On the other hand, new terms and language can help us point to and see new ideas and new opportunities for action. Here’s a recent post from Bob Sutton that sheds light on these challenges and is worth thinking about.

One of my best friends in graduate school was a former physics major named Larry Ford.  When behavioral scientists started pushing for precise definitions of concepts like effectiveness and leadership, he would sometimes confuse them (even though Larry is a very precise thinker) by arguing “there is a negative relationship between precision and accuracy.”   I just ran into a quote from the amazing Nobel winner Richard Feynman that makes a similar point in a lovely way:

We can’t define anything precisely. If we attempt to, we get into that paralysis of thought that comes to philosophers… one saying to the other: “you don’t know what you are talking about!”. The second one says: “what do you mean by talking? What do you mean by you? What do you mean by know?

Feynman’s quote reminded me of the opening pages of the 1958 classic “Organizations” by James March (quite possibly the most prestigious living organizational theorist, and certainly, one of the most charming academics on the planet) and Herbert Simon (another Nobel winner).  They open the book with a great quote that sometimes drives doctoral students and other scholars just crazy.  They kick-off by saying:

“This is a book about a theory of formal organizations.  It is easier, and probably more useful, to give examples of formal organizations than to define them.”

After listing a bunch of examples of organizations including the Red Cross and New York State Highway Department, they note in words that would have pleased Feynman:

“But for the present purposes we need not trouble ourselves with the precise boundaries to be drawn around an organization or the exact distinction between an “organization” and a “non-organization.”  We are dealing with empirical phenomena, and the world has an uncomfortable way of not permitting itself to be fitted into clean classifications.”

I must report, however, that for the second edition of the book, published over 20 years later, the authors elected to insert a short definition in the introduction:

“Organizations are systems of coordinated action among individuals and groups whose preferences, information, interests, or knowledge differ.”

When I read this,  I find myself doing what Feynman complained about.  I think of things they left out: What about norms? What about emotions?  I think of situations where it might not apply: Doesn’t a business owned and operated by one person count as an organization?  I think of the possible overemphasis on differences: What about all the times and ways that people and groups  in organizations have similar preferences, information, interests, and knowledge? Isn’t that part of what an organization is as well?  I could go on and on.

I actually think it is a pretty good definition, but my bias is still that I like original approach, as they did such a nice job of arguing, essentially, that if they tried to get more precise, they would sacrifice accuracy. Nonetheless, I confess that I still love trying to define things and believe that trying to do so can help clarifying your thinking.  You could argue that while the outcome, in the end, will always be flawed and imprecise, the process is usually helpful and there are many times when it is useful pretend that you have a precise and accurate definition even if you don’t (such as when you are developing metrics). ”

Richard Feynman On The Folly Of Crafting Precise Definitions – Bob Sutton:

Your morning dose of Feynman – Boing Boing: “Your morning dose of Feynman By Maggie Koerth-Baker at 7:05 am Wednesday, Oct 12

Richard Feynman, God of Perfect Analogies, explains why it’s not a failure or a scandal when scientists adapt and change their understanding of the world. This is a really important point, applicable in a lot of public debates over science, especially those focused on evolution and climate change. Science isn’t about writing things on tablets of stone. It’s about taking a theory and constantly digging deeper into it—adding layers of nuance, finding stuff that doesn’t make sense, and using both to build a more complete picture. Even if the big idea is right, the details will change. That’s how science is supposed to work.

Via W. Younes

For the past few months, my colleague Jim McGee and I have been hard at work on a project we’ve named Collaborating Minds. It will be an online problem-solving community — with a unique membership recruiting strategy. The goal is to create a resource that will be able to assist organizations with hard problems by providing rich insights and multiple perspectives. It’s a marriage of some of the ideas of crowdsourcing with the principles that make for high performance teams. It’s an example of getting more people to work together better, a topic I wrote about a while back.

