Posts Tagged multidisciplinary

On Imperatives for Innovation

Hi

Last year, innovation guru Julian Loren introduced me to Kim Chandler McDonald, who was researching innovators and how they think. Julian co-founded the Innovation Management Institute,and has helped many Fortune 500 firms with key innovation initiatives. I’ve had the privilege of working with Julian on large game conferences (gameferences) that prove just how quickly collaborators can  dissolve communication barriers and bridge disciplines. Out of this flows proof that design synthesis, when properly facilitated, can emerge in days, not years. Kim is founder/editor of the “Capital I” Innovation Interview Series. She has built a far-reaching network of global thought leaders that she studies, documents, encourages and co-innovates with. I was honored to be interviewed for her 2013 book, !nnovation – how innovators think, act, and change our world. Find it on Amazon, or the online enhanced edition at innovationinterviews.com (also flatworld.me) to see what makes innovators like Kim, Julian and a host of others tick. In light of my recent posts on great innovators in history, reinvigorated by Bruce Vojac’s vibrant series on the same topic, Kim has approved my posting an excerpt of her conversations with me here.

 How do you define Innovation?

Well that term is a bit overloaded these days.  I think traditionally Innovation meant the creation of better or more effective products, services, processes, & ideas. While that’s something bigger than just normal product refinement, I think it pertained more to improvement of an item in a category rather than invention of a new category. More recently, the term seems to indicate new categories and radical breakthroughs and inventions. It’s probably not very productive to get too hung up on differentiating innovation and invention.

Also, many people, perhaps following Clayton Christensen, have come to equate innovation with market disruption, where the radical change results in a product being suddenly available to a new segment because some innovator broke a price or user-skill barrier. Then suddenly, you’re meeting previously unmet customer needs, generating a flurry of consumption and press, which hopefully stimulates more innovation. That seems a perfectly good definition too.

Neither of those definitions seem to capture the essence of the iPhone, the famous example of successful innovation, despite really being “merely” a collection of optimizations of prior art. So maybe we should expand the definitions to include things that improve quality of life very broadly or address some compelling need that we didn’t yet know we had – things that just have a gigantic “wow” factor.

I think there’s also room for seeing innovation as a new way of thinking about something. That doesn’t get much press; but I think it’s a fascinating subject that interacts with the other definitions, particularly in the sense that there are sometimes rather unseen innovations behind the big visible ones. Some innovations are innovations by virtue of spurring a stream of secondary ones. This cascade can occur across product spaces and even across disciplines. We can look at Galileo, Kepler, Copernicus and Einstein as innovators. These weren’t the plodding, analytical types. All went far out on a limb, defying conventional wisdom, often with wonderful fusions of logic, empiricism and wild creativity.

Finally, I think we have to include innovations in government, ethics and art. They occasionally do come along, and are important. Mankind went a long time without democracy, women’s rights or vanishing point perspective. Then some geniuses came along and broke with tradition – in a rational yet revolutionary way that only seemed self-evident after the fact. They fractured the existing model and shifted the paradigm. They innovated.

How important do you envisage innovation going forward?

Almost all businesses identify innovation as a priority, but despite the attention given to the topic, I think we’re still struggling to understand and manage it. I feel like the information age – communications speed and information volume – has profoundly changed competition in ways that we haven’t fully understood. I suppose every era is just like its predecessor in the sense that it perceives itself to be completely unlike its predecessors. That said, I think there’s ample evidence that a novel product with high demand, patented or not, gets you a much shorter time to milk the cow than it used to. Business, and hopefully our education system, is going to need to face the need for innovation (whether we continue with that term or not) much more directly and centrally, not as an add-on, strategy du jour, or department down the hall.

What do you think is imperative for Innovation to have the best chance of success; and what have you found to be the greatest barrier to its success?

A lot has been written about nurturing innovation and some of it is pretty good. Rather than putting design or designers on a pedestal, create an environment of design throughout. Find ways to reward design, and reward well.

One aspect of providing for innovation seems underrepresented in print – planning for the future by our education system and larger corporations. Innovating in all but the narrowest of product spaces – or idea spaces for that matter – requires multiple skills and people who can integrate and synthesize. We need multidisciplinarians, interdisciplinary teams and top-level designers, coordinators and facilitators. Despite all out talk and interest in synthesis as opposed to analysis – and our interest in holism and out-of-the-box thinking – we’re still praising ultra-specialists and educating too many of them. Some circles use the term tyranny of expertise. It’s probably applicable here.

I’ve done a fair amount of work in the world of complex systems – aerospace, nuclear, and pharmaceutical manufacture. In aerospace you cannot design an aircraft by getting a hundred specialists, one expert each in propulsion, hydraulics, flight controls, software, reliability, etc., and putting them in a room for a year. You get an airplane design by combining those people plus some who are generalists that know enough about each of those subsystems and disciplines to integrate them. These generalists aren’t jacks of all trades and masters of none, nor are they mere polymaths; they’re masters of integration, synthesis and facilitation – expert generalists. The need for such a role is very obvious in the case of an airplane, much less obvious in the case of a startup. But modern approaches to product and business model innovation benefit tremendously from people trained in multidisciplinarity.

