I am here at the invitation of Golan Levin, director of the studio and, back in the day, a former colleague at Interval Research. The fellowship is funded by the National Endowment for the Arts.

Golan told me I could do anything I wanted, and so I invited Robin Gianattassio-Malle to come work with me on inventing a better way to help people learn and think about the consequences — both risks and benefits — of innovations in science and technology. We want to go beyond the usual binary, “fawning or damning” approach that dominates media coverage today, to actually informing people about these incredibly complicated issues.

I’m really excited about this project. It’s the first time in a long time I am going to have the opportunity to roll up my sleeves and do what I do best: to help people understand complexity in a way that is engaging, helpful and accurate. We are going to have to confront some tough design issues, but between us we have an amazing network to draw from.

Robin and I will be working at the STUDIO with two other fellows — Kyle McDonald and Jacob Tonsky — both of whom are wicked smart and from whom we expect to learn a lot.

We will be building a prototype over the next few weeks, and I will be posting updates about our progress. Yeehaw!

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.

It’s written to EPA administrator Stephen Johnson, from my colleague Baruch Fischhoff, the Carnegie Mellon risk expert and professor who’s chair of the Homeland Security Advisory Committee for the EPA’s Scientific Advisory Board.

Fischhoff wrote:

[S]everal Committee Members, myself included, were distressed at the lack of systematic, scientific attention to communicating with the public.  … It is not unique to this anthrax project, but reflects a general problem in our national emergency planning … As we saw in 2001, a b. anthracis (“anthrax”) attack has enormous potential for achieving our enemies’ goals, even when causing relatively few casualties … Much of that damage came from our own inability to communicate credibly, causing needless concern and distrust that persists to this day.

With its rigorous methodologies and an impressive body of academic literature supporting it, risk communication represents the bounty of wisdom that can be found in the applied social sciences, from fields including psychology, communications, decision analysis, rhetoric, sociology, political science, law, ethics, linguistics and anthropology.

But the scientific aspects of risk communication are often entirely overlooked or dismissed by technical experts and authorities in both emergency preparation and response. Instead, they assume that  their knowledge of technical details, their intuition about what to say to the public, or their charisma (this being the politicians) will give people enough information to respond to emergencies.

Call it ignorance, arrogance or denial, but that attitude is a big mistake, and it has real consequences.

Look back at Hurricane Katrina for some horrific examples. Not only did authorities fail to get the frail and the poor out of New Orleans, it utterly failed to persuade tens of thousands of them who could evacuate the city to do so.

And recall the disaster that one risk expert called the “Duct Tape Risk Communication” emergency preparation strategy, proposed by the White House in 2003, which immediately was turned into a lampoon to skewer the U.S. government, rather than inspiring citizens to take useful action.

People need to trust their leaders and technical experts to tell them the truth in emergencies, in ways that actually answer their questions — questions which will be different for business leaders than for schoolteachers — and address their fears. Without that trust, the public isn’t going to follow instructions.

As Fischhoff said in his letter to EPA, the only way to prepare for emergencies is to have an inventory of scientifically sound risk communications on hand — pre-scripted press releases, print and electronic explanatory materials, guides to self-testing, FAQs and the like — ready to be adapted to specific circumstances. And,

Communications research planning is not expensive.  However, it requires a skill set that is not represented in the anthrax [Techical Assistance Document] task force.  Nor is it present in most other parts of our national response effort [including the Emergency Consequence Assessment Tool and the WaterSentinel Program (PDF)].  As a result, much of what passes for risk communication advice has no scientific foundation.

Thankfully, compared to some of the other problems facing the Obama administration, this is an easy one to fix. And given the nature of some of those problems, they may want to fix this one now.

The study was called the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial, or ALLHAT. And while I’m sure the authors would never admit it, I desperately want to believe someone built that big ol’ clunky name around the classic cowboy insult “all hat, no cattle,” describing someone that’s all talk and no substance (in this case, the blockbuster drugs).

I do hope that’s what they had in mind, anyhow. It’s not just hilarious; it also makes sense, given what the Times article revealed about why the ALLHAT study had so little impact.

Its findings showed that cheap diuretics were at least as effective at treating high blood pressure as the expensive and heavily promoted drugs like beta blockers and calcium blockers — but that doctors were still prescribing the pricey stuff at a much higher rate.