Collaborating Minds’ main assets will be:

1. Its network of 500-700 part-time participants
2. Its approach to community building and structured problem solving,and
3. Its software platform that supports and enables the community building and structured problem-solving. 

The people will be recruited and selected based on their interest and ability to work together in the community in just the way the software platform allows. They will include people from a very diverse set of backgrounds. We’ll have scientists of various stripes, engineers of various types, humanists, consultants, experts in all kinds of fields. So in that respect it will be like crowdsourcing.

The community and the problem-solving will be actively managed, and the members will be expected to get to know at least some of the other community members outside the context of the specific problems we are working on. Community members will help each other on their own issues and challenges, and can use the problem-solving tools provided to do so if they like.

The software platform includes a social network of a particular kind, and a structured problem-solving process and spaces for the problem-solving to occur. The problem-solving method will combine structured asynchronous elements and structured synchronous elements (online meetings). We also will have an alternative free-form option for members to use when the structure isn’t right for the problem at hand.

There’s a lot more info available now at the Collaborating Minds site. We are almost finished with the alpha version of the software platform and are starting to talk with people about recruiting and membership. We have a lot of unanswered questions (e.g., precise target markets, compensation, and governance) and probably some wrong answers to others. One of the best things about this idea though, is that we can aim our group at ourselves; if this sort of group can generate insightful and powerful solutions to hard problems (which I believe it can) then it help us solve the issues that remain ahead.

Collaborating Minds
David Friedman
Fri, 24 Jun 2011 19:07:11 GMT

Productive stupidity means being ignorant by choice. Focusing on important questions puts us in the awkward position of being ignorant. One of the beautiful things about science is that it allows us to bumble along, getting it wrong time after time, and feel perfectly fine as long as we learn something each time. No doubt, this can be difficult for students who are accustomed to getting the answers right. No doubt, reasonable levels of confidence and emotional resilience help, but I think scientific education might do more to ease what is a very big transition: from learning what other people once discovered to making your own discoveries. The more comfortable we become with being stupid, the deeper we will wade into the unknown and the more likely we are to make big discoveries.

From The importance of stupidity in scientific research

This willingness to move forward without knowing has made for much of the progress we’ve seen and benefitted from in the science and technology real. I wish I saw more of that same willingness manifest in business, education, and elsewhere. Maybe we’d learn to be more comfortable listening to people with provocative and productive questions and less willing to pay attention to people peddling the illusion of right answers.

The Edge question this year is "How has the Internet changed the way you think?". The result is eminently readable – my favorite so far is George Dyson’s answer, which is quoted here in its entirety:

GEORGE DYSON
Science Historian; Author, Darwin Among the Machines

KAYAKS vs CANOES

In the North Pacific ocean, there were two approaches to boatbuilding. The Aleuts (and their kayak-building relatives) lived on barren, treeless islands and built their vessels by piecing together skeletal frameworks from fragments of beach-combed wood. The Tlingit (and their dugout canoe-building relatives) built their vessels by selecting entire trees out of the rainforest and removing wood until there was nothing left but a canoe.

The Aleut and the Tlingit achieved similar results — maximum boat / minimum material — by opposite means. The flood of information unleashed by the Internet has produced a similar cultural split. We used to be kayak builders, collecting all available fragments of information to assemble the framework that kept us afloat. Now, we have to learn to become dugout-canoe builders, discarding unnecessary information to reveal the shape of knowledge hidden within.

I was a hardened kayak builder, trained to collect every available stick. I resent having to learn the new skills. But those who don’t will be left paddling logs, not canoes.

Short and sweet, in other words. Now, where did I leave that informational adze, what P. J. O’Rourke referred to as the "brief-but-insightful-summary" button?

How will the Internet change how we think?
Espen
Fri, 06 Aug 2010 13:47:02 GMT

Anyone with an interest in the continuing role and development of Smalltalk has had lots to chew on over the past few days.