I’m not sure if it’s the greatest barrier, but it seems to me that a significant barrier to almost any activity that combines critical thinking and creativity is to write a cookbook for that activity. We are still bombarded by consultancies, authors and charismatic speakers who capitalize on innovation by trivializing it. There’s a lot of money made by consultancies who reduce innovation to an n-step process or method derived from shallow studies of past success stories. You can get a lot of press by jumping on the erroneous and destructive left-brain/right-brain model. At best, it raises awareness, but the bandwagon is already full. I don’t think lack of interest in innovation is a problem; lack of enduring commitment probably is. Jargon-laden bullet-point lists have taken their toll. For example, it’s hard to even communicate meaningfully about certain tools or approaches to innovation using terms like “design thinking” or “systems thinking” because they’ve been diluted and redefined into meaninglessness.

What is your greatest strength?

Perspective.

What is your greatest weaknesses?

Brevity, on occasion.

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Can the Tech World Hack Intergenerational Learning?

In politically correct America, Intergenerational Learning has become a euphemism for teaching grandpa how to work his AOL account. I’m not talking about that.

Ponderous

In social animal species, there is evidence that it benefits a population to have lifespans far in excess of the age when individuals can reproduce. For non-social species, those of us past our sexual primes are just consuming valuable resources in a limited ecosystem. But we social animals tend to continue to add skills, memories and mental abilities to our libraries, which can then be transmitted to youngsters much more quickly than they could be acquired through experience. That’s the theory anyway. Try it on your teenager.

It seems to me that in the world of tech – particularly software – great opportunities exist for improved cross-generational learning. This is apparent in our history of programming languages and development tools. Much of my history with software involves the C language and its offspring. I’ll draw an example from that experience.

I’ve always had an uneasy relationship with C (I started with Fortran). C seemed in many ways to be the perfectly wrong combination of a high and low level language. Pointer math is indeed fun, but there is danger. In my aerospace days, I was able to get an exemption from the US Air Force on their requirement that certain C-17 avionics be programmed in a “high level” programming language such as C. I opted for Assembly instead, the reason being that Assembly compiled much smaller, allowing us to get everything on a single 87C196 Intel chip. I didn’t think that “high level” of C significantly reduced the risk of bugs that would sneak through functional testing. The Air Force bought it, and history bears me out.

But C proved to be a bit too “low level” for enterprise software development. Higher-level languages (easier to code) like PowerBuilder and Visual Basic (early 90s) and then Java and C# (early 2000s) greatly improved rapid software development while reducing the skill level required for coders to be productive. But not without impact. The C guys were on the street, along with their vast experience in good design. It is far easier to learn to code in high level languages than to design good software (what we call “architecture” in an era of terminological inflation).

Eventually, after gross cost overruns and some clumsy architecture, the new coders grew into their jobs, right about at the time when “social” became a noun and drove the creation of new software tools, database engines, and programming languages. Ruby and Python gave newbie coders a lot of rope. Maybe not enough to hang themselves, but enough to lock some large firms into maintenance-nightmare codebases that will keep on costing until they’re retired. Rapid shifts in technology that inadvertently discard tribal knowledge are well documented in other fields, e.g., energy and heavy manufacturing.

Portrait of a man holding portraits of his ancestors

We see an absence of cross-generational learning not only in programmers, but in those who create programming languages, tools, and development frameworks. VB’s syntax was a complete mess and its object orientation was an afterthought. Java cured all that, and we were glad to be done with VB’s type-promiscuity. But a generation later (in programmer years) Python repeated many of VB’s sins, along with being a scoping-rule disaster.

This problem in the world of software is exacerbated by cultural factors and the geek mystique. It extends beyond the technical realm. As Silicon Valley critic Vivek Wadhwa points out, the tech press and investors can’t get enough of the 20-year-old white male supergeek CEO myth. Incumbent in this myth is the notion that experience has negative value.

So how do we fix this? We can’t blame short-sighted downsizing and retirement for this loss of tribal knowledge. We seem to need broader knowledge, a dose of maturity or both. The problem is cultural, sociological or psychological; but the affected community is tech – not an area known for multidisciplinarity. How to fix it? Perhaps it will have to wait for the next generation. Maybe we can find some old farts who know how to do this.

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Hack: withstand or manage (“I can’t just can’t hack that.”)
Hack: write code (e.g., TechCrunch NY 2013 Disrupt Hackathon)

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A Helicopter Flew Over the Cuckoo’s Nest

flowerpower“Fail early and often.” This war cry du jour of speakers on entrepreneurial innovation addresses several aspects of what big companies need to learn from little ones about market dynamics at the speed of the internet. The shelf life of a product idea is pretty short these days. If you don’t cannibalize your own line, a nimble competitor will eat your lunch. Failure is a necessary step on the path to innovative solutions. Short-cycle failure is much cheaper than the long-cycle variety. Innovation entails new ideas, and the idea generation phase is not the time for Negative Nelly, the devil’s advocate, to demoralize your design team. A lot of bad ideas beget new insights that spawn good ideas.

My favorite story about letting crazy ideas fly deals with Pacific Power and Light, who supplies electricity to some remote spots in the Cascades. As the story goes, storms left thick ice on their power transmission lines. Linemen were sent out into the field, who climbed the icy towers and used long hooks to knock down the ice. The process was slow, expensive and dangerous.

PP&L’s brainstorming sessions initially yielded no clever solutions. They again attacked the issue, this time ensuring cognitive diversity by including linemen, accountants, secretaries, and the mail guy.

As a joke, a lineman suggested training bears to climb the poles and shake them. Someone else added that by putting honey pots on top of the poles, the bears would go for the honey without training, and perhaps shake the poles sufficiently to knock the ice off the lines. Continuing the silliness, someone suggested using helicopters to periodically fill the honey pots.