One reason, according to Curt D. Furberg, a public health sciences professor who was the first chairman of the steering committee for the study, was that “The pharmaceutical industry ganged up and attacked, discredited the findings.”

The Times piece notes that Furberg eventually resigned “in frustration” from the steering committee, while another committee member went on to receive more than $200,000 from Pfizer, largely in speaking fees, the year after the Allhat results were released.

“There’s a lot of magical thinking that it will all be science and [there] won’t be politics,” Sean Tunis, a former chief medical officer for Medicare and an advocate for these kinds of comparative-effectiveness studies, told NYT.

I suspect there’s a lot more hat than cattle for a lot of the expensive drugs doctors are prescribing today to treat chronic conditions. And while of course drug companies are free to sell anything they’d like, I don’t really want to have to pay for the most expensive drug just because my doctor got seduced by the sales rep.

As the Times article noted,

The Allhat experience is worth remembering now, as some policy experts and government officials call for more such studies to directly compare drugs or other treatments, as a way to stem runaway medical costs and improve care.

You can read more on the controversy at the Alliance for Human Research Protection, in a post about the evidence gap in current prescription practices.

But this issue has much broader scope than health care. While the Bush administration gets well-deserved criticism for its outrageous disregard for scientific evidence (just one well known example here), there has never been a shortage of scientists who are adept at contextualizing evidence to their own ends, whatever those ends might be. As a result, citizens/consumers (whatever you want to call us) often don’t know about the range of equitable choices that are available to them.

I deconstructed the problem of evidence and alternatives at great length (in the context of biotech) in Intervention (Chapters 8, 9 and 10), and again more generically in my recent piece on cost-benefit analysis in Strategy+Business. Olivia Judson wrote about it from a slightly different angle on Tuesday in her NYT blog.

I hope the new administration in Washington will take up the fight as well. Comparing the effectiveness of alternatives is a big issue, and giving it serious consideration could have real, salubrious effects on both the quality and the cost of today’s expensive health and environmental interventions.

They’d read my paper on risk and synthetic biology and thought my characterization of their report on synthetic biology, “Genome Synthesis and Design Futures: Implications for the U.S. Economy,” was unfair.

The larger issue that our disagreement is based on — that is, how to pay proper fealty to scientific uncertainty — is at the core of my discontent with how technology innovations are assessed for risk and benefit.

So I told them I would write about our disagreement here. This way, they have an opportunity to respond, and maybe we can get a discussion going on the subject.

Here is what I wrote:

Of the most concern in the context of risk and governance are the reports that uncritically support synthetic biology, as they encourage development and commercial release with little or no acknowledgment of the degree of scientific uncertainty that surrounds the endeavor. A 174-page report on synthetic biology published by Bio-Economic Research Associates in 2007 and funded by the Department of Energy (which itself has invested heavily in synthetic biology research), contained but a single, three-quarter-page discussion of the limitations of the engineering paradigm as applied to living systems. Giving such short shrift to a topic that is still under deep consideration in the broader scientific community lends an air of certainty to a highly uncertain endeavor. Such under-representation has real significance from the perspective of investment and economic risk, as well as from that of health and the environment.

[Italics added by me; they aren't in the paper.]

Aldrich and Newcomb said it was “flatly unfair” to say their report doesn’t touch those issues, and objected to the implication that they were “apologists” for the paradigm of synthetic biology.

They mention the report’s final chapter, “Scenarios for the Future,” about how the synthetic biology future might play out. One of the “major uncertainties” (a key scenario element) is posed as, “How quickly will biological engineering advance?” And they note that in one of these scenarios, “technical challenges impede applications” outside the lab.

But this is precisely my issue. The idea that “technical challenges” are the only issues synthetic biology faces today is flat wrong. The engineering paradigm that synthetic bio is based on — that genetic components are like electronic circuits, with independent, clearly defined functions — simply does not apply to living systems.

Geneticists have known for years that genes and other biological components — the same components bio-engineers are using to snap together their synthetic creations — do not operate independently, like electronic circuits. They have long observed that in addition to whatever their primary function might seem to be, these components appear to operate in some kind of a network, that they interact and overlap with each other in ways that are not yet understood at all.

(The ENCODE study was most recent public acknowledgment of this fact.)

