and Retention: Analogies from tech startups a16z is a podcast from Andreesen Horowitz, one of the leading venture capital firms in the US. Their portfolio has included Airbnb, BuzzFeed, Facebook, Twitter, and many many other big companies—they know what they’re doing! Two recent episodes on the podcast feature Andreesen Horowitz general partners, Andrew Chen and Jeff Jordan (some of the people who make investment decisions). They are interviewed by host Sonal Chokshi about how to think about user (or customer) acquisition and user engagement and retention. (You should also be able to get these episodes using any given podcasting app, searching for a16z, and grabbing the two recent episodes titled The Basics of Growth.) I’ve listened to these episodes a couple of times since they came out a week ago. There’s a lot of terminology and concepts to parse—they explain it all well, but it took me a couple of tries to wrap my head around all of it. Given what I’ve come to learn so far, though, is that the two episodes seem like a (free!) one-oh-one masterclass in growing or scaling any given initiative. Despite being less than an hour long in total, the conversation goes way beyond “number of users”. Andrew, Jeff, and Sonal dive deep into the kind of patterns we should hope to see (and find ways to encourage) in order to garner genuine growth, engagement, and retention patterns. It is super sophisticated while still being kinda simple. That said, they’re talking about startups, customers, and technology-driven businesses. Applying those lessons to initiatives in public post-secondary—co-curricular leadership development programs, in my case—is not straightforward. So, that’s the challenge: how do we generalize their insights into the world of post-secondary student services? Here I explore that question with more questions. There’s probably no simple answer for these, but thinking about these concepts could deepen how we grow (and evaluate the growth of) post-secondary services. Question 1: Lifetime Value vs. Lifetime Impact? The first episode focuses on user acquisition. The analogy for us is when students first use our services, tools, or go to their first event or program. Jeff and Andrew describe organic growth—word of mouth-type acquisition—and inorganic growth (paid ads and other campaigns). They talk a lot about the tension between the “cost” of acquiring users and the lifetime value (LTV) of a given user. How should we think about these ideas in student services? “Student Acquisition Costs” have a direct parallel. Is there a useful analogy for LTV? (I.e., “Degree/Career Impact”?) The implication is that acquiring certain students might cost more, or at least demand different strategies, but have a greater impact. Question 2: Semesterly Active Users? The podcasters reference a variety of “active user” metrics: Daily Active Users (DAU), Monthly Active Users (MAU), last-seven (L7) and last-twenty eight (L28)… What is a useful and realistic “active user” metric for post-secondary student services? We don’t actually want our students to use all of our services daily. As the podcasters put it, there’s a certain ideal cadence to the way they should use our services. But what is that cadence, and how do we ensure we’re meeting it? Question 3: Network effects? Jeff, Andrew, and Sonal talk about the “network effect” in both episodes. This is the concept that a service becomes more valuable/powerful the more users it has. Is there an analogy to the services we’re already running, and are we taking advantage of it? Or, are we missing an opportunity to build in a network effect or similar positive acquisition, engagement, or retention feedback loops somehow? To be clear, I don’t think it’s a good idea to translate directly from the high-growth profit-driven startup world into post-secondary services work and life. The organizations have different motives and needs, incentives and costs, and—most important—different stakeholders, with different obligations to those stakeholders. Still, there may be powerful, creative opportunities hidden in the lessons we borrow from one another. • Keeping the buzz in buzzwords A thought-terminating cliché limits conversation by capturing a complex (but potentially debatable) subject within a reductive term or phrase. Merlin Mann references this idea in episode 164 of Back to Work when discussing curiosity and buzzwords. Thought-terminating clichés can be used to avoid discourse on a subject: by never unpacking the components of an idea that are debatable, those components go unexplored. They can also be exploited to veil ignorance or illogic—the speaker can state the complex term and allow the implication to have impact without contextualizing/explaining it while the intimidated audience shies away from critique or questioning. This explanation makes the phenomena seem villainous, but many of us are prone to committing these crimes—through buzzwords! Buzzwords are terms that catch on because they represent something exciting to a discourse. Then, because they’re popular, they get used frequently, by many people. Because they are somewhat novel, these different uses attach slightly different meanings to the same word. Eventually the buzzword’s overused (reducing the novelty, and therefore the impact of its meaning) and/or overloaded with meaning. Most of our buzzwords were real things at one point (and sometimes they still are). When buzzwords are used effectively they allow a good conversation to move faster between speakers who have the same mental models about the buzzwords.1 Sometimes, however, buzzwords are said to represent concepts that aren’t fully understood by everyone in the conversation. When my meaning of the word “design thinking” differs from yours, but we both refer to design thinking in conversation nonetheless, we can run into trouble. In these situations, buzzwords obfuscate the ideas we’re actually talking about. In my experience, we also know when we’re using buzzwords. We can guess at when others are using them, too. As a result, the conversation loses meaning, and we lose trust in the conversation. # Dealing with buzzwords So what can we do? Well, the easy thing to do is to clarify. When you use a phrase with many potential interpretations, try to clarify how you’re using the phrase. When others use words that may have multiple meanings, ask specific questions about what they actually mean. This clarification might seem like extra work, but it only needs to happen when terms are first invoked—and it’ll prevent lost time and energy due to the consequences of thought-termination later on. More importantly, though, we should try to avoid thought-terminating clichés altogether. Take time to break down the concepts you’re talking about in concrete terms. Explain them in ways you haven’t heard before to avoid relying on trite metaphors and anecdotes. If you can really get at what you mean, your language will be minimally re-interpretable: that is, it should be near-impossible to understand your explanations differently from how you intended. As a result, your communication will become more impactful. The conversations you participate in will have more novelty, too, making it more exciting to discuss the ideas you’re sharing. This may result in more buzzwords emerging, but that’s okay—use the same approach to break those down, too. • A brief, informal guide to doing grounded theory Education 6 notes with this tag • As Lambda students speak out the schools debt-swapping partnership disappears from the internet “The ISA is the business model, not education,” says Kim Crayton, a business strategist and founder of CauseAScene , an organization that’s seeking to disrupt the status quo in tech. “You cannot tell me that education is your business model when you have not registered as an institution.” For months, Crayton has been speaking about the problems with coding bootcamps on her podcast, where she’s argued that they target vulnerable communities. “You’re put in these spaces and putting in 110 percent and it’s still not working and you’re told to ‘trust the process,’” she says. Great reporting on this at The Verge. Kim Crayton makes an excellent point. The promise of many of these neo-credentials is for students to leapfrog the things everyone fears about the conventional education system. No one is more vulnerable to taking on loads of student debt than those who need it most. Those students are also going to suffer the most if their university or college fails to equip them for a career. Lambda solves both of these problems, making it extremely attractive to poor students. Sadly, there’s always a catch. • IBM expert Tamreem El Tohamy on bridging the skills gap in Africa In the next three years, as many as 120 million workers in the world’s 12 largest economies may need to be retrained or reskilled as a result of Artificial Intelligence (AI) and intelligent automation. cf. Lee Se-Dol. This is according to the latest IBM Institute for Business Value (IBV) study, titled The Enterprise Guide to Closing the Skills Gap. Seems like an interesting guide. This metric surprised me: In 2014, it took three days on average to close a capability gap through training in the enterprise. In 2018, it took 36 days. I didn’t know this measure existed, but I can see the utility. As knowledge work grows ever more specialized, this time-to-capability can only grow. • Resources # Resources Updated Nov 14, 2019 Below I’m collecting a set of resources dealing with a variety of topics for shareable reference—a sort of living, semi-public annotated bibliography. Many of these readings should be accessible via a library or a good Internet search, but if you find something here that shouldn’t be this easy to download, feel free to contact me and I’ll remove it. Or, if you come across any broken links, please let me know! # Getting Started with Systemic Innovation Kudoz’ Where Are You Scaling? Placemat (2017) KudozWhere Are You Scaling? “placemat” is an explorable tool to help think through what scaling really means in a given venture. It builds upon Riddell & Moore’s (2015) Scaling Out, Scaling Up, and Scaling Deep in expanding our notion of scaling. When you hear the word “scale” in a conventional conversation, the meaning is likely synonymous with scaling out: reaching more people (stakeholders or customers) with the product, service, program, or policy at the heart of the conversation. Yet there are other underappreciated aspects of scaling: some are required in order to successfully scale out, while others are different ways of achieving impact—maybe scaling out isn’t the best route to take after all! Scaling up, for instance, refers to reaching higher in power hierarchies in order to implement higher-level solutions to the problem you’re addressing. Scaling deep means to reach the same people you’re already reaching more deeply, or with greater impact. Kudoz introduces two more concepts: scaling infrastructure, or building out more tools and supports to make the work more effective and sustainable; and scaling scree, or lending support and legitimacy to other, different actors and initiatives addressing the same issues you are. Mulgan & Leadbeater’s Systemic Innovation (2013) While the above concepts help make concrete the different ways an intervention might change a system, Mulgan and Leadbeater’s (2013) discussion paper on systemic innovation dives a bit deeper into theory. They link the practice of systems thinking to approaches to innovation, providing a framework for “joining up” a set of innovations in order to achieve systemic change. # Getting Started with Social Innovation Mulgan’s Social Innovation: What It Is, Why It Matters, And How It Can Be Accelerated (2007) Geoff Mulgan offers a comprehensive yet down-to-Earth guide to social innovation. The reading really helps communicate what the differences are between social innovation and conventional innovation with practical examples. Phills Et Al.‘S Rediscovering Social Innovation (2008) The Stanford Social Innovation Review has been one of the preeminent publishers on social innovation since its inception in the early 2000’s. In this review Phills et al. summarize a brief history on social innovation itself while paving a way forward in research and practice. # Getting Started with Design What is “design”, really? It’s easy to think that design is the layout of graphics or illustrations—perhaps even making decisions about layouts, as in architecture. These disciplines—graphic design and architecture—certainly leverage design, and many people employed in these industries are designers. Yet these disciplines do not fully capture what design is, thus we should not limit the understanding and application of design to these industries. The term design shares latin roots with designation. To design is therefore to mark; to frame. Framing means to view a given problem or system from different perspectives in order to deeply understand it and, in turn, to develop novel ways of doing something about it or with it. To become a better designer, you must get better at both analyzing and creating frames. # Getting Started with Systems Thinking Systems thinking is most useful when applied to complex, chronic issues: “wicked problems” that resist taming through conventional approaches. David Stroh, who wrote Systems Thinking for Social Change, argues that effective systems initiatives begin with a focusing question: a question that bounds the project (so that you don’t spend forever debating about where the problem system really ends) and anchors your systems-understanding work in a framing that you can return to if you get lost. This is a question of the form “Why, despite our best efforts and intentions, does [x] persist?” or “…have we not reached our goal of [y]?”—where [x] and [y] are phenomena that remain unassailable through conventional initiatives. Goodman, Kemeny & Roberts’ The Language Of Systems Thinking (2000) The Language of Systems Thinking introduces the reader to reinforcing and balancing loops using simple examples. Braun’s The Systems Archetypes (2002) Systems archetypes extend the links and loops of basic systems thinking into more complicated structures – and in doing so, begin to share with the reader deeper insights into the counterintuitive behaviour of the systems we work with. Donella Meadows’ Leverage Points: Places To Intervene In A System (1997) With robust systemic models, we can begin to identify leverage points: key phenomena that have great potential for change throughout the system. # Getting Started with Futures Thinking Jim Dator’s What Futures Studies Is, And Is Not (1995) What Futures Studies Is, and Is Not is a wonderful introductory and reader-friendly summary of futures thinking. Choo’s The Art Of Scanning The Environment (1999) Chun Wei Choo’s The Art of Scanning the Environment offers a walkthrough of scanning practices. Bishop, Hines & Collins’ The Current State Of Scenario Development (2007) The Current State of Scenario Development provides a comprehensive review of scenario development approaches and techniques. # Deeper Reading: Organizational Change Dubberly Et Al.‘S Notes On The Role Of Leadership & Language In Regenerating Organizations (2002) Hugh Dubberly and a suite of colleagues provide an elegant—poetic, even—walkthrough of how change happens to organizations through their language. They reframe an organization as a continuous set of conversations between people, in turn showing the power of changing the language those people use in order to change the nature of the organization itself. Weick & Westley’s Organizational Learning: Affirming An Oxymoron (1999) Karl Weick and Frances Westley attack the very idea of organizational learning by showing how “organizing” and “learning” are, in fact, opposing processes. To organize is to order; to learn is to disrupt. Success in organizational change is therefore rooted in a leader’s ability to handle the tension between organizing and learning. Too much organizing and the organization will miss opportunity in change—but too much learning and the organization might not be stable enough to survive. Gawde’s Learning From Systems Thinking (2017) How can systems thinking help with changemaking in an organization? Writing for People Matters, Sanjay Gawde provides a succinct argument and explanation linking systems approaches to organizational change. • Innovation is a buzzword Notes, slides, and the Innovation Auditing guide presented at the talk are found below. # The research The research presented during the talk is discussed on the following pages: # Slides Find a PDF of the slides I presented at the link below. Beware: the animations don’t translate well to print, so some of the pages have graphical issues. # Innovation Auditing Innovation Auditing is a simple procedure that individuals, organizations, and governments can use to detect the gaps in the innovation process they seek to support. See the PDF guide by clicking the link below. • Innovation Education # Innovation Education What is innovation? How do we define innovation, its outputs and processes, and what are the skills and competencies necessary to practice and excel in innovation? Read the full paper. Many strategies and policies, both federal and provincial, have attempted to improve Canada’s innovation capacity in the last few decades. Universities and colleges are often discussed in these strategies for their role in facilitating new partnerships and in developing (potentially) actionable research. It is rare, however, for these strategies to recognize education plays in the creation of innovators. This is counterintuitive: education is an obvious mechanism with which to develop the knowledge and abilities of a population. Yet we lack a holistic understanding of what it takes to practice innovation, let alone the kinds of curricula that might provide those skills and competencies. Moreover, we are inconsistent in the definitions and language we use to define innovation—often obsessing over technology and commercialization. We tend to assume innovation comes from research and development processes, and that innovators are simply highly skilled people. Presented here is the result of an intensive review of reports, strategies, policy, and theory on innovation in the Canadian context. This literature was scanned and coded—inspired by the ethnographic methods of grounded field theory—in order to synthesize a holistic theory of innovation. This theory includes a universal definition of the innovation process, a recasting of different focuses of innovation as innovation orientations, a comprehensive model of the innovation process, and a synthesis of innovation skills and competencies into 13 learning domains, 47 learning constructs, and 227 learning outcomes. These tools provide utility for policymakers and educators in pursuit of understanding and improving innovation capacity. In particular, the model of innovation education is the most comprehensive of its kind, providing an extensive set of concepts with which to understand education gaps and build curricula. Perhaps the most important contribution of this research, however, is the recognition that our conversations about innovation strategies and education reform must be aligned. **How exactly do people learn to be innovative, and how are our education systems currently facilitating that process? **With this study we have begun to seek answers to these questions, but there is much more work to do. If you use these ideas and learn something from your experience, or if you have thoughts on how to improve them, don’t hesitate to make suggestions and to share your work. Find resources on this page that detail the definitions and models of innovation developed through this research and how these concepts may be applied in innovation education programming. # Explore the Model Across dozens of perspectives on innovation, a set of 13 domains of skills and competencies emerged. These domains have been interactively visualized using Kumu.io. You can play with the work yourself by clicking the button. Use the controls in the bottom corners to focus on specific components of the model, to surface the innovation process so that you can explore both simultaneously, and more. Note that the visualization is best explored on a desktop! # Learn more about the skills and competencies of innovation This document provides an executive summary of the insights and models on innovation education uncovered through this research and guides educators to put these concepts and tools to use. # Read the Research Education reform presents an opportunity to improve innovation education and, in turn, advance innovation capacity. I synthesize the framing and strategy of resources from provincial, national, international, and theoretical perspectives on innovation in order to develop a holistic model of innovation and a curricula for innovation education. Then, I use systemic design to model Newfoundland and Labrador’s current education system and to suggest strategies for reform to enable improvement in Newfoundland and Labrador’s innovation education. Finally, I explore how systemic reform in Newfoundland and Labrador may serve as a systems laboratory for reform efforts in other jurisdictions. Innovation Education is a major research project presented to OCAD University in partial fulfillment of the requirements for the degree of Master of Design in Strategic Foresight & Innovation. This work was supported by the Social Sciences and Humanities Research Council of Canada. • Education Systemics # Education Systemics What are the mechanisms of education systems change? How might we use systemic design to power a reform movement? What does systems thinking teach us about opportunities and barriers for education reform in Newfoundland and Labrador? Education reform is not a new idea. Many organizations and initiatives have reimagined the schools, universities, and colleges that are the backbone of our economy and society—yet, to many, it seems like little has changed in recent decades. As Jal Mehta, Robert Schwartz, and Frederick Hess began their book on the subject, “if we keep doing what we’re doing, we’re never going to get there.” Traditional education reform approaches have depended on a best practices approach in what is glibly called a “silver bullet culture”. A single idea, found successful in a specific institution or district, becomes hailed as the be-all-end-all solution. This solution is then celebrated and championed across contexts until actors realize that expected results have not materialized, and reformers move on to the next silver bullet solution. This approach to education reform has not worked. According to Mehta, Schwartz, and Hess: “If we are to deliver transformative improvement, it is not enough to wedge new practices into familiar schools and districts; we must reimagine the system itself”. In other words, education systems change has been found to be more than difficult. It is a wicked problem: ill-defined, constantly fluxing, with many conflicting stakeholders and no true solutions. How can we provoke change in wicked problems? I argue that reforming education is a sociotechnical problem, involving human psychology; social, political, and economic factors; and complex interactivity–what Don Norman and Pieter Stappers have called a “DesignX” problem. These authors suggested that DesignX problems can only be solved through a process of muddling through, developing incremental sub-solutions through deep analysis. This deep analysis means partitioning the problem into modules and recognizing the intersecting dimensions of the problem. Peter Jones provides further advice for this kind of problem solving, defining an approach called systemic design. Systemic design integrates systems thinking and systemic methods–ways of understanding complex problems through the relationships of the phenomena and actors involved–with design thinking and design methods, applying human-centred design to these seemingly intractable, large-scale problems. With systemic design, Peter says, we use “known design [tools]—form and process reasoning, social and generative research methods, and sketching and visualization practices—to describe, map, propose, and reconfigure complex services and systems”. # Approach & Findings With this in mind, I turned to several types of modelling in order to use systemic design on the complex problem of education reform: process modelling, actor mapping, and causal loop mapping. In this modelling, I focused on Newfoundland and Labrador—my home province—and the education of innovation, examining how our system currently provides innovation learning and how we might do better. Finally, I applied centrality analysis – a quantitative approach to assessing leverage points and bottlenecks in networks and systems maps—in order to surface potential opportunities and challenges in the system. I examined four types of centrality analytics: • Reach efficiency takes an element’s reach (the proportion of the network within two steps of that element) and divides it by the number of neighbouring elements it has. Elements that score the most on this metric tend to be less connected but have high exposure to the rest of the system, making them low-hanging fruit for change efforts. • Betweenness assesses the number of times an element lies on the shortest path between two other elements. Elements high on the betweenness metric are bridges throughout the map, controlling the flow of phenomena throughout the system. This means that these elements may be bottlenecks or single points of failure. • Eigenvector centrality measures an element’s connectedness to other well-connected elements, computing an overall value that is an indicator of the element’s influence over the whole system. • Torque calculates each element’s reach efficiency weighted by its eigenvector centrality (e.g., how influential that element is). Elements with high torque should be relatively easy to impact (as they are not densely influenced by other phenomena in the map), but will impact the rest of the map substantially. These are key leverage points of change. The detailed methods and findings from each of these approaches are discussed in turn in the links below. # Process Modelling, Actor Mapping, And Causal Loop Mapping # Conclusions I aimed to see the education system for what it is in order to describe strategies for the transformative reform that Mehta, Schwartz, and Hess called for. The education system is therefore composed of a number of interrelated components, organized in a hierarchy, whose emergent phenomena lead to its own dynamics. Yet, many might say that this systemic chaos implies a system of constant change, while education is hallmarked for its derelict stagnancy in the 21st century. How is it that such a system has not evolved? Well, perhaps the system is not actually that broken. As eloquently argued by Ryan Burwell, an instructional designer at the MaRS Discovery District: The school system is not broken. It is perfectly aligned to provide equitable access to a canon of high-quality, standardized content with greater rigour and organization than any other knowledge delivery system we currently have. However, it is not designed to foster the problem-solvers, innovators and entrepreneurs that are becoming an increasingly significant part of the global economy. Incorrectly identifying this misalignment as a broken system has created a culture of fear and failure around education, leading to top-down reforms and increased numbers of mandatory programs. I return to Mehta, Schwartz, and Hess’ depiction of school reform’s silver bullet culture. Many stakeholders with competing interests and different priorities are invested in every debate on education systems change. Thus, there are many potential silver bullets–and many advocates for them. The misunderstanding of the problem described by Burwell and the complexities of education reform described by Mehta, Schwartz, and Hess perfectly capture the need for a systemic design-based approach to change. # Process Mapping From process modelling, it is clear that while NL’s education system currently offers some opportunities to learn certain constructs of innovation, the availability of these opportunities is not densely packed throughout their study. It is easy to recognize a dearth of access to the domains of Foresight and Scanning, Vision and Purpose, and Adaptability and Resilience. Further, the degree to students learn the domains and constructs of innovation skills from the public system remains unclear. Ultimately, now that these models exist, further analysis will be able to examine these constructs more closely as students progress through the system. This is especially true for many of the “optional” components of the broader education system. After school programs, hobbies, sports and recreation, volunteer and extra-curricular roles, self-directed learning, and employer training could each be vital sources of innovation education, but it was impossible to study these aspects of the system in any meaningful way in the present study. A dedicated effort should examine the availability of these sources and assess their utility for innovation learning. One research approach would be to survey learners along the learning journey, testing their abilities in the different constructs I’ve outlined. This ethnographic approach could reveal hidden truths: perhaps, for instance, certain regional cultures in the province actually provide powerful learning in design through a community culture alone. # Actor Mapping Systemic modelling reveals the power and wealth subsystems active amongst the actors of the education system. Centrality analysis of the power subsystem illustrates that parents and the provincial government have efficient influence on the system, and change that can mobilize those bodies of actors will quickly take shape. Meanwhile schools, the School Board, and educators have substantial global influence over the system–change efforts that engage these actors may be slow but momentous. Finally, power bottlenecks are educators; schools and school councils; and the Department of Education and Early Childhood Development. This suggests that these actors will ultimately need to be involved if any reform effort were to achieve success. Reach efficiency analysis of the wealth subsystem shows that the federal government, parents and students, and the provincial Department of Advanced Education and Skills each strongly influence the distribution of wealth. The Federal and Provincial Governments have powerful incentives with which to motivate and control reform efforts. Betweenness centrality revealed that the whole system is tightly linked, making it potentially volatile: economic issues in one component of the system may ripple out and impact the others. # Causal Loop Mapping Finally, these maps intimated a causal loop diagram illustrating how innovation education reform might happen in the public education system. Several loops and one archetype demonstrate significant effect over the system. The Low Definition loop describes an acceleration of the impact of ill-defined innovation on our ability to educate on it. The We Teach What We Know loop shows how a lack of innovation education leads to a lack of people capable of teaching it and vice-versa. The New Economy loop shows how economic shocks driven by drops in commodities pricing has raised our awareness of the importance of the innovation economy. The Innovation-driven Growth loop shows how innovation capacity will accelerate jobs in the knowledge economy, which will in turn drive our ability to create more innovators through education. The Limited Resources loop balances our ability to reform education for innovation due to a lack of funding for the reform effort due to austerity budgets, driven by drops in the price of oil. Finally, the R&D, Not Innovation archetype is an instance of the Fixes that Fail systems archetype, showing how a conflation of innovation with R&D efforts fails to improve our innovation capacity while also distracting from true innovation education. The result of centrality analysis on these causally-linked phenomena is rich with pragmatic insight. Three phenomena with efficient reach over the whole system are innovation learning from outside of the public education system, lack of emphasis on innovation education, and low price of oil. The former points to an accessible lever of change: introduce innovation education through extra- and co-curricular programs, volunteer and leadership roles, sports and recreation, or self-directed learning, and the system may catch up by offering its own programming to match. The leverage of a lack of emphasis on innovation education offers another route: increase awareness on innovation education in order to encourage the system to improve on it. Finally, low price of oil retains leverage as a dampener on the system: if the economy continues in recession, the system is less able to offer resources for reform efforts. Other calls for reform is one force with substantial torque over the system, indicating that reformers must be co-opetitive with other education change efforts, else all reform efforts might fail due to competition with one another. The availability of accessible and practical models for innovation education is another high-torque element, however, elevating the potential of the present research to create change in the system. A third element with high torque is the generational shift in work, evidence that a substantial source of impetus for innovation education reform could come from changes in work and careers. Finally, betweenness centrality offers a picture of the bottlenecks and points of failure within the system. Innovation capacity and innovation education are two forces semiotically central to the system, and thus it is intuitive that they will be slow to change, no matter what else is happening within the system. On the other hand, recognition of innovation deficiency, the perceived innovation gap, and the search for solutions to the innovation gap are three phenomena that are clear points of fragility in any systemic change effort. If the system does not recognize its deficiencies, perceive the gap in innovation capacity, or opt to search for solutions, reform efforts are liable to be frustrated. # Limitations Despite these clarion recommendations for systemic design, several limitations prevent wholesale adoption. One key limitation of the presented results of systems modelling is that the connections defined in these models are unquantified. In the refined actor map, for instance, it may be that educators have little power over their school councils, or perhaps the NL Federation of School Councils has far less lobbying capacity than the NL Federation of Teachers. Evaluating the strength of these connections and including these evaluations in our analytics would improve the acuity of those metrics substantially. As previously mentioned, if innovation learning is not coming from the public education system, it must be coming from somewhere else. Yet, these potential sources arguably include the whole of the human experience—as we have, after all, been learning to innovate since pre-history. Future research might take on an ethnographic approach to understanding the system, investigating different student-innovators and where they learned their innovation skills, or a longitudinal approach, following students as they become innovators through their years in the education system. These exercises fell outside the limits of the present research, unfortunately. Another limitation is that, while the scope and approach to mapping were designed to increase the variety of the system as much as possible, the mapping was still completed with the perspective of only this author. The representativeness of the systems models would therefore be strengthened considerably with Delphi-inspired methods as seen in previous research, bringing the mapping process to others in order to iteratively refine and the map from alternative stakeholders’ points-of-view. Another potential future study is to “bring the whole system into the room”. This would mean convening a group of stakeholders who were holistically representative of the actors of the system, engaging them in a systems modelling process to develop a map with their collective perspectives. # ACTIONS AND TAKEAWAYS # In The Short Term A few immediate actions stem from this research. # 1. Adopt A Model First, we must adopt a model of innovation skills and competencies. Regardless of whether the adopted model is the one developed through this project or another alternative, it is imperative that we begin to recognize the skills and competencies used by successful innovators. By identifying these skills, we will be capable of examining our weaknesses and, in turn, developing ways of resolving those weaknesses. To spur this discussion, I plan on sharing the models developed here widely. # 2. Consider The Role Of Education In The Creation Of Canadian Innovators Second and in tandem, we must include the role of the education system in nurturing innovators in our provincial and national innovation strategies. Many approaches to innovation policy discuss the post-secondary education system with respect to its role in public-private partnerships and the commercialization of research. We must expand this role to include the development of innovation skills and competencies as well. In the near future I hope to meet with policymakers involved in the development of Newfoundland and Labrador’s innovation strategies to advocate for this approach there. # 3. Unite Education Reform Movements Education reform movements must be united in their calls for change. A host of movements relate to the notion of innovation education, from code.org (a non-profit urging computer science and programming education in K-12) to the 21st century learning movement (a pedagogical framework for the skills and knowledge necessary for the 21st century; cf. http://www.p21.org). The present research shows that these reform efforts may conflict, however, if they are brought forward asynchronously by their champions. It is therefore crucial that these efforts learn to “co-opete” (as in “co-opetition”) and engage educators and policymakers with aligned advocacy. I hope to work with the education systems change movements I already have relationships with in the immediate future in order to begin this dialogue. # In The Long Term As explored by David Stroh in Systems Thinking for Social Change, systems change is only possible when the actors of the system collectively recognize the tension between where the system is and where they want it to be. That realization isn’t possible, however, before the actors have even talked to one another—let alone come to consensus about a shared vision for the future. We realize that Canada’s future prosperity is predicated on our ability to leverage the boons of our resource economy and evolve it into an “innovation rich” leader in the knowledge economy. Yet, as discussed at the beginning of this paper, the danger is that education’s role in this transformation has yet to be recognized in full. We are not talking about how to create innovators, let alone what strategies we should employ in doing so, or how the system is stuck in becoming better at innovation education. Worse, there are many simultaneously conversations happening in both education reform and innovation—conversations that compete with one another, threatening the potential of the whole. This research offers a model of the education system in Newfoundland and Labrador. Yet these models are untested, and as I have noted, the research is sorely lacking a futures perspective that observes both threats and strategic opportunities in our changing environment. **How might we spark a collective, integrative discourse on innovation and innovation education? **Then, how might we elevate its importance such that collective action is taken—before we’ve missed the opportunities of the knowledge economy? How might we refine the systemic models, and how might we augment this work with a futures perspective, using environmental scanning to develop and integrate changing trends for strategic leverage? These questions point toward a need for a powerful, strategic theory of change, and the willingness to muddle through. In other words, **this change will not come about through the efforts of ad hoc standalone initiatives like this one. ** We need a sustained effort. We need a lab that brings together design science and systemic design, creating and testing designs of the system itself, making sure they are valid constructs of the concepts they are intended to represent, all while obeying the principles of systemic design. This is not a new idea. Many have articulated the notion of social labs, design or change labs, or social innovation labs. In fact, the OECD’s Centre for Educational Research and Innovation seems to operate such an approach for systemic innovation in global education. I argue that Canada–or at least, Newfoundland and Labrador–needs to take a lab-based approach to navigating complex education reform in education. This lab must unite the perspectives, strategies, and actors currently engaged in similar pursuits; build, maintain, and refine models of the systemic change taking place; be engaged in environmental scanning and strategic foresight to monitor for both threats and opportunities; and prototype change initiatives, taking lessons back to these models and strategies. Only a dedicated, intelligent effort will help us build the education systems that will develop the skills and knowledge we need to answer the 21st century. Innovation Education is a major research project presented to OCAD University in partial fulfillment of the requirements for the degree of Master of Design in Strategic Foresight & Innovation. This work was supported by the Social Sciences and Humanities Research Council of Canada. Productivity 6 notes with this tag • Your Notes are an Information System • Systemics and design principles in support of Tiago Forte's PARA framework • Paul Jarvis on Hurry Slowly: Small is Beautiful The ever-refreshing Paul Jarvis shares some uncommon thoughts on productivity in Jocelyn K. Glei’s Hurry Slowly podcast. In particular, Paul and Jocelyn discuss the importance of resilience. Citing research and his own experience, Paul points out that resilience is a more important factor in success than many others. Obviously, though, enabling resilience is not as easy as simply pointing out how important it is. As they discuss, resilience isn’t something innate—which means that it can only be developed through experience. And this is where things get tricky: who gets to have resilience-building experiences? In my research on innovation skills, I discovered that resilience was one of three key domains that wasn’t an important outcome for our public education systems. This means that resilience training isn’t necessarily a public good. Only if you’re lucky (or privileged) will you have the chance to build up your resilience muscle. • Adam Savage on Lists, More Lists, and the Power of Checkboxes # Adam Savage on Lists, More Lists, and the Power of Checkboxes In this Wired article, Adam Savage provides a pragmatic description of how he breaks down complex projects using lists. In my mind, a list is how I describe and understand the mass of a project, its overall size and the weight that it displaces in the world, but the checkbox can also describe the project’s momentum. And momentum is key to finishing anything. Momentum isn’t just physical, though. It’s mental, and for me it’s also emotional. I gain so much energy from staring at a bunch of colored-in checkboxes on the left side of a list, that I’ve been known to add things I’ve already done to a list, just to have more checkboxes that are dark than are empty. That sense of forward progress keeps me enthusiastically plugging away at rudimentary, monotonous tasks as well as huge projects that seem like they might never end. I love the physics metaphor here. There’s lots of other insights to be gained by thinking about how work follows physical principles. For instance, projects also have inertia, friction, and surface area: 1. Inertia. The longer a project sits waiting for you—weighing on your mind—the harder it is to get it moving. 