Wisdom in diagnosis, then, involves not only deep knowledge about human biology and an understanding of the array of diseases that plague humankind but also knowledge and understanding about how the mind works in coming to conclusions. Discerning when these biases are operating in our minds is called metacognition, the ability to think about our thinking. The attribute of humility is embodied in the concept of metacognition; we recognize that our minds are imperfect, that there are limits to the validity of our assumptions, that we are subject to biases, and that therefore we must have the sharp sense to doubt our judgments and question whether we considered everything that should have been considered.

From “The Best Medicine” at In Character, by Harvard’s Jerome Groopman, M.D.

The essay focuses on the effects of cognitive bias in medical diagnoses (and why they’re bad). The practice of monitoring biases is important for any type of decision. It’s an essential aspect of open/conceptual’s “meta factors” discipline.

Designers and marketers (not to mention politicos and entertainers) have become adept at manipulating these biases in consumers and users, but I wonder how many are aware of how their own biases may affect the design process itself — or simply the question of which problem to solve…

Here is the book the launched the “heuristics & biases” paradigm and here is a list of cognitive biases that have probably influenced things you’re working on right now.

If you want some practice, try joining the discussion at Less Wrong for a few days.

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“Meta factors” are the complex, ambiguous, and largely qualitative (or at least very tricky to quantify) factors behind our experience of everything in art, science, commerce, and civics.

Think of it as building on the field of human factors — applied not just to subjects and potential users but to the researchers and designers themselves.

It involves:

• ideas about our ideas
• methods for evaluating methods
• the discipline of developing new disciplines…

The term is new but the idea & practice are as old as philosophy. In a sense, meta factors is philosophy — stripped of its historical connotations and rendered more effective for today’s challenges & opportunities.

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You will hear people talking about “latency,” which means the delay between a trading signal being given and the trade being made. Low latency — high speed — is what banks and funds are looking for. Yes, we really are talking about shaving off the milliseconds that it takes light to travel along an optical cable.

So, is trading faster than any human can react truly worrisome?

The rest is here (if you want to read more about the practical ethics of quantitative finance). What interests me is the more general notion of mechanistic processes making our decisions for us and inhibiting our ability to recognize and react to possible hazards.

The problem isn’t simply speed (or delay), it comes down to mechanistic processes and structures that are inaccessible to human decisions, neutralizing the power of human judgement and intuition to deal with emerging patterns.

Read another recent New York Times piece about how valuable hunches are in battle:

“Not long ago people thought of emotions as old stuff, as just feelings — feelings that had little to do with rational decision making, or that got in the way of it,” said Dr. Antonio Damasio, director of the Brain and Creativity Institute at the University of Southern California. “Now that position has reversed. We understand emotions as practical action programs that work to solve a problem, often before we’re conscious of it. These processes are at work continually, in pilots, leaders of expeditions, parents, all of us.”

The mind accomplished a lot over a couple hundred thousand years and we still don’t understand how the most fundamental processes work. Let’s not sell it out just yet. The mind — including intuitions, emotions, the whole ball of crud — is still our best asset.

What the machine-processes give us is objective safeguarding and reference — like instruments in an airplane.

But don’t planes have autopilot too? Isn’t that the same as algorithm-generated trading?

No. I think the difference is that the plane still goes the same speed and the pilot can still notice emerging dangers and use discretion to take over the controls. A fighter pilot wouldn’t let the computer fly in a dogfight (do they still have those?) — though computers come in damn handy to analyze and prioritize potential threats and targets (something I read about in Popular Mechanics when I was a kid, I think for since-cancelled Comanche helicopter program: I don’t know how sophisticated the real flight and weapons systems are).

In quantitative finance, the computers don’t just take over the controls for a while to make things cheaper and easier; the computers have actually changed the nature of task, introducing a different set of directions we can’t handle. There’s no “going manual” anymore, and we lose the ability to identify and manage emerging patterns.

Automated functions must exist to help us identify and correct mistakes (either by freeing our attention to notice them, or by providing objective benchmarks and measures), but they should not drive the process.

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I’m becoming a real fan of Daniel Little’s UnderstandingSociety blog.

