Now 15 years old, An Experiment in Scientific Organization by Robert L. Kahn, is finally available online. It details the history and practices of the MacArthur Foundation’s long-running Research Networks — “a sustained experiment in the organization of scientific research,” as Kahn states in the paper’s introduction.

His observations are just as fresh and important as when An Experiment was published in 1993.

Anyone who has had difficulty making an interdisciplinary or cross-sector collaborative project work should prepare to have their mind blown by this paper. While there’s a lot of talk about the importance of collaboration across disciplines, there’s very little research activity that delivers on the promise. Interdisciplinary research is difficult, messy, and operates on an entirely different set of cultural rules than traditional research.

But through years of trial and error, the MacArthur Foundation finally hit on a network design that reliably produced significant results. Kahn’s paper details the process by which the Foundation came up with the right elements for a successful collaboration.

He also lists the developmental stages that a collaborative network goes through in order to hit its stride and start producing useful results, as well as the elements of a collaboration that have proven to be critical success factors.

No one really argues against Kahn’s point that “collaboration, within disciplines and between them, can enlarge scientific understanding, accelerate scientific achievement, and increase the contributions of science to well being.”

But while others pay lip service to the concept, his paper provides the guideposts for  designing a successful collaborative endeavor. It’s a tremendously useful document for anyone who is serious about making an interdisciplinary collaboration yield fruit.

Called Program for the Future, the conference aims to explore ways to “enhance our capacity for problem solving, decision making knowledge organization and planning in every field of human endeavor.”

When I interviewed Engelbart on The Site (in 1996 I think it was, and also probably was my favorite interview of all time, he is such a tremendously humble and lovely man), this is how I introduced him:

The very act you are engaged in at this moment–reading and clicking through information on a computer screen–would not be possible if not for Douglas Engelbart. While working at Stanford Research Institute in the late 1960s, Engelbart invented or envisioned almost everything that makes personal computing possible today:  the computer mouse, hypertext links, groupware, on-screen editing and much more. But almost 30 years ago, few if any of his peers shared his vision.

That vision (which I also explored in an NYT column back then) was about the power of technology to enable what Engelbart calls “collaborative intelligence.” And while we are kind of banging our way toward it, his ideas for how technology could serve as the connective tissue between people and information was more methodical and directed than our haphazard efforts today.

I spoke at the 30th anniversary celebration, so it was nice to get a call on Friday from Etan Ayalon (CEO, GlobalTech Research) to join a last-minute panel he was asked to put together and moderate for the conference. We’ll be discussing collective intelligence in the context of one of my favorite subjects:  how to be innovative about innovating.

I’ll be joining Phil McKinney (VP and CTO of the Personal Systems Group at Hewlett-Packard and Dr. Larry Leifer (founder and director of the Stanford Center for Design Research, and founding director of the Stanford Center for Innovations in Learning).

I thought I’d post the questions that Etan sent us to riff off during the panel, and my brief thoughts in response.

How do we best realize Doug Engelbart’s vision of combining people and technology to nurture innovation and better humanity, by addressing major challenges as well as creating new industries, products and jobs?

1. One problem at a time, using the right processes.
2. Need to improve the improvement/innovation process — the C-work, in Doug’s parlance.

•    Today we have pursuit of innovation without considering context. Often ’solutions in search of a problem,’ instead of the other way around.
•    Pursuit of innovation in a solo inventor (or product development department, whatever) model leads to applying collective intelligence post facto; i.e., marketing department and customers aren’t part of the process
•    Context is also provided post facto, and selectively — usually by people with a specific and often narrow point of view
•    Context can only be accurately provided by others.

Is innovation a gift or a skill?

1. Both, and neither. Depends. Some people are natural outside-the-box thinkers. But the organization has to be designed to encourage exploration. And organizational design is a skill.
2. Why do you ask? The thoughts behind the question are as interesting as the question itself.

Is innovation an outcome or a process?

Personally I think it’s an outcome, but if it’s being done in an organization it’s more likely to happen if there are processes to support it. Again, what’s the motive behind the question?

Sharing the Benefits of Innovation for All, Not Just Lucky Digital Few – With an ever widening digital divide, how do we ensure that innovation benefits all segments of society in both developing and developed countries?