2. Friction. Inertia is driven by initial friction. In parallel, of course, kinetic friction can make it hard to stop working on something. This is why multitasking doesn’t make sense with most projects. 3. Surface area: It can be hard to attack a single, huge project idea, just like how a large ice cube melts slower than many little ones. List making is a key way of breaking up the surface of a project into smaller pieces, making it easier to handle. Increasing surface area also facilitates collaboration: it’s easier to hand off smaller pieces to others, and to put them back together again. To return to momentum, though, Adam makes an excellent point: breaking down the work helps keep momentum going even when you put the work down. That may be the greatest attribute of checkboxes and list making, in fact, because there are going to be easy projects and hard projects. With every project, there are going to be easy days and hard days. Every day, there are going to be problems that seem to solve themselves and problems that kick your ass down the stairs and take your lunch money. Progressing as a maker means always pushing yourself through those momentum-killers. A well-made list can be the wedge you need to get the ball rolling, and checkboxes are the footholds that give you the traction you need to keep pushing that ball, and to build momentum toward the finish. Another point in the article that’s worth emphasizing: [I]n a project with any amount of complexity, the early stages won’t look at all like the later stages, and [the manager] wanted to take the pressure off any members of the group who may have thought that quality was the goal in the early stages. I’ve heard this discussed in the context of critique, or “10% feedback”. When sharing work with others, it’s important to disclose the stage the work is at. Typos should be caught at a project that’s basically ready to publish. They shouldn’t even be discussed when a work is being conceptualized. The focus on early stages should be the concepts themselves, and how they fit within the broader context. Last thing. This is excellent: There is a famous Haitian proverb about overcoming obstacles: Beyond mountains, more mountains. 🏔 • Procrastination Station # Procrastination Station Procrastination is itself a systems trap. That balancing loop sucks you in. You take on sneaky little actions as dopaminergic relief to the burden you’re escaping from, while the burden only grows heavier. (A form of Fixes that Fail.) • New year, new you Could New Year’s resolutions be doomed to fail? Driven by New Year’s culture, we commit to actions, call them resolutions, and set off to become better people. This phenomena of setting New Year’s resolutions is reinforcing (R1). Yet, as we get further away from the culture of resolutions, our commitment – linked at heart to New Year’s culture – fades. This, coupled with how slow progress can be, leads to the gradual extinction of our promise to ourselves. (B1) Perhaps, then, resolutions made outside of and separate from the cultural phenomena are more likely to result in real changes, as their founding is based in intrinsic motivation as opposed to the extrinsic incentives of New Year’s culture. (The time since New Year’s sets a limit to growth on the new habit.) Automation 5 notes with this tag • Automatically download Reminders into your Obsidian notes with Shortcuts Want a quick, hands-free, one-step method to capture reminders and tasks into Obsidian? Take advantage of Reminders, Shortcuts, and Shortcuts’s automations feature. This Shortcut will extract all reminders currently incomplete in a given list and append them to your daily note. Here’s a screenshot of the full Shortcut Download it and set it up (i.e., answer all of the configuration questions). Then, create Shortcuts automations (via the Automations tab in Shortcuts) that run on whatever triggers you want (e.g., “Whenever the Obsidian app is opened” and “9am”). Add a “Run Shortcut” action to that automation, then select the shortcut you’ve just configured. 🎉! Whenever the shortcut is triggered, the reminders in the designated list will be added to your daily note. You can now say e.g., “Hey Siri, add ‘Pick up milk’ to my Obsidian list,” and that item will (eventually) be added to your daily note. • Use Metadata Menu and Dataview to tag your notes from a selection of existing tags only • A Keyboard Maestro macro for quickly and easily opening published notes in Obsidian Similar to Notes/A Shortcut for quickly and easily opening published notes in Obsidian, this macro makes it easy to jump from viewing a published note on the web to editing it in Obsidian. Don’t forget to switch Mainframe to your vault’s name! I have it tied to a Stream Deck button, but you can configure it to trigger however you’d like. See a screenshot of the macro • A Shortcut for quickly and easily opening published notes in Obsidian If you publish your notes to the web in any way and you are on iOS/macOS, here’s a simple shortcut that lets you quickly and easily open a note from your website in Obsidian: See the shortcut in action • Publishing my notes Podcasts 5 notes with this tag • Intuition is confident abduction # Intuition is confident abductive-inferential thinking In a recent episode of Hello Monday, Jessi Hempel interviews Dr. Natalie Nixon on creativity and her new book, The Creativity Leap. Natalie’s PhD in Design Management—plus her work in fashion, design, and business—led her to a catchy and compelling description of creative work. We accomplish creative work, she says, “by toggling between wonder and rigour.” In the podcast conversation, Jessi and Natalie talk about intuition—and I was struck by something. “We don’t talk about intuition,” Natalie notes at about 6 minutes in. “We don’t talk about intuition in business school, in law school, or in medical school.” And yet, she says, “I observed that really successful leaders—especially really successful startup leaders—in their origin stories, there’s always this moment where ‘Something told me not to do the deal. Something told me to work with her over him.’ […] Every successful leader really reckons with incorporating acting on their intuition to make decisions.” Jessi agrees, noting that intuition comes up often in her interviews with leaders on Hello Monday as leaders cite it as the reason for their success. The thing is, just because we don’t name intuition doesn’t mean we aren’t talking about it. That’s because intuition is really just confident, logical thinking. Charles Sanders Peirce was a philosopher. He investigated how we inquire into and discover new knowledge.1 Before Peirce, we generally recognized the logical processes of deduction and induction. Deductive thinking helps us identify what must be true about a situation in order to explain it. When we deduce something, we look at the general rules and principles we know of and draw specific conclusions from that evidence. Inductive thinking involves drawing general conclusions from specific, limited evidence. Peirce argued that effective reasoning follows a pattern: we determine the specific consequences of an idea (deduction), and then we judge whether the available evidence fits that idea and its consequences (induction). But how do we develop ideas?2 Abduction is the name of the logical process Peirce described for developing ideas. To think abductively means to generate and choose ideas that fit the situation at hand. A good idea should be verifiable—we should be able to use evidence to judge its fit—and should help us resolve the situation at hand. Peirce also had criteria to help choose the best ideas to test. He suggested that we should strive to conserve resources (e.g., those that most are most efficiently verifiable and usable in the situation), identify the most valuable ideas (specifically the “uberty” of an idea, or how likely it is that a possible idea might bring about an innovation), and the most relevant ideas (e.g., those that may apply beyond our current focus, too).3 Abduction is clearly an important step in any innovative process—but it is no more important than testing and using the ideas you generate. What, then, if you don’t have enough evidence to truly test and prove your ideas? The process Peirce described—abduction, deduction, induction—is the ideal. However, we do not always have time and energy to follow the process diligently. Instead, we quickly make creative judgements based on a few observed qualities. This requires two related processes.4 The first Peirce called “abductory induction,” and it combines the first and last step of the inquiry process. We observe the qualities of the situation, and we generate possible ideas to resolve it based on those observations. The second process is known as “inference to the best explanation” (IBE).5 IBE is exactly what it sounds like. Given a number of possible ways of resolving a problem, choose the best one. (Peirce’s criteria, noted above, apply here.) So what does all this have to do with intuition? Intuition is the confident application of these shorthand logical approaches to creative problem solving. As Jessi and Natalie noted, we aren’t often explicitly taught about strengthening our intuition. Yet, everything we learn supports its development. The more we have to draw on in order to pull into the processes described above, the better our intuitive decisions will be. I say that intuition is the confident application of these processes because they only work when we follow through. In reality, we use abductory induction and IBE all the time. When we engage in creative problem solving, we’re not only using information from the evidence in front of us. We’re drawing on our lived experience and our knowledge base. Even if we don’t directly recall or reference that background information, it is drawn into the creativity of abduction and it defines the general rules and principles we use in deduction. It provides us with the heuristics we use when engaging in IBE. But if we don’t have a bias towards action and instead operate with e.g., perfectionism, we fail to actually execute on these ideas. Thus, we need to have confidence in our abductory induction and IBE processes. All this is simply a gentle challenge of the idea that we don’t talk about intuition. I think that all knowledge management practices and forms of education are actually fundamentally about strengthening our intuition. That said, Natalie’s work is fascinating. I recommend the episode of Hello Monday and plan on picking up her book! 1. In this article, my reading of Peirce comes from the writing of William Mcauliffe↩︎ 2. Peirce was actually specifically concerned with science and hypotheses generation, selection, and testing. Here I refer to generating, selecting, testing, and using ideas to apply these concepts to problem-solving more broadly. ↩︎ 3. He also cautioned not to produce ideas that stop the inquiry process—e.g., magical thinking, or by suggesting that whatever happened must be a complete mystery. ↩︎ 4. Actually, the difference between these two processes is the subject of substantive, controversial debate. This is in part because the scholars who study inference to the best explanation have also used Peirce’s term “abduction” to describe it. This understandably caused extensive confusion, but also probably a lot of philosophical debates and scholarship, so maybe it was for the best. ↩︎ • Roger Martin, Bianca Andreescu, and systemic strategy According to designer/strategist Roger Martin, a strategy is an imagined possibility with which we ask the question “What has to be true for this possibility to become real?” In this episode IDEO U’s Creative Confidence podcast, Roger talks about how that approach helped unlock Bianca Andreescu’s success at the Grand Slam singles championship in 2019. One of the fascinating things about this approach is that it acknowledges the need for system-wide changes. By asking “What has to be true?”, a strategist must consider all of the conditions of a system that should shift to make the imagined possibility a reality. Of course, most approaches to strategy do require some appreciation of the state of the strategic environment (e.g., the five forces model). None, however, emphasize the need to guarantee these systemic conditions quite as explicitly as asking “What must be true?” • Bring It On Haters With Special Guest Ben Thompson Ben Thompson, in discussion with John Gruber: It was mindblowing. It was absolutely incredible. The way that you could just do stuff that wasn’t really possible [on a computer]. Again, it was technically possible on a computer, but the user interface and experience was just transformative on the iPad. It was absolutely incredible. And Jobs knew it. It’s one of my all-time favourites Jobs moments. It’s like fifteen seconds after the demo, and it’s just like… he’s used this. He was involved in the creation of it. They had run through the demo. He knew it. And even then, he was just astonished. He’s just like ‘I can’t believe [this]…’ […] It was, to my mind, the culmination of his life’s work. He comes on there, and he’s like, ‘Isn’t it incredible? Now anyone can make music.’ I almost want to transcribe this whole episode. John Gruber and Ben Thompson discuss the potential of the iPad—and its failure to reach it. Ben uses the term “transformative” deliberately above. They discuss how, before the iPad, no computing experience could adapt to become wholly new tools and environments for whatever the user wanted to do. But the iPad can become a piano or a canvas or a television. In this sense, they argue that the iPad has (or had) the potential for disruptive innovation (RIP Clay Christensen)—but it’s not supposed to be a Mac. These two think the iPad’s lost the chance to fulfill that potential, mostly because Apple has missed the opportunity to build a vibrant developer ecosystem due to App Store policies. I hope that isn’t the case, though I think we have to look beyond the iPad to fully appreciate what might happen next. The introduction of tablets and transformative computing experiences continues to echo throughout a variety of industries. Graphic designers and illustrators have a new suite of tools to directly interact with their creations in the iPad Pro and the Surface. Similarly, tablet or hybrid devices have transformed schools—schoolchildren now have a “homework” device for all kinds of assignments. It’s true that we still need developers to imagine ever-more revolutionary applications for these devices, but there’s no denying that disruption is taking root. Either way, the episode is well worth a listen. Enjoy from 15:50 to ~31:22 and 1:26:59 to the end of the show if you want to focus on the iPad discussion. • Paul Jarvis on Hurry Slowly: Small is Beautiful The ever-refreshing Paul Jarvis shares some uncommon thoughts on productivity in Jocelyn K. Glei’s Hurry Slowly podcast. In particular, Paul and Jocelyn discuss the importance of resilience. Citing research and his own experience, Paul points out that resilience is a more important factor in success than many others. Obviously, though, enabling resilience is not as easy as simply pointing out how important it is. As they discuss, resilience isn’t something innate—which means that it can only be developed through experience. And this is where things get tricky: who gets to have resilience-building experiences? In my research on innovation skills, I discovered that resilience was one of three key domains that wasn’t an important outcome for our public education systems. This means that resilience training isn’t necessarily a public good. Only if you’re lucky (or privileged) will you have the chance to build up your resilience muscle. • Keeping the buzz in buzzwords A thought-terminating cliché limits conversation by capturing a complex (but potentially debatable) subject within a reductive term or phrase. Merlin Mann references this idea in episode 164 of Back to Work when discussing curiosity and buzzwords. Thought-terminating clichés can be used to avoid discourse on a subject: by never unpacking the components of an idea that are debatable, those components go unexplored. They can also be exploited to veil ignorance or illogic—the speaker can state the complex term and allow the implication to have impact without contextualizing/explaining it while the intimidated audience shies away from critique or questioning. This explanation makes the phenomena seem villainous, but many of us are prone to committing these crimes—through buzzwords! Buzzwords are terms that catch on because they represent something exciting to a discourse. Then, because they’re popular, they get used frequently, by many people. Because they are somewhat novel, these different uses attach slightly different meanings to the same word. Eventually the buzzword’s overused (reducing the novelty, and therefore the impact of its meaning) and/or overloaded with meaning. Most of our buzzwords were real things at one point (and sometimes they still are). When buzzwords are used effectively they allow a good conversation to move faster between speakers who have the same mental models about the buzzwords.1 Sometimes, however, buzzwords are said to represent concepts that aren’t fully understood by everyone in the conversation. When my meaning of the word “design thinking” differs from yours, but we both refer to design thinking in conversation nonetheless, we can run into trouble. In these situations, buzzwords obfuscate the ideas we’re actually talking about. In my experience, we also know when we’re using buzzwords. We can guess at when others are using them, too. As a result, the conversation loses meaning, and we lose trust in the conversation. # Dealing with buzzwords So what can we do? Well, the easy thing to do is to clarify. When you use a phrase with many potential interpretations, try to clarify how you’re using the phrase. When others use words that may have multiple meanings, ask specific questions about what they actually mean. This clarification might seem like extra work, but it only needs to happen when terms are first invoked—and it’ll prevent lost time and energy due to the consequences of thought-termination later on. More importantly, though, we should try to avoid thought-terminating clichés altogether. Take time to break down the concepts you’re talking about in concrete terms. Explain them in ways you haven’t heard before to avoid relying on trite metaphors and anecdotes. If you can really get at what you mean, your language will be minimally re-interpretable: that is, it should be near-impossible to understand your explanations differently from how you intended. As a result, your communication will become more impactful. The conversations you participate in will have more novelty, too, making it more exciting to discuss the ideas you’re sharing. This may result in more buzzwords emerging, but that’s okay—use the same approach to break those down, too. Systems sketching 5 notes with this tag • A quick sketch of an interdisciplinary systems model # Why are we exceeding the Earth’s carrying capacity? This is a quickly-sketched model created from a breakout group conversation during the MUN School of Graduate Studies’ “Earth’s Carrying Capacity” dialogue. Download the model • Leadership is # Leadership is… Lessons learned from Memorial Student Leadership Conference (MSLC) 2017. These thoughts were spurred by Director of Student Life Dr. Jennie Massey’s opening remarks for the conference, and were reinforced by the keynote speaker, Mr. Seamus O’Regan, MP. Jennie and Seamus both talked about the oft-haphazard decision making that led to their achievements. The truth about this reinforcing loop is that no matter where you are in the process, you can do something to make it to the next step. No, not every moment will be virtuous – the cycle is not _that_virtuous. It is a cycle nonetheless, and that’s the thing about cycles: they do not stop. • Limits to (personal) growth I’m my own worst enemy when it comes to reading articles. I have 211 in a to-do list as I write this, and the larger that grows the more untenable getting through it seems. In this case the limiter actually escalates, as in order to avoid doing the readings I know I should do, I go off and collect more. 😑 • The snowfall looks so nice! # Last night: “the snowfall looks so nice!”; this morning: “grumble.” Shovelling as a “fix that fails”: it enables us to keep living here, when here means moving solidified rain from one side of the driveway to the other a dozen times each Winter. We should just become snowbirds. • This is why I’m here. Why sketch systems? Partially as a way to productively vent my sarcasm, and partially as a way to practice systems thinking. Also, maybe my handwriting will improve? Presentations 4 notes with this tag • Systemic Strategy # Systemic Strategy: Systemic Design Methods for Complex Systems Change A presentation from Peter Jones and I at RSD9, virtually in Ahmedabad, India. • Leverage analysis in systemic design • Finding the Emic in Systemic Design # Finding the Emic in Systemic Design A paper presented at RSD7 in Turin, Italy. # ABSTRACT I argue that an under-emphasized but crucial variable of success in systemic design is the perspective through which systemic design processes are implemented and executed. While rooted in design (a consciously empathetic discipline, especially in recent years; cf. Kimbell, 2011), it is easy for systemic designers to conduct the research required for their projects in externalized ways. These approaches risk misrepresenting the stakeholders who contribute to projects and, in turn, they are a danger to the potential impact of these misresearched problem systems. I propose to advance a theoretical argument for this danger, the development of an assessment framework to check whether an internalized perspective has been effectively achieved, and provide a proof of concept of this framework through hermeneutic case study analysis. As I will show, systemic design processes that are not executed with the direct and explicit engagement of stakeholders – to the extent of achieving an emic (or from within) understanding of the system – may be flawed at their foundation. By fostering recognition of the importance of an emic perspective, and by providing a framework of principles, practices, and process to accomplish systemic design with this perspective, I hope to ensure that systemic design processes are as accurate and valid as possible with respect to the stakeholders of the system. This is not to suggest that systemic design practice is “too etic”. In fact, with roots in design, systemic design is often deliberately emic. Systemic designers make use of designerly tools that help the researcher to build empathy with system stakeholders (e.g., soft systems methodology, critical systems heuristics, appreciative inquiry; Jones, 2014). They often seek to engage stakeholders in the systemic design process and include reflective analysis of what has been learned in order to assess where deeper engagement with the system is required (Ryan, 2014). That said, with the advent of crowdsourcing (the facilitated involvement of the general public in problem solving, usually using online tools; Lukyanenko & Parsons, 2012) and data science (the use of computational tools to analyze and understand large quantities of data; cf. Scepanovic, 2018), it is likely that data-driven methods will increasingly influence systemic design practice. One recent example sought input from hundreds of people to identify opportunities for change in Canadian post-secondary systems through an iterative online survey (cf. Second Muse, Intel, & Vibrant Data, 2016). This data-driven direction is a powerful opportunity, of course, but it underscores the need to develop principles and best practices for assessing and supporting emic understanding as we gain more data from these tools. This proposal consists of two steps. First, I will look to the principles and theorists of ethnography to develop a framework for assessing the emic/etic perspective of a given research project. Namely, Geertz’ “Thick Description: Toward an Interpretive Theory of Culture” (found in The Interpretation of Cultures, 1973, chapter 1) provides a foundation for the process of emic research, while Creswell and Miller (2000) provide a set of procedural principles for emic validity. Taken together, we generate a critical research framework with which we may assess a given research project’s emic perspective. Second, I will provide a proof-of-concept of this framework (and its theoretical underpinnings) via a casebased assessment of three systemic design projects. Case studies provide an effective venue for learning about the context-dependent manifestations of the phenomena being studied (Flyvbjerg, 2006). One of these case studies is one I have developed through my experience in participating and contributing to the development of the Canadian National Youth Leadership and Innovation Strategy framework, which convened hundreds of youth and youth-serving organizations in order to understand the youth leadership and innovation system in Canada (cf. MaRS Studio Y, 2017). The second and third case studies are those profiled by Ryan and Leung (2014). In order to interpret and analyze the chosen case studies, I turn to the methodology of phenomenological hermeneutics (Eberle, 2014, p. 196; cf. Wernet, 2014). Phenomenological hermeneutics are appropriate as I have access to the described phenomena of the systemic design projects captured by the chosen cases, but these phenomena are not explicitly captured with reference to emic or etic perspectives – thus some construction of the inherent emic or etic data is necessary in order to make judgments about the perspectives found in the projects. In each case, I will use identify phenomena representing the practice of emic (or etic) understanding in the research orientation of the work, as acknowledged by the above framework. In each case, I will examine the step-by-step procedure and any associated notes about the experience of the researchers and participants involved. In each step or experience, I will look for evidence of the four steps of emic understanding or the six techniques of emic validation reported above. # References Creswell, J. W., & Miller, D. L. (2000). Determining Validity in Qualitative Inquiry. Theory Into Practice, 39(3), 124–130. https://doi.org/10.1207/s15430421tip3903_2 Eberle, T. S. (2014). Phenomenology as a Research Method. In U. Flick (Ed.), The SAGE Handbook of Qualitative Data Analysis (pp. 184–202). Los Angeles, Calif. [u.a.]: Sage. Retrieved from https://www.alexandria.unisg.ch/228374/ Flyvbjerg, B. (2006). Five Misunderstandings About Case-Study Research. Qualitative Inquiry, 12(2), 219245. https://doi.org/10.1177/1077800405284363 Geertz, C. (1973). The interpretation of cultures: Selected essays (Vol. 5019). Basic books. Jones, P. (2015). Design Research Methods for Systemic Design: Perspectives from Design Education and Practice. Proceedings of the 58th Annual Meeting of the ISSS - 2014 United States, 1(1). Retrieved from http://journals.isss.org/index.php/proceedings58th/article/view/2353 Kimbell, L. (2011). Rethinking Design Thinking: Part I. Design and Culture, 3(3), 285–306. https://doi.org/10.2752/175470811X13071166525216 Lukyanenko, R., & Parsons, J. (2012). Conceptual modeling principles for crowdsourcing (pp. 3–6). ACM. https://doi.org/10.1145/2390034.2390038 MaRS Studio Y. (2017). A strategic framework for youth leadership & innovation in Canada: Insights from the 2016 National Youth Leadership and Innovation Strategy Summit. Toronto, ON. Retrieved from http://www.studioy.marsdd.com/wp-content/uploads/2016/12/MaRS_NYLISstrategic_framework_Final.pdf Ryan, A. (2014). A Framework for Systemic Design. FORMakademisk–research Journal for Design and Design Education, 7(4). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/787 Ryan, A., & Leung, M. (2014). Systemic Design: Two Canadian Case Studies. FormAkademisk - Research Journal of Design and Design Education, 7(3). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/794 Scepanovic, S. (2018). Data science for sociotechnical systems - from computational sociolinguistics to the smart grid. Aalto University. Retrieved from https://aaltodoc.aalto.fi:443/handle/123456789/30187 Second Muse, Intel, & Vibrant Data. (2016, May 11). What Your Data Says: Post-Secondary Education Mapping Survey Highlights. RECODE. Retrieved from http://re-code.ca/whats_happening/watch-recodewebinar-what-your-data-says/ Wernet, A. (2014). Hermeneutics and Objective Hermeneutics. In U. Flick, The SAGE Handbook of Qualitative Data Analysis (pp. 234–246). SAGE Publications, Inc. https://doi.org/10.4135/9781446282243.n16 • Creative Education Futures # Creative Education Futures What are the futures of art and design schools in Canada? In 2015, I supported Kinetic Café in developing OCAD University’s latest Vision and Mission statements. As part of that work, I helped scan for signals, trends, and drivers in art and design school futures. Our scan revealed five important drivers of change: reforming education, creative economies and cultures, new geographies, empowering technologies, and conscious collective. A walkthrough of this work is visualized and embedded below. If it doesn’t display, you can visit it directly here. Science 4 notes with this tag • The Demon Haunted World I have a foreboding of an America in my children’s or grandchildren’s time—when the United States is a service and information economy; when nearly all the manufacturing industries have slipped away to other countries; when awesome technological powers are in the hands of a very few, and no one representing the public interest can even grasp the issues; when the people have lost the ability to set their own agendas or knowledgeably question those in authority; when, clutching our crystals and nervously consulting our horoscopes, our critical faculties in decline, unable to distinguish between what feels good and what’s true, we slide, almost without noticing, back into superstition and darkness… The thread discusses the growth of anti-intellectualism and conspiracy theories. I’m reminded of this timeless Medium post about how hating Ross in Friends became a meme in and of itself, reinforcing the persecution of science in the ’90s. From David Hopkins: I want to discuss a popular TV show my wife and I have been binge-watching on Netflix. It’s the story of a family man, a man of science, a genius who fell in with the wrong crowd. He slowly descends into madness and desperation, led by his own egotism. With one mishap after another, he becomes a monster. I’m talking, of course, about Friends and its tragic hero, Ross Geller. […] If you remember the 1990s and early 2000s, and you lived near a television set, then you remember Friends. Friends was the Thursday night primetime, “must-see-TV” event that featured the most likable ensemble ever assembled by a casting agent: all young, all middle class, all white, all straight, all attractive (but approachable), all morally and politically bland, and all equipped with easily digestible personas. Joey is the goofball. Chandler is the sarcastic one. Monica is obsessive-compulsive. Phoebe is the hippie. Rachel, hell, I don’t know, Rachel likes to shop. Then there was Ross. Ross was the intellectual and the romantic. Eventually, the Friends audience — roughly 52.5 million people — turned on Ross. But the characters of the show were pitted against him from the beginning (consider episode 1, when Joey says of Ross: “This guy says hello, I wanna kill myself.”) In fact, any time Ross would say anything — about his interests, his studies, his ideas — whenever he was mid-sentence, one of his “friends” was sure to groan and say how boring Ross was, how stupid it is to be smart, and that nobody cares. Cue the laughter of the live studio audience. This gag went on, pretty much every episode, for 10 seasons. Can you blame Ross for going crazy? People in the Reddit thread point out that these seemingly recent trends have been taking root for a long time. While this is true, it’s also true that (just like seemingly everything else) these phenomena have been moving much faster and growing much larger in recent years. Which leads to a curious tangent: how do accelerated scales of change play on our biases? Does the interaction between these biases and our accelerated experiences change our perception of the world? • Science Conferences Are Stuck in the Dark Ages Dr. Ngumbi and Dr. Lovett outline the issues with modern research conferences that are stuck in the 20th (or even 19th) century. By the end of each conference, you’ve heard dozens of people dispense all their knowledge in 10-minute bursts, and you sometimes leave feeling less informed than before you arrived. Where’s the dialog? Where’s the questioning? Where’s the innovation? It’s beyond time that scientific conferences themselves undergo the scientific process, and move forward. I shouldn’t ever be surprised by these events, but every time I go to one, I am shocked by how boring the facilitation is. Some might defend the format. After all, sage-on-a-stage has worked for hundreds of years. The question isn’t whether it works, though. It’s whether it could be better. Surely, in an age of cloud technologies and the Internet and social media—not to mention better recognition of soft power and inclusivity and the processes of scientific revolution—there are modes of conference programming that can leapfrog the conventional format. Having led a number of events over the years that have shirked tradition for more interesting facilitation formats, I know firsthand how disruptive facilitation mistakes can be. But I’ve also seen some incredible results from shaking up the structure. Radhoc’s Unpanel, for instance, turns the structure of a panel upside-down. Instead of having a group of “experts” on a stage speaking to an anonymous crowd, the format puts those invited guests in subgroups that get to introduce one another. The audience becomes the panel, and the expert an anchor in the conversation. It gives everyone a chance to connect with the quasi-celebrities anointed by these events. As a bonus, it’s easier for the guests, too—they don’t need to prepare keynotes, only business cards. • Microsoft wants to capture all of the carbon dioxide it’s ever emitted The most audacious commitment from Microsoft is its push to take carbon out of the atmosphere. The company is putting its faith in nascent technology, and it’s injecting a significant investment into a still controversial climate solution. Proponents of carbon capture, like Friedmann, say that the technology is mature enough to accomplish Microsoft’s aims. It’s just way too expensive right now. Microsoft’s backing — and its1 billion infusion of cash — could ultimately make the tech cheaper and more appealing to other companies looking for new ways to go green.