Here he considers “how good is deliberative democracy?”:

The approach that starts and ends with voting among alternatives has a major shortcoming: no one gets a chance to make persuasive arguments to other citizens; no one has the opportunity of having his/her own beliefs challenged; no one is exposed to new facts or novel considerations that might make a difference in the choice. In other words, the “vote first” approach simply takes people’s preferences and beliefs as fixed, and looks at the problem of choice as simply one of aggregating these antecedent preferences.

The deliberative approach, by contrast, looks at belief formation as itself a cumulative and reasonable process; one in which the individual needs to have the opportunity to think through the facts and values that surround the choice; and, crucially, one in which exposure to other people’s reasoning is an important part of arriving at a sound conclusion.

I’m going to keep hammering this until people are sick of it: The Mindset of the Future is Process. It’s the key conceptual adjustment we need to make in order to address our current challenges — and to move towards the next generation of new opportunities.

Until now, both individuals and groups operate under assumptions of permanence — “this is the way things are” — until a crisis occurs and people start to say “but now we need to change.”

Our own institutions and ideas unintentionally conspire to fool us to believe that change is the exception when the truth is it’s the rule.

Permanence is not just exceptional, it’s deceptional — it’s mythological…

If you look deeply enough into your opinions and beliefs, you’ll find they aren’t just existing there, they actually depend on your ongoing efforts to reinterpret the world, adapting a supporting cast of ideas to keep your opinions and beliefs in accordance with new facts — like a balancing act.

All of this is background for my aim of digitizing our decision-making processes (which I’d like to get back to before this gets too metaphysical).

Any process needs both hard and soft aspects in order to function, i.e. it needs to have an element of fluidity, as in face-to-face conversations, and an element of solidity, as in putting it in writing.

Digital media does both.

The conversations we have in coffee shops and town hall sessions may generate a lot of energy, but that energy has to be channeled and stored or it dissipates. Everyone goes back to whatever everyone does until the next morning or next month when another batch of energy is generated and wasted all over again.

We also tend to forget (or misremember) exactly what our positions and ideas were. Without objective accounts of our conversations (and even with them) we can be astonishingly self-deceptive about our beliefs and reasons for believing.

Without articulation and objective deliberation (or at least deliberation that aspires to objectivity) we fail to notice inconsistencies in our thinking so we miss most of the best opportunities to learn and improve-by-process-of-correction — we fail to make our ideas and institutions more sustainable.

In other words, by failing to embrace change, we become more vulnerable to it.

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As maybe one of the most marked turns in the history of mainstream military strategy, Thomas Friedman quotes a US officer in Afghanistan saying, “We don’t count enemy killed in action anymore.”

Friedman elaborates:

Early in both Iraq and Afghanistan our troops did body counts, à la Vietnam. But the big change came when the officers running these wars understood that R.B.’s (“relationships built”) actually matter more than K.I.A.’s. One relationship built with an Iraqi or Afghan mayor or imam or insurgent was worth so much more than one K.I.A. Relationships bring intelligence; they bring cooperation. One good relationship can save the lives of dozens of soldiers and civilians. One reason torture and Abu Ghraib got out of control was because our soldiers had built so few relationships that they tried to beat information out of people instead. But relationship-building is painstaking.

That’s especially interesting after I was recently introduced to the notion of “relationship centred medicine” by Andrew via email. It’s quite new for me but I’ll surely be looking out for it more often.

Today we also heard about Amazon’s purchase of Zappos — uber-exemplar of not just customer relations but employee relationships and organizational culture as well.

I first heard of Zappos when I read a story last year that they pay new employees to quit.

Here’s Zappos-prez Tony Hsieh presenting at the Web 2.0 Summit a while back, and here’s today’s video of Jeff Bezos talking about Amazon and the immediate implications of the deal.

Hmmm… another topic to watch.

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We’ve been hearing for years about “T-shaped people” (with deep knowledge and competence in one or two areas, crossed with wide knowledge across many domains); Microsoft’s Bill Buxton recently wrote about “I-shaped people”:

These have their feet firmly planted in the mud of the practical world, and yet stretch far enough to stick their head in the clouds when they need to. Furthermore, they simultaneously span all of the space in between. [BusinessWeek]

The concept is well intentioned, but who wants to “firmly planted in the mud” when we’re talking about innovation?! Surely there are better letters — or how about numbers? — to use for a derivative analogy.

