Month: August 2012

complexitydesign thinkinginnovationsocial systemssystems science

The Ideology of Scaling Social Innovations

Box scaling

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.

Conceptualizing Scale

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.


complexityinnovationknowledge translationpsychology

Jonah Lehrer and the Crisis of Knowledge Synthesis

Jonah Lehrer - Pop!Tech 2009 - Camden, ME
Jonah Lehrer is/was as big as it gets in science writing and two weeks ago proved the adage that the higher one climbs the farther the fall after admitting to some false content in his stories. This is bad news for him, but may be much worse for all of us interested in making science and innovation knowledge accessible for reasons that have as much to do with the audience as it does the message and messenger. 

Jonah Lehrer was one of our most prolific and widely read science writers until he admitted fudging some quotes about Bob Dylan in his new book, Imagine, which looks at the process of discovery, creativity and innovation. The discovery by fellow journalist (and fervent Bob Dylan fan) Michael Moynihan set off a wave of reflections and investigations of Lehrer’s work revealing passages in the book (and other pieces) that had been reused from his other writings without proper self-attribution and sparking questions about the integrity of the author’s entire body of work. The “fall of Jonah Lehrer” was big news at a time when the London Olympics were dominating most of the media’s attention.

This case is a testament to the wide appeal that Lehrer’s work had beyond the usual ‘science geeks’ while illustrating the power of the internet to enable the kind of curation and investigation to support on and offline fact checking. But what it spoke to most for me is the role

The Writer and his Craft

Much digital type has been spent on the Lehrer incident. Search Google and you’ll find dozens of commentaries looking at how things transpired and how Lehrer ironically succumbed to the cognitive biases he wrote about.

Roxane Gay, writing in Salon, took a gendered approach to the issue and questioned whether our fascination is less with the science and more about the ‘young male genius’. Lehrer’s youth was something she saw as critical to amplifying the fascination with his work. She writes:

When young people display remarkable intelligence or creativity, we are instantly enamored. We want or need geniuses to show us the power and potential of the human mind and we’re so eager to find new people to bestow this title upon that the term and the concept have become quite diluted.

I agree with her on the point about our desire to over-inflate the accomplishments of youth (as if we are *amazed* that any of them could possibly do anything brilliant, which is as offensive to them and it is to older people), although a careful look at Lehrer’s articles and much of the press around his work suggests that he was much less a focus of the attention than his ideas.

John McQuaid‘s take on the affair in Forbes speaks to a larger issue:

Call it “Gladwellization.” It’s not just lucrative, but powerful: your ideas (or rather, the ideas you’ve turned into compelling anecdotes for a popular audience) can influence everything from editorial choices across the publishing world to corporate management and branding strategies.

But with this comes mounting demands to produce, and to recycle. You have to be prolific, churning out longer pieces that give your insights some ballast, and brilliant, bite-sized items. And yet you can’t be too new either: people want to hear what you’re already famous for. In this cauldron of congratulation and pressure for more and more, it’s not hard to see how standards might erode, how the “ideas” might become more important than doing the necessary due diligence to make sure they sync with reality.

‘Snappy Science’ and Synthesis

Innovation is about ‘new’ and there are good reasons why its a challenge to get the message out that this ‘new’ can be adapted, small, and unsexy and still make a large difference in the long run instead of big, bold and transformative right away. We are in an age of selling “snappy science” and it says more about the media and audiences than the authors and scientists producing the original work.

This snappy, bite-sized science might sell books and make for great TED talks, but it is a misrepresentation of what we actually know and do as scientists. Rarely does a single finding lead to a solution, rather it is an amalgam of discoveries small and large brought together that gets us to closer to answers. Synthesis is the driver of change and synthesis is what journalists do particularly well. Malcolm Gladwell, Steven Johnson and Jonah Lehrer are among the best synthesizers out there and I would imagine (no pun intended) that they contribute to more to public and professional understanding of social innovation than all of the original-sourced scientific knowledge on the subject combined.

When I hear Malcolm Gladwell cited as an original source in serious discussions with colleagues on scientific matters, I realize we have a problem…and an opportunity. Gladwell’s writings popularized the concept of tipping points, but his work is based on a wealth of scientific data on complex systems. They are not his original ideas, but they are his syntheses and (sometimes) his interpretations. This is important work and I am not taking anything from anyone who makes science data digestible and accessible, but it is not the original science.

That Jonah Lehrer is as well known as he is tells me that there is an appetite for science and I’ll freely admit to using his work (and that of the other authors I’ve mentioned) to inform what I do in a general sense. It is good work, however I also acknowledge that I have the scientific training to know how to go beyond the initial articles to critically appraise the information, place it in context, and I have the resources to go to the original sources in academic journals. Most people (professionals and lay people) do not. This access is going to decrease as resources shrink.