Fantastic news. Carbon capture is a key opportunity for decelerating climate change. Hopefully more companies follow suit.

# Facilitating Citizen Science through Gamification

Gamification is the practice of using game elements to change the experience of nongame contexts. It presents a potentially powerful new approach to motivate volunteers and recruit new contributors to citizen science—the phenomenon of engaging members of the public in the collection and analysis of data in scientific projects. This research included a thorough literature review of current gamification and citizen science research and presented a pilot information systems/design science project exploring the efficacy of gamification in the citizen science platform NL Nature

Systemic design

4 notes with this tag

University

4 notes with this tag

• 'This is Sticking with Them:' Professor Explores Benefits of Model-Based Learning

Through model-based learning, students use diagrams as a way to think about and reason with systems—and to think about how complex systems interact and change.

“Model-based learning” seems like a reframing of classic teaching practices, but it’s nonetheless a powerful reframing. Emphasizing the model—and encourage students to test and iterate their models—is catchy. It’s also deliberately organizational—it requires students to organize and structure their thinking about a given system, often visually.

# Innovation Education

What is innovation? How do we define innovation, its outputs and processes, and what are the skills and competencies necessary to practice and excel in innovation?

Read the full paper.

Many strategies and policies, both federal and provincial, have attempted to improve Canada’s innovation capacity in the last few decades. Universities and colleges are often discussed in these strategies for their role in facilitating new partnerships and in developing (potentially) actionable research.

It is rare, however, for these strategies to recognize education plays in the creation of innovators.

This is counterintuitive: education is an obvious mechanism with which to develop the knowledge and abilities of a population. Yet we lack a holistic understanding of what it takes to practice innovation, let alone the kinds of curricula that might provide those skills and competencies. Moreover, we are inconsistent in the definitions and language we use to define innovation—often obsessing over technology and commercialization. We tend to assume innovation comes from research and development processes, and that innovators are simply highly skilled people.

Presented here is the result of an intensive review of reports, strategies, policy, and theory on innovation in the Canadian context. This literature was scanned and coded—inspired by the ethnographic methods of grounded field theory—in order to synthesize a holistic theory of innovation.

This theory includes a universal definition of the innovation process, a recasting of different focuses of innovation as innovation orientations, a comprehensive model of the innovation process, and a synthesis of innovation skills and competencies into 13 learning domains, 47 learning constructs, and 227 learning outcomes. These tools provide utility for policymakers and educators in pursuit of understanding and improving innovation capacity. In particular, the model of innovation education is the most comprehensive of its kind, providing an extensive set of concepts with which to understand education gaps and build curricula.

Perhaps the most important contribution of this research, however, is the recognition that our conversations about innovation strategies and education reform must be aligned. **How exactly do people learn to be innovative, and how are our education systems currently facilitating that process? **With this study we have begun to seek answers to these questions, but there is much more work to do.

If you use these ideas and learn something from your experience, or if you have thoughts on how to improve them, don’t hesitate to make suggestions and to share your work.

Find resources on this page that detail the definitions and models of innovation developed through this research and how these concepts may be applied in innovation education programming.

# Explore the Model

Across dozens of perspectives on innovation, a set of 13 domains of skills and competencies emerged. These domains have been interactively visualized using Kumu.io. You can play with the work yourself by clicking the button. Use the controls in the bottom corners to focus on specific components of the model, to surface the innovation process so that you can explore both simultaneously, and more. Note that the visualization is best explored on a desktop!

# Learn more about the skills and competencies of innovation

This document provides an executive summary of the insights and models on innovation education uncovered through this research and guides educators to put these concepts and tools to use.

# Read the Research

Education reform presents an opportunity to improve innovation education and, in turn, advance innovation capacity. I synthesize the framing and strategy of resources from provincial, national, international, and theoretical perspectives on innovation in order to develop a holistic model of innovation and a curricula for innovation education. Then, I use systemic design to model Newfoundland and Labrador’s current education system and to suggest strategies for reform to enable improvement in Newfoundland and Labrador’s innovation education. Finally, I explore how systemic reform in Newfoundland and Labrador may serve as a systems laboratory for reform efforts in other jurisdictions.

Innovation Education is a major research project presented to OCAD University in partial fulfillment of the requirements for the degree of Master of Design in Strategic Foresight & Innovation. This work was supported by the Social Sciences and Humanities Research Council of Canada.

# Education Systemics

What are the mechanisms of education systems change? How might we use systemic design to power a reform movement? What does systems thinking teach us about opportunities and barriers for education reform in Newfoundland and Labrador?

Education reform is not a new idea. Many organizations and initiatives have reimagined the schools, universities, and colleges that are the backbone of our economy and society—yet, to many, it seems like little has changed in recent decades.

As Jal Mehta, Robert Schwartz, and Frederick Hess began their book on the subject, “if we keep doing what we’re doing, we’re never going to get there.” Traditional education reform approaches have depended on a best practices approach in what is glibly called a “silver bullet culture”.

A single idea, found successful in a specific institution or district, becomes hailed as the be-all-end-all solution. This solution is then celebrated and championed across contexts until actors realize that expected results have not materialized, and reformers move on to the next silver bullet solution.

This approach to education reform has not worked. According to Mehta, Schwartz, and Hess: “If we are to deliver transformative improvement, it is not enough to wedge new practices into familiar schools and districts; we must reimagine the system itself”. In other words, education systems change has been found to be more than difficult. It is a wicked problem: ill-defined, constantly fluxing, with many conflicting stakeholders and no true solutions.

How can we provoke change in wicked problems?

I argue that reforming education is a sociotechnical problem, involving human psychology; social, political, and economic factors; and complex interactivity–what Don Norman and Pieter Stappers have called a “DesignX” problem. These authors suggested that DesignX problems can only be solved through a process of muddling through, developing incremental sub-solutions through deep analysis. This deep analysis means partitioning the problem into modules and recognizing the intersecting dimensions of the problem.

Peter Jones provides further advice for this kind of problem solving, defining an approach called systemic design. Systemic design integrates systems thinking and systemic methods–ways of understanding complex problems through the relationships of the phenomena and actors involved–with design thinking and design methods, applying human-centred design to these seemingly intractable, large-scale problems. With systemic design, Peter says, we use “known design [tools]—form and process reasoning, social and generative research methods, and sketching and visualization practices—to describe, map, propose, and reconfigure complex services and systems”.

# Approach & Findings

With this in mind, I turned to several types of modelling in order to use systemic design on the complex problem of education reform: process modelling, actor mapping, and causal loop mapping. In this modelling, I focused on Newfoundland and Labrador—my home province—and the education of innovation, examining how our system currently provides innovation learning and how we might do better.

Finally, I applied centrality analysis – a quantitative approach to assessing leverage points and bottlenecks in networks and systems maps—in order to surface potential opportunities and challenges in the system. I examined four types of centrality analytics:

• Reach efficiency takes an element’s reach (the proportion of the network within two steps of that element) and divides it by the number of neighbouring elements it has. Elements that score the most on this metric tend to be less connected but have high exposure to the rest of the system, making them low-hanging fruit for change efforts.

• Betweenness assesses the number of times an element lies on the shortest path between two other elements. Elements high on the betweenness metric are bridges throughout the map, controlling the flow of phenomena throughout the system. This means that these elements may be bottlenecks or single points of failure.

• Eigenvector centrality measures an element’s connectedness to other well-connected elements, computing an overall value that is an indicator of the element’s influence over the whole system.

• Torque calculates each element’s reach efficiency weighted by its eigenvector centrality (e.g., how influential that element is). Elements with high torque should be relatively easy to impact (as they are not densely influenced by other phenomena in the map), but will impact the rest of the map substantially. These are key leverage points of change.

The detailed methods and findings from each of these approaches are discussed in turn in the links below.

# Conclusions

I aimed to see the education system for what it is in order to describe strategies for the transformative reform that Mehta, Schwartz, and Hess called for. The education system is therefore composed of a number of interrelated components, organized in a hierarchy, whose emergent phenomena lead to its own dynamics. Yet, many might say that this systemic chaos implies a system of constant change, while education is hallmarked for its derelict stagnancy in the 21st century. How is it that such a system has not evolved?

Well, perhaps the system is not actually that broken. As eloquently argued by Ryan Burwell, an instructional designer at the MaRS Discovery District:

The school system is not broken. It is perfectly aligned to provide equitable access to a canon of high-quality, standardized content with greater rigour and organization than any other knowledge delivery system we currently have. However, it is not designed to foster the problem-solvers, innovators and entrepreneurs that are becoming an increasingly significant part of the global economy. Incorrectly identifying this misalignment as a broken system has created a culture of fear and failure around education, leading to top-down reforms and increased numbers of mandatory programs.

I return to Mehta, Schwartz, and Hess’ depiction of school reform’s silver bullet culture. Many stakeholders with competing interests and different priorities are invested in every debate on education systems change.

Thus, there are many potential silver bullets–and many advocates for them. The misunderstanding of the problem described by Burwell and the complexities of education reform described by Mehta, Schwartz, and Hess perfectly capture the need for a systemic design-based approach to change.

# Process Mapping

From process modelling, it is clear that while NL’s education system currently offers some opportunities to learn certain constructs of innovation, the availability of these opportunities is not densely packed throughout their study. It is easy to recognize a dearth of access to the domains of Foresight and Scanning, Vision and Purpose, and Adaptability and Resilience. Further, the degree to students learn the domains and constructs of innovation skills from the public system remains unclear.

Ultimately, now that these models exist, further analysis will be able to examine these constructs more closely as students progress through the system.

This is especially true for many of the “optional” components of the broader education system. After school programs, hobbies, sports and recreation, volunteer and extra-curricular roles, self-directed learning, and employer training could each be vital sources of innovation education, but it was impossible to study these aspects of the system in any meaningful way in the present study. A dedicated effort should examine the availability of these sources and assess their utility for innovation learning.

One research approach would be to survey learners along the learning journey, testing their abilities in the different constructs I’ve outlined. This ethnographic approach could reveal hidden truths: perhaps, for instance, certain regional cultures in the province actually provide powerful learning in design through a community culture alone.

# Actor Mapping

Systemic modelling reveals the power and wealth subsystems active amongst the actors of the education system.

Centrality analysis of the power subsystem illustrates that parents and the provincial government have efficient influence on the system, and change that can mobilize those bodies of actors will quickly take shape.

Meanwhile schools, the School Board, and educators have substantial global influence over the system–change efforts that engage these actors may be slow but momentous.

Finally, power bottlenecks are educators; schools and school councils; and the Department of Education and Early Childhood Development. This suggests that these actors will ultimately need to be involved if any reform effort were to achieve success.

Reach efficiency analysis of the wealth subsystem shows that the federal government, parents and students, and the provincial Department of Advanced Education and Skills each strongly influence the distribution of wealth. The Federal and Provincial Governments have powerful incentives with which to motivate and control reform efforts.

Betweenness centrality revealed that the whole system is tightly linked, making it potentially volatile: economic issues in one component of the system may ripple out and impact the others.

# Causal Loop Mapping

Finally, these maps intimated a causal loop diagram illustrating how innovation education reform might happen in the public education system.

Several loops and one archetype demonstrate significant effect over the system. The Low Definition loop describes an acceleration of the impact of ill-defined innovation on our ability to educate on it. The We Teach What We Know loop shows how a lack of innovation education leads to a lack of people capable of teaching it and vice-versa. The New Economy loop shows how economic shocks driven by drops in commodities pricing has raised our awareness of the importance of the innovation economy. The Innovation-driven Growth loop shows how innovation capacity will accelerate jobs in the knowledge economy, which will in turn drive our ability to create more innovators through education. The Limited Resources loop balances our ability to reform education for innovation due to a lack of funding for the reform effort due to austerity budgets, driven by drops in the price of oil. Finally, the R&D, Not Innovation archetype is an instance of the Fixes that Fail systems archetype, showing how a conflation of innovation with R&D efforts fails to improve our innovation capacity while also distracting from true innovation education.

The result of centrality analysis on these causally-linked phenomena is rich with pragmatic insight.

Three phenomena with efficient reach over the whole system are innovation learning from outside of the public education system, lack of emphasis on innovation education, and low price of oil. The former points to an accessible lever of change: introduce innovation education through extra- and co-curricular programs, volunteer and leadership roles, sports and recreation, or self-directed learning, and the system may catch up by offering its own programming to match. The leverage of a lack of emphasis on innovation education offers another route: increase awareness on innovation education in order to encourage the system to improve on it. Finally, low price of oil retains leverage as a dampener on the system: if the economy continues in recession, the system is less able to offer resources for reform efforts.

Other calls for reform is one force with substantial torque over the system, indicating that reformers must be co-opetitive with other education change efforts, else all reform efforts might fail due to competition with one another. The availability of accessible and practical models for innovation education is another high-torque element, however, elevating the potential of the present research to create change in the system. A third element with high torque is the generational shift in work, evidence that a substantial source of impetus for innovation education reform could come from changes in work and careers.

Finally, betweenness centrality offers a picture of the bottlenecks and points of failure within the system. Innovation capacity and innovation education are two forces semiotically central to the system, and thus it is intuitive that they will be slow to change, no matter what else is happening within the system. On the other hand, recognition of innovation deficiency, the perceived innovation gap, and the search for solutions to the innovation gap are three phenomena that are clear points of fragility in any systemic change effort. If the system does not recognize its deficiencies, perceive the gap in innovation capacity, or opt to search for solutions, reform efforts are liable to be frustrated.

# Limitations

Despite these clarion recommendations for systemic design, several limitations prevent wholesale adoption.

One key limitation of the presented results of systems modelling is that the connections defined in these models are unquantified. In the refined actor map, for instance, it may be that educators have little power over their school councils, or perhaps the NL Federation of School Councils has far less lobbying capacity than the NL Federation of Teachers. Evaluating the strength of these connections and including these evaluations in our analytics would improve the acuity of those metrics substantially.

As previously mentioned, if innovation learning is not coming from the public education system, it must be coming from somewhere else. Yet, these potential sources arguably include the whole of the human experience—as we have, after all, been learning to innovate since pre-history. Future research might take on an ethnographic approach to understanding the system, investigating different student-innovators and where they learned their innovation skills, or a longitudinal approach, following students as they become innovators through their years in the education system. These exercises fell outside the limits of the present research, unfortunately.

Another limitation is that, while the scope and approach to mapping were designed to increase the variety of the system as much as possible, the mapping was still completed with the perspective of only this author. The representativeness of the systems models would therefore be strengthened considerably with Delphi-inspired methods as seen in previous research, bringing the mapping process to others in order to iteratively refine and the map from alternative stakeholders’ points-of-view.

Another potential future study is to “bring the whole system into the room”. This would mean convening a group of stakeholders who were holistically representative of the actors of the system, engaging them in a systems modelling process to develop a map with their collective perspectives.

# ACTIONS AND TAKEAWAYS

# In The Short Term

A few immediate actions stem from this research.

# 1. Adopt A Model

First, we must adopt a model of innovation skills and competencies.

Regardless of whether the adopted model is the one developed through this project or another alternative, it is imperative that we begin to recognize the skills and competencies used by successful innovators. By identifying these skills, we will be capable of examining our weaknesses and, in turn, developing ways of resolving those weaknesses. To spur this discussion, I plan on sharing the models developed here widely.

# 2. Consider The Role Of Education In The Creation Of Canadian Innovators

Second and in tandem, we must include the role of the education system in nurturing innovators in our provincial and national innovation strategies. Many approaches to innovation policy discuss the post-secondary education system with respect to its role in public-private partnerships and the commercialization of research. We must expand this role to include the development of innovation skills and competencies as well. In the near future I hope to meet with policymakers involved in the development of Newfoundland and Labrador’s innovation strategies to advocate for this approach there.

# 3. Unite Education Reform Movements

Education reform movements must be united in their calls for change. A host of movements relate to the notion of innovation education, from code.org (a non-profit urging computer science and programming education in K-12) to the 21st century learning movement (a pedagogical framework for the skills and knowledge necessary for the 21st century; cf. http://www.p21.org).

The present research shows that these reform efforts may conflict, however, if they are brought forward asynchronously by their champions. It is therefore crucial that these efforts learn to “co-opete” (as in “co-opetition”) and engage educators and policymakers with aligned advocacy. I hope to work with the education systems change movements I already have relationships with in the immediate future in order to begin this dialogue.

