Normative behaviour is what we expect from others operating in the world around us. It is what defines the world “normal”. It’s based on a complex array of history, social conventions, mores, values, context and timing, but it is the reason we know weird or odd from something else. Weird, is by definition, something that is not normal.
What I Learned From Denim
Many years ago I saw a TV special looking at the world of fashion and was struck by the process of designing denim jeans for men. The audience was told that jeans are often designed based on the prototype of the ‘average’ man and then worked out from there. What struck me was that they also said the ‘average’ man has a size that matches about 1 in every 7500 men. So the average — the normal — is not average at all. Indeed, he is particularly rare. Male models who represent this size do very well in their profession.
While there is a norm of social behaviour, there are actually very few people who are wholly ‘normal’ in their actions, nor are there obvious cases where normal is indeed, then norm in social systems. Why? Because social systems are complex by their very nature. They bring together diverse, overlapping, dynamic elements together operating at different scales simultaneously. This is complexity.
Just as individuals we bring our familial history, education, gender, sex, age, faith (if it exists), height, race (which might be highly mixed), experience, physical abilities, fashion choice, body type, vocal acuity, energy level and on to every single interaction we have. Every one of those factors — of this limited group — bring with it a set of unique attributes that individually and socially have differing weight and ‘normality’ depending on the circumstance. To imagine that there is a place where all of these line up with everyone else is utterly absurd if not statistically impossible.
Yet, we cling to the idea that normal exists and might even be something to aspire to. We push a conformity on to our expectations of each other and our research that is unreasonable and often harmful.
It’s not unexepcted. From our earliest days in the society we belong there is pressure to conform. Norms are what hold societies together. They are what creates culture. But where the confusion comes in is with the treatment of norms as truly common things that is universally positive (if attainable).
It is the often mis-attributed following quote to many that still stands out as true:
There is nothing so uncommon as common sense
In complexity science, norms are not disregarded, but are only minimally useful in helping understand patterns of activity. There are path dependencies, which guide certain activities and point to the importance of knowing where things start to help trace the manner in which they project outward. There are things called minimum specifications, often referred to as ‘simple rules’, that can help us create certain conditions within boundaries to shape behaviour. Yet, no matter how we shape these, the normative condition is not and will not be normal in any sense like your favourite pair of jeans.
What Relationship Break-Ups Can Teach Us About Complexity
Psychology and Psychotherapy, when operating at its best, helps people to understanding their true selves independent of, although interdependent with, the world around them. It falls short when it pushes people to conform to social norms apart from their true self. This is a shame.
Ask anyone who has endured a particularly heartfelt breakup of a relationship about normal and you’ll see the pain caused when we ascribe normative behaviour to complex systems. Sensemaking in a breakup is hard to do because of the massive cultural and social baggage we attach to them. Marriages, engagements, boy/girlfriend partnerships, affairs, flings, and flirts all bring socially normative expectations (and taboos) with them. And yet, if you think to any of those relations you’ve had I suspect that you’ll find that at its core there was relatively little ‘normal’ actually going on. Each relationship has its own cadence, pattern and normalness to it.
The best relationships have their own way of creating patterns that are unique to themselves, which is why we can’t replace or hope to replace one with another. They are irreplaceable for the very reason they are special. Not necessarily better or worse — but perhaps more congruent, happy, loving and so on — but different. The things that turn one person on are not the same as some one else and this is what makes relationships hard, but also exciting. This is what a complex adaptive system is like in real life.
Unless there was some obvious punctuated event like an affair or assault or major crime, most relationships don’t end because of a single thing. There might not even be a clear sense of what the “thing” that caused the breakup was. Sometimes people drift apart, sometimes the spark disappears, other times individuals forget who they are, while in some cases people discover themselves to be altogether new. Even still, sometimes this all happens at the same time, over time, in ways that neither couple can see until they are too far apart to connect. A complex system.
Treat this like a linear system and you may find potentially catastrophic consequences and hence the drama that TV and film introduce in their break-up scenes. For a funnier, but no less important take on this, see the video below from Dave Snowden.
This happens with lovers, spouses and friends all the time. A look to popular psychology or media will suggest that there are ways to handle this and no doubt efforts will be made to show how ‘healthy’ people transition and what they do to do so. These ‘healthy’ people will represent the ‘norm’. They’ll take time out for themselves, they’ll ‘get back up on the horse’, they’ll do the Eat, Pray, Love journey.. All of these might work, but they are based on an assumption that whomever is recommending these strategies knows the complexity of the individual’s case to whom they are referring.
Some therapists do, many do not. If you’re in for two or three sessions it will undoubtedly fall to the latter.
This is parallel to what we do in our efforts to inspire systems change. We look to the norms of our society, our discipline, our sector, our community and so on and we hire people for the equivalent of one to three to five sessions to tell us what to expect and do. What we get is Dr. Phil, which sounds great, allows us to boil enormous complications into a one hour soundbite or self-help book, and feel good because we are doing something that matches society’s expectation and we end up with what Russell Ackoff suggests as doing the wrong things righter.
Minding Our Norms
We expect to go into these encounters being the 1 in 7500 male model for jeans, when we are our own model for our our denim.
Work in complexity means breaking up with normative expectations and becoming mindful of what our own unique ones are as well as what the minimum specifications are that link us to that common thread of humanity — society, discipline, family, community, whatever. This is not easy. Mindfulness is very hard, but remarkably simple.
The more mindful we are of the rules and norms we live by or try to live up to, the better we can understand where they fit and where they collide against our own specific condition and setting and better craft strategies and design opportunities for real, genuine social innovation and not a caricature.
We need to be the model for our own jeans. When we do that, the fit will be both bespoke and very fashionable.
Higher education is asking itself some big questions and making substantive changes to the way it sees itself and produces value for society. Education is increasingly being rationalized, which calls into question the metrics that are being used to judge how resources should be allocated. In a previous post, I looked at the jobs metric. Now, it’s time to look at the knowledge metric.
Just the facts
Education writer and teacher Will Richardson‘s TED Book Why School is a provocative read for those connected to teaching or just interested in schooling. While it focuses largely on grade school, the issues are the same for universities and colleges particularly as the primary and secondary students of today are tomorrow’s graduate and professional learners. Richardson questions the role of the school as institution in its current form suggesting that if the status quo — one characterized an information delivery warehouse — is maintained there is little need for schools to exist at all. Yet, if the education within schools is focused on asking better questions and learning when to apply knowledge, not just what knowledge to apply, there is hope.