Bingo.  A secretary, formerly a nurse’s aide in Vietnam, recalled the fury of the down-wash from the helicopter blades and asked if flying a helicopter near the power lines would be sufficient to shake the lines and knock the ice off. In fact, it is! By valuing cognitive diversity and by encouraging crazy thinking, the team found a solution. As the story goes, PP&L now uses helicopters to fly over the power transmission lines after ice storms and it works fabulously.

As is probably apparent to any student of mythology, literary form criticism or biblical criticism, the story is pure fiction. It appears in many tellings on the web, some dating back several decades. Veracity strike one: manuscript (version) differences indicate multiple independent secondary sources. Strike two: earlier versions have less textural detail than later versions (e.g., the lineman is named Bill in later tellings). Strike three: the setups for the convergence of a diverse group are strained and get more detailed over time (compare the aphorism setups in Gospel Mark vs. Matthew).

Sure, the story is fiction – but what of it? The tale itself is aphoristic – an adage. It does not rely on the credibility of its source or the accuracy of the details to be valid; it’s validity is self evident. Or as Jack Nicholson (R.P. McMurphy) is often quoted as saying in One Flew Over the Cuckoo’s Nest, “Just because it didn’t happen, doesn’t mean it isn’t true.”

But as any movie fan with access to web-based movie scripts can attest, that quote never happened either. But just because McMurphy never said that just because it didn’t happen, doesn’t mean it isn’t true doesn’t mean that that isn’t true. (That last sentence contains a level-two embedded phrase, by the way.)

Further, just because Nicholson didn’t say it doesn’t mean it wasn’t said. It turns out a few others are cited as sources for this saying as well. The earliest one I could find. oddly enough, is Marcus Borg, theologian and New Testament scholar who found himself in the odd position of trying to defend Christianity while denying that Jesus said the things attributed to him. Borg’s tools are the same ones I used on the helicopter scriptures above.

Quote attribution is a tricky matter, especially when a more famous guy repeats a line from a less famous guy. Everyone knows the one about Oscar Wilde saying to James Whistler, “I wish I had said that.” To which, Whistler replied, “You will Oscar, you will.” I love this one, because it’s a quote about a quote. And none the worse when we discover, as you might expect, that it never happened – which, of course, doesn’t mean it isn’t true.

The exchange between Whistler and Wilde is cited in the Oxford Dictionary of Quotations. They give the source as page 67 of Leonard Cresswell Ingleby’s 1907 book, Oscar Wilde. As you might expect from my mentioning it here, Inglesby’s book contains no such quote on page 67 or anywhere else in the book. However, the 1973 Monty Python skit, Oscar Wilde, does include this exchange between Whistler and Wilde. Inclusion by the Monty Python crew, who tend to research history better than most textbook authors, is reason enough to dig a bit further for a source. Oscar Wilde researcher Peter Raby would be the guy to check on this trivia. I did. Raby traces the quote back to rumors in the early 1900s. He finds that some time after Wilde’s death Herbert Vivien, Douglas Sladen and Frank Harris all recalled the quote but disagreed on whether Wilde or Whistler or neither were involved.

I will never be ashamed of citing a bad author if the line is good.  – Seneca

Mix a little foolishness with your prudence: It’s good to be silly at the right moment.  – Horace

In a world of crowdsourcing and open innovation, it barely matters – beyond frivolous patents of course – where an idea originates or if its pedigree is respectable. Fables about bears, helicopters and Jack Nicholson are fair game. Let a thousand flowers bloom.

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Richard Rorty: A Matter for the Engineers

William Storage           13 Sep 2012
Visiting Scholar, UC Berkeley Science, Technology & Society Center

Richard Rorty, PhilosopherRichard Rorty (1931-2007) was arguably the most controversial philosopher in recent history. Unarguably, he was the most entertaining. Profoundly influenced by Thomas Kuhn, Rorty is fascinating and inspirational, even for engineers and scientists.

Rorty’s thought defied classification – literally; encyclopedias struggle to pin philosophical categories to him. He felt that confining yourself to a single category leads to personal stagnation on all levels. An interview excerpt at the end of this post ends with a casual yet weighty statement of his confidence in engineers’ ability to save the world.

Unlike many of his contemporaries, Rorty looked at familiar things in different light – and could explain his position in plain English. I never found much of Heidegger to be coherent, let alone important. No such problem with Dick Rorty.

Rorty could simplify arcane philosophical concepts. He saw similarities where others saw differences, being mostly rejected by schools of thought he drew from. This was especially true for pragmatism. Often accused of hijacking this term, Rorty offered that pragmatism is a vague, ambiguous, and overworked word, but nonetheless, “it names the chief glory of our country’s intellectual tradition.” He was enamored with moral and scientific progress, and often glowed with optimism and hope while his contemporaries brooded in murky, nihilistic dungeons.

Richard Rorty, PhilosopherRichard Rorty photo by Mary Rorty. Used by permission.