Yet the field of synthetic biology is pretending as though this gaping chasm of knowledge — a chasm that pretty much negates its entire raison d’etre — has no impact whatever upon the viability of its work. I’ve never known a synthetic biologist to proactively address the issue. If confronted with it directly, the most I’ve heard is the equivalent of, “Yes, it’s complicated. But we’ll figure it out.”

At the same time, investors are sinking hundreds of millions of dollars into developing products based on a fundamentally flawed scientific premise masquerading as a technology with predictable, “engineered” outcomes.

OK, back to Aldrich and Newcomb. In fact, I do not think they are apologists for synthetic biology. As far as I know they have no direct investments or interests in any synthetic biology companies. And they explicitly state at the beginning of the report that they did not intend to address issues of safety, unintended consequences, or ethical, legal and social questions.

Still, there is an inside the tent, it’s-a-done-deal orientation to the report that is discomfiting under such highly uncertain circumstances.

With its sections on “Enabling Technology,” “Economic Dimensions of the Biological Engineering Revolution,” and discussions of “Applications of Genome Synthesis and Design” that specifically target the energy, chemical and vaccine industries — and whether it means to or not — the report presents a de facto case that synthetic biology is already a viable investment.

And while it concurs that there may be some technical speed bumps, it simply does not acknowledge the deep, fundamental scientific uncertainties about the very premise on which synthetic biology is based.

From my perspective, this lack of acknowledgment is misleading to investors and anyone else who is trying to understand what a synthetic biology future might mean.

So, all of that to say:  Respectfully, I stand by my story.

But as I started out saying, I do think that the much bigger, critical issue here is about uncertainty itself, and that concern goes beyond any individual report or technology, particularly as private investment is driving science-based innovations to market much more quickly than ever before.

As a society, we have got to find a way to talk more honestly about and have a strategy to anticipate the impact of uncertainty on innovation. That’s the only way regulators will be able to safely bring new technologies like synthetic biology to market without endangering either investors or the public’s health and welfare.

This is the driving force behind much of the work and thinking that I’m doing now, and I’ll be posting more about it as time goes on.

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!

On Tuesday, the New York Times published package of articles that explored new genetic research and new ideas of what a gene is.

Much of the package was based on the findings of the ENCODE study, which was sponsored by the National Human Genome Research Institute.

The upshot of ENCODE, which was published about a year and a half ago, in June 2007, was pretty straightforward: the human genome is not a “tidy collection of independent genes,” after all, with each sequence of DNA linked to a single protein, which in turn is linked to a single function, like the production of an enzyme.

Instead, genes appear to operate in a complex network, and interact and overlap with one another and with other components in ways will challenge scientists ”to rethink some long-held views about what genes are and what they do.”

The lead story in the package notes this perspective, writing that scientists “no longer conceive of a typical gene as a single chunk of DNA encoding a single protein,” and quoting one of them as saying, simply, “It cannot work that way.”

YES! I was so excited that this issue was finally going to get some attention. Not only was one of the central themes of my book, Intervention, but I too wrote a column about ENCODE for the New York Times — called “A Challenge to Gene Theory: A Tougher Look at Biotech” — right after the results were published, in July 2007.

In it, I asked what (to me) is the most obvious and important question, but it was addressed nowhere in the NYT package:

If so much of what we know about genes is wrong, how does this change the decisions made about the safety of the thousands of biotech products already on the market, from pharmaceuticals to living transgenic organisms, that were based on these very faulty — in fact, almost completely backwards — scientific assumptions?

Fact is, all of the proposed benefit of genetic engineering (including its “no-risk” profile) comes from this assumption: that DNA will produce the same protein in whatever genome it’s planted, and that’s all it will do — that the host organism will be essentially unchanged except for expressing that one additional trait.

The FDA’s consumer magazine published an article on plant breeding in 2003 that made the same declaration. The benefit of genetic engineering, it said, is that it is “more precise and predictable … a single gene may be added” to a plant to give it a single specific characteristic without transferring the undesirable traits.

All things considered, revisiting the question of risk is an absolutely logical, rational, fair — and, I might add, pretty important — line of inquiry. Thus I remain completely baffled about why even the smartest journalists in the mainstream media are completely ignoring it.

I understand that these products are having no gross effects. People aren’t dropping in the streets with big oozy pustules, whole farm fields are not being laid to waste, and so forth. If they were that obvious, we’d have figured out a connection.

But physiological effects can be invisible, subtle, and even cumulative. And because there is no required tracking or monitoring of biotech drugs or organisms once they’ve been sold, we will have no way of knowing what these effects might be until it’s too late.