The current trend in school reform is towards Common Core Standards, which emphasizes specific forms of knowledge, ‘facts’ and asks that students be able to recall such content when required. Under this model, the role of the teacher is one of content manager and facilitator rather than guide or mentor and students are prepped for the tests of their knowledge (memory) rather than be asked to demonstrate its application to anything outside of the test. It is this model that many proponents of online education embrace, because the Internet is a fabulous content delivery system and education can be literally programmed and delivered to students directly without the ‘noise’ that teachers introduce to the signal. Under this model, educational content can be delivered cheaply and widely to support uniform intended effects among learners.
Richardson argues for reforming schools to something closer to the alternative model that was advanced by educational reformer and philosopher John Dewey. Richardson writes:
“In this version of reform, schools and classrooms are seen as nodes in a much larger learning network that expands far beyond local walls. Students are encouraged to connect with others, and to collaborate and create with them on a global scale. It’s not “do your own work,” so much as “do work with others, and make it work that matters.” To paraphrase Tony Wagner, assessments focus less on what students know, and more on what they can do with what they know. And, as Dewey espoused, school is “real life,” not simply a place to take courses, earn grades, amass credits, and compete against others for recognition. There lies the tension.
This second path is simply not as easy to quantify as the first. Developing creativity, persistence, and the skills for patient problem solving, B.S.-detecting, and collaborating may now be more important than knowing the key dates and battles of the Civil War (after all, those answers are just a few taps on our phones away), but they’re all much more difficult to assign a score to. I’m not saying that a foundation of content knowledge isn’t still important. To communicate, function, and reason in the world, students need effective reading and writing skills, as well as a solid foundation in math, science, history, and more. But I’m convinced we must revise the overreaching coursework requirements we place on students — requirements created at a time of scarcity, by the way. And we desperately need to revisit the thinking we’ve developed around assessment that, as Harvard researcher Justin Reich says, “optimizes the measurable at the risk of neglecting the immeasurable.””
Facts vs Problems
The knowledge metric is flawed because it assumes that content solves problems. It also presumes that the curriculum teaches the right knowledge for the right problems and that those problems can be known in advance. Let’s look at these.
One need only look to cigarette smoking as an example of how knowledge alone doesn’t always solve or prevent problems. One would be hard pressed to find anyone over the age of five who doesn’t know that sticking a lit tube of anything in their mouth and sucking on it isn’t at least somewhat unhealthy (and most know it is very unhealthy). An individual’s knowledge of smoking’s effects on physical health may not be complete, but it is often sufficient to inform the decision to quit or not start the unhealthy habit. And yet, citizens in highly educated countries like the United States, Canada and the U.K. smoke more than 1000 cigarettes per year per capita (and over 2700 per capita in places like Russia). These are not countries lacking in information on tobacco and health.
Using students’ ability to recall content makes the presumption that what is contained in a curriculum is what they need to know when they leave their program of study (at least as a start). While it may be somewhat true for students in the humanities and languages, it becomes highly problematic for those in dynamic fields or emergent areas of practice, which is becoming more normal than rare. There is no doubt that a corpus of key concepts, skills and ‘facts’ is useful, but the manner in which this knowledge can and may be applied is changing dramatically. For example, social media has upended communications in ways that very few health professionals are trained for. Journalists are particularly aware of the role that Twitter and related tools have had on their profession.
It also presumes that the content itself is relatively static. Certainly, curriculum renewal is something that most learning institutions engage in, but the primacy of content itself as the driver of education also assumes that the foundation for that knowledge is solid and can be applied today in the manner it was applied yesterday. In dynamic conditions, that isn’t often true. Further, the relevance of knowledge is framed by the problems to which that knowledge is applied. Genetic information, for example, can be incredibly useful when framed against tests that have high confidence, predictability and value to people, yet without such a context it is largely useless to those non-scientists who have it.
Areas of social innovation — which are expanding dramatically in number and scope — illustrate the problem of changing context well. This is a field characterized by problems, problem solving and novelty (which is what innovation is all about). Standard approaches don’t apply easily or at all when we are faced with high levels of novelty. Thinking and re-thinking the problem frame, knowing what to find, where to find it, and the skills to integrate relevant knowledge together is something that is not captured in the knowledge metric. Yet, it is those skills that will lead innovation. Knowledge translation professionals know this and so do knowledge brokers.
Are we designing our educational programming to advance on the kind of design issues of problem framing, finding and solving that our world is facing? Or are we simply taking content that can be obtained through books, the Internet and other materials, repackaging it and creating expensive warehouses of information that take learners out of the world and out of context in the process?
I don’t suggest that universities and continuing education programs stop delivering content, but if knowledge is the metric by which they are judging their success then it behooves educational administrators and funders to justify why they can do it better than other tools. What made sense when content was a rare commodity makes little today when it is overflowing in abundance for little or no cost. Universities and post-graduate training programs have an opportunity to re-imagine education and have the tools to do it in a way that makes learning more powerful and relevant for the 21st century should they choose to change their metrics of success.
How might we take the enormous talent trust that exists among university faculty (and their students) who co-locate (physically, virtually or in some combination) in a school and develop the skills to not only address problems of today, but prepare everyone for possible challenges in the future?
How might we integrate what we know, identify the knowledge we need, and create systems to take advantage of the talent and creativity of individuals to make universities, colleges, and post-professional training venues for innovation and inspiration rather than just content delivery vehicles?
What kind of metrics do we need to evaluate this kind of education should we choose to develop it?
These are questions whose answers might yield more learning than those focused on what knowledge students have when they graduate.
Image source: Shutterstock.
Earlier this week I has the pleasure of attending talks from Bryan Boyer from the Helsinki Design Lab and learning about the remarkable work they are doing in applying design to government and community life in Finland. While the focus of the audience for the talks was on their application of design thinking, I found myself drawn to the issue of evaluation and the discussion around that when it came up.
One of the points raised was that design teams are often working with constraints that emphasize the designed product, rather than its extended outcome, making evaluation a challenge to adequately resource. Evaluation is not a term that frequents discussion on design, but as the moderator of one talk suggested, maybe it should.
I can’t agree more.
Design and Evaluation: A Natural Partnership
It has puzzled me to no end that we have these emergent fields of practice aimed at social good – social finance and social impact investing, social innovation, social benefit (PDF)– that have little built into their culture to assess what kind of influence they are having beyond the basics. Yet, social innovation is rarely about simple basics, it’s influence is likely far larger, for better or worse.