Rorty called himself a “Kuhnian” apart from those Kuhnians for whom The Structure of Scientific Revolution justified moral relativism and epistemic nihilism. Rorty’s critics in the hard sciences – at least those who embrace Kuhn – have gone to great lengths to distance Kuhn from Rorty. Philosophers have done the same, perhaps a bit sore from Rorty’s denigration of analytic philosophy and his insistence that philosophers have no special claim to wisdom. Kyle Cavagnini in the Spring 2012 issue of Stance (“Descriptions of Scientific Revolutions: Rorty’s Failure at Redescribing Scientific Progress”) finds that Rorty tries too hard to make Kuhn a relativist:

“Kuhn’s work provided a new framework in philosophy of science that garnered much attention, leading some of his theories to be adopted outside of the natural sciences. Unfortunately, some of these adoptions have not been faithful to Kuhn’s original theories, and at times just plain erroneous conclusions are drawn that use Kuhn as their justification. These misreadings not only detract from the power of Kuhn’s argument, but also serve to add false support for theories that Kuhn was very much against; Rorty was one such individual.”

Cavagnini may have some valid technical points. But it’s as easy to misread Rorty as to misread Kuhn. As I read Rorty, he derives from Kuhn that the authority of science has no basis beyond scientific consensus. It then follows for Rorty that instituational science and scientists have no basis for a privileged status in acquiring truth. Scientist who know their stuff shouldn’t disagree on this point. Rorty’s position is not cultural constructivism applied to science. He doesn’t remotely imply that one claim of truth – scientific or otherwise – is as good as another. In fact, Rorty explicitly argues against that position as applied to both science and ethics. Rorty then takes ideas he got from Kuhn to places that Kuhn would not have gone, without projecting his philosophical ideas onto Kuhn:

“To say that the study of the history of science, like the study of the rest of history, must be hermeneutical, and to deny (as I, but not Kuhn, would) that there is something extra called ‘rational reconstruction’ which can legitimize current scientific practice, is still not to say that the atoms, wave packages, etc., discovered by the physical scientists are creations of the human spirit.”  – Philosophy and the Mirror of Nature

“I hope to convince the reader that the dialectic within analytical philosophy, which has carried … philosophy of science from Carnap to Kuhn, needs to be carried a few steps further.” – Philosophy and the Mirror of Nature

What Rorty calls “leveling down science” is aimed at the scientism of logical positivists in philosophy – those who try to “science-up” analytic philosophy:

“I tend to view natural science as in the business of controlling and predicting things, and as largely useless for philosophical purposes” – Rorty and Pragmatism: The Philosopher Responds to his Critics

For Rorty, both modern science and modern western ethics can claim superiority over their precursors and competitors. In other words, we are perfectly capable of judging that we’ve made moral and scientific progress without a need for a privileged position of any discipline, and without any basis beyond consensus. This line of thought enabled the political right to accuse Rorty of moral relativism and at the same time the left to accuse him of bigotry and ethnocentrism. Both did vigorously. [note]

You can get a taste of Rorty from the sound and video snippets available on the web, e.g. this clip where he dresses down the standard philosophical theory of truth with an argument that would thrill mathematician Kurt Gödel:

In his 2006 Dewey Lecture in Law and Philosophy at the University of Chicago, he explains his position, neither moral absolutist nor moral relativist (though accused of being both by different factions), in praise of western progress in science and ethics.

Another example of Rorty’s nuanced position is captured on tape in Stanford’s archives of the Entitled Opinions radio program. Host Robert Harrison is an eloquent scholar and announcer, but in a 2005 Entitled Opinions interview, Rorty frustrates Harrison to the point of being tongue-tied. At some point in the discussion Rorty offers that the rest of the world should become more like America. This strikes Harrison as perverse.  Harrison asks for clarification, getting a response he finds even more perverse:

Harrison: What do you mean that the rest of the world should become a lot more like America? Would it be desirable to have all the various cultures across the globe Americanize? Would that not entail some sort of loss at least at the level of diversity or certain wisdoms that go back through their own particular traditions. What would be lost in the Americanization or Norwegianization of the world?

Rorty: A great deal would be lost. A great deal was lost when the Roman Empire suppressed a lot of native cultures. A great deal was lost when the Han Empire in China suppressed a lot of native cultures […]. Whenever there’s a rise in a great power a lot of great cultures get suppressed.  That’s the price we pay for history.

Asked if this is not too high a price to pay, Rorty answers that if you could get American-style democracy around the globe, it would be a small price to have paid. Harrison is astounded, if not offended:

Harrison: Well here I’m going to speak in my own proper voice and to really disagree in this sense: that  I think governments and forms of government are the result of a whole host of contingent geographical historical factors whereby western bourgeois liberalism or democracy arose through a whole set of circumstances that played themselves out over time, and I think that [there is in] America a certain set of presumptions that our form of democracy is infinitely exportable … [and] that we can just take this model of American democracy and make it work elsewhere. I think experience has shown us that it’s not that easy.

Rorty: We can’t make it work elsewhere but people coming to our country and finding out how things are done in the democratic west can go back and try to imitate that in their own countries. They’ve often done so with considerable success. I was very impressed on a visit to Guangzhou to see a replica of the statue of Liberty in one of the city parks. It was built by the first generation of Chinese students to visit America when they got back. They built a replica of the Statue of Liberty in order to help to try to explain to the other Chinese what was so great about the country they’d come back from. And remember that a replica of the Statue of Liberty was carried by the students in Tiananmen Square.

Harrison (agitated): Well OK but that’s one way. What if you… Why can’t we go to China and see a beautiful statue of the Buddha or something, and understand equally – have a moment of enlightenment and bring that statue back and say that we have something to learn from this other culture out there. And why is the statue of liberty the final transcend[ant] – you say yourself as a philosopher that you don’t – that there are no absolutes and that part of the misunderstanding in the history of philosophy is that there are no absolutes. It sounds like that for you the Statue of Liberty is an absolute.

