Tag: complexity theory

complexityeducation & learningevaluationinnovationknowledge translation

You Want It Darker?


It is poetic irony on many levels that weeks after Leonard Cohen releases his album about the threat of death that he passes on, mere days after we saw the least poetic, most crass election campaign end in the United States with an equally dramatic outcome. This points to art, but also to the science of complexity and how we choose to approach this problem of understanding– and whether we do at all — will determine whether we choose to have things darker or not. 

A million candles burning for the love that never came
You want it darker
We kill the flame

Canadian-born and citizen-of-the-world poet, literary author, and songwriter Leonard Cohen passed away last night and the words above were part of his final musical contribution to the world. It is fitting that those words were penned at time not only when Cohen was ill and dying, but also as we’ve witnessed the flames of social progress, inclusion, and diversity fall ill.

Donald Trump is the president-elect of the United States, a fact that for many is not only unpalatable, but deeply troubling for what it represents. A Trump presidency and the social ills that have been linked to his campaign are just the latest sign that we are well into a strange, fear-ful, period of history within Western democracies. His was not a win for ideas, policy, but personality and as a vector for many other things that simply cannot be boiled down exclusively to racism, sexism, celebrity, or education — although all of those things played some part. It was about the complexity of it all and the ability for simplicity to serve as a (false) antidote.

No matter what side of the political spectrum you sit, it’s hard to envision someone less suited to the job of President of a diverse, powerful nation like the United States than Donald Trump using any standard measure of leadership, personality, experience, personal integrity or record of public conduct. Yet, he’s in and his election provides another signal that we are living in complex times and, like with Brexit, the polls got it very wrong.

We are seeing global trade shrink at a time when globalization is thought to be at its highest. We are witnessing high-profile acts of hatred, discrimination and abuse at at time when we have more means to be socially connected across contexts than ever before. We are lonely when the world and connection is at our fingertips.  It is a time of paradox and when we have so many means to cast light on the world, we seem to find new ways to kill the flame.

It is for this reason that those who deal with complexity and seek positive social change in the world need to take action lest things get darker.

Complexity just got real

The election of Donald Trump and the Brexit vote are two examples that should serve to wake-up anyone who seeks greater accounting of complexity in the making of social decisions.

This is not about voting for a Republican President or for citizens wanting greater control of Britain, it’s about understanding the premise of which those decisions were based on. The amount of cognitive dissonance required to assume that Donald Trump has the qualities befitting a leader of a country like the United States is truly astounding. And just like Brexit, the theories and models proposed post-event by the same people who predicted the opposite outcome pre-event will be just words, backed with too little understanding of complexity or why things actually happened.

Those who understand complexity know that these simplistic explanations are likely to be problematic. But that doesn’t make us better people, but it does mean we have certain responsibilities.

Complexity rhetoric vs science

For those who rely on complexity science as a means of understanding these kinds of events its now time to start matching the science to our rhetoric so we can back up the talk. In crude, but truth-speaking pop culture parlance: “This shit just got real“.

As complexity and systems thinking has gained attention in social science and policy studies we are seeing much more attention to the idea of complexity. Yet, the level of rhetoric on social complexity has overwhelmed any instances of evidence of how complexity actually is manifest, emergent, harnessed, or accounted for in practical means.

This isn’t to say that the tenets of complexity for understanding social systems aren’t true, but rather we don’t know that it’s true for sure and to what extent in what situations. I write this as a true-believer, but also as one who believes in science. Science is about challenging our beliefs and only if we cannot refute our theories through our best efforts can claim something is true. Thus, if we can’t show consistently how the principles of complexity are employed to make useful choices and inform the documentation of some of the outcomes related to our actions based on those choices, we are simply making fables not flourishing organizations, communities and societies.

Showing our work

Without something more than rhetoric to back our claims up we become no better than a politician claiming to make America great again because we’ve got great ideas and will be the greatest president ever because we have great ideas.

This is not about reverting to positivist science to understand the entire world, but about responsible practice in evaluation and research that allows us to document what we do and explore the consequences in context. Powered by complexity theory and the appropriate methods, we can do this. Yet, too often I hear reference to complexity theories in presentations, discussions and papers without any reference to how its been used in real terms (and not just extracted from some other realm of science like bee colonies, natural ecosystems and simulation models) to influence something of value beyond serving as an organizing framework.