What is the impact being invested in? What is the new thing being created of value? and what is the benefit and for whom? What else happened because we intervened?
Evaluation is often the last thing to go into a program budget (along with knowledge translation and exchange activities) and the first thing to get cut (along with the aforementioned KTE work) when things go wrong or budgets get tightened. Regrettably, our desire to act supersedes our desire to understand the implication of those actions. It is based on a fundamental idea that we know what we are doing and can predict its outcomes.
Yet, with social innovation, we are often doing things for the first time, or combining known elements into an unknown corpus, or repurposing existing knowledge/skills/tools into new settings and situations. This is the innovation part. Novelty is pervasive and with that comes opportunities for learning as well as the potential for us to good as well as harm.
An Ethical Imperative?
There are reasons beyond product quality and accountability that one should take evaluation and strategic design for social innovation seriously.
Design thinking involves embracing failure (e.g, fail often to succeed sooner is the mantra espoused by product design firm IDEO) as a means of testing ideas and prototyping possible outcomes to generate an ideal fit. This is ideal for ideas and products that can be isolated from their environment safely to measure the variables associated with outcomes, if considered. This works well with benign issues, but can get more problematic when such interventions are aimed at the social sphere.
Unlike technological failures in the lab, innovations involving people do have costs. Clinical intervention trials go through a series of phases — preclinical through five stages to post-testing — to test their impact, gradually and cautiously scaling up with detailed data collection and analysis accompanying each step and its still not perfect. Medical reporter Julia Belluz and I recently discussed this issue with students at the University of Toronto as part of a workshop on evidence and noted that as complexity increases with the subject matter, the ability to rely on controlled studies decreases.
Complexity is typically the space where much of social innovation inhabits.
As the social realm — our communities, organizations and even global enterprises — is our lab, our interventions impact people ‘out of the gate’ and because this occurs in an inherently a complex environment, I argue that the imperative to evaluate and share what is known about what we produce is critical if we are to innovate safely as well as effectively. Alas, we are far from that in social innovation.
Barriers and Opportunities for Evaluation-powered Social Innovation
There are a series of issues that permeate through the social innovation sector in its current form that require addressing if we are to better understand our impact.
- Becoming more than “the ideas people”: I heard this phrased used at Bryan Boyer’s talk hosted by the Social Innovation Generation group at MaRS. The moderator for the talk commented on how she had wished she’d taken more interest in statistics in university because they would have helped in assessing some of the impact fo the work done in social innovation. There is a strong push for ideas in social innovation, but perhaps we should also include those that know how to make sense and evaluate those ideas in our stable of talent and required skillsets for design teams.
- Guiding Theories & Methods: Having good ideas is one thing, implementing them is another. But tying them both together is the role of theory and models. Theories are hypotheses about the way things happen based on evidence, experience, and imagination. Strategic designers and social innovators rarely refer to theory in their presentations or work. I have little doubt that there are some theories being used by these designers, but they are implicit, not explicit, thus remaining unevaluable and untestable or challenged by others. Some, like Frances Westley, have made theories guiding her work explicit, but this is a rarity. Social theory, behaviour change models and theories of discovery beyond just use of Rogers’ Diffusion of Innovation theory must be introduced to our work if we are to make better judgements about social innovation programs and assess their impact. Indeed, we need the kind of scholarship that applies theory and builds it as part of the culture of social innovation.
- Problem scope and methodological challenges with it. Scoping social innovation is immensely wide and complicated task requiring methods and tools that go beyond simple regression models or observational techniques. Evaluators working social innovation require a high-level understanding of diverse methods and I would argue cannot be comfortable in only one tradition of methods unless they are part of a diverse team of evaluation professionals, something that is costly and resource intensive. Those working in social innovation need to live the very credo of constant innovation in methods, tools and mindsets if they are to be effective at managing the changing conditions in social innovation and strategic design. This is not a field for the methodologically disinterested.
- Low attendance to rigor and documentation. When social innovators and strategic designers do assess impact, too often there is a low attention to methodological rigor. Ethnographies are presented with little attention to sampling and selection or data combination, statistics are used sparingly, and connections to theory or historical precedent are absent. Of course, there are exceptions, but this is hardly the rule. Building a culture of innovation within the field relies on the ability to take quality information from one context and apply it to another critically and if that information is absent, incomplete or of poor quality the possibility for effective communication between projects and settings diminishes.
- Knowledge translation in social innovation. There are few fora to share what we know in the kind of depth that is necessary to advance deep understanding of social innovation, regularly. There are a lot of one-off events, but few regular conferences or societies where social innovation is discussed and shared systematically. Design conferences tend towards the ‘sage on the stage’ model that favours high profile speakers and agencies, while academic conferences favour research that is less applied or action-oriented. Couple that with the problem of client-consultant work that is common in social innovation areas and we get knowledge that is protected, privileged or often there is little incentive to add a KT component to the budget.
- Poor cataloguing of research. To the last point, we have no formalized methods of determining the state-of-the-art in social innovation as research and practice is not catalogued. Groups like the Helsinki Design Lab and Social Innovation Generation with their vigorous attention to dissemination are the exception, not the rule. Complicating matters is the interdisciplinary nature of social innovation. Where does one search for social innovation knowledge? What are the keywords? Innovation is not a good one (too general), yet neither is the more specialized disciplinary terms like economics, psychology, geography, engineering, finance, enterprise, or health. Without a shared nomenclature and networks to develop such a project the knowledge that is made public is often left to the realm of unknown unknowns.
Moving forward, the challenge for social innovation is to find ways to make what it does more accessible to those beyond its current field of practice. Evaluation is one way to do this, but in pursuing such a course, the field needs to create space for evaluation to take place. Interestingly, FSG and the Center for Evaluation Innovation in the U.S. recently delivered a webinar on evaluating social innovation with the principle focus being on developmental evaluation, something I’ve written about at length.
Developmental evaluation is one approach, but as noted in the webinar : an organization needs to be a learning organization for this approach to work.
The question that I am left with is: is social innovation serious about social impact? If it is, how will it know it achieved it without evaluation?
And to echo my previous post: if we believe learning is essential to strategic design we must ask: How serious are we about learning?
Tough questions, but the answers might illuminate the way forward to understanding social impact in social innovation.
* Photo credit from Deviant Art innovation_by_genlau.jpg used under Creative Commons Licence.