Process innovations can benefit everyone, I think. But with products, it’s more than a digital divide. Biotechnologies have this issue as well — expensive drugs, expensive seeds, etc. And we can’t ensure this without government intervention, at least not at first. I don’t think that’s how it works. But we can be thoughtful about how to stage innovations so they eventually get there.

Balancing Innovation Risks and Rewards – How? Who Should Participate in the Dialogue?

Who? All the relevant experts and stakeholders

How? By having the risk-reward conversation very early in the product development cycle. And by having a process that respects the question, which requires changing the R&D culture.

Also, we need to acknowledge that product innovation today in particular is more about driving profit than solving problems. This may need to be rethought if we are serious about creating a sustainable economy that isn’t wholly based on getting people to endlessly buy more stuff. It’s a very different risk-reward conversation when it’s framed that way.

Does innovation emerge from/require ambiguity and uncertainty?

Life is ambiguous and uncertain, which causes problems that need to be solved. So, yes. Also it emerges from the drive to improve, which some people have innately.

Over the course of five days in November, from Thursday the 13th to Monday the 17th, four conversations about synthetic biology took place. They involved everyone from non-profit leaders to engineers, social scientists, biologists and government regulators. We need more open-minded, smart people from many sectors thinking and talking about this technology, and pronto.

What on earth am I talking about? If you’ve never heard of synthetic biology, you aren’t alone. According to the Project on Emerging Nanotechnologies, less than one in 10 (9%) Americans say they have heard some or a lot about synthetic biology — and a whopping 67% have heard nothing at all. [Edited in response to first comment. Never let it be said that I do not listen to my critics.]

But venture capitalists, multinational chemical, energy and “life science” companies, and just about every government agency you can name are already investing millions of dollars to develop commercial synthetic biology applications. According to one report, the research market in 2006 was already $600 million, and “the potential for growth in the next 10 years is projected to expand this market to over $3.5B.”

Proponents and opponents and everyone in-between agree these applications will have a direct and significant effect on our lives and on the planet. (I’ve put links to good/accessible background reading at the end of this post.)

The first event was on Thursday the 13th, a day-long “teach-in” in San Francisco, held by and for civil society groups and NGOs, which as far as I can tell was organized by the ETC Group in Montreal. It was private, so there’s not much else to say about it — I found a link about it on the Food First site. If you want more information, contact Jim Thomas at the ETC Group.

The second, on Friday the 14th, was hosted by the Wilson Center’s Project on Emerging Nanotechnologies, which was a conversation with — well, it was with me, actually, and Rick Weiss, a former senior fellow at the Center for American Progress (you may know him from his previous incarnation as the Washington Post science writer). The occasion was the publication of my paper on synthetic biology, which you can read or download here. The audience was terrific, with representatives from the biotech industry, government regulators and academics from a variety of fields.

The event is archived here.

The third was a Sunday morning panel on synthetic biology at Convergence 08 in Mountain View, CA, billed as a place where “the world’s most dangerous ideas will collide.” Moderated by Christine Peterson of the Foresight Institute, the first organization to educate society about the benefits and risks of nanotechnology, the panel included Chris Anderson of UC Berkeley’s Department of Bioengineering, the physicist, novelist and life-extension proponent Greg Benford, Andrew Hessel, a supporter of and activist for open-source synthetic biology, and me.

You can read one commentary about the conference, including our panel, here. Our panel is specifically discussed here.

And finally, on Monday night, the Long Now Foundation hosted a conversation in San Francisco, between synthetic biology pioneer Drew Endy of Stanford and critic Jim Thomas of ETC. You can read Long Now founder Stewart Brand’s succinct blog post on the event here.

Steven Levy (most recently of WIRED) was there; he called the event “well-argued, excruciatingly civil debate about the wonderful/dreadful future” of synthetic bio. (At least one synthetic biologist is recommending that his peers read Levy’s first and classic book, Hackers, for a reality check on their perceptions of some of the issues on the table. I would concur that this is a splendid idea.)

I hope that all of us who were involved in these civil and civic-minded conversations can find ways to keep them going. And I hope that those of you who don’t know much if anything about synthetic biology will take the time to learn a bit more about it. To that end, I’ve dug up a few overviewy-type things that I hope will be helpful.