# In The Long Term

As explored by David Stroh in Systems Thinking for Social Change, systems change is only possible when the actors of the system collectively recognize the tension between where the system is and where they want it to be.

That realization isn’t possible, however, before the actors have even talked to one another—let alone come to consensus about a shared vision for the future.

We realize that Canada’s future prosperity is predicated on our ability to leverage the boons of our resource economy and evolve it into an “innovation rich” leader in the knowledge economy. Yet, as discussed at the beginning of this paper, the danger is that education’s role in this transformation has yet to be recognized in full. We are not talking about how to create innovators, let alone what strategies we should employ in doing so, or how the system is stuck in becoming better at innovation education. Worse, there are many simultaneously conversations happening in both education reform and innovation—conversations that compete with one another, threatening the potential of the whole.

This research offers a model of the education system in Newfoundland and Labrador. Yet these models are untested, and as I have noted, the research is sorely lacking a futures perspective that observes both threats and strategic opportunities in our changing environment.

**How might we spark a collective, integrative discourse on innovation and innovation education? **Then, how might we elevate its importance such that collective action is taken—before we’ve missed the opportunities of the knowledge economy? How might we refine the systemic models, and how might we augment this work with a futures perspective, using environmental scanning to develop and integrate changing trends for strategic leverage?

These questions point toward a need for a powerful, strategic theory of change, and the willingness to muddle through. In other words, **this change will not come about through the efforts of ad hoc standalone initiatives like this one. **

We need a sustained effort. We need a lab that brings together design science and systemic design, creating and testing designs of the system itself, making sure they are valid constructs of the concepts they are intended to represent, all while obeying the principles of systemic design.

This is not a new idea. Many have articulated the notion of social labs, design or change labs, or social innovation labs. In fact, the OECD’s Centre for Educational Research and Innovation seems to operate such an approach for systemic innovation in global education.

I argue that Canada–or at least, Newfoundland and Labrador–needs to take a lab-based approach to navigating complex education reform in education. This lab must unite the perspectives, strategies, and actors currently engaged in similar pursuits; build, maintain, and refine models of the systemic change taking place; be engaged in environmental scanning and strategic foresight to monitor for both threats and opportunities; and prototype change initiatives, taking lessons back to these models and strategies.

Only a dedicated, intelligent effort will help us build the education systems that will develop the skills and knowledge we need to answer the 21st century.

Innovation Education is a major research project presented to OCAD University in partial fulfillment of the requirements for the degree of Master of Design in Strategic Foresight & Innovation. This work was supported by the Social Sciences and Humanities Research Council of Canada.

# Innovation Systemics

# Takeaways

# Problem 1: Canada Struggles To Understand How It Can Fit The ‘Idea Economy’ Into The Broader Economic Context (I.e. Other Sectors).

Thus, Canada should take steps to foster the idea economy. The world is changing, and Canada needs to understand how the tenets of the idea and knowledge economy will best flourish across the primary sectors that drive the broader Canadian economy. Building regional collectives (like the Waterloo-Kitchener corridor) to advance innovation is only one step, whereas our findings suggest the need to take a collective leap and author a White Paper that will activate a national approach on the new, ideas-based economy. In doing so, the Government of Canada will engage a collective of stakeholders, thought leaders and businesses both large and small to lead a national dialogue on how innovation ought to play out across Canada’s diverse communities, companies and campuses.

# Problem 2: Canadians Do Not Recognize The Unique Strengths Of The Economy As It Is, And Neglect Recognition Of The Innovations Already Taking Place.

Canada should change the narrative. Innovation is happening, but it is taking place in sectors and industries different than the ones we tend to pay attention to. Increasing awareness about the need for, and impact of, innovation within advanced manufacturing, natural resources and agriculture will help cross pollinate the economy with more robust, productive approaches and solutions. This will also help to shift the culture of entrepreneurship by empowering a generation of Canadians to create sustainable value and ensure they and their communities prosper.

# Problem 3: Canada Currently Allocates A Disproportionate Amount Of Resources (Talent And Capital) To “Tech Solutionism”, At The Cost Of Others.

Canada should redirect the pipeline. The ultimate step is to increase the carrying capacity of the system to generate value for entrepreneurs from outside the technology sector. Drawing sectors and industries together with the innovation ecosystem will build deeper and more diverse connections. Diverting the flow of resources—talent and capital—and binding it with existing infrastructure and institutional support will build a depth that will support a more robust Canadian economy. Furthermore, investing in improving the structures that nurture prosperity—incubators, accelerators, entrepreneurship, and innovation programs—and bringing them together with campuses and companies already making an impact, will propel Canada forward.

# The Context

“Innovation drives an economy’s ability to create more economic value from an hour of work, thereby increasing economic output per capita. The resulting productivity growth creates potential for rising wages and incomes, and thus for a higher standard of living.” (University of Lethbridge Research Services, 2015)

A robust innovation ecosystem has the ability to improve productivity, economic growth, and job creation metrics in countries adequately supporting this process. In these countries, there also tend to be more resources available to support spending in education, health, and infrastructure, to name a few (“Innovation details and analysis”, 2013). Accordingly, the importance of a healthy innovation system is tied closely to that of a healthy national economy, along with its people, communities and institutions.

In Canada, however, economic discourse around innovation and entrepreneurship has recently pointed towards a decline in productive returns from startup investment. Although an improvement from previous years, in 2015 Canada was ranked 9th out of 16 peer countries in innovation by the Conference Board of Canada, receiving a letter grade of “C” on its Innovation Report Card (“Innovation details and analysis”, 2013). This ranking points to a persistent weakness in the Canadian innovation system, commonly referred to as the “innovation gap”. This phenomenon is being reported by some of the country’s top journalists, startup CEOs, established investors, think-tanks, and members of various levels of government across the country. While these reports highlight culture, politics, economics, and education as the cause of this gap, and underlining the need for reform, policy changes, and new programs, few of these calls to action are gaining traction. There is no easy answer to this wicked problem.

With the above in mind, we initially sought to answer the question “Why are investments in innovation resulting in diminishing returns in productivity?” through our research, but we quickly realized that in order to address this issue, we would first need develop a thorough understanding of the innovation ecosystem in Canada and thus we broadened our research questions to “How might we understand the Canadian innovation system?” all the while still focusing on this oft reported, elusive innovation gap.

Innovation details and analysis. (2013). The Conference Board of Canada. Retrieved from http://www.conferenceboard.ca/hcp/details/innovation.aspx

University of Lethbridge Research Services. (2015). Putting Innovation in Context. Lethbridge, Alberta, Canada: University of Lethbridge. Retrieved from http://www.agility-ulethbridge. ca/2015/09/11/putting-innovation-in-context/

# Research Synthesis Map

This synthesis map summarizes our research on Canada’s systemic innovation challenges this past term.

# Leverage Analysis

We used centrality analysis to examine our map of the system for potential leverage points. The elements that surface from this analysis offer opportunities (or, in some cases, roadblocks) for policy and program interventions.

# The Paper

# The Researchers

This work was completed by a team of Master of Design students in OCAD U’s Strategic Foresight & Innovation program.

Workflows

4 notes with this tag

• Why the grass is greener: Making sure that shiny new alternative tool is actually going to help you

“The grass is always greener on the other side.” The popular idiom discourages whoever’s listening from seeking out alternatives, suggesting that other options always look better from wherever we’re currently standing. But it has a funny problem: nobody ever explains why the grass is greener on the other side.

That’s because it isn’t. The truth is that your side is just yellower/trampled on/eaten… and that’s because you’re on it.

Moving to a different place will be fine at first. Then you’ll use it, too, and eventually it’ll look the same as where you started.

(In this metaphor, you’re a goat. 🐐)

In workflow design, in addition to the novelty of “shiny new object,” new and alternative tools are great simply because they don’t have the cruft you’ve built up in the old tool. That cruft might be noisy notes, a lifetime of guilt-inducing task management, or even just bad habits and behaviours. The problem isn’t the tool. It isn’t you, either. It’s you and the tool.

So, after switching, the problems seem to go away… only to re-emerge (possibly in a new form) later because the issues are generated by your usage, not by the tool.

The solution is to fall in love with the problem, not the (shiny, potential) solutions.

1. Determine what your issues actually are, and try to figure out why they’re happening.
2. Then, abstractly identify how you might be able to mitigate the problems.
• Don’t say “I’ll use Bunch,” say “If I standardize certain work spaces on my computer, I can develop muscle memory for using those workspaces, reducing distraction and allowing me to spend less cognitive energy on finding everything I need to get engaged.”
3. Last, identify some tests or success conditions that will tell you whether the solution is actually working. This’ll help minimize irrational perspectives on how well the honeymoon stage is going.

Only after taking those three steps should you choose a tool. Find something that can implement the abstract principles you’ve articulated, and be sure to follow-through on the tests.

In doing this, you’re actually creating and implementing a rough design theory. You’re using design science to make your work as easy and engaging as it can be! High-five for that.

• Automatically download Reminders into your Obsidian notes with Shortcuts

Want a quick, hands-free, one-step method to capture reminders and tasks into Obsidian? Take advantage of Reminders, Shortcuts, and Shortcuts’s automations feature.

This Shortcut will extract all reminders currently incomplete in a given list and append them to your daily note.

Here’s a screenshot of the full Shortcut

Download it and set it up (i.e., answer all of the configuration questions). Then, create Shortcuts automations (via the Automations tab in Shortcuts) that run on whatever triggers you want (e.g., “Whenever the Obsidian app is opened” and “9am”). Add a “Run Shortcut” action to that automation, then select the shortcut you’ve just configured.

🎉! Whenever the shortcut is triggered, the reminders in the designated list will be added to your daily note.

You can now say e.g., “Hey Siri, add ‘Pick up milk’ to my Obsidian list,” and that item will (eventually) be added to your daily note.

Changemaking

3 notes with this tag

• The changing work of innovation for public value and social impact

In two senses, the work of innovation for public value and social impact is changing in Australia and around the world. What we expect public innovation to do and what we need it to achieve, and how that work should be done, are both changing. And they are changing together while they are changing each other.

It’s true. It’s hard to keep up with the discipline of changemaking, but it’s even harder to keep up with the change that needs to be made. Therefore Martin Stewart-Weeks calls for optimism:

Despite some of the uncomfortable and unsettled conditions, there is real energy in the search for more effective ways to solve the big problems we face in common – managing our complex cities, rewiring large and complex health and social care systems, tackling climate change, searching for better ways to integrate the human and technology capabilities of the digital age and making our communities healthy and resilient.

The speed, intensity and sheer connectedness of these and many other complex, public challenges are giving rise to new methods and tools that can help to tackle them with purpose and skill.

# Systems Practice, Abridged

For serious system mapping work, spending [significant] time studying, thinking about, and mapping your system helps ensure you are addressing root causes rather than instituting quick fixes. In the long term, the time and resources you invest in Systems Practice will pay dividends.

But what if youʼre not quite sold on the Systems Practice methodology yet? What if you havenʼt encountered systems thinking before and just want to dip your toes in? Or what if youʼre an expert or an educator with only a few hours to introduce Systems Practice to a fresh new group of systems thinkers?

I have been in the latter situation, and it’s a challenge. In my experience, people who are wholly new to systems thinking can take a lot of time to acclimate to the mindset. But! If, as a teacher, you can’t illustrate the benefits quickly, it’s easy to disengage.

So, I’m glad this exists. This is a wonderful new resource from Kumu’s Alex Vipond that helps walk you through systems and Kumu’s tools at the same time.

• Piret Tõnurist & Systems Change: how to get started and keep going?

This is a great talk from Piret Tönurist of the Observatory on Public Sector Innovation.

One of the core issues of the talk is innovation doubt—the “if it ain’t broke, don’t fix it” mentality. To paraphrase Piret:

[…] why are we doing innovation at all? Maybe sometimes things are working fine, why do we think about innovation at all? We start off with four questions:

1. Do you want to do things better?
2. Do you have goals and purposes to fulfill?
3. Do you want to address the needs of your stakeholders?
4. Do you want to prepare for the risks and uncertainties that the future holds? If you answered “yes” to at least one of those questions, then your job is to do innovation—your job is to be a changemaker.

Also, the talk includes a neat model for different varieties of innovation, image courtesy of this post by Adrian M. Senn over on Medium: https://miro.medium.com/max/1210/1*AaPZeqAVLoo85RfY7Dxspw.png

Crowdsourcing

3 notes with this tag

• TED and YouTube launch global climate initiative

Anyone, anywhere can propose an idea. YouTube creators will help spread the word, and the best proposals could be put into motion with the help of businesses, policymakers, and and celebrities supporting the initiative.

The initiative will culminate in a summit in Bergen, Norway next October to share the solutions that came out of the effort. Countdown will work with a panel of experts and scientists to vet proposals, and the strongest will be turned into TED talks. The talks will be filmed at the summit in Norway, in front of “a hand-picked audience capable of turning those ideas into action,” according to a press release.

An interesting partnership, and yet another example of “crowdsolving”: trying to find solutions to wicked problems via the mobilizing power of the Internet.

• Medical Crowdsourcing: Harnessing the 'Wisdom of the Crowd' to Solve Medical Mysteries

Medical crowdsourcing offers hope to patients who suffer from complex health conditions that are difficult to diagnose. Such crowdsourcing platforms empower patients to harness the “wisdom of the crowd” by providing access to a vast pool of diverse medical knowledge.

An interesting application of crowdsourcing. What’s the incentive for healthcare providers to participate, though? I’m not sure doctors can bill for participation in Figure 1. I think the main reason they engage at all is curiosity, and that would likely degrade if, as the authors of the linked study discuss, there was a lot of “noise” from uninteresting posts by patients who aren’t medically literate.

# Facilitating Citizen Science through Gamification

Gamification is the practice of using game elements to change the experience of nongame contexts. It presents a potentially powerful new approach to motivate volunteers and recruit new contributors to citizen science—the phenomenon of engaging members of the public in the collection and analysis of data in scientific projects. This research included a thorough literature review of current gamification and citizen science research and presented a pilot information systems/design science project exploring the efficacy of gamification in the citizen science platform NL Nature

Data

3 notes with this tag

• ∎ Data Science and Prediction - Dhar - 2013 - Reading Session 202301271312

In situations where we are able to design randomized trials, big data makes it feasible to uncover the causal models generating the data.

The author doesn’t make this point very big but it is actually quite important. There are many cases in which it is unethical to undertake a conventional scientific study of certain phenomena… Even though we know that those phenomena are happening anyway. If the data is collected “naturally,” however, we may be able to trace and track patterns in these data without putting ourselves in precarious ethical situations

• The Tyranny of Categorization

Herein, then, lies the tyranny of classification: The borders we draw for ourselves create a prison of thought and collaboration, inhibiting movement, connectivity, and learning.

Dominic Hofstetter outlines the many benefits of categorization, too. We have to have both specialization and generalization—categories and loose files. The key is developing processes, protocols, and ways of working that elevate the benefits of both.

# README.txt: Introducing Into the Dataverse, the article series

There is a significant gap in research about Canadian data collection activities on a granular scale. This lack of knowledge regarding data collection practices within Canada hinders the ability of policymakers, civil society organizations, and the private sector to respond appropriately to the challenges and harness unrealized benefits.

So true. This looks like an interesting series from the great team at Brookfield.

Psychology

3 notes with this tag

• Keeping the buzz in buzzwords

A thought-terminating cliché limits conversation by capturing a complex (but potentially debatable) subject within a reductive term or phrase. Merlin Mann references this idea in episode 164 of Back to Work when discussing curiosity and buzzwords.

Thought-terminating clichés can be used to avoid discourse on a subject: by never unpacking the components of an idea that are debatable, those components go unexplored. They can also be exploited to veil ignorance or illogic—the speaker can state the complex term and allow the implication to have impact without contextualizing/explaining it while the intimidated audience shies away from critique or questioning.

This explanation makes the phenomena seem villainous, but many of us are prone to committing these crimes—through buzzwords! Buzzwords are terms that catch on because they represent something exciting to a discourse. Then, because they’re popular, they get used frequently, by many people. Because they are somewhat novel, these different uses attach slightly different meanings to the same word. Eventually the buzzword’s overused (reducing the novelty, and therefore the impact of its meaning) and/or overloaded with meaning.

Most of our buzzwords were real things at one point (and sometimes they still are). When buzzwords are used effectively they allow a good conversation to move faster between speakers who have the same mental models about the buzzwords.1

Sometimes, however, buzzwords are said to represent concepts that aren’t fully understood by everyone in the conversation. When my meaning of the word “design thinking” differs from yours, but we both refer to design thinking in conversation nonetheless, we can run into trouble.

In these situations, buzzwords obfuscate the ideas we’re actually talking about. In my experience, we also know when we’re using buzzwords. We can guess at when others are using them, too. As a result, the conversation loses meaning, and we lose trust in the conversation.

# Dealing with buzzwords

So what can we do?

Well, the easy thing to do is to clarify. When you use a phrase with many potential interpretations, try to clarify how you’re using the phrase. When others use words that may have multiple meanings, ask specific questions about what they actually mean. This clarification might seem like extra work, but it only needs to happen when terms are first invoked—and it’ll prevent lost time and energy due to the consequences of thought-termination later on.

More importantly, though, we should try to avoid thought-terminating clichés altogether. Take time to break down the concepts you’re talking about in concrete terms. Explain them in ways you haven’t heard before to avoid relying on trite metaphors and anecdotes. If you can really get at what you mean, your language will be minimally re-interpretable: that is, it should be near-impossible to understand your explanations differently from how you intended.

As a result, your communication will become more impactful. The conversations you participate in will have more novelty, too, making it more exciting to discuss the ideas you’re sharing. This may result in more buzzwords emerging, but that’s okay—use the same approach to break those down, too.

# Beautiful is Good and Good is Reputable: Multiple-Attribute Charity Website Evaluation and Initial Perceptions of Reputation Under the Halo Effect

The halo effect is essentially how positive—but irrelevant—traits influence our perception of what the thing with the halo actually says or does. These authors explored how charities manifest the halo effect on their websites, and find evidence for four varieties of halo effect.

this study employs charity websites as a multi-attribute donation channel consisting of three attributes of information content quality (mission information, financial information, and donation information) and four attributes of system quality (navigability, download speed, visual aesthetics, and security). Based on the proposed framework, this study proposes four types of halos that are relevant to charity website evaluation —collective halo (attribute-to-attribute), aesthetics halo (attribute-to- dimension), reciprocal-quality halo (dimension-to-dimension), and quality halo (dimension-to-dimension)

# Adam Savage on Lists, More Lists, and the Power of Checkboxes

In this Wired article, Adam Savage provides a pragmatic description of how he breaks down complex projects using lists.

In my mind, a list is how I describe and understand the mass of a project, its overall size and the weight that it displaces in the world, but the checkbox can also describe the project’s momentum. And momentum is key to finishing anything.

Momentum isn’t just physical, though. It’s mental, and for me it’s also emotional. I gain so much energy from staring at a bunch of colored-in checkboxes on the left side of a list, that I’ve been known to add things I’ve already done to a list, just to have more checkboxes that are dark than are empty. That sense of forward progress keeps me enthusiastically plugging away at rudimentary, monotonous tasks as well as huge projects that seem like they might never end.

I love the physics metaphor here. There’s lots of other insights to be gained by thinking about how work follows physical principles. For instance, projects also have inertia, friction, and surface area:

1. Inertia. The longer a project sits waiting for you—weighing on your mind—the harder it is to get it moving.
2. Friction. Inertia is driven by initial friction. In parallel, of course, kinetic friction can make it hard to stop working on something. This is why multitasking doesn’t make sense with most projects.
3. Surface area: It can be hard to attack a single, huge project idea, just like how a large ice cube melts slower than many little ones. List making is a key way of breaking up the surface of a project into smaller pieces, making it easier to handle. Increasing surface area also facilitates collaboration: it’s easier to hand off smaller pieces to others, and to put them back together again.

To return to momentum, though, Adam makes an excellent point: breaking down the work helps keep momentum going even when you put the work down.

That may be the greatest attribute of checkboxes and list making, in fact, because there are going to be easy projects and hard projects. With every project, there are going to be easy days and hard days. Every day, there are going to be problems that seem to solve themselves and problems that kick your ass down the stairs and take your lunch money. Progressing as a maker means always pushing yourself through those momentum-killers. A well-made list can be the wedge you need to get the ball rolling, and checkboxes are the footholds that give you the traction you need to keep pushing that ball, and to build momentum toward the finish.

Another point in the article that’s worth emphasizing:

[I]n a project with any amount of complexity, the early stages won’t look at all like the later stages, and [the manager] wanted to take the pressure off any members of the group who may have thought that quality was the goal in the early stages.

I’ve heard this discussed in the context of critique, or “10% feedback”. When sharing work with others, it’s important to disclose the stage the work is at. Typos should be caught at a project that’s basically ready to publish. They shouldn’t even be discussed when a work is being conceptualized. The focus on early stages should be the concepts themselves, and how they fit within the broader context.

Last thing. This is excellent:

There is a famous Haitian proverb about overcoming obstacles: Beyond mountains, more mountains.

🏔

Talks

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# Design management for wicked problems - ADMC 2020

Our toughest problems resist conventional strategies for change. In this talk from Peter Jones and I, we show how designerly approaches—namely methods from systemic design—can help create and implement systemic theories of change. Those theories may then be used to develop effective strategies for wicked problems.

We presented this talk at the Academic Design Management Conference in 2020, and it led to a follow-up paper.

# Applied Systems Thinking

Based on the Applied Systems Thinking workshop, I’ve collected a variety of resources to help you map complex problems below. The buttons link directly to files to save you some trouble. Be mindful that most of these files are published documents or books, so if you really like them, you should buy a copy and support the authors!

If you have questions or if you’re looking for more resources, never hesitate to reach out to me via  ryan@fulcra.design.

# Introduction

What are systems? Interconnected sets of elements whose interactions lead to emergent, “purposeful” behaviour. (A system’s purpose is not necessarily what someone intends of it, though, nor can it be derived from rhetoric about the system. A system’s purpose can only be defined by examining its actual behaviour.)

Systems—and the actors within them—do exactly what they are “designed” to do. That is, systems act perfectly in tune with the structures and incentives that they have. Only by understanding these complex structures and incentives can we begin to make real progress on the challenges we’re addressing.

# Key Things To Remember

1. The most important thing about mapping is not the map itself. It is the conversations that the map (and the mapping process!) can spark.
2. Stay focused on answering complex questions. Mapping is not an end in itself. You are “finished” mapping when you’ve answered your focusing questions (more below).

# Case Studies

• Remember the story of the development worker trying to support water access in rural Malawi. (37.4 kb) By identifying someone else who was working on a similar problem (community health workers), the development worker was able to gain substantial leverage over their problem with minimal effort. Systems work helps is to identify leverage points.
• Remember the story of The After Prison Initiative (TAPI). (37.4 kb) By helping changemakers working on the same issue see the whole system, each was able to recognize the problems with the system that they were responsible for. Systems help us recognize that every participant in a system has responsibility for the whole system, not just their part.
• Remember the story of the spruce budworm. (37.4 kb) The Atlantic Canadian lumber industry made itself addicted to insecticide by beginning and sustaining insecticide sprays before they understood the long-term forest ecosystem. Systemic innovation is often counterintuitive; the wrong fix in the wrong place can make matters worse.
• Remember the story of the well-intended conference organizers. (37.4 kb) This story teaches two lessons. First, systemic problems are rarely shifted by simple solutions. If you account for only one part of the problem, your fix may fail. Second, it is difficult to understand a systemic problem without involving all of the key stakeholders, particularly the beneficiaries you aim to serve. Involve them in order to see the whole system.

# Developing A Focusing Question

# Why Are “How Might We..?” Questions Useful?

• “How” invokes a sense of opportunity. Therefore, “How might we..?” questions are appreciative.
• “Might” invokes a sense of pluralism. Therefore, “How might we..?” questions are open-ended: there is more than one possible solution.
• “We” invokes togetherness. Therefore, “How might we..?” questions are pursued collaboratively, particularly by asking and answering questions with stakeholders.

However, “How might we..?” questions aim to provide solutions. Before we can “solve” systemic issues, however, we must understand them. And unfortunately for us, these are usually  wicked problems.

To understand a problem, we must begin to explore causality. Systemic designers seek to understand complexity by searching for the patterns that cause our problems—and finding the underlying structure of those patterns that enable their persistence.

To that end, David Stroh suggests developing a “focusing question” in systems work. The purpose of systems mapping, he says, is not to map a system; it is to answer the focusing question

A focusing question has the form “Why does this problem persist?” or “Why, despite our best efforts, intentions, and resources, have we been unable to achieve a certain goal or solve a particular problem?”

# FOUR TYPES OF SYSTEMS MAPPING

# Rich Pictures

Rich pictures come from Checkland’s Soft Systems Methodology (SSM). Akin to a sketchy infographic, these maps are illustrated and make heavy use of labels and symbols to help the mapper or the reader understand a messy situation.

# Actor Maps

Actor maps graph the relationships in a social system. Who (or what organizations) influence who? Who funds who? How is the vision of the system determined? By identifying different stakeholders, including who are the most important beneficiaries and victims of a system, systemic designers might catch gaps, missed connections, or other issues.

# Causal Loop Diagrams

Also known as influence diagrams and effect maps, Causal Loop Diagrams graph the phenomena of a system. What are we trying to stop from happening (or what do we want to happen more often)? What encourages or limits those phenomena? Then, what encourages or limits _those_causes or limits? By drawing causal connections between the phenomena of the system, we can recognize the complex interactions that lead to the (frequently counterintuitive) emergent patterns of behaviour normally invisible.