If to think and be aware of those thoughts (to think about thinking) is a defining feature of what it means to be human, why is it such a challenge to think about types of thinking? An answer to that question might help explain why design thinking is so difficult to translate into action and scholarship and why it continues to be the recipient of intense criticism and boosterism.
The other day a colleague reminded me of an essay on the demise of design thinking that I commented on in an earlier post . The post by William Storage adds further to the growing list of critiques of design thinking and ends this way:
In short, Design Thinking is hopelessly contaminated. There’s too much sleaze in the field. Let’s bury it and get back to basics like good design. Everyone already knows that solution-focus is as essential as problem-focus. Stop arguing the point. If good design doesn’t convince the world that design should be fully integrated into business and society, another over-caffeinated Design Thinking book isn’t likely to do so either.
Storage is right to argue that another book will not convince people of the merits of design or design thinking (which is different), but I can’t imagine it is just because of its merits. There appears to be something that troubles people with picking up metacognitive concepts.
Thinking about (Design) Thinking
Metacogntion is thinking about thinking and concepts like design thinking and systems thinking are, at their most basic, about the thought processes involved in contemplating systems or design. What commentators like Storage and Bruce Nussbaum are railing against is how this more sophisticated concept of design thinking (design metacognition if you will) has over time become synonymous at best, but a wholesale replacement at worst with a set of tools and creativity exercises.
Here we see the gap between the methods and their methodology.
Systems thinking, having had a few decades jump on design thinking seems to be faring better in that its common use is treated more as a metacognitive exercise than just a method, but only slightly. Why does adding thinking to something make it so difficult to communicate?
There is a reductionist push towards making thinking — design thinking, systems thinking, critical thinking, visual thinking — into a discussion of methods and tools. The concern, not unfounded, is that concepts like design thinking is pitched as a set of very simple techniques to provoke innovation while being stripped of its genuine innovation potential and reflective capacity, ironically removing the “thinking” part of the approach. These tools are manifest expressions of thinking and facilitators of it, but they are not thinking on its own.
The business and evidence of thinking
Maybe this is our fault for not putting thinking into the development of these concepts from the start. For example, the field of design suffers greatly from a lack of scholarship and theory around its methods and approaches. Designers are a practical bunch and seek to create and build things over theorizing and submitting their own processes to research. There are notable exceptions to this of course, but overall it is safe to say given design’s pervasiveness in our world that we know relatively little about it.
Systems thinking (as it applies to human systems) is in a different position, almost an opposite position. Whereas design thinking has come from a long history of practice with little formal research supporting it, systems thinking has emerged largely from academia and has far less empirical support for its applications to social affairs.
Another issue is economic. The drive for innovation-led market advantages in many fields is pushing anything to support such activity — something design thinking can do — into high demand. Markets abhor vacuums so they get filled and early markets favour the swift and bold, not necessarily quality. As my doctoral advisor once told me when I was hesitating on publishing my research: “people remember the first, not necessarily the best“.
Thus, we have entire business enterprises founded on teaching people design thinking without much depth in their process or intellectual foundations to support their work. They are out there in spades and contributing to the reasoned distrust, frustration and dislike of design thinking by many who could be its biggest advocates. Whether that’s hopeless or not remains to be seen.
So what is to be done? One option, that taken by Bruce Nussbaum, is to consider design thinking a failed experiment and seek alternative terms and concepts that capture the essence of what it does to improve innovative thinking, but in a manner that is less distorted. The challenge here is that, even if a new term does supplant design thinking, what is to prevent that concept from being co-opted and distorted as well with the same innovation-related market drivers in place?
Some argue that by formalizing design thinking into accredited programs, designations, certificates or degrees can assure quality just as we’ve started to see creep into the field of evaluation,. This presumes that have an empirically supported or widely agreed definition of what design thinking is and what are its core competencies. It also presumes we have the faculty with these skills and in positions to train people using methods tested to produce specific outcomes. Neither of these is true at present. This is the equivalent of suggesting that artists must have art degrees. Some artists do, but many do not and there is little to distinguish the difference in quality of the work between them.
A third option, the more complicated one and the most flexible, is to consciously build a community of practice around design thinking aimed at improving the scholarship, research and communications about design thinking to enable the wider world to learn about it, debate it, and apply it. This is already starting to form through such venues as the Design Thinking LinkedIn group and the Design Thinking Network. To that end, we could see a tremendous opportunity for professional organizations such as DMI and AIGA to contribute to this by opening themselves up to the wider community in the focus of their events and training options. By increasing commitment from those doing design and design thinking to education and contemplative inquiry into their craft we are naturally developing a field of practice that forms an attractor basin for better thinking and action.
Some further suggests to this point:
- Follow what psychology did after the American Psychological Association President George Miller suggested they “give away psychology” to the world. Psychology was once an elitist, opaque field of therapy and science and now is widely taught, incorporated into nearly every human-centred discipline, and is founded on a strong scientific and practice base. Democratize design thinking.
- Enlist creative professionals from fields like environmental studies, public health, social work, and education into the design thinking fold beyond traditional design disciplines. Get those living the spirit of Herb Simon who are out there trying to actively change current conditions into preferred ones — the social innovators, the public servants, the entrepreneurs of every stripe — to contribute their stories and insights on design thinking and get those into the public sphere for debate and dialogue.
- Fund and support more research programs beyond examples of my own modestly-supported Design Foundations project , which has sought to study design thinking by interviewing those experts that do it and the literature on its practice across disciplines. And rather than proclaim design thinking’s success and power, prove it and document it.
- Evaluate the programs that teach it, the processes used and determine what works, under what context, and document what happened along the way so we can learn more and be better at advocating for the power of design than simply proclaiming its worth.
Let’s contemplate more, study more, and reflect more about design thinking and maybe we’ll become better design thinkers.
What are your thoughts? Comment below.
Does it scale? That question is central to the discussion of social innovation, yet the answer to it might lead us to questions about why it is so important to us in the first place and answers that could surprise us.
“Does it scale?” or “how to we take [idea, product, service] to scale?” are commonly heard questions in social innovation circles; so much so that they are left unquestioned. The thinking behind these questions is that if something works well at one level (or scale) then taking it another scale larger and achieving a wider reach must be better. Who wouldn’t want to see the benefits of something that serves the needs of one population, community or user extended outward and upward?
This is a laudable utilitarian goal, but it is a deceptively problematic one when we look a little closer at what scaling something actually means in practice.