Also, it must be stressed, ENCODE’s findings are not new information.

Molecular biologists and geneticists did and do know that the “one gene, one protein” theory hasn’t held water for several decades.

Just for starters, they know that there are some 20,000 protein coding sequences in the human genome, while there are probably hundreds of thousands of proteins (some even say millions). They know they are nowhere near knowing how the mechanisms work that trigger their production.

Epigenetics, which studies changes in the appearance of an organisms or in gene expression that are caused by mechanisms other than changes in the underlying DNA sequence, is just one of many areas of study in molecular biology that demonstrates a long-standing rejection of this simplistic notion of the gene.

For their part, organismal biologists — those who study whole organisms, like fish and insects and mammals, not just their DNA — as well as population geneticists and evolutionary biologists and behavioral geneticists, have never hewed to the “über DNA” perspective. For them, it has never held explanatory power outside the lab, in the real world that they live in and study.

As one molecular biologist I know once said to me, “This perspective changes the nature of the questions we ask.”

Oh, how I wish that were true!

Today’s business culture thrives on on performance, success, winning, and constant availability. The world continues on its frenzied trend toward 24×7 services, “five 9’s” of up-time, and six sigma products. The drive to succeed has provided us with all sorts of modern conveniences—and plenty of modern instances.

Perfect.

But I’d like to say a few words in defense of failure, because I believe failure has an important purpose and we can’t simply wish failure away by focusing on success. In my view, systemic failures can be averted simply by introducing some planned imperfections into the systems we build. One of the lessons that should be learned from the current financial crisis is how securities originally thought to be insular from the housing market were proven to be directly on the financial fault line.

Here’s the problem: when a system (such as a computer network, power grid, or financial market) performs steadily for a period of time, it fades into the background and seems as certain as the rising of the sun. Over time, a complex and interdependent mesh of relationships develops. Because these dependencies aren’t explicit, it becomes nearly impossible to predict how the beating of the proverbial butterfly’s wings in one part of the system can wreak havoc in another.

Is there a way to tease out the dependencies in such networks and develop complex distributed systems that fail safely? I think there’s a simple solution: introduce the element of failure. Shoot for 4 9’s instead of 5. Interrupt the broadcast so that we can run the drill before the disaster strikes. Learning to fail on a regular basis could help us deal better with much larger, systemic failures in the future.

I particularly liked Bob’s phrasing of the “collective margin call” on the banks. It indicates that part of what’s happened is a failure in coordination: banks have cash on hand as long as only a few percent of their patrons want to withdraw their cash. This echoes a theme of a post I wrote about the credit crunch back in June. Here’s an excerpt from that post:

Clearly, a great crime has been committed. An entire nation has been robbed. World markets are shaken. But who’s responsible? Nobody. And everybody. The insidious nature of this crime is that we all collaborated to commit it and without a master plan. Can such collective action crimes be avoided? Or is the commons forever doomed to be the scene of tragedy?

Bob’s comments on risk management are also strongly reminiscent of Denise’s work on risk management in the biotech industry. Bob writes:

Risk management failures created the current financial crisis, and risk management failures have also created the personal information disclosure crisis, and the malware crisis, and a bunch of other problems which are not yet crises. We do risk management poorly in all disciplines. We do it poorly for a bunch of reasons: executives don’t understand their own businesses well enough to understand their risks; risk managers don’t know how to talk to executives about risk; incentives favor creating long-term risks in order to accrue short-term profits; the list goes on and on.

Denise’s main assertion in her book, “Intervention: Confronting the Real Risks of Genetic Engineering and Life on a Biotech Planet,” is that the biotech industry is similarly awash in poorly managed risk. Genetic engineering is another impending crisis that, once it reaches crisis levels, people will be dumbfounded to explain.

As an avalanche of new laws and regulations hit Wall Street over the next few years, I fear that we’ll lose sight of the most important learning to take away from this disaster. Again, Bob Blakley explains:

A final thought.  The financial crisis exists because of a failure of risk management. There will be a temptation to fix the problem using compliance mandates. Compliance mandates, however, don’t fix risk management problems. All they do is prevent specific risk management failures from happening over and over again. Organizations whose risk management is weak will find new ways to fail – and these new ways will circumvent compliance regulations. The right way to fix a risk management problem is to do a better job of risk management.