Like little kids in math class: we need to show our work.

How did complexity manifest in practice in this case? What methods were used to systematically document the process? How does this fit / challenge the theories we know? These are questions that are what responsible scientists and evaluators ask of their subjects and its time to do this with complexity, regularly and often. No longer can we give it the relatively unchallenged ride it’s been given since first being introduced as a viable contributor to social theory about 20 years ago.

The reasons have to do with what happens when we stop trying to understand complex systems.

Evaluators and social sciences’ new moral imperative

As the US election was unfolding I became aware of some prescient, wise words that were uttered by former US Supreme Court Justice David Souter speaking at a town hall prior to the last election. His words were chilling to anyone paying attention to the world today. In the quote and interview (see link) he says on the matter of government and democracy:

What I worry about is that when problems are not addressed, people will not know who is responsible.

His words are not just about the United States or even politics alone. The further we get from understanding how our social, economic, political and environmental systems work the more we all become vulnerable to the kind of simplistic thinking that leads us to someone that embodies H.L. Mencken’s mis-paraphrased words*:

There is always an easy solution to every human problem — neat, plausible, and wrong

It is our duty as scientists and evaluators to show the world the work of the programs, policies and initiatives that are aimed at changing systems — no matter what that system is. We need to be better at telling the story of programs using data and communicating what we learn to the world. It’s our role to show the work of others and to let others see our work in the process. By doing so we can make a contribution to helping address what Justice Souter meant about people not knowing who is responsible.

And like Mencken’s message, our answer won’t be one that is all that neat, but we if we approach our work with the wisdom and knowledge of how systems work we can avoid Mencken’s trap and avoid presenting the complex as simple, but we will go further and illustrate what complexity means.

It is our moral duty to do this. For if not us, who?

People do understand complexity. Anyone with a child or garden knows that there is no ‘standard practice’ that applies to all kids or any years’ crop of vegetables all the time in all cases. It’s evident all around us. We have the tools, theories and models to help illuminate this in the world and a duty to test them and make this visible to help shed that light on how our increasingly complex world works. Without that we are at risk of demagogues and the darker forces of our nature taking hold.

We have the means for people to see light through the work of those who build programs, policies and communities to illuminate our world. In doing so we not only create the candles as Leonard Cohen speaks of, but the curiosity and love that keeps that flame burning. We can’t kill the flame.

And we could use some love right now.

Thanks Leonard for sharing your gifts with us. I hope your art inspires us to reflect on what world you left to better create a world we move to.

*Mencken’s original quote was: “Explanations exist; they have existed for all time; there is always a well-known solution to every human problem — neat, plausible, and wrong.” Alas, this doesn’t make as pithy, Powerpoint worthy comment. Despite the incorrectness of the paraphrased quote attributed to Mencken, it’s fair to say that in many organizations we see this as a true statement nonetheless.

Image Credit: Shutterstock, used under licence.


Of tails, dogs and the wagging of both

Who's wagging whom?

Who’s wagging whom?

Evaluation is supposed to be driven by a program’s needs and activities, but that isn’t always the case. What happens when the need for numbers, metrics, ‘outcomes’ and data shape the very activities programs do and how that changes everything is something that is worth paying some attention to. 

Since the Second World War we’ve seen a gradual shift towards what has been called presence of neo-liberal values across social institutions, companies, government and society. This approach to the world is characterized, among other things, by its focus on personal and economic efficiency, freedom, and policies that support actions that encourage both. At certain levels of analysis, these policies have rather obvious benefits.

Who wouldn’t like to have more choice, more freedom, more perceived control and derive more value from their products, services and outputs? Not many I suspect. Certainly not me.

Yet, when these practices move to different levels and systems they start to produce enormous complications that are at odds with — and produce distortions of — the very values that they espouse. We’ve seen the same happen with other value systems that have produced social situations that are highly beneficial in some contexts and oppressive and toxic in others – capitalism and socialism both fit this bill.

Invisible tails and wags

What makes ‘isms’ so powerful is that they can become so prevalent that their purpose, value and opportunity stop being questioned at all. It is here that the tail starts to wag the dog.