Jamer Hunt, the Director of the MFA program in Transdisciplinary Design at the New School in New York, speaking at last year’s DMI Fall Conference (which is available to view for DMI members), looked at the issue of design scaling through the lens of complexity and pointed to some of the problems with ‘scaling design’ in varied contexts. One of the examples he suggested is that of an ant compared with a human being taking a shower. For humans, the shower’s droplets of water are fine bodies of liquid that perform a particular task of facilitating cleaning, but for an ant those same droplets are enormous orbs of potential death. Water doesn’t scale the same for a human and an ant even though it is the same substance at both levels and the shower is identical in its structure.
In physics this is called scalar variance. What works ideally for humans is terrible for ants even though we are speaking of the same substance, same planet, same context. Water (most notably, a shower of it) doesn’t scale well in this case.
Yet, there is this insatiable desire among those working in social innovation to “scale things up” and “bring our innovations to scale” (even if we have little concept of how that would look or — as I will discuss — what that really means). The adherence to scaling as an ideology in social innovation (and applied social science in general) is bordering on “four legs good, two legs better” territory.
The Cult of Efficiency
International affairs scholar Janice Gross Stein attributes some of this fascination with scaling to a cult of efficiency, a political ideology that assumes that we can always rationalize human services optimally. What she found is that efficiency is used falsely as a stand-in for accountability, particularly in fields like education. Far from being against striving for optimal use of scarce resources, Stein nonetheless concludes that efficiency in human systems doesn’t always scale (my phrase, not hers) and that bigger and faster is often not better. Anyone who has taken a lecture with hundreds of others knows the difference of scale in learning between that and a seminar of five to ten people.
Taking Jamer Hunt’s argument: Bigger is just bigger…and whether its better or not is dependent on whether you’re an ant, a human and need to come into contact with water.
Designing for Systems and Scale: The Powers of 10
Designers and systems thinkers probably know the movie “The Powers of 10” by legendary designers Charles and Ray Eames. It’s a fascinating short film that looks at the universe moving out from a human being into the cosmos and inward towards what would now be quarks and everything in between. It is perhaps the best example of scaling ever produced. Beyond its educational and entertainment value, the Powers of 10 provide an illustrative example of where striving for scaling social innovations could be foolish and where it could have potential.
When traveling through the universe it is easy to see scales that are self-similar, thus they share properties that make them optimally relatable. These forms are often fractal in nature (thus, they share the same properties at different scales like that of a snowflake). Imperfectly, certain scales in the Powers of 10 are close to self-similarity where one scale looks and shows behaviour similar to those adjacent to it. These are spaces where it may be possible to transport an innovation from one to the other to good effect. Others scales look radically different from one another, suggesting a mis-fit in the scalar variance.
This is an idea, not an empirical point as we have little research on scalar variance in social innovation. Scaling innovation makes greater sense when the social systems have similar structures and ‘shapes’ and less when they do not. It is why in organizational science, certain models of management and decision making transport well from setting to setting and others do not. It’s why we’ve seen quality improvement processes like Six Sigma achieve great success in certain industries and firms and spectacularly fail in others.
Rather than adhere to an ideology that imposes scaling as a goal, social innovators need to generate the kinds of intelligence about the systems they are operating in (or seeking to operate or expand into) before making plans for scaling a promising intervention or product. As funders and policymakers this means setting performance targets that are appropriate or, perhaps better yet, working developmentally with innovators to co-create the outcomes of interest and the measures and metrics used to determine scalability and appropriateness early in the design and implementation cycle.
Without best evidence (which is almost always lacking in social innovation by its very nature), setting performance targets related to scale a priori is foolish. For innovators themselves, equally foolish is not gathering the kind of information about the systems they are operating in to know if they are the human or the ant and whether a shower is on the way.
When journalist and book author Daniel Pink tweeted the above image the other day it provoked thinking about what real learning means and what it takes to achieve it. We produce enormous amounts of knowledge, yet struggle to put it into use, but we also teach much and learn little because the systems we’ve designed for education and experience don’t match our expressed interest and rhetoric around learning.
In my graduate course on behaviour change I would ask students on the first day why they were taking the class in the first place. Aside from the few students for whom the course was required everyone else was doing it by choice because there were many others to choose from. So why would they choose this one?
The answers would vary, but inevitably I’d hear over and again that students love learning and wanted to understand more about behaviour change, because they were interested in change and some would even say they were good at it and wanted to help others do it.
These are all well-meaning and said in a spirit that I think was honest and true. Except the reality is that it is likely a big, huge lie and one that we all share in its telling.
I would counter with two things:
- Loving the idea of learning something new is different than actually seeking out learning opportunities and that most of us love the former, but are not so enthused about the latter;
- The only people who regularly welcome change are babies with soiled diapers.
To illustrate the first point I simply ask people to consider the last conference they went to where there were options on what sessions to attend. How many of the sessions did they attend that featured content that confirmed or gently extended what they already knew versus content that was new? If you’re a health promoter doing community engagement work, sessions on Bayesian modelling for epidemics might offer far more learning than a session on working with diversity in communities (particularly if that is what you already do). Even more, how often do people go to sessions from people they know or have already seen speak? Chances are, many.
One could argue that there are subtleties that a conference presentation might offer on a familiar topic that are worth attending and while I would say that has merit, most learning that has impact is uncomfortable at some level. It extends our thinking, challenges our beliefs, or re-arranges our worldview — in ways small and large.
Wanting knowledge and living learning
Many people will say “I love change”, but that is usually in the context that everyone else is changing, not them. When I was the boss and said “things must change” it was very different than when my staff or my boss would say “things must change“. As a behaviour change educator and intervener, I need to be mindful of my own ironies and resistance to change. So should we all.
The same thing goes for knowledge. Academics are famous for ending studies with “more research is needed”. We never seem to have enough knowledge. There are two problems with this idea.
The first is that, in dynamic and evolving environments, we will never have perfect knowledge that fits like a glove, because the contexts are always novel. This isn’t to say that evidence isn’t useful, but ‘good enough’ knowledge might be a more reasonable demand than ‘best evidence’ in many of the situations where complexity is high and so is change. That’s why data gathering techniques like developmental evaluation aren’t attractive to those who need certainty.
But there is another problem with the knowledge quest and that is one of integration. In our efforts to seek more knowledge, are we integrating what we are learning from what we already have? Are we savouring the data we collect, the articles we read, the Tweets and blogs that get forwarded are way?
We quest for more, but should we quest for better?