As part of a series of investigations into the most widely-used programming languages, Computerworld Australia has published a conversation with Alan Kay about his role in the development of the “foundation of much of modern programming today: Smalltalk-80″, Object-Oriented Programming, and modern software development.

The Weekly Squeak: Smalltalk: the past, the present, and the future?
Michael Davies
Thu, 15 Jul 2010 10:00:45 GMT

Here’s a sample of Alan’s thinking :

What are the hurdles to those leaps in personal computing technology and concepts? Are companies attempting to redefine existing concepts or are they simply innovating too slowly?

It’s largely about the enormous difference between “News” and “New” to human minds. Marketing people really want “News” (= a little difference to perk up attention, but on something completely understandable and incremental). This allows News to be told in a minute or two, yet is interesting to humans. “New” means “invisible” “not immediately comprehensible”, etc.

So “New” is often rejected outright, or is accepted only by denaturing it into “News”. For example, the big deal about computers is their programmability, and the big deal about that is “meta”.

For the public, the News made out of the first is to simply simulate old media they are already familiar with and make it a little more convenient on some dimensions and often making it less convenient in ones they don’t care about (such as the poorer readability of text on a screen, especially for good readers).

For most computer people, the News that has been made out of New eliminates most meta from the way they go about designing and programming.

One way to look at this is that we are genetically much better set up to cope than to learn. So familiar-plus-pain is acceptable to most people.

[ComputerWorld Australia]

Alan can occasionally be a bit cryptic, but that’s because he assumes that you will do your share of the thinking when you listen to what he has to say.

Tech Support Cheat Sheet
Mon, 24 Aug 2009 04:00:00 GMT

There’s a striking amount of wisdom and good advice packed into this flowchart. It’s not about the body of knowledge stored away in your head. It’s about a robust strategy for generating and testing ideas that are likely to be productive.

What puzzles me is why individuals choose not to employ such a simple strategy.

The first is a clip by the late Nobel prize winning physicist Richard Feynman. In it he talks about his drive to figure out how nature works and the need to comfortable with not knowing. He believes in the process that has been given the fancy name of "the scientific method" despite its underlying simplicity. Make a guess, work out the consequences of your guess, run an experiment to compare your guess to reality, accept what reality tells you, and revise your guess for the next iteration. It’s very powerful, once you learn how to say "I don’t know, let’s find out."

The second clip comes from TED and shows Princeton molecular biologist, Bonnie Bassler describing her quest to understand how bacteria communicate. It’s a riveting look at how one person’s simple curiosity works in practice. Who knows, maybe she’ll get to go to Sweden some day.

Here is what Asimov had to say about believing in data…

"Don’t you believe in flying saucers, they ask me? Don’t you believe in telepathy? – in ancient astronauts? – in the Bermuda triangle? – in life after death?

No, I reply. No, no, no, no, and again no.

One person recently, goaded into desperation by the litany of unrelieved negation, burst out "Don’t you believe in anything?"

"Yes," I said. "I believe in evidence. I believe in observation, measurement, and reasoning, confirmed by independent observers. I’ll believe anything, no matter how wild and ridiculous, if there is evidence for it. The wilder and more ridiculous something is, however, the firmer and more solid the evidence will have to be."

Isaac Asimov, The Roving Mind (1997), 43

Asimov on evidence

The trouble is how easily our desire to believe can overwhelm the evidence.

1000 Times
Fri, 20 Mar 2009 04:00:00 GMT

We live in complicated times. We’re all trying to make sense of what is going on. That sense making isn’t made any easier by lazy writing and thinking. Actually, I don’t think this is a matter of deliberate efforts to mislead so much as it represents a continuing laziness when it comes to dealing with numbers, particularly big ones.

Two good places to start if you want to improve your own ability to make sense out of the numbers getting thrown around are Guesstimation: Solving the World’s Problems on the Back of a Cocktail Napkin and Filters Against Folly : How to Survive Despite Economists, Ecologists, and the Merely Eloquent.