I’m a big fan of 8.

Rather than being stuck in the mud, let’s continuously circulate from Ground-Level to Blue-Sky — picking up insights at various places along the way, which feed back into the system, converging, colliding, mingling, and remixing in the middle.

Even 0 would be better than I.

The latter resembles a pedestal, calling to mind impressions of permanence and supposed perfection — precisely the wrong way to go.

Anything that suggests static existence has to be tossed out asap. We need images and metaphors that accommodate motion and growth.

Which makes me wonder, what shape are innovation gurus?

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As I started reading Tyler Cowen’s Create Your Own Economy today, I was delighted to discover the whole book is framed by the concept of neurodiversity — specifically, the notion that autism shouldn’t be conceived strictly as an impairment, but as one cognitive style among many, with its own strengths and weaknesses.

From the book:

I prefer the word “learning” to “recovery”; many autistics learn how to overcome their cognitive disadvantages. Would we say that a non-autistic person, as he or she grows, “recovers” from having the disabilities of a four-year-old? Or would we say that the person has learned a lot?

Personally, I started learning a lot more — and with a lot less anxiety, guilt, resentment, depression… I became a lot happier — when I came to terms with my autism-like cognitive style and worked with it rather than against it.

Developing practices and ideas that nurture these characteristics has always been part of Open/Conceptual’s fundamental purpose. That should be evident by reading a lot of what I’ve written in the past two years (especially here).

I suppose I’m “out of the closet” now. I can’t figure out how high-profile I should be about this aspect (which is itself a manifestation of a characteristic from the autistic spectrum). Regardless of how much self-disclosure I use, watch for neurodiversity to come up more often in the discussion here.

Oh, and also, why don’t you get the book and read along?

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[Update: within minutes I decided to change the title to "Designing Ideas for Democracy" -- replacing "methodologies" with "ideas" -- which occurred to me after I thought about search results, then realized "ideas" is more appropriate anyways.]

This will be the provisional mission for Open/Conceptual.

As usual, “designing methodologies ideas for democracy” is something that spontaneously occurred to me after a a long period of germination. I didn’t sit down and decide “ok, I’m going to articulate the mission now,” but the connotations are nonetheless intentional and specific.

“Designing” deliberately refers to “design thinking” as practiced by the firms like IDEO and promoted by leading consultants and educators. This has been a part of Open/Conceptual’s foundational background since the start, if not earlier.

Design and design thinking, of course, have their own methodologies; roughly speaking (according to my own interpretation), they come down to a fusion of art, science, and commerce:

• Art: Aesthetics and emotions are essential; also, the process is open to spontaneous insights and inspirations.
• Science: It’s a social, reiterative process that assumes imperfection, fallibility, and continuous improvement through observation and experiments.
• Commerce: The ultimate test of merit is, “Are people willing to spend their time, attention, energy, and money on this?”

What’s missing is the Civic element…

While I don’t deny that design can improve (and has improved) things in civic and social domains, I think there are some important ways the civic sphere is inaccessible to current design methodologies — starting with the fact that design tends to be oriented around specific projects and objectives, while civics is endless; it lacks any ultimate & agreed-upon objective.

So that’s kind of where Open/Conceptual comes in: at the level of epistemology, or meta-methodology: the objective is to design an ultimate objective... keeping in mind that “design” infers that the process is reiterative — an endless succession of improving-but-still-imperfect results — i.e. we have to accept we won’t ever arrive at (or even articulate) “the” objective, but it’s the process of working it out that matters.

To put it another way, this is a philosophical enterprise: an attempt to do philosophy — not via weighty tomes full of impenetrable prose, but by modeling it into organizations and institutions that generate analogies and metaphors.

It’s kind of a microcosm for how we should try to conceive and organize the rest of our world. As I wrote last year:

Open Conceptual is where we end up by thinking creatively about everything — or at least that’s the objective. But the notion that creative thinking leads someplace is just a metaphor. We don’t really go anywhere: we grow: we cultivate creative mastery and freedom — which brings us back to the first meaning: Open Conceptual is the enterprise led foremost by creative thinking.