A newly published paper synthesized research on event horizons on memory and found that shifts in activities around an event — boundaries — can prompt forgetting and recall. We remember transitions between activities, but they also prompt forgetting depending on the mindfulness associated with the act. When we are deluging ourselves with more data, more media, more everything, we are increasing the potential remember rate, but due to the volume of content, I would surmise that we are increasing the forget rate much more. Simply reflect on your high school or undergraduate education and ask yourself if you remember more than you forgot about what you learned.
We are so busy with our search for new knowledge that we interrupt opportunities to learn from what we have.
Serious learning means non-doing
Returning to the tweet from Dan Pink, it’s worthwhile considering what it means to learn and the systems we have in place to facilitate learning. The tweet links to a discussion of how German companies give their employees five days of off-site continuing education each year. This concept of Bildungsurlaub is a leave designed to allow employees to stretch their thinking and integrate something new. Not only is off-site learning important, but the time associated with integrating material is critical.
A read of the literature on innovation and research shows consistently how time off, quiet time, slow time and down time all contribute to discovery. Robert Scott Root-Bernstein’s brilliant Discovering, Jonah Lehrer’s Imagine, or Steven Johnson’s Where Good Ideas Come From are all books that dive deep into creative production and show that great discoveries and innovations come from having time (with limits) to integrate material to learn. Freedom to create, explore and sit and mindfully reflect are all united concepts in the pursuit of good learning. Not everything requires this, but big concepts and bold ideas do from mathematics to science to social science and philosophy.
Yet, at an organizational and systems level, where is the support for this? Even university faculty (the tenured ones at least) who have generous vacations and sabbaticals are finding themselves crunched for time between the fight for one of the ever-fewer grants, increasing numbers of students and teaching demands, and the added push to ensure knowledge is translated. The image of faculty sitting and reading and thinking is truly an imagination. Most of my colleagues in academia do little of this, because they are out of time.
In the corporate and non-profit world this is worse. Every hour and day is to be accounted for. The idea of sending people off to learn and to think seems anathema to productivity, yet research shows incredible powers associated with taking a break and doing less and not more.
Getting serious about learning
To illustrate the scope of the problem, the University of Toronto holds one of the finest academic library systems in the world and has over 11.5 million books and 5.7 million microform materials. It is one university (of many) in one city. Add in the local Toronto public library system, the network of universities and other libraries it is connected to, local and global bookstores and all the content freely available online that is not part of this system and I challenge anyone working in social innovation or public health to say with conviction that there is a lack of knowledge out there on any important topic. Yes, we don’t know it all, but we don’t do nearly enough with what we do know because there is so much.
We will not read it all nor can we hope to synthesize it all, but we can do much with what we have. Just looking at my own personal library of physical books (not including all I have in the digital realm between books and papers) it’s easy to see that I have more than enough knowledge to tackle most of what I am facing in my work. Most of us do. But do we have the wisdom to use it? Do we have the systems — organizations and personal — that allow us to take the time and soak this in, share our ideas with others, and be mindful of the world around us enough to learn, not just consume?
When we spend as much time creating those spaces, places and systems, then we can answer “yes” to the question of whether we’re serious about learning.
Paying attention to the social, technological, economic and environmental stresses and challenges we face isn’t always conducive to positive thinking and sometimes its useful to look at where problems are being addressed rather than created. Where to go for such inspiration is question is where this post begins.
And all the roads that lead you there are winding
And all the lights that light the way are blinding
There are many things that I
Would like to say to you but I don’t know how
I said maybe, you’re gonna be the one that saves me
And after all, you’re my wonderwall
- lyrics from “Wonderwall” by Oasis (1995)
Inspiring words and the desire for inspiring action
Marketer and blogger Mitch Joel recently wrote on the growing trend towards appending inspirational quotes to images and posting them on Facebook. I’ve seen it, too. Sites like Values.com, apps like Little Buddha and tweet feeds like @Zen_Moments do a great job of providing a daily dose of inspiring words. These daily doses of inspiring words can motivate further action or pacify us, but it is only when something happens that our world is changed. There is wishing for change, imagining change, intending change and then there is action. Our social world only experiences the latter and thus, for social innovation to take place we need to understand actions not just words.
With that, it occurred to me that there are far fewer places online that provide the same sort of wonderwall of resources highlighting actions as there is words. As I mindfully comb through the Web in my daily journeys I find myself amazed at what social innovations are out there facilitated by technology with the World Wide Web. These range from simple one-horse projects to complex initiatives, all working towards making the world a better place.
Why don’t we have a social innovation wonderwall?
With the many challenges facing us in adapting to a rapidly changing social world it would be useful to have some places and examples that show actions (and particularly the lessons learned from those actions). Listed here are three examples of resources I’ve found and highlight creative examples of social action from fundraising to creation to sharing.
Three socially innovative contributions to a wonderwall
1. Kickstarter. I’m a big fan of Kickstarter and have supported many projects on that site. Kickstarter has projects that are not all social ventures, but many aim to do good. Films, books, performances and other projects that don’t have mechanisms for raising funds from grants or attracting funding from traditional venture capitalists or lenders. Browse through and you will find a host of creative ways to use technology, share ideas and maybe find something you want to back.
2. OneWorld Futbol . I am a big fan of Sting‘s music and enjoy his fabulous (and free!) iPad app and noticed a link on the latest update that led to the latest charitable initiative he’s supporting called the OneWorld Futbol project. The idea brings technological innovation together with social need to create an indestructible soccer ball that can be distributed globally to children in war-torn and impoverished countries. Through a buy-one-get-one program, you can get your own ball to perhaps inspire youth here to connect to their peers in less advantaged parts of the world. Soccer will not save the world and, like similar-spirited programs such as Right to Play, there is no mistaking sport for replacing the need for food, clean water and shelter, but it adds a quality of life to youth that is also important while providing opportunities for leadership and joy-making.
3. Fast Company. The social design and technology magazine has long been a leader in reporting on innovations, but recently it launched three spin-off sites (FastCoDesign, FastCoCreate and FastCoExist) that highlight ideas and products that are making a difference in the world in creative ways. For-profit, for-benefit and governmental innovations are all profiled here. Nearly every day there are updates on initiatives taking place across the globe (although mostly in the United States) providing a veritable feast of inspiring actions taken to potentially spur social innovation.
These are but three examples to show how actions are being done in different ways: raising funds, creating products, and showcasing work of products already created. Know of more? Add them to the comments and perhaps we can start creating a wonderwall to inspire others.