# Stock And Flow Diagrams

How much of what quantities flow at what rates? Stock and flow diagrams make explicit the system’s stores (e.g., the heat in a cup of coffee) and its rates of change (e.g., how quickly heat escapes from the cup). These diagrams also recognize what controls these rates of change.

# Applied Systems Thinking

# Dimensions Of A System:

Add detail to your systems maps by exploring the different dimensions along which influence might flow: wealth, power, values, knowledge, or beauty. Different types of obstructions—poverty, maldistribution, and insecurity—can cause different types of problems in each of these dimensions.

# Leverage Points:

Leverage points are places within a system with which a little effort yields great reward. Likewise, bottlenecks are places within a system which resistance could cause significant problems.

# Leverage Points:

Leverage points are places within a system with which a little effort yields great reward. Likewise, bottlenecks are places within a system which resistance could cause significant problems.

# Systems Archetypes:

Systems archetypes are common patterns identified in causal loop diagrams or stock-and-flow diagrams. Archetypes exhibit similar behaviours and can be resolved by similar solutions.

# The Systems “Business Idea”:

Do you need a particular actor or phenomena to receive resources/power/etc.? Where would that resource come from? What influences how much of the resource gets distributed? How can you increase those influencing forces? The business idea uses a causal loop diagram to map the systemic structure of an organization’s strategic sustainability. It makes explicit the phenomena that generate resources for the system to reinvest—and the strategic competencies that the organization can use to enhance those phenomena.

# Systemic Theories Of Change:

What is the change strategy you’re adopting? Similar to the business idea, a systemic theory of change plots a theory of change model in systemic form, identifying the goal phenomena to enhance (or limit), the key activities that can support that enhancement (or limitation), and the inputs required to sustain and scale those activities.

# Systems Stories:

Never explain a systems map in a pitch or to a general audience. Instead, follow the iceberg model to distill a systems story

1. Describe what happened (an example of the event or phenomena the systemic designer seeks to address);
2. Describe what has been happening (the pattern of events that lead to the problem or issue); and
3. Describe why (the underlying causal structure that enforces the persistence of these problematic patterns).

# Technology For Systems Mapping

Mural

Mural.co is a collaborative tool for design sprints. As such, it provides features for collaborative whiteboarding and sticky noting, voting via dotmocracy, and a variety of other neat and helpful tools. It is very free-form (and as such has no features specifically made for systemic design) but that open-endedness may be useful.

Loopy

Nicky Case’s  Loopy is a simple tool that allows you to simulate systemic behaviours. It is very unsophisticated (e.g., it is challenging to provide precise system settings) but it is extremely gestural and is therefore fun to use to illustrate and explore ideas.

Plectica

Plectica is a “visual mapping software”. It allows you to nest and draw connections between cards representing anything. The goal of the app is to provide a simple interface for complex ideas.

Kumu

Kumu is a web app built specifically for systems mapping. It  features extensive features and documentation and a lively support community full of fellow systems mappers who like to help one another. The developers/founders are active participants in that community and regularly provide customer support, too. Develop actor maps, systems maps, and all kinds of other interesting interactive visuals with Kumu.

I’ve collected and described resources on related topics at https://systemic.design/resources. In particular, you may want to check out the items on organizational change (e.g., the “Notes on Leadership and Language in Regenerating Organizations” paper and the article on organizational learning).

• Innovation is a buzzword

Notes, slides, and the Innovation Auditing guide presented at the talk are found below.

# The research

The research presented during the talk is discussed on the following pages:

# Slides

Find a PDF of the slides I presented at the link below. Beware: the animations don’t translate well to print, so some of the pages have graphical issues.

# Innovation Auditing

Innovation Auditing is a simple procedure that individuals, organizations, and governments can use to detect the gaps in the innovation process they seek to support.

See the PDF guide by clicking the link below.

Tools

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• Why the grass is greener: Making sure that shiny new alternative tool is actually going to help you

“The grass is always greener on the other side.” The popular idiom discourages whoever’s listening from seeking out alternatives, suggesting that other options always look better from wherever we’re currently standing. But it has a funny problem: nobody ever explains why the grass is greener on the other side.

That’s because it isn’t. The truth is that your side is just yellower/trampled on/eaten… and that’s because you’re on it.

Moving to a different place will be fine at first. Then you’ll use it, too, and eventually it’ll look the same as where you started.

(In this metaphor, you’re a goat. 🐐)

In workflow design, in addition to the novelty of “shiny new object,” new and alternative tools are great simply because they don’t have the cruft you’ve built up in the old tool. That cruft might be noisy notes, a lifetime of guilt-inducing task management, or even just bad habits and behaviours. The problem isn’t the tool. It isn’t you, either. It’s you and the tool.

So, after switching, the problems seem to go away… only to re-emerge (possibly in a new form) later because the issues are generated by your usage, not by the tool.

The solution is to fall in love with the problem, not the (shiny, potential) solutions.

1. Determine what your issues actually are, and try to figure out why they’re happening.
2. Then, abstractly identify how you might be able to mitigate the problems.
• Don’t say “I’ll use Bunch,” say “If I standardize certain work spaces on my computer, I can develop muscle memory for using those workspaces, reducing distraction and allowing me to spend less cognitive energy on finding everything I need to get engaged.”
3. Last, identify some tests or success conditions that will tell you whether the solution is actually working. This’ll help minimize irrational perspectives on how well the honeymoon stage is going.

Only after taking those three steps should you choose a tool. Find something that can implement the abstract principles you’ve articulated, and be sure to follow-through on the tests.

In doing this, you’re actually creating and implementing a rough design theory. You’re using design science to make your work as easy and engaging as it can be! High-five for that.

# Systems Practice, Abridged

For serious system mapping work, spending [significant] time studying, thinking about, and mapping your system helps ensure you are addressing root causes rather than instituting quick fixes. In the long term, the time and resources you invest in Systems Practice will pay dividends.

But what if youʼre not quite sold on the Systems Practice methodology yet? What if you havenʼt encountered systems thinking before and just want to dip your toes in? Or what if youʼre an expert or an educator with only a few hours to introduce Systems Practice to a fresh new group of systems thinkers?

I have been in the latter situation, and it’s a challenge. In my experience, people who are wholly new to systems thinking can take a lot of time to acclimate to the mindset. But! If, as a teacher, you can’t illustrate the benefits quickly, it’s easy to disengage.

So, I’m glad this exists. This is a wonderful new resource from Kumu’s Alex Vipond that helps walk you through systems and Kumu’s tools at the same time.

3 notes with this tag

• What part of 'viral' content makes platforms want to encourage its spread?

The Twttr prototype app gave me another feedback form today. It’s been my habit to complain, at every opportunity, about the trends page you have to engage with whenever you go to the Search tab. I feel a little bad for the designers and developers, because the beta is really all about how conversations on Twitter look and feel. Still, this feedback form was no different. Here’s what I wrote in the “Dislike” section:

I wish I could control the trends page.

It is the absolute worst part of my Twitter experience. It just feels… unhealthy. Like going through a grocery store magazine aisle. Sure, some of the headings are instructive or inspiring, but many are gross, irrelevant, or completely malignant gossip.

The experience is also invasive. Because trends are forced upon you when you intend on searching for something specific, and because they’re algorithmically-tunes to be as attention grabbing as possible, it’s easy to be distracted and forget why you even entered the search pane. I never explicitly consent to learning about celebrity gossip or US politics when I use Twitter. If I tap on some of those topics, it’s not because I want to. It’s because it’s malicious click bait. In turn, it’s corrupt to design an experience that drags the user through it repeatedly.

Sure, this content is viral. But shouldn’t we be inoculating against viruses, not encouraging them to spread?

• Twitter announces Bluesky: a team seeking and developing an open standard for social media

Twitter is funding a small independent team of up to five open source architects, engineers, and designers to develop an open and decentralized standard for social media. The goal is for Twitter to ultimately be a client of this standard. 🧵

The thread is worth the read, as are some of the comments. There’s a few interesting resources shared within, including a couple of articles from Jack and a few existing open standards.

• Elon Musk attempts to explain Twitter to normal people in court

Every part of this trial sounds made up. They should just air it in lieu of a Good Fight episode. Elizabeth Lopatto’s writeup is worth worshipping.

Spiro then coined the worst acronym I’ve heard in years, and I edit stories about aerospace so I know from bad acronyms. It is: JDART, for joking, deleted, apologized-for, responsive tweets.

Incredible.

But there’s at least one abstract takeaway that’s interesting to me:

At this point, Wood tried to enter an email exchange into evidence, resulting in a great deal of confusion on Judge Wilson’s part about how email reply chains work. (You read from the bottom.)

[…]

At this point, the “pedo guy” Twitter thread was entered into evidence, and the befuddled court had to be told that the reply chains work the other way on Twitter — the first tweet is at the top, and the last tweet is at the bottom.

Yet another example of the ways in which the world’s accelerating faster than many institutions can keep up.

Automation

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• Automatically download Reminders into your Obsidian notes with Shortcuts

Want a quick, hands-free, one-step method to capture reminders and tasks into Obsidian? Take advantage of Reminders, Shortcuts, and Shortcuts’s automations feature.

This Shortcut will extract all reminders currently incomplete in a given list and append them to your daily note.

Here’s a screenshot of the full Shortcut

Download it and set it up (i.e., answer all of the configuration questions). Then, create Shortcuts automations (via the Automations tab in Shortcuts) that run on whatever triggers you want (e.g., “Whenever the Obsidian app is opened” and “9am”). Add a “Run Shortcut” action to that automation, then select the shortcut you’ve just configured.

🎉! Whenever the shortcut is triggered, the reminders in the designated list will be added to your daily note.

You can now say e.g., “Hey Siri, add ‘Pick up milk’ to my Obsidian list,” and that item will (eventually) be added to your daily note.

• A Keyboard Maestro macro for quickly and easily opening published notes in Obsidian

Similar to Notes/A Shortcut for quickly and easily opening published notes in Obsidian, this macro makes it easy to jump from viewing a published note on the web to editing it in Obsidian.

Don’t forget to switch Mainframe to your vault’s name!

I have it tied to a Stream Deck button, but you can configure it to trigger however you’d like.

See a screenshot of the macro

• A Shortcut for quickly and easily opening published notes in Obsidian

If you publish your notes to the web in any way and you are on iOS/macOS, here’s a simple shortcut that lets you quickly and easily open a note from your website in Obsidian:

See the shortcut in action

Climate change

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• ∎ Mexico bans solar geoengineering experiments after startup’s field tests - Reading Session 202301191446

The company, called Make Sunsets, conducted the field tests without prior notice or consent from the Mexican government.

This is one of the scary consequences of democratizing technology: volatility. It is getting easier for small teams to take big actions without oversight.

And this is a well-intended initiative. The opposite of this would be ecological or environmental terrorism against businesses or governments perceived to be direct contributors to climate change, which surely will happen as climate change advances and people get desperate.

At least this test was small:

Iseman says he launched two balloons in Baja California last year, each carrying less than 10 grams of sulfur dioxide. That’s a tiny amount of the compound that’s typically released into the air by fossil fuel power plants and volcanoes in much larger quantities — so the release isn’t likely to have had much impact.

The business model is interesting:

Founded in October 2022, Make Sunsets started with the grandiose vision of releasing enough sulfur dioxide to offset global warming from all the world’s CO2 emissions annually. It’s already selling “cooling credits” for the service at $10 per gram of sulfur dioxide — even though it has yet to achieve any measurable impact and can’t guarantee that releasing sulfur dioxide at a bigger scale wouldn’t trigger any unintended problems. This has obvious parallels with Climeworks, who was recently paid by a few big tech companies to pull carbon from the atmosphere. It is hard to imagine this business model working at scale, though… surely there is a kind of prisoner’s dilemma at play that will keep every company from chipping in. Perhaps we need regulators to require businesses to purchase credits like these to properly recognize the environmental costs of business. • Microsoft wants to capture all of the carbon dioxide it’s ever emitted The most audacious commitment from Microsoft is its push to take carbon out of the atmosphere. The company is putting its faith in nascent technology, and it’s injecting a significant investment into a still controversial climate solution. Proponents of carbon capture, like Friedmann, say that the technology is mature enough to accomplish Microsoft’s aims. It’s just way too expensive right now. Microsoft’s backing — and its$1 billion infusion of cash — could ultimately make the tech cheaper and more appealing to other companies looking for new ways to go green.

Fantastic news. Carbon capture is a key opportunity for decelerating climate change. Hopefully more companies follow suit.

Conversations

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Creativity

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# Intuition is confident abductive-inferential thinking

In a recent episode of Hello Monday, Jessi Hempel interviews Dr. Natalie Nixon on creativity and her new book, The Creativity Leap. Natalie’s PhD in Design Management—plus her work in fashion, design, and business—led her to a catchy and compelling description of creative work. We accomplish creative work, she says, “by toggling between wonder and rigour.”

In the podcast conversation, Jessi and Natalie talk about intuition—and I was struck by something. “We don’t talk about intuition,” Natalie notes at about 6 minutes in. “We don’t talk about intuition in business school, in law school, or in medical school.” And yet, she says, “I observed that really successful leaders—especially really successful startup leaders—in their origin stories, there’s always this moment where ‘Something told me not to do the deal. Something told me to work with her over him.’ […] Every successful leader really reckons with incorporating acting on their intuition to make decisions.” Jessi agrees, noting that intuition comes up often in her interviews with leaders on Hello Monday as leaders cite it as the reason for their success.

The thing is, just because we don’t name intuition doesn’t mean we aren’t talking about it. That’s because intuition is really just confident, logical thinking.

Charles Sanders Peirce was a philosopher. He investigated how we inquire into and discover new knowledge.1 Before Peirce, we generally recognized the logical processes of deduction and induction. Deductive thinking helps us identify what must be true about a situation in order to explain it. When we deduce something, we look at the general rules and principles we know of and draw specific conclusions from that evidence. Inductive thinking involves drawing general conclusions from specific, limited evidence.

Peirce argued that effective reasoning follows a pattern: we determine the specific consequences of an idea (deduction), and then we judge whether the available evidence fits that idea and its consequences (induction). But how do we develop ideas?2

Abduction is the name of the logical process Peirce described for developing ideas. To think abductively means to generate and choose ideas that fit the situation at hand. A good idea should be verifiable—we should be able to use evidence to judge its fit—and should help us resolve the situation at hand. Peirce also had criteria to help choose the best ideas to test. He suggested that we should strive to conserve resources (e.g., those that most are most efficiently verifiable and usable in the situation), identify the most valuable ideas (specifically the “uberty” of an idea, or how likely it is that a possible idea might bring about an innovation), and the most relevant ideas (e.g., those that may apply beyond our current focus, too).3

Abduction is clearly an important step in any innovative process—but it is no more important than testing and using the ideas you generate. What, then, if you don’t have enough evidence to truly test and prove your ideas?

The process Peirce described—abduction, deduction, induction—is the ideal. However, we do not always have time and energy to follow the process diligently. Instead, we quickly make creative judgements based on a few observed qualities. This requires two related processes.4 The first Peirce called “abductory induction,” and it combines the first and last step of the inquiry process. We observe the qualities of the situation, and we generate possible ideas to resolve it based on those observations. The second process is known as “inference to the best explanation” (IBE).5 IBE is exactly what it sounds like. Given a number of possible ways of resolving a problem, choose the best one. (Peirce’s criteria, noted above, apply here.)

So what does all this have to do with intuition?

Intuition is the confident application of these shorthand logical approaches to creative problem solving. As Jessi and Natalie noted, we aren’t often explicitly taught about strengthening our intuition. Yet, everything we learn supports its development. The more we have to draw on in order to pull into the processes described above, the better our intuitive decisions will be.

I say that intuition is the confident application of these processes because they only work when we follow through. In reality, we use abductory induction and IBE all the time. When we engage in creative problem solving, we’re not only using information from the evidence in front of us. We’re drawing on our lived experience and our knowledge base. Even if we don’t directly recall or reference that background information, it is drawn into the creativity of abduction and it defines the general rules and principles we use in deduction. It provides us with the heuristics we use when engaging in IBE. But if we don’t have a bias towards action and instead operate with e.g., perfectionism, we fail to actually execute on these ideas. Thus, we need to have confidence in our abductory induction and IBE processes.

All this is simply a gentle challenge of the idea that we don’t talk about intuition. I think that all knowledge management practices and forms of education are actually fundamentally about strengthening our intuition.

That said, Natalie’s work is fascinating. I recommend the episode of Hello Monday and plan on picking up her book!

1. In this article, my reading of Peirce comes from the writing of William Mcauliffe↩︎

2. Peirce was actually specifically concerned with science and hypotheses generation, selection, and testing. Here I refer to generating, selecting, testing, and using ideas to apply these concepts to problem-solving more broadly. ↩︎

3. He also cautioned not to produce ideas that stop the inquiry process—e.g., magical thinking, or by suggesting that whatever happened must be a complete mystery. ↩︎

4. Actually, the difference between these two processes is the subject of substantive, controversial debate. This is in part because the scholars who study inference to the best explanation have also used Peirce’s term “abduction” to describe it. This understandably caused extensive confusion, but also probably a lot of philosophical debates and scholarship, so maybe it was for the best. ↩︎

• DeepMindʼs StarCraft 2 AI is now better than 99.8 percent of all human players

Incredible achievement, but it makes me wonder—what are the .2% of humans doing differently?

These stories of AI achievement are sure to proliferate in the coming years. By focusing on those people who are still able to think around machine learning strategies, we might learn something about how humans and machines can best complement each other.

Ethics

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# Finding the Emic in Systemic Design

A paper presented at RSD7 in Turin, Italy.

# ABSTRACT

I argue that an under-emphasized but crucial variable of success in systemic design is the perspective through which systemic design processes are implemented and executed. While rooted in design (a consciously empathetic discipline, especially in recent years; cf. Kimbell, 2011), it is easy for systemic designers to conduct the research required for their projects in externalized ways. These approaches risk misrepresenting the stakeholders who contribute to projects and, in turn, they are a danger to the potential impact of these misresearched problem systems. I propose to advance a theoretical argument for this danger, the development of an assessment framework to check whether an internalized perspective has been effectively achieved, and provide a proof of concept of this framework through hermeneutic case study analysis.

As I will show, systemic design processes that are not executed with the direct and explicit engagement of stakeholders – to the extent of achieving an emic (or from within) understanding of the system – may be flawed at their foundation. By fostering recognition of the importance of an emic perspective, and by providing a framework of principles, practices, and process to accomplish systemic design with this perspective, I hope to ensure that systemic design processes are as accurate and valid as possible with respect to the stakeholders of the system.

This is not to suggest that systemic design practice is “too etic”. In fact, with roots in design, systemic design is often deliberately emic. Systemic designers make use of designerly tools that help the researcher to build empathy with system stakeholders (e.g., soft systems methodology, critical systems heuristics, appreciative inquiry; Jones, 2014). They often seek to engage stakeholders in the systemic design process and include reflective analysis of what has been learned in order to assess where deeper engagement with the system is required (Ryan, 2014). That said, with the advent of crowdsourcing (the facilitated involvement of the general public in problem solving, usually using online tools; Lukyanenko & Parsons, 2012) and data science (the use of computational tools to analyze and understand large quantities of data; cf. Scepanovic, 2018), it is likely that data-driven methods will increasingly influence systemic design practice. One recent example sought input from hundreds of people to identify opportunities for change in Canadian post-secondary systems through an iterative online survey (cf. Second Muse, Intel, & Vibrant Data, 2016). This data-driven direction is a powerful opportunity, of course, but it underscores the need to develop principles and best practices for assessing and supporting emic understanding as we gain more data from these tools.

This proposal consists of two steps. First, I will look to the principles and theorists of ethnography to develop a framework for assessing the emic/etic perspective of a given research project. Namely, Geertz’ “Thick Description: Toward an Interpretive Theory of Culture” (found in The Interpretation of Cultures, 1973, chapter 1) provides a foundation for the process of emic research, while Creswell and Miller (2000) provide a set of procedural principles for emic validity. Taken together, we generate a critical research framework with which we may assess a given research project’s emic perspective. Second, I will provide a proof-of-concept of this framework (and its theoretical underpinnings) via a casebased assessment of three systemic design projects. Case studies provide an effective venue for learning about the context-dependent manifestations of the phenomena being studied (Flyvbjerg, 2006). One of these case studies is one I have developed through my experience in participating and contributing to the development of the Canadian National Youth Leadership and Innovation Strategy framework, which convened hundreds of youth and youth-serving organizations in order to understand the youth leadership and innovation system in Canada (cf. MaRS Studio Y, 2017). The second and third case studies are those profiled by Ryan and Leung (2014).

In order to interpret and analyze the chosen case studies, I turn to the methodology of phenomenological hermeneutics (Eberle, 2014, p. 196; cf. Wernet, 2014). Phenomenological hermeneutics are appropriate as I have access to the described phenomena of the systemic design projects captured by the chosen cases, but these phenomena are not explicitly captured with reference to emic or etic perspectives – thus some construction of the inherent emic or etic data is necessary in order to make judgments about the perspectives found in the projects.

In each case, I will use identify phenomena representing the practice of emic (or etic) understanding in the research orientation of the work, as acknowledged by the above framework. In each case, I will examine the step-by-step procedure and any associated notes about the experience of the researchers and participants involved. In each step or experience, I will look for evidence of the four steps of emic understanding or the six techniques of emic validation reported above.

# References

Creswell, J. W., & Miller, D. L. (2000). Determining Validity in Qualitative Inquiry. Theory Into Practice, 39(3), 124–130. https://doi.org/10.1207/s15430421tip3903_2

Eberle, T. S. (2014). Phenomenology as a Research Method. In U. Flick (Ed.), The SAGE Handbook of Qualitative Data Analysis (pp. 184–202). Los Angeles, Calif. [u.a.]: Sage. Retrieved from https://www.alexandria.unisg.ch/228374/

Flyvbjerg, B. (2006). Five Misunderstandings About Case-Study Research. Qualitative Inquiry, 12(2), 219245. https://doi.org/10.1177/1077800405284363

Geertz, C. (1973). The interpretation of cultures: Selected essays (Vol. 5019). Basic books.

Jones, P. (2015). Design Research Methods for Systemic Design: Perspectives from Design Education and Practice. Proceedings of the 58th Annual Meeting of the ISSS - 2014 United States, 1(1). Retrieved from http://journals.isss.org/index.php/proceedings58th/article/view/2353

Kimbell, L. (2011). Rethinking Design Thinking: Part I. Design and Culture, 3(3), 285–306. https://doi.org/10.2752/175470811X13071166525216

Lukyanenko, R., & Parsons, J. (2012). Conceptual modeling principles for crowdsourcing (pp. 3–6). ACM. https://doi.org/10.1145/2390034.2390038

MaRS Studio Y. (2017). A strategic framework for youth leadership & innovation in Canada: Insights from the 2016 National Youth Leadership and Innovation Strategy Summit. Toronto, ON. Retrieved from http://www.studioy.marsdd.com/wp-content/uploads/2016/12/MaRS_NYLISstrategic_framework_Final.pdf

Ryan, A. (2014). A Framework for Systemic Design. FORMakademisk–research Journal for Design and Design Education, 7(4). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/787

Ryan, A., & Leung, M. (2014). Systemic Design: Two Canadian Case Studies. FormAkademisk - Research Journal of Design and Design Education, 7(3). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/794

Scepanovic, S. (2018). Data science for sociotechnical systems - from computational sociolinguistics to the smart grid. Aalto University. Retrieved from https://aaltodoc.aalto.fi:443/handle/123456789/30187

Second Muse, Intel, & Vibrant Data. (2016, May 11). What Your Data Says: Post-Secondary Education Mapping Survey Highlights. RECODE. Retrieved from http://re-code.ca/whats_happening/watch-recodewebinar-what-your-data-says/

Wernet, A. (2014). Hermeneutics and Objective Hermeneutics. In U. Flick, The SAGE Handbook of Qualitative Data Analysis (pp. 234–246). SAGE Publications, Inc. https://doi.org/10.4135/9781446282243.n16

# Creative Education Futures

What are the futures of art and design schools in Canada?

In 2015, I supported Kinetic Café in developing OCAD University’s latest Vision and Mission statements. As part of that work, I helped scan for signals, trends, and drivers in art and design school futures. Our scan revealed five important drivers of change: reforming education, creative economies and cultures, new geographies, empowering technologies, and conscious collective.

A walkthrough of this work is visualized and embedded below. If it doesn’t display, you can visit it directly here.

Ethnography

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# Finding the Emic in Systemic Design

A paper presented at RSD7 in Turin, Italy.

# ABSTRACT

I argue that an under-emphasized but crucial variable of success in systemic design is the perspective through which systemic design processes are implemented and executed. While rooted in design (a consciously empathetic discipline, especially in recent years; cf. Kimbell, 2011), it is easy for systemic designers to conduct the research required for their projects in externalized ways. These approaches risk misrepresenting the stakeholders who contribute to projects and, in turn, they are a danger to the potential impact of these misresearched problem systems. I propose to advance a theoretical argument for this danger, the development of an assessment framework to check whether an internalized perspective has been effectively achieved, and provide a proof of concept of this framework through hermeneutic case study analysis.

As I will show, systemic design processes that are not executed with the direct and explicit engagement of stakeholders – to the extent of achieving an emic (or from within) understanding of the system – may be flawed at their foundation. By fostering recognition of the importance of an emic perspective, and by providing a framework of principles, practices, and process to accomplish systemic design with this perspective, I hope to ensure that systemic design processes are as accurate and valid as possible with respect to the stakeholders of the system.