Exactly where it leads is impossible to know at this point, but generally, it’s the best way to go (I mean “grow”), because as long as we’re working this way, we continue to learn — we continue to stay informed and in practice so we’ll be competent and resourceful enough when genuine opportunities and challenges emerge.

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In the process of summarizing my last post, Jeff Jarvis suggested I was “searching for a metaphor for what I’ve been calling beta-think.” He’s exactly right — though I wasn’t aware of it when I started writing — so I’m going to take that up with a bit more brevity and focus.

The search for a “beta-think” metaphor builds on a more fundamental one I worked out last year, when I proposed that relevance will become the key to a new theory of human motivation:

I may not have realized it at the time, but my intellectual project was being supplied by metaphors from the internet — and more importantly, from the social web, or “Web 2.0.” The old dichotomies were inspired and perpetuated by mechanical metaphors — collisions and friction, turning gears, pressurized steam, etc — so it’s perhaps inevitable for us to conceive a new theory (or at least attitude, or vocabulary) of human nature using the marquee technology of our age. [...]

So I stumbled on the term “relevance” to replace “power.” It’s essentially in the same spirit as Nietzsche’s original, but “relevance” changes the connotation from domination and control to connectedness and meaning…

Google’s search engine acts as a metaphor for this theory the same way that mechanical engines provided metaphors for nineteenth century psychology, and, for that matter, the same way that older computing vocabularies in the mid-twentieth century provided metaphors for cognitive psychology.

So what’s the improved metaphor for beta-think? I don’t know yet — but I do know how we can work it out: by simply doing and making things in beta: prototyping and adapting and reiterating, etc.

By developing more open organizations and processes — based on the idea that people are motivated by relevance, not just money, power, and prestige — we’ll get progressively better metaphors and models for imagining how the mind works; as we get a better understanding of how the mind works, we can develop more effective organizations and processes… and so on, heuristically & recursively.

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Jeff Jarvis has been “thinking a lot about this lately: the need to risk and fail and not hold perfection as the standard of success.”

That’s a ‘perfect’ jump-off to introduce an important concept I’m trying to promote: generativity: instead of evaluating things on how well they accord with preconceived models and assumptions, let’s evaluate things by looking at how many unexpected new opportunities they generate.

Failure breaks things open and allows us to remix the pieces in different ways. If we don’t do this from time-to-time — if we just keep accumulating more mass onto the same framework — eventually it gets too bulky and falls on our heads.

It’s like forests that don’t have enough regular little manageable fires: eventually they get too dense, the ground accumulates too much dry wood, until one spark destroys thousands of acres without anything anyone can do to stop it.

This isn’t pseudo-profound stuff. This is just how life works — life outside the boxed-in board game version we’ve imagined ourselves playing for decades.

It’s like the shift from Newton’s physics to the less intuitive models of quantum physics and Einstein’s relativity: the new ideas aren’t as neat (and in many cases aren’t as useful) but they’re more accurate… and one day they will make sense and people will wonder how we could have been so stupid — just as we wonder how people could have once believed the universe revolves around a flat Earth.

That in itself is a good demonstration of what generativity means. Newton’s physics and calculus succeeded because it passed its DNA through generation after generation of subsequent discoveries, inventions, and ultimately a cult of efficiency that took over the world.

But now it’s becoming more difficult to stand on Newton’s shoulders. His ideas aren’t as generative anymore; they perpetuate more than they generate.

The technical edifice is so massive and sophisticated and dense that younger generations are having trouble seeing opportunities there. In science there isn’t much left that’s fit for Newton to explain; in engineering there’s plenty left to build, but the great challenges have already been conquered is largely gone.

The bridges and dams have been built, the moon has been conquered, the atom has already been split….

So we’ve been breaking-off Newton’s limbs and leaping away from the edifice to smash bosons, create ambient intelligence, and who-knows-what-else.

The new sciences address things that happen randomly, things that grow, things that don’t fit on the static grid: string theory, genetics, nanotech, etc.