* Photo of the Wonder Octopus from the Wikimedia Commons used under license.
The human body is oriented towards forward motion and so too are our institutions, yet while this helps us move linearly and efficiently from place to place, it may obscure opportunities and challenges that come from other directions such as those posed by complexity. Thinking about and re-orienting our perceptions of who we are and where we are going might be the key to understanding and dealing with complexity now and in the future.
When heading out into the turbulent waters that face us we humans tend to look straight ahead and press forward. Our entire physical being and that of all mammals is aimed at facing forward. We look forward, walk forward and this often means thinking forward.
Doing this predisposes us to seeing problems ahead of us or behind us, but is less useful when what challenges us is positioned elsewhere. For this reason, fish and birds, with their eyes on the side of their head, are able to adapt to challenges from nearly any direction quickly. It also allows them to fly/swim in flocks/swarms/schools and operate with high degrees of coordination on a large scale.
These are skills that are useful for handling the social problems that are complex in nature and require mass action to address. But, we don’t have eyes on the side of our head and we tend to look forward or backward to orient ourselves and our activities.
One way this expresses itself in our perceptions of time. Thor Muller, writing in Psychology Today online, highlighted how our perceptions of time influence the way we handle appointments and punctuality with modern technology. Citing the work of anthropologist Edward T. Hall (although mistakenly referring to Manhattan Project contributor Edward Teller), Muller points to the differences in perceived time across cultures and the way that plays out in our treatment of time and technology used to “manage” it and the complexity of everyday life. Monochronistic and polychronistic time orientations matter to whether you see time as a linear, quantifiable phenomenon or a more non-linear, contextual one. One allows you to “bank” time while the other perception deals more with the present moment, less dependent on forward-backward thinking.
Western society and the technologies developed within it are oriented primarily towards dealing with a monochronistic form of time. This works well when patterns, problems and situations have a linear, ordered set of circumstances to them. The cause-and-effect world of normal science fits within this worldview.
Complexity is non-linear and not easily defined in cause-and-effect terms and conditions. Two-dimensional space doesn’t capture complexity the way it can for linear situations. It also means thinking solely in forward and back terms is problematic.
An example of where this comes to conflict is in program planning and evaluation. Traditional evaluation methods and metrics are set up for looking at programs that are planned to start and end with impacts developed and detected in between. This implies a certain level of consistency in the conditions in which that program operates. This control and measure aspect of evaluation is part of the hallmark features of scientific inquiry.
For programs operating in environments of great change and flux, this is a faulty proposition. We cannot hold constant the environment for starters. Secondly, feedback gained from learning about the program as it proceeds is critical to ensuring adaptation and promoting resilience in the face of changing conditions. In these cases, failure to act and adapt on the go may result in a program failing catastrophically.
This is where developmental evaluation comes in. Developmental evaluation works with these conditions to generate data in a manner that programs can make sense of and use to facilitate strategic adaptation rather than simply reacting to changes. As the name suggests, it promotes development rather than improvement.Developmental design is the incorporation of this feedback into an ongoing program development and design process.
Both developmental design and evaluation require ways of seeing the world beyond forward/backward. This seeing comes from understanding where one’s position is in the first place and that requires methods of centring that take us into the world of polychronistic time. One example of a strategy that suits this approach is mindfulness programming. Mindfulness-based programs have shown remarkable efficacy in healing and health interventions aimed at stress reduction across conditions. Mindfulness techniques ranging from meditation to contemplative inquiry (video) brings focus to the present moment away from an orientation towards linear trajectories of time, thought and attention.
Some forms of martial arts promote attentive awareness to the present moment by training practitioners in strategies that are focused on simple rules of engagement, rather than just learning techniques for defence.
These approaches combine inward reflection — reflective practice — with an openness to the data that comes in around them without imposing an order on it a priori. The orientation is to the data and the lessons that come from it rather than its directionality or imposing values on what the data might mean at the start. It means slowing down, contemplating things, and acting on reflection not reacting based on protocol. This is a fundamental shift for many of our activities, but may be the most necessary thing we can focus on if we are to have any hope of understanding, dealing with, and adapting to complexity.
All the methods and tools at our disposal will not help if we cannot change our mindset and orientation — even in the temporary — to this reality when looking at complexity in our work. One of complexity’s biggest challenges right now is that it is seductive in accounting for the massive, dynamic sets of conditions we face every day, yet it lacks methods beyond evaluation to do things with it. The irony of mindfulness and contemplative approaches is that they are less about acting differently and more about seeing things in new ways, yet it is that orientation that is the key to making real change from talking about change. It is the design doing that comes with design thinking and the systems change from systems thinking.
The days of creating programs, products and services and setting them loose on the world are coming to a close posing challenges to the models we use for designing and evaluation. Adding the term ‘developmental’ to both of these concepts with an accompanying shift in mindset can provide options moving forward in these times of great complexity.
We’re at the tail end of a revolution in product and service design that has generated some remarkable benefits for society (and its share of problems), creating the very objects that often define our work (e.g., computers). However, we are in an age of interconnectedness and ever-expanding complexity. Our disciplinary structures are modifying themselves, “wicked problems” are less rare
At the root of the problem is the concept of developmental thought. A critical mistake made in comparative analysis — whether through data or rhetoric — is one that mistakenly views static things to moving things through the same lens. Take for example a tree and a table. Both are made of wood (maybe the same type of wood), yet their developmental trajectories are enormously different.
Tables are relatively static. They may get scratched, painted, re-finished, or modified slightly, but their inherent form, structure and content is likely to remain constant over time. The tree is also made of wood, but will grow larger, may lose branches and gain others; it will interact with the environment providing homes for animals, hiding spaces or swings for small children; bear fruit (or pollen); change leaves; grow around things, yet also maintain some structural integrity that would allow a person to come back after 10 years and recognize that the tree looks similar.
It changes and it interacts with its environment. If it is a banyan tree or an oak, this interaction might take place very slowly, however if it is bamboo that same interaction might take place over a shorter time frame.
If you were to take the antique table shown above, take its measurements and record its qualities and come back 20 years later, you will likely see an object that looks remarkably similar to the one you lefty. The time of initial observation was minimally relevant to the when the second observation was made. The manner by which the table was used will have some effect on these observations, but to a matter of degree the fundamental look and structure is likely to remain consistent.