Take our economy (or THE economy as it is somewhat referred to). An economy is intended to be a facilitator and product of activities used to create certain types of value in a society. We work and produce goods (or ideas), exchange and trade them for different things, and these allow us to fulfill certain human goals. It can take various shapes, be regulated more or less, and can operate at multiple scales, but it is a human construction — we invented it. Sometimes this gets forgotten and in times when we use the economy to justify behaviour we forget that it is our behaviour that is the economy.

We see over and again with neoliberalism (which is among the most dominant societal ‘ism’ of the past 50 years in the West and more reflected globally all the time) taken at the broadest level, the economy becomes the central feature of our social systems rather than a byproduct of what we do as social beings. Thus, things like goods, experiences, relations and so on we used to consider as having some type of inherent value suddenly become transformed into objects that judgements can be made.

The role of systems

This can make sense where there are purpose-driven reasons to assign particular value scores to something, but the nature of value is tied to the systems that surround what is valued. If we are dealing with simple systems, those where there are clear cause-and-effect connections between the product or service under scrutiny and its ability to achieve its purpose, then valuation measurement makes sense. We can assert that X brand of laundry detergent is better than Y on the basis of Z. We can conduct experiments, trials and repeated measures that can compare across conditions.

It is also safe to make an assumption of value based on the product’s purpose that can be generalized. In other words, our reason for using the product is clear and relatively unambiguous (e.g., to clean clothes using the above example). There may be additional reasons for choosing X brand over Y, but most of those reasons can be also controlled for and understood discretely (e.g., scent, price, size, bottle shape etc..).

This kind of thinking breaks down in complex systems. And to make it even more complex, it breaks down imperfectly so we have simple systems interwoven within complex ones. We have humans using simple products and services that operate in new, innovative and complex conditions. Unfortunately, what comes with simple systems is simple thinking. Because they are — by their nature — simple, these system dynamics are easy to understand. Returning to our example of the economy, classical micro-economic models of supply and demand as illustrated below.

Relationships and the systems that surround them


Using this model, we can do a reasonable job of predicting influence, ascertaining value and hypothesizing relationships between both.

In complex systems, the value links are often in flux, dynamic, and relative requiring a form of adaptive evaluation like developmental evaluation. But that doesn’t happen as much as it should, mostly because of a failure to question the systems and their influence. Without questioning the values and value that systems create — the isms that were mentioned earlier — and their supposed connection to outcomes, we risk measuring things that have no clear connection to value and worse, we create systems that get designed around these ineffective measures.

What this manifests itself in is mindless bureaucracy, useless meetings, pompous and intelligible titles, and innovation-squashing regulations that get divorced from the purpose that they are meant to solve. And in doing so, this undermines the potential benefit that the original purpose of a bureaucracy (to document and create an organizational memory to guide decisions), meetings (to discuss and share ideas and solve problems), titles (to denote role and responsibility — although these aren’t nearly as useful as people think in the modern organization), and regulations (to provide a systems lens to constrain uncoordinated individual actions from creating systems problems like the Tragedy of the Commons).

More importantly, this line of thinking also focuses us on measuring the things that don’t count. And as often quoted and misquoted, the phrase that is apt is:

Not everything that counts can be counted, and not everything that can be counted counts.

Counting what counts

It is critical to be mindful of the purpose — or to reconnect, rediscover, reinvent and reflect upon the purposes we create lest we allow our work to be driven by isms. Evaluators and their program clients and partners need to stand back and ask themselves: What is the purpose of this system I am dealing with?

What do we measure and is that important enough to matter? 

Perhaps the most useful way of thinking about this is to ask yourself: what is this system being hired to do? 

Regular mindful check-ins as part of reflective practice at the individual, organizational and, where possible, systems level are a way to remind ourselves to check our values and practices and align and realign them with our goals. Just as a car’s wheels go out of alignment every so often and need re-balancing, so too do our systems.

In engaging in reflective practice and contemplating what we measure and what we mean by it we can better determine what part of what we do is the dog, what is the tail and what is being wagged and by whom.

Photo credit: Wagging tail by Quinn Dombrowski used under Creative Commons License via Flickr. Thanks Quinn for making your great work available to the world.