This is not to suggest that systemic design practice is “too etic”. In fact, with roots in design, systemic design is often deliberately emic. Systemic designers make use of designerly tools that help the researcher to build empathy with system stakeholders (e.g., soft systems methodology, critical systems heuristics, appreciative inquiry; Jones, 2014). They often seek to engage stakeholders in the systemic design process and include reflective analysis of what has been learned in order to assess where deeper engagement with the system is required (Ryan, 2014). That said, with the advent of crowdsourcing (the facilitated involvement of the general public in problem solving, usually using online tools; Lukyanenko & Parsons, 2012) and data science (the use of computational tools to analyze and understand large quantities of data; cf. Scepanovic, 2018), it is likely that data-driven methods will increasingly influence systemic design practice. One recent example sought input from hundreds of people to identify opportunities for change in Canadian post-secondary systems through an iterative online survey (cf. Second Muse, Intel, & Vibrant Data, 2016). This data-driven direction is a powerful opportunity, of course, but it underscores the need to develop principles and best practices for assessing and supporting emic understanding as we gain more data from these tools.

This proposal consists of two steps. First, I will look to the principles and theorists of ethnography to develop a framework for assessing the emic/etic perspective of a given research project. Namely, Geertz’ “Thick Description: Toward an Interpretive Theory of Culture” (found in The Interpretation of Cultures, 1973, chapter 1) provides a foundation for the process of emic research, while Creswell and Miller (2000) provide a set of procedural principles for emic validity. Taken together, we generate a critical research framework with which we may assess a given research project’s emic perspective. Second, I will provide a proof-of-concept of this framework (and its theoretical underpinnings) via a casebased assessment of three systemic design projects. Case studies provide an effective venue for learning about the context-dependent manifestations of the phenomena being studied (Flyvbjerg, 2006). One of these case studies is one I have developed through my experience in participating and contributing to the development of the Canadian National Youth Leadership and Innovation Strategy framework, which convened hundreds of youth and youth-serving organizations in order to understand the youth leadership and innovation system in Canada (cf. MaRS Studio Y, 2017). The second and third case studies are those profiled by Ryan and Leung (2014).

In order to interpret and analyze the chosen case studies, I turn to the methodology of phenomenological hermeneutics (Eberle, 2014, p. 196; cf. Wernet, 2014). Phenomenological hermeneutics are appropriate as I have access to the described phenomena of the systemic design projects captured by the chosen cases, but these phenomena are not explicitly captured with reference to emic or etic perspectives – thus some construction of the inherent emic or etic data is necessary in order to make judgments about the perspectives found in the projects.

In each case, I will use identify phenomena representing the practice of emic (or etic) understanding in the research orientation of the work, as acknowledged by the above framework. In each case, I will examine the step-by-step procedure and any associated notes about the experience of the researchers and participants involved. In each step or experience, I will look for evidence of the four steps of emic understanding or the six techniques of emic validation reported above.

# References

Creswell, J. W., & Miller, D. L. (2000). Determining Validity in Qualitative Inquiry. Theory Into Practice, 39(3), 124–130. https://doi.org/10.1207/s15430421tip3903_2

Eberle, T. S. (2014). Phenomenology as a Research Method. In U. Flick (Ed.), The SAGE Handbook of Qualitative Data Analysis (pp. 184–202). Los Angeles, Calif. [u.a.]: Sage. Retrieved from https://www.alexandria.unisg.ch/228374/

Flyvbjerg, B. (2006). Five Misunderstandings About Case-Study Research. Qualitative Inquiry, 12(2), 219245. https://doi.org/10.1177/1077800405284363

Geertz, C. (1973). The interpretation of cultures: Selected essays (Vol. 5019). Basic books.

Jones, P. (2015). Design Research Methods for Systemic Design: Perspectives from Design Education and Practice. Proceedings of the 58th Annual Meeting of the ISSS - 2014 United States, 1(1). Retrieved from http://journals.isss.org/index.php/proceedings58th/article/view/2353

Kimbell, L. (2011). Rethinking Design Thinking: Part I. Design and Culture, 3(3), 285–306. https://doi.org/10.2752/175470811X13071166525216

Lukyanenko, R., & Parsons, J. (2012). Conceptual modeling principles for crowdsourcing (pp. 3–6). ACM. https://doi.org/10.1145/2390034.2390038

MaRS Studio Y. (2017). A strategic framework for youth leadership & innovation in Canada: Insights from the 2016 National Youth Leadership and Innovation Strategy Summit. Toronto, ON. Retrieved from http://www.studioy.marsdd.com/wp-content/uploads/2016/12/MaRS_NYLISstrategic_framework_Final.pdf

Ryan, A. (2014). A Framework for Systemic Design. FORMakademisk–research Journal for Design and Design Education, 7(4). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/787

Ryan, A., & Leung, M. (2014). Systemic Design: Two Canadian Case Studies. FormAkademisk - Research Journal of Design and Design Education, 7(3). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/794

Scepanovic, S. (2018). Data science for sociotechnical systems - from computational sociolinguistics to the smart grid. Aalto University. Retrieved from https://aaltodoc.aalto.fi:443/handle/123456789/30187

Second Muse, Intel, & Vibrant Data. (2016, May 11). What Your Data Says: Post-Secondary Education Mapping Survey Highlights. RECODE. Retrieved from http://re-code.ca/whats_happening/watch-recodewebinar-what-your-data-says/

Wernet, A. (2014). Hermeneutics and Objective Hermeneutics. In U. Flick, The SAGE Handbook of Qualitative Data Analysis (pp. 234–246). SAGE Publications, Inc. https://doi.org/10.4135/9781446282243.n16

# Creative Education Futures

What are the futures of art and design schools in Canada?

In 2015, I supported Kinetic Café in developing OCAD University’s latest Vision and Mission statements. As part of that work, I helped scan for signals, trends, and drivers in art and design school futures. Our scan revealed five important drivers of change: reforming education, creative economies and cultures, new geographies, empowering technologies, and conscious collective.

A walkthrough of this work is visualized and embedded below. If it doesn’t display, you can visit it directly here.

Futures

2 notes with this tag

# Resources

Updated Nov 14, 2019

Below I’m collecting a set of resources dealing with a variety of topics for shareable reference—a sort of living, semi-public annotated bibliography. Many of these readings should be accessible via a library or a good Internet search, but if you find something here that shouldn’t be this easy to download, feel free to contact me and I’ll remove it. Or, if you come across any broken links, please let me know!

# Getting Started with Systemic Innovation

Kudoz’ Where Are You Scaling? Placemat (2017) KudozWhere Are You Scaling? “placemat” is an explorable tool to help think through what scaling really means in a given venture. It builds upon Riddell & Moore’s (2015) Scaling Out, Scaling Up, and Scaling Deep in expanding our notion of scaling. When you hear the word “scale” in a conventional conversation, the meaning is likely synonymous with scaling out: reaching more people (stakeholders or customers) with the product, service, program, or policy at the heart of the conversation. Yet there are other underappreciated aspects of scaling: some are required in order to successfully scale out, while others are different ways of achieving impact—maybe scaling out isn’t the best route to take after all! Scaling up, for instance, refers to reaching higher in power hierarchies in order to implement higher-level solutions to the problem you’re addressing. Scaling deep means to reach the same people you’re already reaching more deeply, or with greater impact. Kudoz introduces two more concepts: scaling infrastructure, or building out more tools and supports to make the work more effective and sustainable; and scaling scree, or lending support and legitimacy to other, different actors and initiatives addressing the same issues you are.

Mulgan & Leadbeater’s Systemic Innovation (2013) While the above concepts help make concrete the different ways an intervention might change a system, Mulgan and Leadbeater’s (2013) discussion paper on systemic innovation dives a bit deeper into theory. They link the practice of systems thinking to approaches to innovation, providing a framework for “joining up” a set of innovations in order to achieve systemic change.

# Getting Started with Social Innovation

Mulgan’s Social Innovation: What It Is, Why It Matters, And How It Can Be Accelerated (2007) Geoff Mulgan offers a comprehensive yet down-to-Earth guide to social innovation. The reading really helps communicate what the differences are between social innovation and conventional innovation with practical examples.

Phills Et Al.‘S Rediscovering Social Innovation (2008) The Stanford Social Innovation Review has been one of the preeminent publishers on social innovation since its inception in the early 2000’s. In this review Phills et al. summarize a brief history on social innovation itself while paving a way forward in research and practice.

# Getting Started with Design

What is “design”, really? It’s easy to think that design is the layout of graphics or illustrations—perhaps even making decisions about layouts, as in architecture. These disciplines—graphic design and architecture—certainly leverage design, and many people employed in these industries are designers. Yet these disciplines do not fully capture what design is, thus we should not limit the understanding and application of design to these industries.

The term design shares latin roots with designation. To design is therefore to mark; to frame. Framing means to view a given problem or system from different perspectives in order to deeply understand it and, in turn, to develop novel ways of doing something about it or with it. To become a better designer, you must get better at both analyzing and creating frames.

# Getting Started with Systems Thinking

Systems thinking is most useful when applied to complex, chronic issues: “wicked problems” that resist taming through conventional approaches. David Stroh, who wrote  Systems Thinking for Social Change, argues that effective systems initiatives begin with a focusing question: a question that bounds the project (so that you don’t spend forever debating about where the problem system really ends) and anchors your systems-understanding work in a framing that you can return to if you get lost. This is a question of the form “Why, despite our best efforts and intentions, does [x] persist?” or “…have we not reached our goal of [y]?”—where [x] and [y] are phenomena that remain unassailable through conventional initiatives.

Goodman, Kemeny & Roberts’ The Language Of Systems Thinking (2000) The Language of Systems Thinking introduces the reader to reinforcing and balancing loops using simple examples.

Braun’s The Systems Archetypes (2002) Systems archetypes extend the links and loops of basic systems thinking into more complicated structures – and in doing so, begin to share with the reader deeper insights into the counterintuitive behaviour of the systems we work with.

Donella Meadows’ Leverage Points: Places To Intervene In A System (1997) With robust systemic models, we can begin to identify leverage points: key phenomena that have great potential for change throughout the system.

# Getting Started with Futures Thinking

Jim Dator’s What Futures Studies Is, And Is Not (1995) What Futures Studies Is, and Is Not is a wonderful introductory and reader-friendly summary of futures thinking.

Choo’s The Art Of Scanning The Environment (1999) Chun Wei Choo’s The Art of Scanning the Environment offers a walkthrough of scanning practices.

Bishop, Hines & Collins’ The Current State Of Scenario Development (2007) The Current State of Scenario Development provides a comprehensive review of scenario development approaches and techniques.

# Deeper Reading: Organizational Change

Dubberly Et Al.‘S Notes On The Role Of Leadership & Language In Regenerating Organizations (2002) Hugh Dubberly and a suite of colleagues provide an elegant—poetic, even—walkthrough of how change happens to organizations through their language. They reframe an organization as a continuous set of conversations between people, in turn showing the power of changing the language those people use in order to change the nature of the organization itself.

Weick & Westley’s Organizational Learning: Affirming An Oxymoron (1999) Karl Weick and Frances Westley attack the very idea of organizational learning by showing how “organizing” and “learning” are, in fact, opposing processes. To organize is to order; to learn is to disrupt. Success in organizational change is therefore rooted in a leader’s ability to handle the tension between organizing and learning. Too much organizing and the organization will miss opportunity in change—but too much learning and the organization might not be stable enough to survive.

Gawde’s Learning From Systems Thinking (2017) How can systems thinking help with changemaking in an organization? Writing for People Matters, Sanjay Gawde provides a succinct argument and explanation linking systems approaches to organizational change.

# 2019 Tech Trends Report – The Future Today Institute

This report is intentionally broad and robust. We have included a list of adjacent uncertainties, a detailed analysis of 315 tech trends, a collection of weak signals for 2020, and more than four dozen scenarios describing plausible near futures.

Impressive work. I particularly like the CIPHER heuristic they use in analysis signals: contradictions, infections, practices, hacks, extremes, rarities.

Personal knowledge management

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Privacy

2 notes with this tag

• Starting the Decade by Giving You More Control Over Your Privacy

My bank, fitness and workout apps, and food delivery services I haven’t used in months—those were some of the 30+ apps interacting with Facebook data. Ostensibly this data is used to personalize ads.

As of today, our Off-Facebook Activity tool is available to people on Facebook around the world. Other businesses send us information about your activity on their sites and we use that information to show you ads that are relevant to you. Now you can see a summary of that information and clear it from your account if you want to.

Off-Facebook Activity marks a new level of transparency and control. We’ve been working on this for a while because we had to rebuild some of our systems to make this possible.

Now, thankfully, you can review these connections yourself and clear any history manually. Check out Facebook’s Off-Facebook Activity controls, and happy Data Privacy Day.

• Leaked Documents Expose the Secretive Market for Your Web

If the product is free, you are the product:

An antivirus program used by hundreds of millions of people around the world is selling highly sensitive web browsing data to many of the world’s biggest companies.

Research

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• ∎ Data Science and Prediction - Dhar - 2013 - Reading Session 202301271312

In situations where we are able to design randomized trials, big data makes it feasible to uncover the causal models generating the data.

The author doesn’t make this point very big but it is actually quite important. There are many cases in which it is unethical to undertake a conventional scientific study of certain phenomena… Even though we know that those phenomena are happening anyway. If the data is collected “naturally,” however, we may be able to trace and track patterns in these data without putting ourselves in precarious ethical situations

Shortcuts

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• Automatically download Reminders into your Obsidian notes with Shortcuts

Want a quick, hands-free, one-step method to capture reminders and tasks into Obsidian? Take advantage of Reminders, Shortcuts, and Shortcuts’s automations feature.

This Shortcut will extract all reminders currently incomplete in a given list and append them to your daily note.

Here’s a screenshot of the full Shortcut

Download it and set it up (i.e., answer all of the configuration questions). Then, create Shortcuts automations (via the Automations tab in Shortcuts) that run on whatever triggers you want (e.g., “Whenever the Obsidian app is opened” and “9am”). Add a “Run Shortcut” action to that automation, then select the shortcut you’ve just configured.

🎉! Whenever the shortcut is triggered, the reminders in the designated list will be added to your daily note.

You can now say e.g., “Hey Siri, add ‘Pick up milk’ to my Obsidian list,” and that item will (eventually) be added to your daily note.

• A Shortcut for quickly and easily opening published notes in Obsidian

If you publish your notes to the web in any way and you are on iOS/macOS, here’s a simple shortcut that lets you quickly and easily open a note from your website in Obsidian:

See the shortcut in action

Social media

2 notes with this tag

Strategy

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• Roger Martin, Bianca Andreescu, and systemic strategy

According to designer/strategist Roger Martin, a strategy is an imagined possibility with which we ask the question “What has to be true for this possibility to become real?”

In this episode IDEO U’s Creative Confidence podcast, Roger talks about how that approach helped unlock Bianca Andreescu’s success at the Grand Slam singles championship in 2019.

One of the fascinating things about this approach is that it acknowledges the need for system-wide changes. By asking “What has to be true?”, a strategist must consider all of the conditions of a system that should shift to make the imagined possibility a reality. Of course, most approaches to strategy do require some appreciation of the state of the strategic environment (e.g., the five forces model). None, however, emphasize the need to guarantee these systemic conditions quite as explicitly as asking “What must be true?”

# The Global Steering Group for Impact Investment’s (2018) systemic theory of change

A systems model I helped visualize for the Global Steering Group on Impact Investment in 2018:

1 notes with this tag

# A Systemic View of Research Impact

If academia ceases to have an impact it loses its raison d’être. Impact is what differentiates meaningful academic work from mere busywork. It makes the difference between signal and noise.

[…]

Ultimately, the questions that concerns us [are] what role research plays in society and how we can create a research system with impact at its core?

I like this project. Benedikt and Sascha say they’re taking a systemic approach to model the full complexity of academic impact:

academia struggles with creating/measuring/generating impact because it struggles to conceptualise and structurally anticipate it. We are missing a systemic perspective on impact that is grounded in the fact that different forms of meaningful academic work show very different forms of impact.

The work is supposedly semi-open. The authors ask anyone that reads each chapter, released incrementally on Google Docs, to contribute comments, and then they will work to incorporate these insights back into the final output.

Activism

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• John Kerry, Arnold Schwarzenegger wage ‘World War Zero’ on climate change

Today former Secretary of State John Kerry and former California governor Arnold Schwarzenegger declared war on climate change. The two led an all-star cast of lawmakers and celebrities to launch an initiative called World War Zero, which aims to get individuals, businesses, and governments to drastically slash greenhouse gas emissions. The initiative, for now, boasts a lot of glitzy names without many details on how it will achieve its goal. Its bipartisan founding members — which include Bill and Hillary Clinton, Richard Branson, Jimmy Fallon, Cindy McCain, and Al Sharpton, and more than 70 other notable names — plan to hold 10 million “climate conversations” in 2020, The New York Times reported over the weekend.

Seems like an incredible effort. And it’s an excellent angle. “War”—when declared by major public figures—certainly catches the public attention.

Kerry compared the urgency of climate change to the challenges facing America during World War II. “When America was attacked in World War II we set aside our differences, united and mobilized to face down our common enemy,” Kerry said in a statement. “We are launching World War Zero to bring that spirit of unity, common purpose, and urgency back to the world today to fight the great threat of our time.”

Of course, actually waging war doesn’t always garner the unity or have the results we aim for, especially when it’s a war against a social issue.

Ai

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# How to recognize AI snake oil

The over- and misuse of AI is one of my biggest tech pet peeves. It truly is evil to tack the AI term onto the description of most products. It also damages the long-term potential of AI by corrupting what it means—especially for the everyday people who aren’t involved or invested in building these tools, but who will use them (or be used by them).

Arvind Narayanan on Twitter:

Much of what’s being sold as “AI” today is snake oil. It does not and cannot work. In a talk at MIT yesterday, I described why this happening, how we can recognize flawed AI claims, and push back. Here are my annotated slides: https://www.cs.princeton.edu/~arvindn/talks/MIT-STS-AI-snakeoil.pdf

Key point #1: AI is an umbrella term for a set of loosely related technologies. Some of those technologies have made genuine, remarkable, and widely-publicized progress recently. But companies exploit public confusion by slapping the “AI” label on whatever they’re selling.

Key point #2: Many dubious applications of AI involve predicting social outcomes: who will succeed at a job, which kids will drop out, etc. We can’t predict the future — that should be common sense. But we seem to have decided to suspend common sense when “AI” is involved.

Key point #3: transparent, manual scoring rules for risk prediction can be a good thing! Traffic violators get points on their licenses and those who accumulate too many points are deemed too risky to drive. In contrast, using “AI” to suspend people’s licenses would be dystopian.

Analysis

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Apple

1 notes with this tag

• Bring It On Haters With Special Guest Ben Thompson

Ben Thompson, in discussion with John Gruber:

It was mindblowing. It was absolutely incredible. The way that you could just do stuff that wasn’t really possible [on a computer]. Again, it was technically possible on a computer, but the user interface and experience was just transformative on the iPad. It was absolutely incredible.

And Jobs knew it. It’s one of my all-time favourites Jobs moments. It’s like fifteen seconds after the demo, and it’s just like… he’s used this. He was involved in the creation of it. They had run through the demo. He knew it. And even then, he was just astonished. He’s just like ‘I can’t believe [this]…’

[…]

It was, to my mind, the culmination of his life’s work. He comes on there, and he’s like, ‘Isn’t it incredible? Now anyone can make music.’

I almost want to transcribe this whole episode. John Gruber and Ben Thompson discuss the potential of the iPad—and its failure to reach it.

Ben uses the term “transformative” deliberately above. They discuss how, before the iPad, no computing experience could adapt to become wholly new tools and environments for whatever the user wanted to do. But the iPad can become a piano or a canvas or a television. In this sense, they argue that the iPad has (or had) the potential for disruptive innovation (RIP Clay Christensen)—but it’s not supposed to be a Mac.

These two think the iPad’s lost the chance to fulfill that potential, mostly because Apple has missed the opportunity to build a vibrant developer ecosystem due to App Store policies. I hope that isn’t the case, though I think we have to look beyond the iPad to fully appreciate what might happen next. The introduction of tablets and transformative computing experiences continues to echo throughout a variety of industries. Graphic designers and illustrators have a new suite of tools to directly interact with their creations in the iPad Pro and the Surface. Similarly, tablet or hybrid devices have transformed schools—schoolchildren now have a “homework” device for all kinds of assignments. It’s true that we still need developers to imagine ever-more revolutionary applications for these devices, but there’s no denying that disruption is taking root.

Either way, the episode is well worth a listen. Enjoy from 15:50 to ~31:22 and 1:26:59 to the end of the show if you want to focus on the iPad discussion.

Apps or tools

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• Why the grass is greener: Making sure that shiny new alternative tool is actually going to help you

“The grass is always greener on the other side.” The popular idiom discourages whoever’s listening from seeking out alternatives, suggesting that other options always look better from wherever we’re currently standing. But it has a funny problem: nobody ever explains why the grass is greener on the other side.

That’s because it isn’t. The truth is that your side is just yellower/trampled on/eaten… and that’s because you’re on it.

Moving to a different place will be fine at first. Then you’ll use it, too, and eventually it’ll look the same as where you started.

(In this metaphor, you’re a goat. 🐐)

In workflow design, in addition to the novelty of “shiny new object,” new and alternative tools are great simply because they don’t have the cruft you’ve built up in the old tool. That cruft might be noisy notes, a lifetime of guilt-inducing task management, or even just bad habits and behaviours. The problem isn’t the tool. It isn’t you, either. It’s you and the tool.

So, after switching, the problems seem to go away… only to re-emerge (possibly in a new form) later because the issues are generated by your usage, not by the tool.

The solution is to fall in love with the problem, not the (shiny, potential) solutions.

1. Determine what your issues actually are, and try to figure out why they’re happening.
2. Then, abstractly identify how you might be able to mitigate the problems.
• Don’t say “I’ll use Bunch,” say “If I standardize certain work spaces on my computer, I can develop muscle memory for using those workspaces, reducing distraction and allowing me to spend less cognitive energy on finding everything I need to get engaged.”
3. Last, identify some tests or success conditions that will tell you whether the solution is actually working. This’ll help minimize irrational perspectives on how well the honeymoon stage is going.

Only after taking those three steps should you choose a tool. Find something that can implement the abstract principles you’ve articulated, and be sure to follow-through on the tests.

In doing this, you’re actually creating and implementing a rough design theory. You’re using design science to make your work as easy and engaging as it can be! High-five for that.

Book

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# Interference by Sue Burke

[People] tend to ignore outside forces and focus on each other. This comes naturally. They believe they are responsible for everything because they believe they have no limits to the mastery of their fates, a false belief but their central motivation, perhaps good for their mental health, since powerlessness is hopelessness.

If you haven’t heard of Sue Burke’s “Pax” duology, and you like sci-fi, I’m happy to recommend a new favourite book series for you.

The Pax books are about a rebellious attempt to save humanity in which several families build their own ship and escape to a new planet to begin a new colony. Doing that is about as straightforward as it sounds. Sue Burke brings this premise to life masterfully.

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# Innovation Systemics

# Takeaways

# Problem 1: Canada Struggles To Understand How It Can Fit The ‘Idea Economy’ Into The Broader Economic Context (I.e. Other Sectors).

Thus, Canada should take steps to foster the idea economy. The world is changing, and Canada needs to understand how the tenets of the idea and knowledge economy will best flourish across the primary sectors that drive the broader Canadian economy. Building regional collectives (like the Waterloo-Kitchener corridor) to advance innovation is only one step, whereas our findings suggest the need to take a collective leap and author a White Paper that will activate a national approach on the new, ideas-based economy. In doing so, the Government of Canada will engage a collective of stakeholders, thought leaders and businesses both large and small to lead a national dialogue on how innovation ought to play out across Canada’s diverse communities, companies and campuses.

# Problem 2: Canadians Do Not Recognize The Unique Strengths Of The Economy As It Is, And Neglect Recognition Of The Innovations Already Taking Place.

Canada should change the narrative. Innovation is happening, but it is taking place in sectors and industries different than the ones we tend to pay attention to. Increasing awareness about the need for, and impact of, innovation within advanced manufacturing, natural resources and agriculture will help cross pollinate the economy with more robust, productive approaches and solutions. This will also help to shift the culture of entrepreneurship by empowering a generation of Canadians to create sustainable value and ensure they and their communities prosper.

# Problem 3: Canada Currently Allocates A Disproportionate Amount Of Resources (Talent And Capital) To “Tech Solutionism”, At The Cost Of Others.

Canada should redirect the pipeline. The ultimate step is to increase the carrying capacity of the system to generate value for entrepreneurs from outside the technology sector. Drawing sectors and industries together with the innovation ecosystem will build deeper and more diverse connections. Diverting the flow of resources—talent and capital—and binding it with existing infrastructure and institutional support will build a depth that will support a more robust Canadian economy. Furthermore, investing in improving the structures that nurture prosperity—incubators, accelerators, entrepreneurship, and innovation programs—and bringing them together with campuses and companies already making an impact, will propel Canada forward.

# The Context

“Innovation drives an economy’s ability to create more economic value from an hour of work, thereby increasing economic output per capita. The resulting productivity growth creates potential for rising wages and incomes, and thus for a higher standard of living.” (University of Lethbridge Research Services, 2015)

A robust innovation ecosystem has the ability to improve productivity, economic growth, and job creation metrics in countries adequately supporting this process. In these countries, there also tend to be more resources available to support spending in education, health, and infrastructure, to name a few (“Innovation details and analysis”, 2013). Accordingly, the importance of a healthy innovation system is tied closely to that of a healthy national economy, along with its people, communities and institutions.