However, if we were to do the same with the tree, things could look wildly different. If the tree was a sapling, coming back 20 years might find an object that is 2,3,4 times larger in size. If the tree was 120 years old, the differences might be minimal. It’s species, growing conditions and context matters a great deal.
Design for Development / Developmental Design
In social systems and particularly ones operating with great complexity, models of creating programs, policies and products that simply release into the world like a table are becoming anachronistic. Tables work for simple tasks and sometimes complicated ones, but not complex ones (at least, consistently). It is in those areas that we need to consider the tree as a more appropriate model. However, in human systems these “trees” are designed — we create the social world, the policies, the programs and the products, thus design thinking is relevant and appropriate for those seeking to influence our world.
Yet, we need to go even further. Designing tables means creating a product and setting it loose. Designing for trees means constantly adapting and changing along the way. It is what I call developmental design. Tim Brown, the CEO of IDEO and one of the leading proponents of design thinking, has started to consider the role of design and complexity as well. Writing in the current issue of Rotman Magazine, Brown argues that designers should consider adapting their practice towards complexity. He poses six challenges:
- We should give up on the idea of designing objects and think instead about designing behaviours;
- We need to think more about how information flows;
- We must recognize that faster evolution is based on faster iteration;
- We must embrace selective emergence;
- We need to focus on fitness;
- We must accept the fact that design is never done.
Bringing Design and Evaluation Together
Image (Table) Table à ouvrage art nouveau (Musée des Beaux-Arts de Lyon) by dalbera
All used under licence.
Social innovation is often about engaging complicated systems like technology (dry) with complex systems like humans (wet). The implementation and evaluation approaches we take must match wet with dry and knowing when we are dealing with each.
If you’ve ever fixed any kind of machinery, you know that a device that’s exposed to the elements is incredibly difficult to maintain. A washing machine or the underside of a car gets grungy, fast.
On the other hand, the dryest, cleanest environment of all is the digital one. Code stays code. If it works today, it’s probably going to work tomorrow.
The wettest, weirdest environment is human interaction. Whatever we build gets misunderstood, corroded and chronic, and it happens quickly and in unpredictable ways. That’s one reason why the web is so fascinating–it’s a collision between the analytic world of code and wet world of people.
Much of social innovation is becoming like this: a collision between the wet world of people and the dry world of technology. It is hard not to be impressed at the technological capabilities we have at our disposal and how they can be put to use to serve humankind. Mobile handsets, low-cost portable computing tablets, social network platforms like Facebook or LinkedIn, or digital common spaces created by tools like Reddit and Twitter all provide incredible means to connect people and ideas together. Stop and think about what we have at our disposal and it is truly mindblowing, particularly when you think how much that’s changed in just 5 years, 10 years or 20 years.
Yet, the enormity of the scale of these tools and their ubiquity can mask their significance and not always for good. Take Facebook, which just launched its IPO and is the current champion of social networks with over 900 million users. It’s easy to forget that Facebook didn’t even exist 8 years ago and now almost one in 7 citizens on this earth have an account with its service.
This could be a tremendous opportunity for social innovation. Yet, it also speaks to the issue of Seth Godin’s wet and dry analogies for design.
Tom Chatfield, a tech writer from the UK, recently blogged about rethinking our social networks. He points to Dunbar’s number, a well-researched figure that estimates the limits to meaningful human relationships to be between 100 and 230. The drive to scale technologies (the dry) to ever-expanding and increasing numbers is problematic if the limits to my ability to meaningfully connect with the networks they create (the wet) are relatively fixed or difficult to change.
It’s dangerously easy simply to gawp and grimace at the sheer scale of the networks connecting us. The numbers are staggering, and offer a powerful index of how much and how fast our world is changing. But we mustn’t overlook the great lesson to be drawn from work like Dunbar’s: the weight of a special few will always outweigh the many, no matter how great the “many” becomes.
Some have argued that Dunbar’s number is a fallacy in the social media world, choosing to rely more heavily on sociologist Mark Granovetter’s work often summed up as the argument for The Strength of Weak Ties . His early research (see link [pdf] for original paper) focused not on the strong ties between people who were close, but the ‘friends of friends’ effects on transmission of information, which is the space where many innovations and novelty comes from in a network.
This confuses the potential innovation and the human capability to connect across large, diverse networks (a technical, ‘dry’ issue) with the quality of the interaction (a relational, ‘wet’ one). Both exist and both will exist, but there is a difference between learning something new and taking it to scale.
Novelty of information and new ideas comes from the intersection created by cognitive diversity in the design process. This is why designers seek to bring people with different perspectives together to explore concepts and generate ‘wild ideas’ as part of an ideation phase. Lots of information can be very useful in this situation and allow designers (social and otherwise) to see things they might miss if they stuck with a narrow band of perspectives. Yet, bringing these ideas to focus, refining them and transforming them into a social innovation that matters to people is far more relational than we give credit for.
Facebook might be great at linking us to ‘friends’ we’ve lost track of, but in applying a model where all of these friends are treated more or less equally, along with all of the information streamed at us through the main feed, our ‘wet’ interactions are made to feel ‘dry’. Drawing the motivation to scale ideas and engage in the efforts needed to make real change happen from such an approach is unlikely.
A recent post from FastCoExist, part of the Fast Company network of sites, by Ashoka changemakers Alexa Kay and Jon Camfield pointed to the barriers and facilitators for making change happen. Among their principal barriers is the need to connect deeper, rather than broader with each other:
How do we learn to be change makers? Much of the art of change making involves soft skills that we absorb from others that model or demonstrate change making behaviors. This means that learning opportunities are limited by one-to-one interactions and by exposure to other change makers. Compared to traditional fields like entrepreneurship, where there are plentiful resources for training, the practice of change making is still far from being widespread.
One of their principles for change reflects the complexity of social change by encouraging and supporting self-organized networks:
Often leaders or institutions promote dependency with a community. But successful change making communities depend on reducing dependence on one anointed leader. Flat networks and peer-based accountability structures are necessary if a community is to sustain change beyond one individual. The need for change communities and networks to be self-regulating is vital for their sustainability.
This is where walled gardens like Facebook are likely to fall down, just as many custom Ning-based communities have fallen into disuse. Create systems that are too bounded (dry) and we risk sucking the moisture from the human elements (the wet) that make real social innovation happen. Our challenge is finding the right balance between the controlled, stable environments that these new technologies afford and the self-organized, emergent and innovative environments needed to implement and scale our initiatives more effectively.
Wet Leaf By Faustas L, via Wikimedia Commons used under Creative Commons License