It’s hard to find explanations that aren’t technical, or that don’t take one point of view or another (or both), so keep that in mind as you explore the references below:

• YouTube video of Drew Endy defining synthetic biology. Drew is one of the founders of the field. This is a wee bit technical but entertaining enough that it doesn’t really matter. I suspect you’ll get the drift.

• “Backgrounder: Open Letter on Synthetic Biology“, by the ETC Group, a Montreal NGO “dedicated to the conservation and sustainable advancement of cultural and ecological diversity and human rights.”

• My paper: “Synthetic Biology: An Overview and Recommendations for Anticipating and Addressing Emerging Risks,” published by Center for American Progress and funded by the Wilson Center.

• A paper published in Public Library of Science about intellectual property, one of the most critical non-science issues facing synbio: “Synthetic Biology: Caught between Property Rights, the Public Domain, and the Commons,” by Artie Rai and James Boyle

• A useful essay by Andrew Maynard, the chief science advisor for the Wilson Center’s Project on Emerging Nanotechnologies, about the parallels between synthetic biology and synthetic chemistry, is here. Maynard is also the author of the exceptional PEN publication, “Nanotechnology: A Research Strategy for Addressing Risk.”

Feel free to send me links to other good papers, or post them in comments.

In that regard, Barack Obama’s call for a return to scientific integrity is cause for tremendous hope for those who have spent eight long years battling the anti-science, anti-innovation era of the outgoing administration.

The very first item on the Obama campaign’s science fact sheet, which was published in September 2008, states that Obama’s science-friendly science policy will ensure that “decisions that can be informed by science are made on the basis of the strongest possible evidence.”

It goes on to say that the Obama administration will (among many other things):

• Appoint individuals with strong science and technology backgrounds to key positions;
• Take advantage of the work of the National Academies to identify the federal government positions that require a strong science and technology background;
• Ensure independent, non-ideological, expert science and technology advisory committees; and (last but certainly not least from Hybrid Vigor’s perspective);
• Actively encourage multidisciplinary research and education, noting that “innovation often arises from combining the tools, techniques, and insights from researchers in different fields.”

Yes! That’s what I’m talkin’ about! That last one even takes a page straight out of Hybrid Vigor’s mission statement.

But … I’m concerned that social scientists are not specifically mentioned anywhere in the policy fact sheet, either in spirit or in fact, not even in the last item. This is a serious omission as well as risky one, and unfortunately it is all too common in discussions of interdisciplinary, multidisciplinary or cross-disciplinary research.

Social scientists can — and should — provide a critical bridge between innovation and the people that the products of innovation purport to serve. They can help policy makers think about the social and cultural context for research priorities and decisions in a way that technologists cannot, making sure that the “strongest possible evidence” that scientists provide is also the evidence that is most relevant to the decision at hand.

As consumers become more concerned about the contemporary, industrialized food chain, for example, some economists have made the case that social scientists need to be intimately involved with both technological development and technology policy. That way, they will be able to help both companies and governments understand what consumers will require from a sustainable food chain, both in terms of both transparency about the basic science behind food innovations and the choices that they will demand.

Similarly, social science also informs decision makers how to communicate most effectively during pandemics, natural disasters or terrorist attacks.  As one group said during Congressional testimony, “While new tools and technologies have improved the prediction of many natural hazards, complete preparedness and response also requires an understanding of human behavior, particularly in emergency situations. This is the domain of the social sciences.”

Not doing so has, at least on one notable occasion (I’m sure there are many others), led to unnecessary disaster. It was social science researchers that explained, in forensic analyses after the Three Mile Island meltdown, why nuclear power plant engineers needed to include human factors in both their designs and their risk analyses — something which the engineers failed to do until it was too late.

But this position has been rejected by biologists, physicists, engineers and the like — practitioners of the “hard” sciences of the laboratory and the work bench. They see the research and the data of social scientists as inferior and, as a result, the two camps of science have long since been at war.