In Canada, however, economic discourse around innovation and entrepreneurship has recently pointed towards a decline in productive returns from startup investment. Although an improvement from previous years, in 2015 Canada was ranked 9th out of 16 peer countries in innovation by the Conference Board of Canada, receiving a letter grade of “C” on its Innovation Report Card (“Innovation details and analysis”, 2013). This ranking points to a persistent weakness in the Canadian innovation system, commonly referred to as the “innovation gap”. This phenomenon is being reported by some of the country’s top journalists, startup CEOs, established investors, think-tanks, and members of various levels of government across the country. While these reports highlight culture, politics, economics, and education as the cause of this gap, and underlining the need for reform, policy changes, and new programs, few of these calls to action are gaining traction. There is no easy answer to this wicked problem.

With the above in mind, we initially sought to answer the question “Why are investments in innovation resulting in diminishing returns in productivity?” through our research, but we quickly realized that in order to address this issue, we would first need develop a thorough understanding of the innovation ecosystem in Canada and thus we broadened our research questions to “How might we understand the Canadian innovation system?” all the while still focusing on this oft reported, elusive innovation gap.

Innovation details and analysis. (2013). The Conference Board of Canada. Retrieved from http://www.conferenceboard.ca/hcp/details/innovation.aspx

University of Lethbridge Research Services. (2015). Putting Innovation in Context. Lethbridge, Alberta, Canada: University of Lethbridge. Retrieved from http://www.agility-ulethbridge. ca/2015/09/11/putting-innovation-in-context/

# Research Synthesis Map

This synthesis map summarizes our research on Canada’s systemic innovation challenges this past term.

# Leverage Analysis

We used centrality analysis to examine our map of the system for potential leverage points. The elements that surface from this analysis offer opportunities (or, in some cases, roadblocks) for policy and program interventions.

# The Paper

# The Researchers

This work was completed by a team of Master of Design students in OCAD U’s Strategic Foresight & Innovation program.

Cognition

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Collaboration

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• Science Conferences Are Stuck in the Dark Ages

Dr. Ngumbi and Dr. Lovett outline the issues with modern research conferences that are stuck in the 20th (or even 19th) century.

By the end of each conference, you’ve heard dozens of people dispense all their knowledge in 10-minute bursts, and you sometimes leave feeling less informed than before you arrived. Where’s the dialog? Where’s the questioning? Where’s the innovation? It’s beyond time that scientific conferences themselves undergo the scientific process, and move forward.

I shouldn’t ever be surprised by these events, but every time I go to one, I am shocked by how boring the facilitation is. Some might defend the format. After all, sage-on-a-stage has worked for hundreds of years.

The question isn’t whether it works, though. It’s whether it could be better. Surely, in an age of cloud technologies and the Internet and social media—not to mention better recognition of soft power and inclusivity and the processes of scientific revolution—there are modes of conference programming that can leapfrog the conventional format.

Having led a number of events over the years that have shirked tradition for more interesting facilitation formats, I know firsthand how disruptive facilitation mistakes can be. But I’ve also seen some incredible results from shaking up the structure. Radhoc’s Unpanel, for instance, turns the structure of a panel upside-down. Instead of having a group of “experts” on a stage speaking to an anonymous crowd, the format puts those invited guests in subgroups that get to introduce one another. The audience becomes the panel, and the expert an anchor in the conversation. It gives everyone a chance to connect with the quasi-celebrities anointed by these events. As a bonus, it’s easier for the guests, too—they don’t need to prepare keynotes, only business cards.

Complexity

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• Embracing multilingualism to enhance complexity sensitive research

In this research article, the authors point out that the cycles of translation from English to the language of the context and back again can be costly and inconvenient. But, they point out three benefits to investing in translation and multi-lingual research spaces.

First, the authors argue that disseminating the results of research in local languages not only makes your research accessible to stakeholders, but it also helps stakeholders value all research more. They write:

Translations are expensive and time-consuming, so a large part of our work stays in English unavailable to the local stakeholders, who may have participated in the research process. This is an issue not only because it reduces their possibilities to learn from the systematized outcomes of the processes in which they participate, but because it reduces their perception of the value of research. When stakeholders feel that researchers write exclusively for other foreign researchers, their readiness to support and fund research may decrease.

The second benefit:

Second, academics who don’t read English may find it difficult to continue building on knowledge published only in that language.

This takeaway is obvious. So many publications are translated to English, but the reverse is rare.

Third, and by no means least, naming complex issues or ideas only in English impoverishes other languages. When we forsake finding a word for a particular concept or idea in a given language, we impoverish that language.

This is quite insightful. Language is intrinsic to organizational learning. If the concepts advanced in our research are never introduced to the local language, then it may be impossible for that learning to take root.

The authors recognize a fascinating tension in this work. They demonstrated the possibility of multi-language research spaces via a virtual research commons for their project.

What we have learned from working with different languages and acknowledging them during the full research cycle, including the dissemination stage, is that they are time- consuming, costly and even a bit messy and uncomfortable. For example, in the case of the virtual space above, some participants complained that having to find their own language among texts written in other languages begs an extra effort from them and slows them down. However, the alternative is renouncing inclusion and plurality, which is at odds with the challenge faced by academia to address complex societal problems.

There is a cost to complexity, but solution spaces need to be more complex than the problems they’re resolving.1

1. See Ashby’s Law of Requisite Variety; http://pespmc1.vub.ac.be/ASHBBOOK.html, p. 207 ↩︎

Cybernetics

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Data science

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Engagement

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• Student Acquisition, Engagement, and Retention: Analogies from tech startups

a16z is a podcast from Andreesen Horowitz, one of the leading venture capital firms in the US. Their portfolio has included Airbnb, BuzzFeed, Facebook, Twitter, and many many other big companies—they know what they’re doing!

Two recent episodes on the podcast feature Andreesen Horowitz general partners, Andrew Chen and Jeff Jordan (some of the people who make investment decisions). They are interviewed by host Sonal Chokshi about how to think about user (or customer) acquisition and user engagement and retention. (You should also be able to get these episodes using any given podcasting app, searching for a16z, and grabbing the two recent episodes titled The Basics of Growth.)

I’ve listened to these episodes a couple of times since they came out a week ago. There’s a lot of terminology and concepts to parse—they explain it all well, but it took me a couple of tries to wrap my head around all of it. Given what I’ve come to learn so far, though, is that the two episodes seem like a (free!) one-oh-one masterclass in growing or scaling any given initiative. Despite being less than an hour long in total, the conversation goes way beyond “number of users”. Andrew, Jeff, and Sonal dive deep into the kind of patterns we should hope to see (and find ways to encourage) in order to garner genuine growth, engagement, and retention patterns. It is super sophisticated while still being kinda simple.

That said, they’re talking about startups, customers, and technology-driven businesses. Applying those lessons to initiatives in public post-secondary—co-curricular leadership development programs, in my case—is not straightforward.

So, that’s the challenge: how do we generalize their insights into the world of post-secondary student services? Here I explore that question with more questions. There’s probably no simple answer for these, but thinking about these concepts could deepen how we grow (and evaluate the growth of) post-secondary services.

Question 1: Lifetime Value vs. Lifetime Impact? The first episode focuses on user acquisition. The analogy for us is when students first use our services, tools, or go to their first event or program. Jeff and Andrew describe organic growth—word of mouth-type acquisition—and inorganic growth (paid ads and other campaigns). They talk a lot about the tension between the “cost” of acquiring users and the lifetime value (LTV) of a given user.

How should we think about these ideas in student services? “Student Acquisition Costs” have a direct parallel. Is there a useful analogy for LTV? (I.e., “Degree/Career Impact”?) The implication is that acquiring certain students might cost more, or at least demand different strategies, but have a greater impact.

Question 2: Semesterly Active Users? The podcasters reference a variety of “active user” metrics: Daily Active Users (DAU), Monthly Active Users (MAU), last-seven (L7) and last-twenty eight (L28)… What is a useful and realistic “active user” metric for post-secondary student services? We don’t actually want our students to use all of our services daily. As the podcasters put it, there’s a certain ideal cadence to the way they should use our services. But what is that cadence, and how do we ensure we’re meeting it?

Question 3: Network effects? Jeff, Andrew, and Sonal talk about the “network effect” in both episodes. This is the concept that a service becomes more valuable/powerful the more users it has. Is there an analogy to the services we’re already running, and are we taking advantage of it? Or, are we missing an opportunity to build in a network effect or similar positive acquisition, engagement, or retention feedback loops somehow?

To be clear, I don’t think it’s a good idea to translate directly from the high-growth profit-driven startup world into post-secondary services work and life. The organizations have different motives and needs, incentives and costs, and—most important—different stakeholders, with different obligations to those stakeholders. Still, there may be powerful, creative opportunities hidden in the lessons we borrow from one another.

Facilitation

1 notes with this tag

• Science Conferences Are Stuck in the Dark Ages

Dr. Ngumbi and Dr. Lovett outline the issues with modern research conferences that are stuck in the 20th (or even 19th) century.

By the end of each conference, you’ve heard dozens of people dispense all their knowledge in 10-minute bursts, and you sometimes leave feeling less informed than before you arrived. Where’s the dialog? Where’s the questioning? Where’s the innovation? It’s beyond time that scientific conferences themselves undergo the scientific process, and move forward.

I shouldn’t ever be surprised by these events, but every time I go to one, I am shocked by how boring the facilitation is. Some might defend the format. After all, sage-on-a-stage has worked for hundreds of years.

The question isn’t whether it works, though. It’s whether it could be better. Surely, in an age of cloud technologies and the Internet and social media—not to mention better recognition of soft power and inclusivity and the processes of scientific revolution—there are modes of conference programming that can leapfrog the conventional format.

Having led a number of events over the years that have shirked tradition for more interesting facilitation formats, I know firsthand how disruptive facilitation mistakes can be. But I’ve also seen some incredible results from shaking up the structure. Radhoc’s Unpanel, for instance, turns the structure of a panel upside-down. Instead of having a group of “experts” on a stage speaking to an anonymous crowd, the format puts those invited guests in subgroups that get to introduce one another. The audience becomes the panel, and the expert an anchor in the conversation. It gives everyone a chance to connect with the quasi-celebrities anointed by these events. As a bonus, it’s easier for the guests, too—they don’t need to prepare keynotes, only business cards.

Gamification

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# Facilitating Citizen Science through Gamification

Gamification is the practice of using game elements to change the experience of nongame contexts. It presents a potentially powerful new approach to motivate volunteers and recruit new contributors to citizen science—the phenomenon of engaging members of the public in the collection and analysis of data in scientific projects. This research included a thorough literature review of current gamification and citizen science research and presented a pilot information systems/design science project exploring the efficacy of gamification in the citizen science platform NL Nature

Habits

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• New year, new you

Could New Year’s resolutions be doomed to fail? Driven by New Year’s culture, we commit to actions, call them resolutions, and set off to become better people. This phenomena of setting New Year’s resolutions is reinforcing (R1).

Yet, as we get further away from the culture of resolutions, our commitment – linked at heart to New Year’s culture – fades. This, coupled with how slow progress can be, leads to the gradual extinction of our promise to ourselves. (B1)

Perhaps, then, resolutions made outside of and separate from the cultural phenomena are more likely to result in real changes, as their founding is based in intrinsic motivation as opposed to the extrinsic incentives of New Year’s culture.

(The time since New Year’s sets a limit to growth on the new habit.)

Health

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• Systemic lessons from South Korea's Patient 31

This changed with the emergence of “Patient 31.”

Reuters’ coverage of the “Korean clusters” provided the world with a vivid glimpse of the volatility of COVID-19. One person showed poor judgement, and in turn caused cascading catastrophe in her communities.

Events like the COVID-19 pandemic are thankfully rare. Moments like these—when a lot happens all at once, and the experience is shared by a collective—shape future history like nothing else. We are learning a lot from this. Not only are epidemiologists now a famous profession, but we’re all learning exactly what it takes to provide good healthcare, what good governance looks like, how public health is community health, and more.

Patient 31 holds a simple lesson for systemics: the fragility of apparently solid social systems. South Korea seemed to do everything right. Yet, due to the volatile nature of this particular socio-health system, a single “free radical” caused immense damage.

Similar volatility is evident—but more subtle—in other social systems. Consider how memes spread. Our massive communities may seem immovable at times, but it’s clear that the wrong (or right) phenomena can spread rapidly and deeply.

Stay safe.

Highlights, change, systems

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Highlights, tech, design

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Impact

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# A Systemic View of Research Impact

If academia ceases to have an impact it loses its raison d’être. Impact is what differentiates meaningful academic work from mere busywork. It makes the difference between signal and noise.

[…]

Ultimately, the questions that concerns us [are] what role research plays in society and how we can create a research system with impact at its core?

I like this project. Benedikt and Sascha say they’re taking a systemic approach to model the full complexity of academic impact:

academia struggles with creating/measuring/generating impact because it struggles to conceptualise and structurally anticipate it. We are missing a systemic perspective on impact that is grounded in the fact that different forms of meaningful academic work show very different forms of impact.

The work is supposedly semi-open. The authors ask anyone that reads each chapter, released incrementally on Google Docs, to contribute comments, and then they will work to incorporate these insights back into the final output.

Information systems

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1 notes with this tag

• Bring It On Haters With Special Guest Ben Thompson

Ben Thompson, in discussion with John Gruber:

It was mindblowing. It was absolutely incredible. The way that you could just do stuff that wasn’t really possible [on a computer]. Again, it was technically possible on a computer, but the user interface and experience was just transformative on the iPad. It was absolutely incredible.

And Jobs knew it. It’s one of my all-time favourites Jobs moments. It’s like fifteen seconds after the demo, and it’s just like… he’s used this. He was involved in the creation of it. They had run through the demo. He knew it. And even then, he was just astonished. He’s just like ‘I can’t believe [this]…’

[…]

It was, to my mind, the culmination of his life’s work. He comes on there, and he’s like, ‘Isn’t it incredible? Now anyone can make music.’

I almost want to transcribe this whole episode. John Gruber and Ben Thompson discuss the potential of the iPad—and its failure to reach it.

Ben uses the term “transformative” deliberately above. They discuss how, before the iPad, no computing experience could adapt to become wholly new tools and environments for whatever the user wanted to do. But the iPad can become a piano or a canvas or a television. In this sense, they argue that the iPad has (or had) the potential for disruptive innovation (RIP Clay Christensen)—but it’s not supposed to be a Mac.

These two think the iPad’s lost the chance to fulfill that potential, mostly because Apple has missed the opportunity to build a vibrant developer ecosystem due to App Store policies. I hope that isn’t the case, though I think we have to look beyond the iPad to fully appreciate what might happen next. The introduction of tablets and transformative computing experiences continues to echo throughout a variety of industries. Graphic designers and illustrators have a new suite of tools to directly interact with their creations in the iPad Pro and the Surface. Similarly, tablet or hybrid devices have transformed schools—schoolchildren now have a “homework” device for all kinds of assignments. It’s true that we still need developers to imagine ever-more revolutionary applications for these devices, but there’s no denying that disruption is taking root.

Either way, the episode is well worth a listen. Enjoy from 15:50 to ~31:22 and 1:26:59 to the end of the show if you want to focus on the iPad discussion.

Kumu

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# Systems Practice, Abridged

For serious system mapping work, spending [significant] time studying, thinking about, and mapping your system helps ensure you are addressing root causes rather than instituting quick fixes. In the long term, the time and resources you invest in Systems Practice will pay dividends.

But what if youʼre not quite sold on the Systems Practice methodology yet? What if you havenʼt encountered systems thinking before and just want to dip your toes in? Or what if youʼre an expert or an educator with only a few hours to introduce Systems Practice to a fresh new group of systems thinkers?

I have been in the latter situation, and it’s a challenge. In my experience, people who are wholly new to systems thinking can take a lot of time to acclimate to the mindset. But! If, as a teacher, you can’t illustrate the benefits quickly, it’s easy to disengage.

So, I’m glad this exists. This is a wonderful new resource from Kumu’s Alex Vipond that helps walk you through systems and Kumu’s tools at the same time.

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Lessons learned from Memorial Student Leadership Conference (MSLC) 2017. These thoughts were spurred by Director of Student Life Dr. Jennie Massey’s opening remarks for the conference, and were reinforced by the keynote speaker, Mr. Seamus O’Regan, MP.

Jennie and Seamus both talked about the oft-haphazard decision making that led to their achievements. The truth about this reinforcing loop is that no matter where you are in the process, you can do something to make it to the next step. No, not every moment will be virtuous – the cycle is not _that_virtuous. It is a cycle nonetheless, and that’s the thing about cycles: they do not stop.

Learning

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• 'This is Sticking with Them:' Professor Explores Benefits of Model-Based Learning

Through model-based learning, students use diagrams as a way to think about and reason with systems—and to think about how complex systems interact and change.

“Model-based learning” seems like a reframing of classic teaching practices, but it’s nonetheless a powerful reframing. Emphasizing the model—and encourage students to test and iterate their models—is catchy. It’s also deliberately organizational—it requires students to organize and structure their thinking about a given system, often visually.

Leverage analysis

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Meta

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# Divide & conquer

I have often hesitated to draft up an idea because I’m not sure the folks reading this site want to hear it. I (aim to) publish about a few disparate subjects, really:

• Systemics, design, and social change
• Data modelling and data for social change
• Productivity and personal knowledge management
• Scripting and (personal) automation
• Leadership, innovation, and changemaking

Obviously, this is too many topics for any one blog. If you’re reading this, you probably came here for just one of the topics above, and you might be interested in another one or two. And listen, I like you, and I want any visit of yours to be a valuable one. That’s why I’ve launched a sibling blog.

I could cluster the topics above a number of ways. Here’s what I think makes the most sense: This blog, Fulcra, will focus on finding leverage for complex change, including:

• Systemics, design, and social change
• Data modelling and data for social change
• Leadership, innovation, and changemaking

The newest one, Axle, will focus on how we change ourselves, including:

• Personal development
• Design and technology for augmented cognition
• Productivity and personal knowledge management
• Scripting and (personal) automation

Moving forward, this site (Fulcra) will be a platform for writing on complex systems change. I aim to study, share, and write about how the world changes—and how we can get better at changing it.

Axle is a new site I will use to share my thoughts on how we change ourselves. After all, the better we get, the better we better get. The easy thing to write about (and what you’ll probably see the most often there) are the apps and tools I use and the designs I apply in my life and work. I also plan to share functional resources (such as scripts) as well as ask questions and debate about making progress in life and work.

This was a weird decision. After all, I barely publish here, so running two different sites seems like a terrible idea. I hope, however, that having more focused platforms for these different topics will help me publish more impulsively. Feel free to follow both, or none!

Metrics

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• Student Acquisition, Engagement, and Retention: Analogies from tech startups

a16z is a podcast from Andreesen Horowitz, one of the leading venture capital firms in the US. Their portfolio has included Airbnb, BuzzFeed, Facebook, Twitter, and many many other big companies—they know what they’re doing!

Two recent episodes on the podcast feature Andreesen Horowitz general partners, Andrew Chen and Jeff Jordan (some of the people who make investment decisions). They are interviewed by host Sonal Chokshi about how to think about user (or customer) acquisition and user engagement and retention. (You should also be able to get these episodes using any given podcasting app, searching for a16z, and grabbing the two recent episodes titled The Basics of Growth.)

I’ve listened to these episodes a couple of times since they came out a week ago. There’s a lot of terminology and concepts to parse—they explain it all well, but it took me a couple of tries to wrap my head around all of it. Given what I’ve come to learn so far, though, is that the two episodes seem like a (free!) one-oh-one masterclass in growing or scaling any given initiative. Despite being less than an hour long in total, the conversation goes way beyond “number of users”. Andrew, Jeff, and Sonal dive deep into the kind of patterns we should hope to see (and find ways to encourage) in order to garner genuine growth, engagement, and retention patterns. It is super sophisticated while still being kinda simple.

That said, they’re talking about startups, customers, and technology-driven businesses. Applying those lessons to initiatives in public post-secondary—co-curricular leadership development programs, in my case—is not straightforward.

So, that’s the challenge: how do we generalize their insights into the world of post-secondary student services? Here I explore that question with more questions. There’s probably no simple answer for these, but thinking about these concepts could deepen how we grow (and evaluate the growth of) post-secondary services.

Question 1: Lifetime Value vs. Lifetime Impact? The first episode focuses on user acquisition. The analogy for us is when students first use our services, tools, or go to their first event or program. Jeff and Andrew describe organic growth—word of mouth-type acquisition—and inorganic growth (paid ads and other campaigns). They talk a lot about the tension between the “cost” of acquiring users and the lifetime value (LTV) of a given user.

How should we think about these ideas in student services? “Student Acquisition Costs” have a direct parallel. Is there a useful analogy for LTV? (I.e., “Degree/Career Impact”?) The implication is that acquiring certain students might cost more, or at least demand different strategies, but have a greater impact.

Question 2: Semesterly Active Users? The podcasters reference a variety of “active user” metrics: Daily Active Users (DAU), Monthly Active Users (MAU), last-seven (L7) and last-twenty eight (L28)… What is a useful and realistic “active user” metric for post-secondary student services? We don’t actually want our students to use all of our services daily. As the podcasters put it, there’s a certain ideal cadence to the way they should use our services. But what is that cadence, and how do we ensure we’re meeting it?

Question 3: Network effects? Jeff, Andrew, and Sonal talk about the “network effect” in both episodes. This is the concept that a service becomes more valuable/powerful the more users it has. Is there an analogy to the services we’re already running, and are we taking advantage of it? Or, are we missing an opportunity to build in a network effect or similar positive acquisition, engagement, or retention feedback loops somehow?

To be clear, I don’t think it’s a good idea to translate directly from the high-growth profit-driven startup world into post-secondary services work and life. The organizations have different motives and needs, incentives and costs, and—most important—different stakeholders, with different obligations to those stakeholders. Still, there may be powerful, creative opportunities hidden in the lessons we borrow from one another.

Open

1 notes with this tag

• Twitter announces Bluesky: a team seeking and developing an open standard for social media

Twitter is funding a small independent team of up to five open source architects, engineers, and designers to develop an open and decentralized standard for social media. The goal is for Twitter to ultimately be a client of this standard. 🧵

The thread is worth the read, as are some of the comments. There’s a few interesting resources shared within, including a couple of articles from Jack and a few existing open standards.

Personal knowledge management

1 notes with this tag

Practice

1 notes with this tag

• This is why I’m here.

Why sketch systems? Partially as a way to productively vent my sarcasm, and partially as a way to practice systems thinking.

Also, maybe my handwriting will improve?

Procrastination

1 notes with this tag

• Limits to (personal) growth

I’m my own worst enemy when it comes to reading articles. I have 211 in a to-do list as I write this, and the larger that grows the more untenable getting through it seems.

In this case the limiter actually escalates, as in order to avoid doing the readings I know I should do, I go off and collect more. 😑

Research methods

1 notes with this tag

• ∎ Data Science and Prediction - Dhar - 2013 - Reading Session 202301271312

In situations where we are able to design randomized trials, big data makes it feasible to uncover the causal models generating the data.

The author doesn’t make this point very big but it is actually quite important. There are many cases in which it is unethical to undertake a conventional scientific study of certain phenomena… Even though we know that those phenomena are happening anyway. If the data is collected “naturally,” however, we may be able to trace and track patterns in these data without putting ourselves in precarious ethical situations

Resources

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# Resources

Updated Nov 14, 2019

Below I’m collecting a set of resources dealing with a variety of topics for shareable reference—a sort of living, semi-public annotated bibliography. Many of these readings should be accessible via a library or a good Internet search, but if you find something here that shouldn’t be this easy to download, feel free to contact me and I’ll remove it. Or, if you come across any broken links, please let me know!

# Getting Started with Systemic Innovation

Kudoz’ Where Are You Scaling? Placemat (2017) KudozWhere Are You Scaling? “placemat” is an explorable tool to help think through what scaling really means in a given venture. It builds upon Riddell & Moore’s (2015) Scaling Out, Scaling Up, and Scaling Deep in expanding our notion of scaling. When you hear the word “scale” in a conventional conversation, the meaning is likely synonymous with scaling out: reaching more people (stakeholders or customers) with the product, service, program, or policy at the heart of the conversation. Yet there are other underappreciated aspects of scaling: some are required in order to successfully scale out, while others are different ways of achieving impact—maybe scaling out isn’t the best route to take after all! Scaling up, for instance, refers to reaching higher in power hierarchies in order to implement higher-level solutions to the problem you’re addressing. Scaling deep means to reach the same people you’re already reaching more deeply, or with greater impact. Kudoz introduces two more concepts: scaling infrastructure, or building out more tools and supports to make the work more effective and sustainable; and scaling scree, or lending support and legitimacy to other, different actors and initiatives addressing the same issues you are.

Mulgan & Leadbeater’s Systemic Innovation (2013) While the above concepts help make concrete the different ways an intervention might change a system, Mulgan and Leadbeater’s (2013) discussion paper on systemic innovation dives a bit deeper into theory. They link the practice of systems thinking to approaches to innovation, providing a framework for “joining up” a set of innovations in order to achieve systemic change.

# Getting Started with Social Innovation

Mulgan’s Social Innovation: What It Is, Why It Matters, And How It Can Be Accelerated (2007) Geoff Mulgan offers a comprehensive yet down-to-Earth guide to social innovation. The reading really helps communicate what the differences are between social innovation and conventional innovation with practical examples.

Phills Et Al.‘S Rediscovering Social Innovation (2008) The Stanford Social Innovation Review has been one of the preeminent publishers on social innovation since its inception in the early 2000’s. In this review Phills et al. summarize a brief history on social innovation itself while paving a way forward in research and practice.