Economic model image credit from Resources for Teachers used under Creative Commons License. Check out their great stuff for helping teachers teach better.

complexitydesign thinkingeducation & learningsocial mediasocial systems

Jaron Lanier and Dominant Design

What happens when the system of innovation that serves us so well provides the very means of hindering creativity and limiting our potential? That is a process that Jaron Lanier calls”Lock in” and it is something that doesn’t get enough attention as we contemplate the systems we’re in. The term “lock-in” refers to what we might associate with path dependence in complexity science. It is the well-worn path that guides us in certain ways, often without us knowing it, and consequently limits the range of possibilities that we have before us.

Designer or technologists might also call this phenomenon ‘dominant design‘ . Regardless of what you call it, the phenomenon is worth looking at intently, which is just what Lanier does in his new  new book. Jaron Lanier is a unique figure in the technology world, filling the role of both pioneer, advocate and intense critic. His work on virtual reality has paved the way for a host of later innovations in ways of marrying the person and their perception with technology that can amplify or mediate this experience in virtual environments. Second Life, Flight Simulator and the very real use of VR to explore case scenarios (such as the one that Loyalist College in Ontario has used to train border guards via Second Life)  for practical purposes owe a lot to his him.

It is for this reason that Lanier’s opinion holds some weight. His recent book is a critical look at how we’ve unwittingly created paths that are leading us to stifle innovation, creativity and expression through tools that invoke a type of non-reflective “hive mind” that rewards the mediocre, the middle, and shaves off the edges, where much creative work really happens. Wikipedia, while useful and generating content that might not otherwise be available, also rewards the view of the majority or those types most likely to edit, re-edit and commit to a topic. In a drive towards providing a version of the truth, albeit an edited one, tools like Wikipedia aim for the middle or the points of agreement as the focus of the articles. This might be fine if there were many Wikipedias out there, but there really isn’t. It has become the dominant form of ‘encyclopedia’ out there.

Think of search and you get: Google. The reason is likely because it provides a great search, but also becomes something you’re accustomed to. Have you considered what other relevant things you are NOT seeing because they don’t fit Google’s search algorithm?

Ever organize your files into something other than a folder or dragging it to your desktop? Probably not very often. The reason is that there is a dominant design out there that pushes us to create spaces with similar features across conditions so we have Macs and PCs use folders, have desktops, employ icons and organize information using hierarchies.

Jaron Lanier is worried that we’re creating a social web where creative opportunities that favour individual expression and innovation are getting squashed at the expense of tools and resources that appeal broadly, but have little depth or breadth for innovation. He’s not an anti-technology luddite here, rather providing a series of arguments for why we need to spend more energy contemplating the systems we create and critically examining their impact. Otherwise, we create knowledge generating tools that do little to help people learn, music programs that limit sound quality, and problem-solving tools that actually create more problems than they solve. It’s an interesting read and, while I don’t agree with all of his arguments, there is much to consider as social media becomes bigger, more connected and an ever-greater part of our life. More on this to come.

complexityeducation & learningemergencepsychologysocial media

Social (non) Sense-making

Ripples of knowledge or folly?

A couple days ago I wrote about the idea of social sense-making and how fostering a climate of knowledge sharing that involves trusting people teach and giving them the opportunity to do so. One powerful argument is that teaching is a powerful method of learning in its own right and evidence suggests that we retain much more when we teach someone than when we simply take something in passively. The value here is predicated on a constellation of assumptions that the teacher is providing something of value, can communicate the message effectively, inspires a response in the learner that activates pathways in the brain that encourages reflection and retention, and that the learner and teacher are co-participating in this process.

What is  sometimes forgotten and more problematic is whether or not the content being shared is true.

The Oxford English Dictionary defines true as:

True: Oxford English Dictionary

When you parse through this definition in the context of social learning, much of its component terms such as ‘reality’, ‘genuine’ , ‘standard’, and ‘accurate’ become highly problematic. Much of the literature on sense-making supports the concept of knowledge being socially constructed within a context. The work of Dave Snowden at Cognitive Edge, John Seely Brown, or Gary Klein at Klein Associates are worth looking at in this regard.   The critical realist perspective, which posits that reality is co-created by humans who function within a set of conditions that can be known, but only partly, is the most common expression of this viewpoint. It is a perspective that is congruent with much scholarship in the social sciences and philosophy (although purists will argue how true — as in the definition above — this is).