Rorty: How about it’s the best thing anybody has come up with so far. It’s done more for humanity than the Buddha ever did. And it gives us something that … [interrupted]

Harrison: How can we know that!?

Rorty: From history.

Harrison: Well, for example, what do we know about the happiness of the Buddhist cultures from the inside?  Can we really know from the outside that we’re happier than they are?

Rorty: I suspect so. We’ve all had experiences in moving around from culture to culture. They’re not closed off entities, opaque to outsiders. You can talk to people raised in lots of different places about how happy they are and what they’d like.

Then it spirals down a bit further. Harrison asks Rorty if he thinks capitalism is a neutral phenomenon. Rorty replies that capitalism is the worst system imaginable except for all the others that have been tried so far. He offers that communism, nationalization of production and state capitalism were utter disasters, adding that private property and private business are the only option left until some genius comes up with a new model.

Harrison then reveals his deep concern over the environment and the free market’s effect on it, suggesting that since the human story is now shown to be embedded in the world of nature, that philosophy might entertain the topic of “life” – specifically, progressing beyond 20th century humanist utopian values in light of climate change and resource usage. Rorty offers that unless we develop fusion energy or similar, we’ve had it just as much as if the terrorists get their hands on nuclear bombs. Rorty says human life and nature are valid concerns, but that he doesn’t see that they give any reason for philosophers to start talking about life, a topic he says philosophy has thus far failed to illuminate.

This irritates Harrison greatly. At one point he curtly addresses Rorty as “my dear Dick.” Rorty’s clarification, his apparent detachment, and his brevity seem to make things worse:

Rorty: “Well suppose that we find out that it’s all going to be wiped out by an asteroid. Would you want philosophers to suddenly start thinking about asteroids? We may well collapse due to the exhaustion of natural resources but what good is it going to do for philosophers to start thinking about natural resources?”

Harrison: “Yeah but Dick there’s a difference between thinking of asteroids, which is something that is outside of human control and which is not submitted to human decision and doesn’t enter into the political sphere, and talking about something which is completely under the governance of human action. I don’t say it’s under the governance of human will, but it is human action which is bringing about the asteroid, if you like. And therefore it’s not a question of waiting around for some kind of natural disaster to happen, because we are the disaster – or one could say that we are the disaster – and that the maximization of wealth for the maximum amount of people is exactly what is putting us on this track toward a disaster.

Rorty: Well, we’ve accommodated environmental change before. Maybe we can accommodate it again; maybe we can’t. But surely this is a matter for the engineers rather than the philosophers.

A matter for the engineers indeed.

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Notes

1) Rorty and politics: The academic left cheered as Rorty shelled Ollie North’s run for the US Senate. As usual, not mincing words, Rorty called North a liar, a claim later repeated by Nancy Reagan. There was little cheering from the right when Rorty later had the academic left in his crosshairs; perhaps they failed to notice.. In 1997 Rorty wrote that the academic left must shed its anti-Americanism and its quest for even more abusive names for “The System.” “Outside the academy,  Americans still want to feel patriotic,” observed Rorty. “They still want to feel part  of a nation which can take control of its destiny and make itself a  better place.”

On racism, Rorty observed that the left once promoted equality by saying we were all Americans, regardless of color. By contrast, he said, the contemporary left now “urges that America should  not be a melting-pot, because we need to respect one another  in our differences.” He chastised the academic left for destroying any hope for a sense of commonality by highlighting differences and preserving otherness. “National pride is to countries what self-respect is to individuals,” wrote Rorty.

For Dinesh D’Souza, patriotism is no substitute for religion. D’Souza still today seems obsessed with Rorty’s having once stated his intent “to arrange things so that students who enter as  bigoted, homophobic religious fundamentalists will leave college with  views more like our own.” This assault on Christianity lands Rorty on a D’Souza enemy list that includes Sam Harris, Christopher Hitchens, and Richard Dawkins, D’Souza apparently unaware that Rorty’s final understanding of pragmatism included an accomodation of liberal Christianity.

2) See Richard Rorty bibliographical material and photos maintained by the Rorty family on the Stanford web site. 

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Dislodged Systems Engineers

When I mostly dislodged myself from aerospace a while back and became mostly embedded in Silicon Valley, I was surprised by the undisciplined use of the term “Systems Engineer.”

To me, Systems Engineering was a fairly concise term for an interdisciplinary approach to design and construct successful systems. Systems Engineering – as seen by INCOSE,  the International Council on Systems Engineering – involves translating customer needs into requirements, then proceeding with design synthesis. This process integrates many disciplines and specialty groups into a team effort to transform concept into design, production and operation. Systems Engineering accommodates business, technical and regulatory needs and requirements toward the goal of providing a quality product that makes investors, customers, regulators and insurers happy. It’s a methodical, top-down, big-picture approach.

In Silicon Valley, “systems engineering” is usually short for “embeddedsystems engineering,” i.e., the engineering of embedded systems. An embedded system is usually a computer system that performs specific control functions, often within a larger system – like those designed by systems engineers as described above. Embedded systems get their name by being completely contained within a physical (hardware) device. Embedded systems typically contain microcontrollers or digital signal processors for a particular task within the device. A common form of embedded system is the firmware that provides the logic for your smart phone.