# Getting Started with Design

What is “design”, really? It’s easy to think that design is the layout of graphics or illustrations—perhaps even making decisions about layouts, as in architecture. These disciplines—graphic design and architecture—certainly leverage design, and many people employed in these industries are designers. Yet these disciplines do not fully capture what design is, thus we should not limit the understanding and application of design to these industries.

The term design shares latin roots with designation. To design is therefore to mark; to frame. Framing means to view a given problem or system from different perspectives in order to deeply understand it and, in turn, to develop novel ways of doing something about it or with it. To become a better designer, you must get better at both analyzing and creating frames.

# Getting Started with Systems Thinking

Systems thinking is most useful when applied to complex, chronic issues: “wicked problems” that resist taming through conventional approaches. David Stroh, who wrote  Systems Thinking for Social Change, argues that effective systems initiatives begin with a focusing question: a question that bounds the project (so that you don’t spend forever debating about where the problem system really ends) and anchors your systems-understanding work in a framing that you can return to if you get lost. This is a question of the form “Why, despite our best efforts and intentions, does [x] persist?” or “…have we not reached our goal of [y]?”—where [x] and [y] are phenomena that remain unassailable through conventional initiatives.

Goodman, Kemeny & Roberts’ The Language Of Systems Thinking (2000) The Language of Systems Thinking introduces the reader to reinforcing and balancing loops using simple examples.

Braun’s The Systems Archetypes (2002) Systems archetypes extend the links and loops of basic systems thinking into more complicated structures – and in doing so, begin to share with the reader deeper insights into the counterintuitive behaviour of the systems we work with.

Donella Meadows’ Leverage Points: Places To Intervene In A System (1997) With robust systemic models, we can begin to identify leverage points: key phenomena that have great potential for change throughout the system.

# Getting Started with Futures Thinking

Jim Dator’s What Futures Studies Is, And Is Not (1995) What Futures Studies Is, and Is Not is a wonderful introductory and reader-friendly summary of futures thinking.

Choo’s The Art Of Scanning The Environment (1999) Chun Wei Choo’s The Art of Scanning the Environment offers a walkthrough of scanning practices.

Bishop, Hines & Collins’ The Current State Of Scenario Development (2007) The Current State of Scenario Development provides a comprehensive review of scenario development approaches and techniques.

# Deeper Reading: Organizational Change

Dubberly Et Al.‘S Notes On The Role Of Leadership & Language In Regenerating Organizations (2002) Hugh Dubberly and a suite of colleagues provide an elegant—poetic, even—walkthrough of how change happens to organizations through their language. They reframe an organization as a continuous set of conversations between people, in turn showing the power of changing the language those people use in order to change the nature of the organization itself.

Weick & Westley’s Organizational Learning: Affirming An Oxymoron (1999) Karl Weick and Frances Westley attack the very idea of organizational learning by showing how “organizing” and “learning” are, in fact, opposing processes. To organize is to order; to learn is to disrupt. Success in organizational change is therefore rooted in a leader’s ability to handle the tension between organizing and learning. Too much organizing and the organization will miss opportunity in change—but too much learning and the organization might not be stable enough to survive.

Gawde’s Learning From Systems Thinking (2017) How can systems thinking help with changemaking in an organization? Writing for People Matters, Sanjay Gawde provides a succinct argument and explanation linking systems approaches to organizational change.

Sci fi

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# Interference by Sue Burke

[People] tend to ignore outside forces and focus on each other. This comes naturally. They believe they are responsible for everything because they believe they have no limits to the mastery of their fates, a false belief but their central motivation, perhaps good for their mental health, since powerlessness is hopelessness.

If you haven’t heard of Sue Burke’s “Pax” duology, and you like sci-fi, I’m happy to recommend a new favourite book series for you.

The Pax books are about a rebellious attempt to save humanity in which several families build their own ship and escape to a new planet to begin a new colony. Doing that is about as straightforward as it sounds. Sue Burke brings this premise to life masterfully.

Signal

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• ∎ Mexico bans solar geoengineering experiments after startup’s field tests - Reading Session 202301191446

The company, called Make Sunsets, conducted the field tests without prior notice or consent from the Mexican government.

This is one of the scary consequences of democratizing technology: volatility. It is getting easier for small teams to take big actions without oversight.

And this is a well-intended initiative. The opposite of this would be ecological or environmental terrorism against businesses or governments perceived to be direct contributors to climate change, which surely will happen as climate change advances and people get desperate.

At least this test was small:

Iseman says he launched two balloons in Baja California last year, each carrying less than 10 grams of sulfur dioxide. That’s a tiny amount of the compound that’s typically released into the air by fossil fuel power plants and volcanoes in much larger quantities — so the release isn’t likely to have had much impact.

The business model is interesting:

Founded in October 2022, Make Sunsets started with the grandiose vision of releasing enough sulfur dioxide to offset global warming from all the world’s CO2 emissions annually. It’s already selling “cooling credits” for the service at 10 per gram of sulfur dioxide — even though it has yet to achieve any measurable impact and can’t guarantee that releasing sulfur dioxide at a bigger scale wouldn’t trigger any unintended problems. This has obvious parallels with Climeworks, who was recently paid by a few big tech companies to pull carbon from the atmosphere. It is hard to imagine this business model working at scale, though… surely there is a kind of prisoner’s dilemma at play that will keep every company from chipping in. Perhaps we need regulators to require businesses to purchase credits like these to properly recognize the environmental costs of business. Sketching 1 notes with this tag • Procrastination Station # Procrastination Station Procrastination is itself a systems trap. That balancing loop sucks you in. You take on sneaky little actions as dopaminergic relief to the burden you’re escaping from, while the burden only grows heavier. (A form of Fixes that Fail.) Skills 1 notes with this tag • IBM expert Tamreem El Tohamy on bridging the skills gap in Africa In the next three years, as many as 120 million workers in the world’s 12 largest economies may need to be retrained or reskilled as a result of Artificial Intelligence (AI) and intelligent automation. cf. Lee Se-Dol. This is according to the latest IBM Institute for Business Value (IBV) study, titled The Enterprise Guide to Closing the Skills Gap. Seems like an interesting guide. This metric surprised me: In 2014, it took three days on average to close a capability gap through training in the enterprise. In 2018, it took 36 days. I didn’t know this measure existed, but I can see the utility. As knowledge work grows ever more specialized, this time-to-capability can only grow. Social 1 notes with this tag • What part of 'viral' content makes platforms want to encourage its spread? The Twttr prototype app gave me another feedback form today. It’s been my habit to complain, at every opportunity, about the trends page you have to engage with whenever you go to the Search tab. I feel a little bad for the designers and developers, because the beta is really all about how conversations on Twitter look and feel. Still, this feedback form was no different. Here’s what I wrote in the “Dislike” section: I wish I could control the trends page. It is the absolute worst part of my Twitter experience. It just feels… unhealthy. Like going through a grocery store magazine aisle. Sure, some of the headings are instructive or inspiring, but many are gross, irrelevant, or completely malignant gossip. The experience is also invasive. Because trends are forced upon you when you intend on searching for something specific, and because they’re algorithmically-tunes to be as attention grabbing as possible, it’s easy to be distracted and forget why you even entered the search pane. I never explicitly consent to learning about celebrity gossip or US politics when I use Twitter. If I tap on some of those topics, it’s not because I want to. It’s because it’s malicious click bait. In turn, it’s corrupt to design an experience that drags the user through it repeatedly. Sure, this content is viral. But shouldn’t we be inoculating against viruses, not encouraging them to spread? Startups 1 notes with this tag • Student Acquisition, Engagement, and Retention: Analogies from tech startups a16z is a podcast from Andreesen Horowitz, one of the leading venture capital firms in the US. Their portfolio has included Airbnb, BuzzFeed, Facebook, Twitter, and many many other big companies—they know what they’re doing! Two recent episodes on the podcast feature Andreesen Horowitz general partners, Andrew Chen and Jeff Jordan (some of the people who make investment decisions). They are interviewed by host Sonal Chokshi about how to think about user (or customer) acquisition and user engagement and retention. (You should also be able to get these episodes using any given podcasting app, searching for a16z, and grabbing the two recent episodes titled The Basics of Growth.) I’ve listened to these episodes a couple of times since they came out a week ago. There’s a lot of terminology and concepts to parse—they explain it all well, but it took me a couple of tries to wrap my head around all of it. Given what I’ve come to learn so far, though, is that the two episodes seem like a (free!) one-oh-one masterclass in growing or scaling any given initiative. Despite being less than an hour long in total, the conversation goes way beyond “number of users”. Andrew, Jeff, and Sonal dive deep into the kind of patterns we should hope to see (and find ways to encourage) in order to garner genuine growth, engagement, and retention patterns. It is super sophisticated while still being kinda simple. That said, they’re talking about startups, customers, and technology-driven businesses. Applying those lessons to initiatives in public post-secondary—co-curricular leadership development programs, in my case—is not straightforward. So, that’s the challenge: how do we generalize their insights into the world of post-secondary student services? Here I explore that question with more questions. There’s probably no simple answer for these, but thinking about these concepts could deepen how we grow (and evaluate the growth of) post-secondary services. Question 1: Lifetime Value vs. Lifetime Impact? The first episode focuses on user acquisition. The analogy for us is when students first use our services, tools, or go to their first event or program. Jeff and Andrew describe organic growth—word of mouth-type acquisition—and inorganic growth (paid ads and other campaigns). They talk a lot about the tension between the “cost” of acquiring users and the lifetime value (LTV) of a given user. How should we think about these ideas in student services? “Student Acquisition Costs” have a direct parallel. Is there a useful analogy for LTV? (I.e., “Degree/Career Impact”?) The implication is that acquiring certain students might cost more, or at least demand different strategies, but have a greater impact. Question 2: Semesterly Active Users? The podcasters reference a variety of “active user” metrics: Daily Active Users (DAU), Monthly Active Users (MAU), last-seven (L7) and last-twenty eight (L28)… What is a useful and realistic “active user” metric for post-secondary student services? We don’t actually want our students to use all of our services daily. As the podcasters put it, there’s a certain ideal cadence to the way they should use our services. But what is that cadence, and how do we ensure we’re meeting it? Question 3: Network effects? Jeff, Andrew, and Sonal talk about the “network effect” in both episodes. This is the concept that a service becomes more valuable/powerful the more users it has. Is there an analogy to the services we’re already running, and are we taking advantage of it? Or, are we missing an opportunity to build in a network effect or similar positive acquisition, engagement, or retention feedback loops somehow? To be clear, I don’t think it’s a good idea to translate directly from the high-growth profit-driven startup world into post-secondary services work and life. The organizations have different motives and needs, incentives and costs, and—most important—different stakeholders, with different obligations to those stakeholders. Still, there may be powerful, creative opportunities hidden in the lessons we borrow from one another. Students 1 notes with this tag • Student Acquisition, Engagement, and Retention: Analogies from tech startups a16z is a podcast from Andreesen Horowitz, one of the leading venture capital firms in the US. Their portfolio has included Airbnb, BuzzFeed, Facebook, Twitter, and many many other big companies—they know what they’re doing! Two recent episodes on the podcast feature Andreesen Horowitz general partners, Andrew Chen and Jeff Jordan (some of the people who make investment decisions). They are interviewed by host Sonal Chokshi about how to think about user (or customer) acquisition and user engagement and retention. (You should also be able to get these episodes using any given podcasting app, searching for a16z, and grabbing the two recent episodes titled The Basics of Growth.) I’ve listened to these episodes a couple of times since they came out a week ago. There’s a lot of terminology and concepts to parse—they explain it all well, but it took me a couple of tries to wrap my head around all of it. Given what I’ve come to learn so far, though, is that the two episodes seem like a (free!) one-oh-one masterclass in growing or scaling any given initiative. Despite being less than an hour long in total, the conversation goes way beyond “number of users”. Andrew, Jeff, and Sonal dive deep into the kind of patterns we should hope to see (and find ways to encourage) in order to garner genuine growth, engagement, and retention patterns. It is super sophisticated while still being kinda simple. That said, they’re talking about startups, customers, and technology-driven businesses. Applying those lessons to initiatives in public post-secondary—co-curricular leadership development programs, in my case—is not straightforward. So, that’s the challenge: how do we generalize their insights into the world of post-secondary student services? Here I explore that question with more questions. There’s probably no simple answer for these, but thinking about these concepts could deepen how we grow (and evaluate the growth of) post-secondary services. Question 1: Lifetime Value vs. Lifetime Impact? The first episode focuses on user acquisition. The analogy for us is when students first use our services, tools, or go to their first event or program. Jeff and Andrew describe organic growth—word of mouth-type acquisition—and inorganic growth (paid ads and other campaigns). They talk a lot about the tension between the “cost” of acquiring users and the lifetime value (LTV) of a given user. How should we think about these ideas in student services? “Student Acquisition Costs” have a direct parallel. Is there a useful analogy for LTV? (I.e., “Degree/Career Impact”?) The implication is that acquiring certain students might cost more, or at least demand different strategies, but have a greater impact. Question 2: Semesterly Active Users? The podcasters reference a variety of “active user” metrics: Daily Active Users (DAU), Monthly Active Users (MAU), last-seven (L7) and last-twenty eight (L28)… What is a useful and realistic “active user” metric for post-secondary student services? We don’t actually want our students to use all of our services daily. As the podcasters put it, there’s a certain ideal cadence to the way they should use our services. But what is that cadence, and how do we ensure we’re meeting it? Question 3: Network effects? Jeff, Andrew, and Sonal talk about the “network effect” in both episodes. This is the concept that a service becomes more valuable/powerful the more users it has. Is there an analogy to the services we’re already running, and are we taking advantage of it? Or, are we missing an opportunity to build in a network effect or similar positive acquisition, engagement, or retention feedback loops somehow? To be clear, I don’t think it’s a good idea to translate directly from the high-growth profit-driven startup world into post-secondary services work and life. The organizations have different motives and needs, incentives and costs, and—most important—different stakeholders, with different obligations to those stakeholders. Still, there may be powerful, creative opportunities hidden in the lessons we borrow from one another. Systemic change 1 notes with this tag • ∎ Mexico bans solar geoengineering experiments after startup’s field tests - Reading Session 202301191446 The company, called Make Sunsets, conducted the field tests without prior notice or consent from the Mexican government. This is one of the scary consequences of democratizing technology: volatility. It is getting easier for small teams to take big actions without oversight. And this is a well-intended initiative. The opposite of this would be ecological or environmental terrorism against businesses or governments perceived to be direct contributors to climate change, which surely will happen as climate change advances and people get desperate. At least this test was small: Iseman says he launched two balloons in Baja California last year, each carrying less than 10 grams of sulfur dioxide. That’s a tiny amount of the compound that’s typically released into the air by fossil fuel power plants and volcanoes in much larger quantities — so the release isn’t likely to have had much impact. The business model is interesting: Founded in October 2022, Make Sunsets started with the grandiose vision of releasing enough sulfur dioxide to offset global warming from all the world’s CO2 emissions annually. It’s already selling “cooling credits” for the service at10 per gram of sulfur dioxide — even though it has yet to achieve any measurable impact and can’t guarantee that releasing sulfur dioxide at a bigger scale wouldn’t trigger any unintended problems.

This has obvious parallels with Climeworks, who was recently paid by a few big tech companies to pull carbon from the atmosphere. It is hard to imagine this business model working at scale, though… surely there is a kind of prisoner’s dilemma at play that will keep every company from chipping in. Perhaps we need regulators to require businesses to purchase credits like these to properly recognize the environmental costs of business.

Systems sketching

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# Why are we exceeding the Earth’s carrying capacity?

This is a quickly-sketched model created from a breakout group conversation during the MUN School of Graduate Studies’ “Earth’s Carrying Capacity” dialogue.

Lessons learned from Memorial Student Leadership Conference (MSLC) 2017. These thoughts were spurred by Director of Student Life Dr. Jennie Massey’s opening remarks for the conference, and were reinforced by the keynote speaker, Mr. Seamus O’Regan, MP.

Jennie and Seamus both talked about the oft-haphazard decision making that led to their achievements. The truth about this reinforcing loop is that no matter where you are in the process, you can do something to make it to the next step. No, not every moment will be virtuous – the cycle is not _that_virtuous. It is a cycle nonetheless, and that’s the thing about cycles: they do not stop.

• Limits to (personal) growth

I’m my own worst enemy when it comes to reading articles. I have 211 in a to-do list as I write this, and the larger that grows the more untenable getting through it seems.

In this case the limiter actually escalates, as in order to avoid doing the readings I know I should do, I go off and collect more. 😑

# Last night: “the snowfall looks so nice!”; this morning: “grumble.”

Shovelling as a “fix that fails”: it enables us to keep living here, when here means moving solidified rain from one side of the driveway to the other a dozen times each Winter.

We should just become snowbirds.

• This is why I’m here.

Why sketch systems? Partially as a way to productively vent my sarcasm, and partially as a way to practice systems thinking.

Also, maybe my handwriting will improve?

Technology

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• Researchers detail huge hack-for-hire campaigns against environmentalists

The report concludes that the campaigns represent “a clear danger to democracy” and could allow powerful organizations to target their opponents. “The extensive targeting of American nonprofits exercising their first amendment rights is exceptionally troubling,” Citizen Lab’s report says.

We didn’t want this part of cyberpunk sci-fi…

Theory

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Volatility

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• Systemic lessons from South Korea's Patient 31

This changed with the emergence of “Patient 31.”

Reuters’ coverage of the “Korean clusters” provided the world with a vivid glimpse of the volatility of COVID-19. One person showed poor judgement, and in turn caused cascading catastrophe in her communities.

Events like the COVID-19 pandemic are thankfully rare. Moments like these—when a lot happens all at once, and the experience is shared by a collective—shape future history like nothing else. We are learning a lot from this. Not only are epidemiologists now a famous profession, but we’re all learning exactly what it takes to provide good healthcare, what good governance looks like, how public health is community health, and more.

Patient 31 holds a simple lesson for systemics: the fragility of apparently solid social systems. South Korea seemed to do everything right. Yet, due to the volatile nature of this particular socio-health system, a single “free radical” caused immense damage.

Similar volatility is evident—but more subtle—in other social systems. Consider how memes spread. Our massive communities may seem immovable at times, but it’s clear that the wrong (or right) phenomena can spread rapidly and deeply.

Stay safe.

Workshops

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# Applied Systems Thinking

Based on the Applied Systems Thinking workshop, I’ve collected a variety of resources to help you map complex problems below. The buttons link directly to files to save you some trouble. Be mindful that most of these files are published documents or books, so if you really like them, you should buy a copy and support the authors!

If you have questions or if you’re looking for more resources, never hesitate to reach out to me via  ryan@fulcra.design.

# Introduction

What are systems? Interconnected sets of elements whose interactions lead to emergent, “purposeful” behaviour. (A system’s purpose is not necessarily what someone intends of it, though, nor can it be derived from rhetoric about the system. A system’s purpose can only be defined by examining its actual behaviour.)

Systems—and the actors within them—do exactly what they are “designed” to do. That is, systems act perfectly in tune with the structures and incentives that they have. Only by understanding these complex structures and incentives can we begin to make real progress on the challenges we’re addressing.

# Key Things To Remember

1. The most important thing about mapping is not the map itself. It is the conversations that the map (and the mapping process!) can spark.
2. Stay focused on answering complex questions. Mapping is not an end in itself. You are “finished” mapping when you’ve answered your focusing questions (more below).

# Case Studies

• Remember the story of the development worker trying to support water access in rural Malawi. (37.4 kb) By identifying someone else who was working on a similar problem (community health workers), the development worker was able to gain substantial leverage over their problem with minimal effort. Systems work helps is to identify leverage points.
• Remember the story of The After Prison Initiative (TAPI). (37.4 kb) By helping changemakers working on the same issue see the whole system, each was able to recognize the problems with the system that they were responsible for. Systems help us recognize that every participant in a system has responsibility for the whole system, not just their part.
• Remember the story of the spruce budworm. (37.4 kb) The Atlantic Canadian lumber industry made itself addicted to insecticide by beginning and sustaining insecticide sprays before they understood the long-term forest ecosystem. Systemic innovation is often counterintuitive; the wrong fix in the wrong place can make matters worse.
• Remember the story of the well-intended conference organizers. (37.4 kb) This story teaches two lessons. First, systemic problems are rarely shifted by simple solutions. If you account for only one part of the problem, your fix may fail. Second, it is difficult to understand a systemic problem without involving all of the key stakeholders, particularly the beneficiaries you aim to serve. Involve them in order to see the whole system.

# Developing A Focusing Question

# Why Are “How Might We..?” Questions Useful?

• “How” invokes a sense of opportunity. Therefore, “How might we..?” questions are appreciative.
• “Might” invokes a sense of pluralism. Therefore, “How might we..?” questions are open-ended: there is more than one possible solution.
• “We” invokes togetherness. Therefore, “How might we..?” questions are pursued collaboratively, particularly by asking and answering questions with stakeholders.

However, “How might we..?” questions aim to provide solutions. Before we can “solve” systemic issues, however, we must understand them. And unfortunately for us, these are usually  wicked problems.

To understand a problem, we must begin to explore causality. Systemic designers seek to understand complexity by searching for the patterns that cause our problems—and finding the underlying structure of those patterns that enable their persistence.

To that end, David Stroh suggests developing a “focusing question” in systems work. The purpose of systems mapping, he says, is not to map a system; it is to answer the focusing question

A focusing question has the form “Why does this problem persist?” or “Why, despite our best efforts, intentions, and resources, have we been unable to achieve a certain goal or solve a particular problem?”

# FOUR TYPES OF SYSTEMS MAPPING

# Rich Pictures

Rich pictures come from Checkland’s Soft Systems Methodology (SSM). Akin to a sketchy infographic, these maps are illustrated and make heavy use of labels and symbols to help the mapper or the reader understand a messy situation.

# Actor Maps

Actor maps graph the relationships in a social system. Who (or what organizations) influence who? Who funds who? How is the vision of the system determined? By identifying different stakeholders, including who are the most important beneficiaries and victims of a system, systemic designers might catch gaps, missed connections, or other issues.

# Causal Loop Diagrams

Also known as influence diagrams and effect maps, Causal Loop Diagrams graph the phenomena of a system. What are we trying to stop from happening (or what do we want to happen more often)? What encourages or limits those phenomena? Then, what encourages or limits _those_causes or limits? By drawing causal connections between the phenomena of the system, we can recognize the complex interactions that lead to the (frequently counterintuitive) emergent patterns of behaviour normally invisible.

# Stock And Flow Diagrams

How much of what quantities flow at what rates? Stock and flow diagrams make explicit the system’s stores (e.g., the heat in a cup of coffee) and its rates of change (e.g., how quickly heat escapes from the cup). These diagrams also recognize what controls these rates of change.

# Applied Systems Thinking

# Dimensions Of A System:

Add detail to your systems maps by exploring the different dimensions along which influence might flow: wealth, power, values, knowledge, or beauty. Different types of obstructions—poverty, maldistribution, and insecurity—can cause different types of problems in each of these dimensions.

# Leverage Points:

Leverage points are places within a system with which a little effort yields great reward. Likewise, bottlenecks are places within a system which resistance could cause significant problems.

# Leverage Points:

Leverage points are places within a system with which a little effort yields great reward. Likewise, bottlenecks are places within a system which resistance could cause significant problems.

# Systems Archetypes:

Systems archetypes are common patterns identified in causal loop diagrams or stock-and-flow diagrams. Archetypes exhibit similar behaviours and can be resolved by similar solutions.

# The Systems “Business Idea”:

Do you need a particular actor or phenomena to receive resources/power/etc.? Where would that resource come from? What influences how much of the resource gets distributed? How can you increase those influencing forces? The business idea uses a causal loop diagram to map the systemic structure of an organization’s strategic sustainability. It makes explicit the phenomena that generate resources for the system to reinvest—and the strategic competencies that the organization can use to enhance those phenomena.

# Systemic Theories Of Change:

What is the change strategy you’re adopting? Similar to the business idea, a systemic theory of change plots a theory of change model in systemic form, identifying the goal phenomena to enhance (or limit), the key activities that can support that enhancement (or limitation), and the inputs required to sustain and scale those activities.

# Systems Stories:

Never explain a systems map in a pitch or to a general audience. Instead, follow the iceberg model to distill a systems story

1. Describe what happened (an example of the event or phenomena the systemic designer seeks to address);
2. Describe what has been happening (the pattern of events that lead to the problem or issue); and
3. Describe why (the underlying causal structure that enforces the persistence of these problematic patterns).

# Technology For Systems Mapping

Mural

Mural.co is a collaborative tool for design sprints. As such, it provides features for collaborative whiteboarding and sticky noting, voting via dotmocracy, and a variety of other neat and helpful tools. It is very free-form (and as such has no features specifically made for systemic design) but that open-endedness may be useful.

Loopy

Nicky Case’s  Loopy is a simple tool that allows you to simulate systemic behaviours. It is very unsophisticated (e.g., it is challenging to provide precise system settings) but it is extremely gestural and is therefore fun to use to illustrate and explore ideas.

Plectica

Plectica is a “visual mapping software”. It allows you to nest and draw connections between cards representing anything. The goal of the app is to provide a simple interface for complex ideas.

Kumu

Kumu is a web app built specifically for systems mapping. It  features extensive features and documentation and a lively support community full of fellow systems mappers who like to help one another. The developers/founders are active participants in that community and regularly provide customer support, too. Develop actor maps, systems maps, and all kinds of other interesting interactive visuals with Kumu.