It is for this reason that synthetic work is so important. My Twitter feed often is filled with references to such synthetic work, rather than original works of research because I aim to fill role that is somewhere between journalism and the science of design, systems and psychology. I am not a pure science blogger, nor am I speaking to the lay public, but rather other professionals seeking to enrich their knowledge base. That is a role I’ve created for myself, largely because there is a high demand and low supply.

We have a need for synthesis and a demand for it, but little acknowledgement of the value of this role in professional scientific circles. Yet, when we leave journalists to do the work for us, we allow a different system to take charge. John McQuaid ended his article with this caution:

 Book publishers don’t do fact-checks, so there’s no fail-safe, just the conscience of the writer. Reach that point, and all is lost.

Filling the gap, meeting a need and shooting the messenger

Journalists like Johnson, Gladwell and Lehrer fill a gap, which is why I am saddened by the loss of one of them and angry at what has transpired. While there is no doubt that Lehrer made mistakes, they were of a rather minor nature in the grand scheme of things. Synthetic work is designed to provide a big picture overview, not guide microscopic decisions. I would like people to read Lehrer and learn about the creative process and the role of neuroscience in making our lives better, to appreciate systems thinking and decision making because of Malcolm Gladwell, and see innovation, emergence and discovery in new ways because of writers like Steven Johnson.

Yet, when we seek more and more from these authors, we might get less and less. This is what happened to Jonah Lehrer. As more people found themselves drawn to his work, the pressure grew for doing more, faster and getting that ‘snappy science’ out the door. GOOD magazine in the ‘tyranny of the big idea‘ goes further:

The problem is that it’s unreasonable to expect that every new piece of media should upend conventional wisdom or deliver a profound new insight. To think that Jonah Lehrer could expose an amazing new facet of human psychology every week, in 1,000-odd words no less, is ludicrous. There are only so many compelling, counterintuitive, true ideas out there.

But the demand for them doesn’t abate. That’s why you see so many science writers talking about the same handful of studies (the Stanford prison experimentthe rubber hand illusionDunbar’s numberthe marshmallow test) over and over. That’s why you see pop economists who should know better creating flimsy and irresponsible contrarian arguments about climate change for shock value. That’s why you get influential bloggers confessing they’re only 30 percent convinced of their own arguments but “you gotta write something.” That’s why the#slatepitches meme hits home.

Search Censemaking and you’ll find many of these topics not just because they are punchy, but because they are useful.

I hope we haven’t lost Jonah Lehrer as a voice just as I hope more people stop putting writers like him on a pedestal, where they don’t belong (nor do the scientists who produce the research). Synthesis is about bringing ideas together to produce innovative insights that often lead to bigger conversations about how to socially innovate. Synthesis is bigger than science, but dependent on it. It means paying attention to parts and wholes together and is the epitome of systems thinking in knowledge work.

It also means taking responsibility as knowledge producers and consumers and be wary of shooting the messengers while asking more from the messages they deliver.

Unless we are prepared to give people time to search, appraise and synthesize research on their own — and train them to make informed choices — the role of synthesizers – professional, journalistic, or otherwise – will become more important than ever.

Photo from Wikimedia Commons and is used under licence.


Keith Sawyer adds another important reflection on the issue of creativity-focused scholarship and the challenge of interdisciplinarity in the academy. When we create meta-disciplines of sorts, we challenge the status quo and that can make for a hard slog. Academics are used to thinking in disciplinary terms, using the structures that those organizing frames provide. They change constantly, but slowly and some things take off (e.g., microbiology forms from biology), but certain things do not. In the social sciences, this is particularly true as we’ve seen creativity or fields like evaluation find many homes and no homes at the same time (as Sawyer speaks to on the matter of creativity). Understanding this issue and working around it is a big challenge and opportunity for those of us interested in advancing the reach and respectability of inquiry into creativity.

The Creativity Guru

Creativity researchers don’t really have a place we can call home.

It’s because the study of creativity is interdisciplinary. That’s the key take-home message of my 2012 book Explaining Creativity: The Science of Human Innovation. And that’s a problem, if you want a home, because universities are organized into disciplines–such as psychology, anthropology, economics, computer science. And where do creativity researchers fit, into this organizational structure? Most of us don’t fit comfortably anywhere. So where are we?

Many of us are psychologists, and we have homes in psychology departments. (My PhD is in psychology.) And psychologists have made the majority of the scientific contributions to our understanding of creativity. But being in a psychology department has big limitations: you can’t study cultural influences on creativity, you can’t study group and organizational issues–you really are expected to focus on the solitary individual.

I’ve made my home in a department of education…

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