Much of the new science — like the new economy — is not about layering subsequent successes on top of each other, but they are generative in the sense that they open up new fields to explore. They are adventures that could very likely fail to prove their original hypotheses but can’t fail to generate new ideas and insights.

E.g. String theory might eventually prove to be a “failure” in the limited sense — I suspect because it is tethered by what our math and mental models are capable of; we need to make some kind of conceptual leap — but whatever resolves the problems will be articulated by ideas that emerged by accident in the process of adventure.

In the process of writing this I remembered an older post (that should have been imported to this blog but doesn’t seem to have made it) about failing in a good way:

I just published (and deleted) a truly stupid post. Which is fine.

This blog is all about trying things out, challenging myself to explore and define new boundaries — that I don’t quite understand yet — as opposed to beginning (and then staying) within bounds.

Some of the best things are discovered by accident, and I wouldn’t want to miss out on them.

For example, a few days ago I was picking out random books and I accidentally found one about Henry Hudson.

I’d never heard of Hudson — or so I thought — until I flipped it over and read the back. Turns out this is the guy who lent his name to the Hudson River in New York, and Hudson Bay — and thus the Hudson Bay Company, HBC, The Bay.

Yes, he found the Hudson River for the Dutch (at the site of what is now New York City), and he found Hudson Bay for the British. For these accomplishments, Henry Hudson was seen as a total failure in his time.

Hudson’s backers weren’t looking for what he eventually found — nor even where they very interested after he found them. They wanted to find a route to “the Orient.” The expidition that took him all the way to (what is now) Albany NY was supposed to travel north of Russia, to China…

That obviously didn’t go as planned.

Nor did his expidition that took him into Hudson Bay, which was also supposed to reach China, although it did manage to set up one of history’s longest commercial dynasties. That expidition — and Hudson’s life — ended in mutinous disaster.

As we explore new ideas and new ways of doing things through the web, are we emulating Columbus and Hudson by “failing good”? Are we paying enough attention to the potentially positive accidents around us? Or are we more like Hudson’s financiers, who were disappointed that he never sailed over the North Pole?

Sometimes we react to these accidental discoveries as, “Oh well, I’ll take what I can get… could’ve been worse,” but accidents are aren’t mere consolations, they are the heart of life’s most essential processes.

Randomness and uncertainty are the keys to what we know of evolution and quantum theory so far — and, I believe we’ll soon learn, the keys to psychology and every related human science.

After all, what motivates us? What actually compels us to do things?

It isn’t perfection, and it sure as hell isn’t efficiency.

Even looking at the people who hold perfection in high esteem, it isn’t perfection itself that motivates them, it’s the challenge of pursuing it — and the sneaking uncertainty that they can’t attain it: it’s a dare.

Then there are the discoverers, creators, and adventurers who are drawn to the unknown — or rather, to what-they-think-they-know-but-can’t-prove…

If you take the uncertainty and randomness and genuine risk out of life (as in, risking oneself, not just other people’s money) you take the life out of life…

So why would we perpetuate organizations, rules, and systems that are based on the fundamental assumption that randomness and uncertainty can be mechanized and ordered into a irrelevance?

It’s the fatal flaw of both communism and industrial capitalism — not to mention fascism.

As a partial aside, I worry that our response to the finance crisis — “we’re getting it under control” — is simply an extension of the same defective ideas and attitudes that set off the crisis in the first place… like smothering a fire with wood: it’s still smoldering underneath, and now we’ve adding more fuel.

We’ve got a long way to go before overcoming these defects. And how do we get there?

I don’t know — but I do know that in order to move-on we’ll need to generate a lot of new ideas and a lot of new stuff. Most of it will fail — yes, but most of the stuff we have now is failing too… at least we won’t be sitting helplessly in the midst of collapse.

Ultimately there’s no single solution — nothing we can design and plan and settle on. What saves us at critical moments is a) luck, b) an abundance of options, and c) the ability to navigate uncertain terrain…

That last is the one that’s most in our control. Like any ability, it develops through practice. Unfortunately for most, by the time you actually need it, it’ll be too late to start learning.

The society that embraces uncertainty, nurtures a love for it (i.e. a love of learning) and develops institutions that thrive because of randomness rather than despite it, will eventually have the most success, generation-by-generation.

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