Some scholars believe that the schism is artificial, and their arguments make a lot of sense to me. One of them, Bent Vlyvbjerg at Aalborg University, has developed a concept of social science based on Aristotle’s concept of phronesis. In an excerpt from his book “Making Social Science Matter,” Flyvbjerg writes,

In Aristotle’s words, phronesis … goes beyond both analytical, scientific knowledge (episteme) and technical knowledge or know-how (techne) and involves judgments and decisions made in the manner of a virtuoso social and political actor. … [In this role], the social sciences are strongest where the natural sciences are weakest: Just as the social sciences have not contributed much to explanatory and predictive theory, neither have the natural sciences contributed to the reflexive analysis and discussion of values and interests, which is the prerequisite for an enlightened political, economic, and cultural development in any society.

I don’t entirely agree; I think social science has contributed quite a lot to explanatory and predictive theory — maybe not about the workings of matter, but certainly about how groups (including scientists) think and how they will act, and how those behaviors affect outcomes (including scientific outcomes). Nevertheless, I think he is on the right track.

From what I’ve heard so far, I can’t imagine that the Obama administration is striving for anything less than “enlightened political, economic and cultural development” in these difficult times. So I hope that President Obama and his new team, whoever they are, won’t let old, outmoded and short-sighted prejudices stop them from doing what promises the best results — for innovation, for industry, for the country, and for the rest of the world …

Bring on the social scientists!

As ridiculous as this statement now seems (especially to those of us whose retirement funds have been decimated) I’d argue that the statement holds true—even in a grizzly market. Yes, good bankers do know how to manage risk—their own risk. Which is why the best investment bankers view a recession more like a sabbatical, while the rest of us have to figure out how to keep food on the table. And even as the government is coming to the rescue, the Fed won’t be doing the risk management part: they’re paying bankers to figure out how to get out of the mess they’ve created. Talk about a win-win!

Not that these guys aren’t suffering. Here’s a bit of anecdotal evidence of how bad things have gotten:

This is a finance guy making a ton of money and he was trying to decide whether he should sell the country home in Connecticut, the apartment here in the city or the 8,000-square-foot dream home in Oregon that he just finished…  (from “End of an Era on Wall Street: Goodbye to All That“)

A dilemma for sure, but global financial crises demand desperate measures.

Markets Transfer Risk, Not Trust

The foundation of modern financial markets is seeped in the mathematics of probability. Over the years, rules and regulations have been piled on to promote competition and reduce overall risks. The results are compelling. And something in the human psyche tells us that since these guys are so much better at managing their own risk—and they obviously are, since they have several luxury houses at their disposal—then maybe we should trust them to manage our risk too. A market allows us to transfer our assets to someone who can navigate a risky terrain better than we might ourselves.

But risk management in itself doesn’t guarantee collaborative outcomes—that is, outcomes in which gains and losses are shared proportionally—nor does risk management inexorably produce social trust.

Clearly, the current crisis is as much about a breakdown in social trust and a loss of social capital as it is about debt ratios and credit freezes. We’ve already seen how even an injection of more than a trillion dollars won’t allay lenders’ anxieties. If you’re not an actuary, the reason is obvious: anxiety isn’t a risk equation, it’s a human emotion. Anxiety is symptomatic of a collapse of trust.

The problem with words like “anxiety” and “trust” of course is that they’re mystical to the mathematical mind. How’s a actuary to calculate the value of trust futures? or social trust default swaps?

Restoring Social Trust

What the world needs now is a renewed social trust. Until recently, social trust seemed like an intangible commodity with a will of its own; it couldn’t be systematically cultivated, measured, forecasted, or valued. But a growing canon of research into successful resolutions of social dilemmas demonstrates that collaborative arrangements are more likely to emerge when certain conditions are met. It’s time to develop mechanisms that foster pro-social behaviors by supporting natural processes of recognition, reciprocity, and community awareness. Most of the fundamental research is available to build such a system, so it’s more a matter of applying these ideas to real world relations, institutions, and markets.

Laws of Relation Revisited: Codifying Pathways to Trust

A few years ago, I challenged the software industry to take ideas about trust from various branches of science (such as game theory, social science, evolutionary biology, and psychology) and produce a system that greatly improved the likelihood of collaborative outcomes and improvement in social trust. The system could then be applied to trust-related problems on the Internet, such as spam, identity theft, and credit fraud. If such a “trust leavening” could be invented, it might even be applicable to a wider range of problems, including stronger trust in financial markets.