The sense-making scholarship looks at how relationships influence our decisions and the meaning that is constructed from it. When you engage in a relationship with someone, you’re able to send signals that convey meaning through gesture, tonality, and circumstance that go well beyond what we often bound as the “information” we are trying to share.

But as work popularized by Jeff Howe in Crowdsourcing or James Surowiecki in The Wisdom of Crowds points out, having little relationship with others and partial knowledge is more than sufficient if one’s ability to make sense of the whole is leveraged with collective decision-making capacity of many others. In these models, one only need to see part of the problem to make effective decisions when combined with the equally limited perspective of many other people who, when working together, see the whole. This form of collective decision making has become exceptionally popular in business and even health. One of the other ways to view this model is that it operates something like the SETI@home Project, which was one of the first initiatives to use the power of grid computing to solving problems that required massive computing power to make calculations based on large, complicated datasets. Grid computing uses excess processing power from dormant computers to feed into a large, networked ‘grid’ to create a virtual supercomputer. Howe and Surowiecki describe social decision-making models that look a lot like grid computing. In these models we can afford to use less than our full capacity to understanding a problem because the collective capacity is so much more powerful and will fill in the blanks. This kind of decision-making works well with complicated tasks, those with many different parts, but configured in a manner where we can understand their relationship to each other. Complex problems are quite different. Here, knowledge of the parts and their relationship to each other is only partially useful in understanding the impact on the whole. The crowd-sourcing model might be good for the former, but the latter is where many of the challenges in our health and social system lie and I’m not convinced that this is always a good thing.

Combine cognitive off-loading with a massive amount of information and the tools to enable this information to be distributed and re-distributed quickly and you create new problems, ones that are exacerbated by the shift in our social network ties. Media scholar Clay Shirky recently spoke to this issue in a recent ‘rush’ on the BBC’s Virtual Revolution show by pointing to the example of the Obama administration’s implementation of change.gov and how, in spite of the economic challenges facing the US, two wars, and the threat of climate change, participants on the site chose legalizing marijuana as the #1 issue to solve problems on. The Change.gov site was not making decisions for the country, but the model it employs is consistent with social decision making. It’s probably why we haven’t heard much about this initiative that was the much promoted way to take the engaged citizenry that supported Obama’s election and transform it into a guide for government.

On Facebook, people posted their bra colour on their status to show support for breast cancer (even when there appears to be doubt as to its origins, motives or even rationale for how this was to work). Have you joined a group to show support for something that has no method of converting that support into anything except through collecting names? On email, have you received or been sent a note promising you a free laptop if you forward something on or help save someone by doing the same because each forwarded message will raise money for a good cause? These things abound and the social web allows it to flourish. Yet, by indulging in such things we are creating patterns of decision-making that continue the off-loading of cognition (and maybe action) to the group and go from social sense-making to nonsense making. Someone else will take care of it.

Taking it slow, reducing media consumption to allow processing of information mindfully, and building up your strong social ties (relationships) are three ways to address this problem. But the latter is what I think is critical. In his interview with the BBC, Clay Shirky discusses the challenge a world where weak ties are growing at the expense of strong ties and wonders aloud what impact this will have on democracy and decision making. In a world that is currently fascinated with social networks, the ‘strength of weak ties’ argument posed by Mark Granovetter and many other social networking researchers has become cocktail party talk. While I am glad that social networking research is getting its time in the sun, the concern is that – perhaps for the very reasons I’ve discussed here — people are off-loading the deep thought about it and going into the realm of weak ties over-enthusiastically. Because it is a lot harder to off-load when your close relations will hold you to account and know you well enough to tell when you’re not making sense (and will be comfortable telling you as much). It is in these interactions that the concept of ‘true’ can really be known.

behaviour changecomplexityhealth promotionpsychologypublic health

The Fallacy of New Year’s Resolutions

Happy New Year everyone!

Did you make a resolution or two to do things different this year? I suspect there are already more than a few readers who have measured 2010 by the number of resolutions that have already fallen. If so, you’re not alone. In fact, you’re probably quite normal.

