How to Fail (well).

February 19, 2010

From a very interesting article in WIRED entitled “Accept Defeat: the neuroscience of screwing up.”  Although I initially was just drawing to the fun graphic on “How to Learn From Failure” when I read the article it was fascinating.  I recommend following the link.  But here are a few sneak peaks.  Even scientists are guilty of editing and ignoring abberant data.  We are all to inclined to dismiss the unexpected as a fluke, or our own mistake.  Its a natural human trait:

“The lesson is that not all data is created equal in our mind’s eye: When it comes to interpreting our experiments, we see what we want to see and disregard the rest. The physics students, for instance, didn’t watch the video and wonder whether Galileo might be wrong. Instead, they put their trust in theory, tuning out whatever it couldn’t explain. Belief, in other words, is a kind of blindness.

“But this research raises an obvious question: If humans — scientists included — are apt to cling to their beliefs, why is science so successful? How do our theories ever change? How do we learn to reinterpret a failure so we can see the answer?”

How can we mitigate this?

“While the scientific process is typically seen as a lonely pursuit — researchers solve problems by themselves — Dunbar found that most new scientific ideas emerged from lab meetings, those weekly sessions in which people publicly present their data. Interestingly, the most important element of the lab meeting wasn’t the presentation — it was the debate that followed. Dunbar observed that the skeptical (and sometimes heated) questions asked during a group session frequently triggered breakthroughs, as the scientists were forced to reconsider data they’d previously ignored. The new theory was a product of spontaneous conversation, not solitude; a single bracing query was enough to turn scientists into temporary outsiders, able to look anew at their own work.”

“When Dunbar reviewed the transcripts of the meeting, he found that the intellectual mix generated a distinct type of interaction in which the scientists were forced to rely on metaphors and analogies to express themselves. (That’s because, unlike the E. coli group, the second lab lacked a specialized language that everyone could understand.) These abstractions proved essential for problem-solving, as they encouraged the scientists to reconsider their assumptions. Having to explain the problem to someone else forced them to think, if only for a moment, like an intellectual on the margins, filled with self-skepticism.

“This is why other people are so helpful: They shock us out of our cognitive box. “I saw this happen all the time,” Dunbar says. “A scientist would be trying to describe their approach, and they’d be getting a little defensive, and then they’d get this quizzical look on their face. It was like they’d finally understood what was important.””

I’ve often felt this to be true in architecture (not that we’re trying for right answers necessarily).  Too high a concentration of people all trained to see things in a particular way can be unproductive and result in insular design.  Jargon is especially dangerous.  I often felt frustrated with my fellow architecture students when they tossed around “archi-babel” because as often as not I doubted that they even knew precisely what they meant and they certainly weren’t conveying any specific meaning to their audiences!

(via Swissmiss)


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