IrrigationThere is often overlap. Aircraft, hospitals and irrigation management networks are all proper systems. And they contain many devices with embedded systems. Systems engineers need to have a cursory knowledge of what embedded-systems engineers do, and often detailed knowledge of the requirements for embedded systems. It’s a rare Systems Engineer who also does well at detailed design of embedded systems (Ron Bax at Crane Hydro-Aire take a bow). And vice versa. Designers of embedded systems usually only deal with a subset of the fundamentals of systems engineering – business problem statement, formulation of alternatives (trade studies), system modeling, integration, prototyping, performance assessment, reevaluation and iteration on these steps.

Because there are a lot more embedded-systems engineers than systems engineers in Silicon Valley, its residents are happy with dropping the “embedded” part, probably not realizing that doing so would make it hard for a systems engineer to find consulting work. Or perhaps “embedded” seems superfluous if you don’t know about the discipline of systems engineering at all. This is a shame, since a lot of firms who make things with embedded systems could use a bit – perhaps quite a bit – of systems engineering perspective.

This is an appeal for more discipline in the semantics of engineering (call me a pedantic windbag – my wife does) and for awareness of the discipline of Systems Engineering. Systems Engineering is a thing and the world could use more of it. Silicon Valley firms would benefit from the methodical, big-picture perspective of Systems Engineering by better transforming concept to design and design to product. Their investors would like it too.

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Tangent:

In my work as a software engineer – not of the embedded sort – I’ve spent some time with various aspects of semantics and linguistics – forensic linguistics being the most fun. “Embedded” in linguistics refers to a phrase contained in a phrase of the same type. This makes for very difficult machine – and often human – parsing. Humans have little trouble with single embedding but struggle with double embedding. Triple embedding, though it appeared in ancient writing, sends modern humans running for the reboot switch. The ancient Romans were far more adept at parsing such sentences than we are today, though their language was more suited to it.

The child the dog bit got rabies shots. The child the dog the man shot bit got rabies shots. The child the dog the man the owner sued shot bit got rabies shots.

My wife is probably right.

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Collective Decisions and Social Influence

VictrolaPeople have practiced collective decision-making here and there since antiquity. Many see modern social connectedness as offering great new possibilities for the concept. I agree, with a few giant caveats. I’m fond of the topic because I do some work in the field and because it is multidisciplinary, standing at the intersection of technology and society. I’ve written a couple of recent posts on related topics. A lawyer friend emailed me to say she was interested in my recent post on Yelp and crowd wisdom. She said the color-coded scatter plots were pretty; but she wondered if I had a version with less whereas and more therefore. I’ll do that here and give some high points from some excellent studies I’ve read on the topic.

First, in my post on the Yelp data, I accepted that many studies have shown that crowds can be wise. When large random crowds respond individually to certain quantitative questions, the median or geometric mean (though not the mean value) is often more accurate than answers by panels of experts. This requires that crowd members know at least a little something about the matter they’re voting on.

Then my experiments with Yelp data confirmed what others found in more detailed studies of similar data:

  1. Yelp raters tend to give extreme ratings.
  2. Ratings are skewed toward the high end.
  3. Even a rater who rates high on average still rates many businesses very low.
  4. Many businesses in certain categories have bimodal distributions – few average ratings, many high and low ratings.
  5. Young businesses are more like to show bimodal distributions; established ones right-skewed.

I noted that these characteristics would reduce statisticians’ confidence in conclusions drawn from the data. I then speculated that social influence contributed to these characteristics of the data, also seen in detailed studies published on Amazon, Imdb and other high-volume sites. Some of those studies actually quantified social influence.

Two of my favorite studies show how mild social influence can damage crowd wisdom; and how a bit more can destroy it altogether. Both studies are beautiful examples of design of experiments and analysis of data.

In one (Lorenz, et. al., full citation below), the experimenters asked six questions to twelve groups of twelve students. In half the groups, people answered questions with no knowledge of the other members’ responses. In the other groups the experimenters reported information on the group’s responses to all twelve people in that group. Each member in such groups could then give new answers. They repeated the process five times allowing each member to revise and re-revise his response with knowledge about his group’s answers, and did statistical analyses on the results. The results showed that while the groups were initially wise, knowledge about the answers of others narrowed the range of answers. But this reduced range did not reduce collective error. This convergence is often called the social influence effect.

A related aspect of the change in a group’s answers might be termed the range reduction effect. It describes that fact that the correct answer moves progressively toward the periphery of the ordered group of answers as members revise their answers. A key consequence of this effect is that representatives of the crowd become less valuable in giving advice to external observers.

The most fascinating aspect of this study was the confidence effect. Communication of responses by other members of a group increased individual members’ confidence about their responses during convergence of their estimates – despite no increase in accuracy. One needn’t reach far to find examples in the form of unfounded guru status, overconfident but misled elitists, and Teflon financial advisors.

Another favorite of the many studies quantifying social influence (Salganik, et. al.) built a music site where visitors could listen to previously-unreleased songs and download them. Visitors were randomly placed in one of eight isolated groups. All groups listened to songs, rated them, and were allowed to download a copy. In some of the groups visitors could see a download count of each song, though this information was not emphasized. The download count, where present, was a weak indicator of the preferences of other visitors. Ratings from groups with no download count information yielded a measurement of song quality as judged by a large population (14,000 participants total). Behavior of the groups with visible download counts allowed the experimenters to quantify the effect of mild social influence.