New year’s resolutions don’t work in changing behaviour. In fact,  research reported by Jonah Leherer at the the Wall Street Journal’s health blog points to the problems with these annual rituals and points out that, not only do some resolutions fail to inspire change, they may just impair change. Among the research that Leherer cites is work from Roy Baumeister and his lab at Florida State University that has looked at willpower and cognition. The article reports:

In a 2007 experiment, Prof. Baumeister and his colleagues found that students who fasted for three hours and then had to perform a variety of self-control tasks, such as focusing on a boring video or suppressing negative stereotypes, had significantly lower glucose levels than students who didn’t have to exert self-control. Willpower, in other words, requires real energy.

Anyone who’s tried to quit smoking, exercise more, or suppress any kind of unhelpful thought knows that its hard work. The article cites another study that looked at the role of cognition and attention and diet:

In another experiment, Mr. Baumeister and his colleagues gave students an arduous attention task—they had to watch a boring video while ignoring words at the bottom of the screen—before asking them to drink a glass of lemonade. Half of the students got lemonade with real sugar, while the other half got a drink with Splenda. On a series of subsequent tests of self-control, the group given fake sugar performed consistently worse. The scientists argue that their lack of discipline was caused by a lack of energy, which hampered the performance of the prefrontal cortex.

Since the most popular New Year’s resolution is weight loss, it’s important to be aware that starving the brain of calories—even for just a few hours—can impact behavior. Skipping meals makes it significantly harder to summon up the strength to, say, quit cigarettes. Even moderation must be done in moderation.

When we talk of energy balance in public health we typically refer to issues related to diet and obesity, balancing energy output with energy input from calories. The above research has less to do with this directly and more about ensuring one has the psychological energy necessary to make the changes we want happen.

I’ve discussed this before when referring to organizations. Energy is important to taking information and using it, but so is applying it in a manner that fits with how change happens and on this level much of the conventional thinking fails us. In mainstream psychology, behaviour change tends to focus first on getting the right information, rationally processing it, and then transforming it into a plan of action (goal) that has structure and clearly anticipated and expected outcomes. We place a timeline (consider the Transtheoretical Model and Stages of Change, which suggest 6 months, 3 months, and 30 days as reasonable timelines for thinking about and planning change). We might enlist friends or allies in the battle too or find a role model to follow like with Social Cognitive Theory.

All of this takes place in a very linear, planned way. Yet, that isn’t really how most people change. Robert West and others have pointed out how on issues of smoking cessation (for example), nearly half of quitters had no plan when they finally quit. Indeed, many just quit almost spontaneously. Linear, rational models of change are so prevalent because they make sense to our brain that wants to make things simple, yet change is rarely like this. I would argue that our change processes — individual, organizational or otherwise — are far more complex than this and therefore require a complex model of understanding change to fully address and support change. Maybe we need to create the mental equivalent of catalytic probes to focus the mind or perhaps we need to engage in diverse experiences to transform the way we process information to support new self-organized mental patterns.

What this looks like is something I’m planning to give much more thought to in 2010 on these pages, because on a personal level the linear ways of doing things didn’t work so well in 2009 and not for the world either. Over the next few months, this issue will be explored further on this site and I welcome readers’ thoughts on how this might look from your point of view.

The first stop on this journey will be information, which serves as the foundation for most of the models of change we adhere to and, as you’ll see, not all is what it seems to be.

Best wishes for a great start to 2010 and may the complexity you find bring with it much joy.


complexityeducation & learningpublic healthresearchsocial media

Storytelling in the Age of Twitter


Storytelling has been on my mind this week. Not the kind of stories that many of us had a children like those in Mother Goose, but rather the ones that we more often tell through chance encounters in the hallway or Tweet about over the Internet. However, like Mother Goose many of the stories we tell include narratives that feature archetypes and draw on a long history of shared knowledge between the storyteller and her or his audience. Unlike in cultures where storytelling is fashioned in a manner that requires sustained attention and considerable skill and practice (think of the many First Nations & Aboriginal communities worldwide or the Irish Seanachaidhean), tools like Twitter, blogs and Facebook enable us to tell stories in new, short form ways to audiences we might not even know about. Sorting through the tweets of 150 different people per day requires a process of sensemaking that is different from those used to ascertain meaning in a long form story. Both are valuable.