To design a trust system, there needs to be some workable theory on trust that explains how it’s created, how it’s maintained, and how it’s used. The theory needs to be intellectually accessible to a wide range of professionals. Just to get the conversation started, I offered three “Laws of Relation” (which are really more like postulates at this point). They are:

Law of Relational Symmetry

The party in control of the terms of a relationship controls the relationship and, in the absence of symmetrical countervailing controls, will eventually exploit the other participants.

Law of Relational Risk

Contribution to the relationship that is not met proportionally by the other participants is a loss to the contributor.

Law of Relational Projection

Any party with more than an informational interest in a relationship is a participant in the relationship.

As it turns out, financial markets illustrate these laws rather well.

The first law says that exploitation will occur in asymmetrical relations. Who controls the playing field in financial markets? The SEC? The Fed? It seems in many cases, the large investment banks who continually added exotic financial instruments, pushed for rule changes, and lobbied for reduction in government oversight. The prevailing belief in Washington was that these are smart guys who know how to manage risk. As it turns out, they were easily the smartest guys in the room and they were exceptional at managing their own risk, but not motivated at all to think of market risk. The average investor has almost no say in matters regarding market rules, so the relation was systematically slanted in favor of the rule makers.

The Law of Relational Risk predicts that collaborative outcomes are more likely when all parties experience a loss proportionally. The losses on Wall Street have been catastrophic, but not for everyone. Many of the people directly involved in creating this mess won’t suffer from the crisis the way some of the shareholders or general public will.

And the Law of Relational Projection distinguishes participants from on-lookers. One thing that has been a surprise to everyone is how interrelated and interdependent we’ve all become. Interdependency can be a vital pro-collaborative element to relations (per the Law of Relational Risk). In fact, it’s our agreement on a shared conflict, our mutually assured financial destruction–that has formed the basis for cooperation in congress and among world banks. But the strategy only works well when these relations are explicit. Instead, as our home loans have been sold, resold, hedged, and bet on through derivatives of derivatives, it’s no longer clear to anyone who is a participant and who’s a bystander. So what’s happened is that people who were believed to be bystanders have brought the house down with little or no accountability.

Designing Pro-Collaborative Systems
Few of society’s existing institutions are set up to support collaborative outcomes, and so exploitation is inexorable. With an informed understanding of elements that promote collaboration and trust, we can greatly improve our institutions, including financial institutions. I’ll continue to present my ideas on how to do this in follow-on posts, but I hope that professionals from a wide range of disciplines will contribute their ideas as well.

This is a hard thing for organizations to swallow. They are accustomed to the command-and-control approach where making something a goal is the first step to getting it done. I’ve seen companies that have as a shared goal “to become more innovative.” This means that the personal goals of everyone in the organization include something about “being more innovative.”

But a manager cannot order someone to innovate! He or she has to create the environment where there is enough freedom and the right resources so that their employees can and will innovate. In this view, the manager’s role is to help frame the problem, convene the conversation and get the right people to the table.That’s why I think of innovation as the “new” strategy. It requires a completely different view of how to plan for the future of your company. It is not about identifying the right course and executing it flawlessly. It is about first deciding what problems need to be solved, then attracting the right resources, creating the right ecosystem and supporting a process of continuous learning. It is about leveraging the collective expertise of your employees, your customers and your partners to collectively solve the tough problems.

Contrast this with the recent New York Times editorial by songwriter and author Billy Bragg, The Royalty Scam. Bragg tells the story of Bebo, the social-networking site that grew to 40 million members in two years and, in Britain, apparently ranks with MySpace and Facebook in popularity.

A couple years ago, Bebo founder Michael Birch asked to meet Bragg after Bragg had lobbied MySpace on its proprietary rights clause. Birch assured him that Bebo would always put the interests of artists first—although this “support” never included any kind of royalty to the artists contributing content. Last week, when Bebo sold to AOL for $850 million, Bragg observed:

The musicians who posted their work on Bebo.com are no different from investors in a start-up enterprise. Their investment is the content provided for free while the site has no liquid assets. Now that the business has reaped huge benefits, surely they deserve a dividend.

If Bebo owners had shared this purchase price equally (and kept nothing for themselves) each member would get $21. Is this they way it should work? Or are some members more equal than others? What is fair compensation for building a site versus providing content? Could content creators band together and share in the revenue from a marketplace they control? Or should they use sites like Bebo for advertising and create their own direct sales model on a dedicated site owned by the artist?