The results of the music experiment were profound. It showed that mild social influence contributes greatly to inequality of outcomes in the music market. More importantly, it showed, by comparison of the isolated populations that could see download count, that social influence introduces instability and unpredictability in the results. That is, wildly different “hits” emerged in the identical groups when social influence was possible. In an identical parallel universe, Rihanna did just OK and Donnie Darko packed theaters for months.

Engineers and mathematicians might correctly see this instability situation as something like a third order dynamic system, highly sensitive to initial conditions. The first vote cast in each group was the flapping of the butterfly’s wings in Brazil that set off a tornado in Texas.

This study’s authors point out the ramifications of their work on our thoughts about popular success. Hit songs, top movies and superstars are orders of magnitude more successful than their peers. This leads to the sentiment that superstars are fundamentally different from the rest. Yet the study’s results show that success was weakly related to quality. The best songs were rarely unpopular; and the worst rarely were hits. Beyond that, anything could and did happen.

This probably explains why profit-motivated experts do so poorly at predicting which products will succeed, even minutes before a superstar emerges.

When information about a group is available, its members do not make decisions independently, but are influenced subtly or strongly by their peers. When more group information is present (stronger social influence), collective results become increasingly skewed and increasingly unpredictable.

The wisdom of crowds comes from aggregation of independent input. It is a matter of statistics, not of social psychology. This crucial fact seems to be missed by many of the most distinguished champions of crowdsourcing, collective wisdom, crowd-based-design and the like. Collective wisdom can be put to great use in crowdsourcing and collective decision making. The wisdom of crowds is real, and so is social influence; both can be immensely useful. Mixing the two makes a lot of sense in the many business cases where you seek bias and non-individualistic preferences, such as promoting consumer sales.

But extracting “truth” from a crowd is another matter – still entirely possible, in some situations, under controlled conditions. But in other situations, we’re left with the dilemma of encouraging information exchange while maintaining diversity, independence, and individuality. Too much social influence (which could be quite a small amount) in certain collective decisions about governance and the path forward might result in our arriving at a shocking place and having no idea how we got there. History provides some uncomfortable examples.

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Sources cited:

Jan Lorenza, Heiko Rauhutb, Frank Schweitzera, and Dirk Helbing.  “How social influence can undermine the wisdom of crowd effect” Proceedings of the National Acadamy of Science, May 31 2011.

Matthew J. Salganik, Peter Sheridan Dodds et. al. “Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market,” Science Feb 10 2006.

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The Systems Thinking Wars

My goal for The Multidisciplinarian is to talk about multidisciplinary and interdisciplinary problem solving. This inevitably leads to systems, since problems requiring more than one perspective or approach tend to involve systems, whether biological, social, logical, mechanical or political.

I hope to touch upon a bunch of systems concepts at some point, including:

I started following some of these terms on Twitter a few weeks ago, and ended up reading a lot of web topics on Systems Thinking. I found all the classics, along with, surprisingly, something of a battleground. I don’t mean attacks from the outside, like the view that organizations are not systems but processes. Instead I’m talking about the enemy within. It seems there are several issues of contention.

The matter of whether Systems Thinking is a deterministic or “hard” approach percolates through many of the discussions. “Hard” in this context means that it’s a mere extension of systems engineering, treating humans, society, and business organizations as predictable machinery. But on the street (as opposed to in academics), there’s also disagreement over whether that attribute is desirable or not. Some proponents defend Systems Thinking as being largely deterministic against criticism that it is soft. Other defenders of the approach argue against criticism that it is deterministic.

Is Systems Thinking an approach, a model, a methodology, or a theory? That’s debatable too; and therefore, it’s being debated. One can infer from the debates and discussions that much of the problem stems from semantics. The term means different things to different communities. Such overloaded terminology works fine as long as the communities don’t overlap. But they do overlap, since systems tend to involve multiple disciplines.

From a distance, you can grasp the gist of Systems Thinking. At its most rudimentary level, it is seeing the forest from the trees and using that vision to get things done. Barry Richmond, celebrated systems scientist, gave this high level definition:

At the conceptual end of the spectrum is adoption of a systems perspective or viewpoint. You are adopting a systems viewpoint when you are standing back far enough—in both space and time—to be able to see the underlying web of ongoing, reciprocal relationships which are cycling to produce the patterns of behavior that a system is exhibiting.

Peter Senge of MIT says that Systems Thinking is an approach for getting beyond cause and effect to the patterns of behavior that surface the cause and effect, and further, for identifying the underlying structure responsible for the patterns of behavior. If you, perhaps recalling your philosophy studies, detect a degree of rejection of reductionism in that definition, you’re right on track. More on that below. See the Systems Thinking World‘s definition page for a list of other definitions.

Barry Richmond, like Jay W Forrester, his mentor and prolific writer on Systems Thinking, was also heavily involved in System Dynamics. While many people equate the two concepts, others distinguish System Dynamics from Systems Thinking by the former’s use of feedback-loop computer models. Forrester, a consummate engineer and true innovator, developed the Systems Dynamics approach at MIT in the 1960s.

Caffeine Systems Thinking
System dynamics model showing processing of caffeine by the body and effects on drowsiness

For several decades Forrester applied Systems Thinking to business management, society and politics, maintaining throughout, that system dynamics is the necessary foundation underlying effective thinking about systems. In a 2010 paper, Forrester, then in the Sloan School of Management, wrote:

Without a foundation of systems principles, simulation, and an experimental approach, systems thinking runs the risk of being superficial, ineffective, and prone to arriving at  counterproductive conclusions. Those seeking an easy way to design better social systems will be as disappointed as if they were to seek an effortless route to designing bridges or doing heart transplants.