Although it is tempting to privilege long-form storytelling, the kind found in essays, feature films, and books, it may be those tweets that better fit with our cognitive tendencies for sensemaking. If you think about your average day, you might interact with a few dozen people face-to-face and perhaps many dozens more through your social networks. How many of those interactions featured a full-fledged story; one that had a clear start, middle, end and coherence that could only be gathered from the story itself, not past relationships with the storyteller? Probably very few. Instead, we much more often speak, write, and even film in narrative fragments; small chunks co-constructed and contextually bound. Think about any buzzword or catch phrase and you can see this in action. From ‘whassup‘ to ‘getting Kanyed‘, these terms have meanings that go far beyond the obvious and can be conveyed with one or two words. Twitter represents this very well with its 140 character limit.

This past week I spent three days with a great group of people getting learning about complexity-based approaches to sensemaking using narrative fragments, software and a variety of facilitation techniques aimed at taking the science of complexity into the practical change realm with the folk at Cognitive Edge. What this accreditation process did was provide a theory-based set of tools and strategies for making sense of vast amounts of information in the form of stories and narrative fragments for purposes of decision-making and research. What this method does is acknowledge the complex spaces in which many organizational decisions are made and, through the Cynefin framework, help groups make sense of the many bits of knowledge that they generate and share that is often unacknowledged. It provides a theoretically-grounded and data-driven method of making sense of large quantities of narrative fragments; the kind we tell in organizations and communities.

From a systems perspective, viewing knowledge exchange and generation through the narrative fragments that we produce is far more likely to lead to insights about how the system operates and developing anticipatory guidance for decision-making than waiting for fully-formed stories to appear and analyzing those. This, like nearly everything in systems thinking, requires a mind-shift from the linear and whole to the non-linear and fragmented. But thanks to Michael Cheveldave and Dave Snowden and their team this non-linearity need not be incoherent. I’d recommend checking out their amazing website for a whole list of novel and open-source methods of applying cognitive and complexity science to problem identification and intelligence.

Thanks Michael and the Toronto knowledge workers group for a great three days! I’m looking at my tweets in a whole new way.

complexitydesign thinkingpublic healthscience & technologysocial media

Amazing Stuff: Halloween Edition

Happy Halloween everyone,

Halloween is a rather important day. It’s not only the day that dentists fear, but also the end to my favourite month and the end of the busiest period in the academic calendar when the last of the mid-terms have been graded (round one, anyway) and most grants are in (for now). Tomorrow, retailers will be rushing out the Christmas stuff in North America (at least those that didn’t have it out after Labour Day in September). But as these dates come and go, the amazing stuff continues to find its way into my inbox, Twitter feed, Facebook page, web browser and Google Reader feed. Here’s the neatest and most interesting things I discovered this past week:

1. How to Organize A Children’s Party (or how complexity science can help your work). Interested in complexity science, but don’t really know what it is or how you’d use it in everyday life? This very brief and entertaining video from Dave Snowdon (@snowded) at Cognitive Edge consultancy  explains the difference between ordered, chaotic and complex systems and how they might look from the perspective of organizing a party for 11-year old boys.

2. What Does Meaningful Mean? is an infographic developed by Frog Design to show how to design products and services that actually have meaning to people, not just tell people that they are meaningful. A good reminder to all of us who design things — which is most of us.

3. Brian Solis. OK, so this is not an amazing ‘thing’, but rather a website where Brian Solis, a marketer and PR consultant, hosts his blog and details his ideas and products for public consumption. There are a LOT of new media pundits out there (I won’t name names, but chances are you’ve heard of them) who are being raved about and followed by thousands who have very little to say when you actually listen closely. Brian isn’t one of them. Tour his site and you’ll see some interesting thoughts and insights on how social media can be used effectively by everyone to communicate, and not in some ‘jingo-istic’ manner, but in real terms.

4. Green Porno. I owe a deep debt of gratitude to my colleague Andrea Yip (@andie86) who told me about this entertaining, informative and very odd set of short videos hosted by Isabella Rossellini that combines nuveau performance art, sketch comedy, sex, environmental education and awareness into a funny and uniquely effective medium for communicating about the serious issue of climate change and environmental stewardship.

5. And lastly, Healthmap, is a health and geographic information aggregator that maps infectious disease outbreaks across the globe. Become your own Centre for Disease Control at home and watch where the hotspots are for the flu and other illnesses in your neighbourhood or around the world.