|Connect the dots. |
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The left-brain dominated problem solving is an analytical step-by-step procedure. It goes through the existing knowledge and applies known methods to a problem. Candidates solving a problem by this method have usually a feeling of making progress, of getting closer to a solution.
The right-brain dominated problem solving relies on pattern recognition and associations. It often kicks in after the left-brain method failed. Candidates solving a problem by this method have no feeling of making progress till they suddenly come up with a solution, often accompanied by an “aha-moment.” (Another study showed that brain activity indicates a solution has been found before people became consciously aware of that. The “aha” is produced just above your right ear.)
The problems that were used in this study, verbal puzzles and trick questions and so on, are highly artificial. In real life, most problems require a mixture of both approaches, though some more heavily rely on one or the other. If you are for example adding prices when shopping, that’s a very straight-forward left-brain problem. Figuring out how to fit the twin stroller and two baby seats plus two adults into a Renault Twingo (clearly a misnomer) will take forever if you’d indeed go through all possible options. Now visualize the space, or lack thereof, take off the stroller’s wheels and, aha, the trunk will close. I was very proud of my right brain.
But I am usually addressing problems exactly the way described in Lehrer’s book: First, search through existing knowledge and see if a method is known to solve the problem. If that doesn’t work, I have an intermediate step in which I try to come up with knowledge about where the solution can be found. If that fails too, I’ll try to match the problem to other problems that I know, simplify it, look at limiting cases, rewrite it, iterate, take off the wheels, and so on and so forth.
By and large my pattern searching mechanism seems to be somewhat overactive. It frequently spits out more associations than I’d want to, resulting in what the psychologists call divergent thinking. That, I’m afraid, is very noticeable if you talk to me, as I have the habit of changing topic in the middle of the sentence, making several loops and detours before coming back, if I come back. Needless to say, this makes perfect sense to me. In my experience (watch out, anecdotal evidence) most women have no problem following me. Most men get glassy eyes and either interrupt me, or patiently wait till I’ve made my loops and detours. I know at least one exception to this and, yes, I’m talking about you. So you should have no problem following the connections I’m about to draw from Lehrer’s book to some other books I’ve read recently.
Micheal Nielsen in his book “Reinventing Discovery” preaches that scientists should not only share their knowledge, but also share their ideas that are still under construction. In essence, his point is that our present knowledge is badly connected and has lots of unused potential. You might just have exactly that piece of knowledge that I am missing, but how will you know if I don’t tell you what it is I’m looking for? There are some prominent examples where this crowd-sourcing for knowledge matches has been successful, the Polymath project is often named.
Reading this, introspection reveals I rarely, if ever, blog about research I am working on. It’s not so much that I don’t want to, but that I can’t. I talk of course to my colleagues about what I am working on, people I have known and who have known me for a while. But they usually can’t make much sense of what I’m telling them. Heck, even my husband usually has no clue what I’m trying to say - till he has a finished paper in his hand that is. I mostly talk to them just for the merit of talking, and they know pretty well that their role is primarily to listen. I know this procedure from both sides, it’s quite common and clearly serves a purpose. But that purpose isn't sharing, it's improving the pattern seeking by bouncing loose connections off other people’s frowned foreheads.
Most often the problem I’m plaguing myself with is not the answer to a specific question, but to find a useful way to ask a question to begin with. And the way it feels to me, that’s mostly a right-brain task, a pattern-seeking, sense-making effort; a searching through the bits and pieces from papers and seminars, a matching and mixing, a blending and crossing. Once you have a concrete question, you can get out the toolbox and nail it to the wall, left-brain dominated.
Science needs both finding a question and finding an answer to that question, one can debate to which extent. But these two types of problems don’t communicate the same way. In fact, Sunstein in his book “Infotopia” points out it is very relevant for crowd-sourcing to work well that one has a well-posed question, the solution to which, if it is found, everybody will be able to agree on.
So I am thinking, there are problems we are plaguing ourselves with that we just can’t talk about. They are lonely problems.
Another connection I want to draw is to Michael Chorost’s book “World Wide Mind,” because that piece of information from Lehrer’s book had me realize just why I was so skeptic of the brain-to-brain communication method which is Chorost’s vision for the future.
Chorost suggests in his book to record each person’s pattern of neuronal activity for certain impressions, sights, smells, views, words, emotions and so on, which he calls “cliques.” An implant in your brain will pick up and decode your neural activity into “cliques” and transmit them to trigger the same cliques by somebody else’s implant in that person’s brain, which might have a different neuronal representation of the clique. That is, the cliques are essentially the basic units of brain-to-brain communication.
But what you cannot communicate this way is your brain’s attempt to find patterns in all the cliques. Neither can you, by this method, ever try to find patterns in other people’s cliques. Or, in the words that I used in my earlier post on “collective intelligence,” these are no examples for type-2 collective intelligence, the type in which the intelligence of the collective is not due to a shared and well-connected pool of knowledge, but to shared processes acting on that knowledge.
Finally, let us revisit an argument from Mark Pagel that we discussed recently. Pagel believes, in a nutshell, that we need fewer and fewer inventors because we are constantly improving the way we share ideas. The better we share the ideas we have, the fewer people we need to produce them. But what do we do with the part of the idea seeking that’s unshareable, at least for now? The better we share ideas the fewer similar ideas we need, but that leaves open the question how many people are needed to produce one shareable idea. And, distinguishing the two types of problem solving that we use, sharing doesn’t cut down the amount of necessary pattern seeking per idea. Sharing can improve the repository you search through, but taking into account that the problems are getting more involved too, it is far from clear that we need fewer people per idea.
If you’ve been following along all the way till here, thank you for your patience. If not, good to see you again in the last paragraph and either way, let me just come to the conclusion now. As I argued above, improvements in sharing and connecting ideas don’t work equally well for all types of thought processes. This bears the risk of smothering the lonely and unshareable sense-making, right-brain efforts. Much like a forest with two types of trees that receives a fertilizer which benefits only one type of trees, the shade of larger trees can cut off sunlight to the smaller trees. So I hope your lonely thoughts receive sufficient sunlight, and may you have many aha-moments right above your ear.