These bold and beautiful words are lost on the those who only know systems thinking from its current usage as little more than a strategic-initiative group-hug word. The quote is from Forrester’s appeal that Systems Thinking, at least as popularly defined, is insufficient without system dynamics modeling. Forrester speaks to usage of Systems Thinking that is nearly as deflated as current usage of “six-sigma,” by which our ancestors meant standard deviations of manufacturing tolerance (statistical process control). Nevertheless, as sociolinguists point out, a word means what a large body of its users think it means.

In the spirit of multidisciplinarity, it’s tempting to view this war from the perspective of study of religious cults. Too tempting – so I’ll succumb.

As with the internecine battles of religious cults, this is a war of small differences; often the factions in greatest dispute are the ones with the most similar views. Their differences are  real, but  imperceptible to most outsiders. They argue over definitions and interpretations, engaging in doctrinal disputes with constant deference to the cults’ founders. I also detect a fair amount of anxiety of influence in Systems Thinking advocates with roots in hard sciences.

Many systems engineers, including some very good ones, after opening the door to systems thinking, strain to differentiate themselves from their less evolved brethren.  John Boardman and Brain Sauser, thought leaders for whom I have the utmost respect, oddly display the anxiety of influence in statements like this from their Worlds of Systems site:

Our engineering friends believe the term ‘system’ is theirs of right and they alone understand systems. After all, who builds them? Who gets the job done? You would think, to hear some engineers talk, that they invented the term itself. In fact what propelled it into the high currency values it occupies today were the ideas of Ludwig von Bertalanffy.

Here we have two brilliant engineers (see in particular their work on Systems of Systems) who – though perhaps in jest – downplay the development of systems thinking a la Forrester, deferring to Bertalanffy, the biologist who first used the term Systems Theory. Semantic mapping tools available on the web clearly show that Bertalanffy, ground-breaking as he was, had next to nothing to do with the propulsion of the term “system” to its current status. The route was, as you’d expect, from Greek philosophy to Renaissance astronomy, to biology and engineering, and then on to computers.

Without delving into heady problems of Bertalanffy’s worldview, such as the paradox of emergence and the paradox of system environment, I’ll suggest that Bertalanffy was a great thinker, but should not occupy too high a pedestal. His view that the reductionist nature of biology of the mid 1900s stemmed solely from the influence of Descartes and Newton (who thought nature could be modeled as mechanism) ignored the obvious necessity of reduction in order to link stimulus with response. Testing ten foods separately, to see which causes your allergic reaction, does not conflict with holism. Bertalanffy, despite his great contributions, beat a reductionist straw man to death. Finally, can anyone not find Bertalanffy’s language of his later works indistinguishable from that of liberal theologians? Paul Tillich meets business management?

Boardman and Sauser similarly quote Philip Spor’s remark, “the engineer must often go beyond the limits of science, or question judgment based on alleged existing science,” as if such going-beyond isn’t inherent in engineering. Really guys, does anyone really think that the science of turbomachinery predated the engineering of turbomachines? Recall that special relativity was solid before the fourth-order partial differential equations governing a turbocharger were nailed down, at which time Alfred Büchi ‘s invention was common on trucks and trains. The opponent here is also mostly made of straw – a purely reductionist caricature of a systems engineer.

As a scholar of history of science and a fan of history of religion, here’s what I think is going on. Systems thinking is often at the intersection of systems science and social and management science; and the most orthodox of each of those root beliefs accuses the others of being too hard (as seen by social science) or too soft (as seen by engineers). The most liberal (or reformist, in the religious model) accuse their own party of being entrenched in orthodoxy.

Cult members mine the writings of these clergymen for ammunition against rival cults, thus we see quotes from Forrester, Bertalanffy, Ackoff and the like on websites, grossly misunderstood, and out of context. And we see ludicrous and undisciplined extensions of their material, as with Gary Zukav, Fritjof Capra, and Roger Penrose. The cult’s most vocal advocates insist on deifying the movement’s founders, and speak in terms of discovery and illumination rather than evidence and development.

Reasoning by analogy, yes; but I think you’ll admit this analogy holds rather well.

Another face of the Systems Thinking wars deals not with definitions and philosophy but with efficacy. In a 2009 Fast Company piece Fred Collopy, an experienced practitioner and teacher of Systems Thinking opined more or less that Systems Thinking is a failure – not because it has internal flaws but because it is hard. Systems Thinking, says Collopy, requires mastery of a large number of techniques, none of which is particularly useful by itself. This requirement is at odds with the way people learn, except in strict academic circles. Collopy offers that Design Thinking is an alternative, but only if we can keep it from being bogged down in detailed process definition and becoming an overly restrictive framework. He notes that if Systems Thinking had worked like its early advocates hoped it would, there would be no management-by-design movement or calls for integrated management practice.

Interesting stuff indeed. It will be fun to see how this plays out. If history is a guide, and as Collopy seems to suggest, it may fizzle out before it plays out. Business schools and corporate leadership have a record of moving on to new, more fashionable approaches, independent of the value of current ones. More on that tomorrow.

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Philosophy of science is as useful to scientists as ornithology is to birds. – Richard Feynman

Thanks to Ventana Systems, Inc. for use of their VENSIM® tools.
Thanks to @DanMezick for recent tweet exchange on Systems Thinking.

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