The fundamental question is whether a Web 2.0 world is ready to compensate content creators directly—and take the traditional media out of the picture entirely.

I believe that we have a lot of work to do to learn how to manage the intangibles that determine the winners and the losers in this “flat” world. And the American farmers are just the latest in the long line of businesspeople on the losing end of the intangibles game.

Fortunately, around the same time, I met Denise Caruso, who runs the Hybrid Vigor Institute and edits this blog. We became acquainted after she wrote a wonderful piece in the New York Times, “When Balance Sheets Collide With the New Economy” which highlighted the inadequacy of financial reporting to deal with the knowledge economy.

Denise explained how knowledge intangibles are invisible in financial and managerial reporting. They are also often passed over in decision making—in the assumption that “soft” issues cannot stand up to the rigor of traditional analysis.

But it is the soft issues that count. They help farmers in Brazil beat out their American competitors. They are at the heart of successful innovation. They create the competitive advantage of companies as diverse as Toyota and Google. We all need to get better at “seeing” and managing the soft, intangible side of our organizations.

So I was thrilled when Denise invited me to join in the budding, cross-disciplinary discussion at Hybrid Vigor. The challenges that we face in the “flat” world require new kinds of solutions—solutions that often lie beyond the ken of traditional economics, accounting and management. The topic of intangibles is no exception. I know that it will benefit from a broad diversity of perspectives. I look forward to joining in and bringing an “intangible” point of view to the conversation.

[Editor's note: We are thrilled to have Mary on board here at hybridvigor.net. I was tremendously impressed by her in our conversations, and I believe the work she is doing on intangibles and intellectual capital is critically important to the future success of the global economy. I also loved her description of herself on the website of her consultancy, Trek Consulting: 'Mary is a good listener, a studious thinker and an honest critic.' Who could ask for more? You can read her full bio here. D.C.]

POST recently published three POSTnotes entitled “Ecological Networks” [PDF], “Smart Metering of Electricity and Gas” [PDF] and “Autism” [PDF]. The first two POSTnotes for 2008 were on “smart” materials and systems, and synthetic biology.

You can subscribe to the POST reports yourself, by sending an email to: mailto:post@parliament.uk.

“Ecological Networks” considers the possible conservation benefits of ecological network implementation in the UK. Ecological networks are intended to maintain environmental processes and to help to conserve biodiversity where remnants of semi-natural habitat have become fragmented and isolated.

“Smart Metering” examines the potential benefits, costs and policy considerations involved with technology that enables accurate measuring of energy usage and the provision of improved information to consumers, suppliers and the market. Smart meters are expected to be installed in all of the U.K.’s 25 million homes over the next ten years.

“Autism” describes autism and autism research, and considers policy approaches to this disorder whose prevalence is greater than previously recognized, thus putting pressure on service providers and highlighting the need for greater awareness. Autism affects how a person communicates, socializes and interprets the world, and can lead to wide ranging difficulties in every day life, including forming relationships and living independently.

From “Smart Materials”: “The most commonly accepted definition is that smart materials and systems can sense and respond to the environment around them in a predictable and useful manner. For example, the ‘photochromic’ materials used in reactive spectacle lenses become darker in response to increased light. Smart materials arise from research in many different areas and there is a large overlap with nanotechnology.

“From “Synthetic Biology”: “In the US, where most of the research takes place, the term ’synthetic biology’ describes research that combines biology with the principles of engineering to design and build standardized, interchangeable biological DNA building-blocks. These have specific functions and can be joined to create engineered biological parts, systems and, potentially, organisms. It may also involve modifying naturally occurring genomes (an organism’s entire hereditary information usually encoded in DNA) to make new systems or by using them in new contexts. There is sometimes confusion about the definition of synthetic biology amongst those outside the research community, reflecting its position as a complex, new and rapidly developing field.”

In 2001, Diana Rhoten and I wrote Hybrid Vigor’s first white paper on roadblocks to interdisciplinary practice, that included tenure as well as several other factors that continue to relegate interdisciplinary scholarship to 2nd-class (or so) status.

It’s called “Lead, Follow, Get Out of the Way: Sidestepping the Barriers to Effective Practice of Interdisciplinarity.” You can download it here [PDF].