In the article, author Jonah Lehrer shares:
When we look at a problem from the outside, we’re more likely to notice
what doesn’t work. Instead of suppressing the unexpected, shunting it
aside with our “Oh shit!” circuit and Delete key, we can take the
mistake seriously. A new theory emerges from the ashes of our surprise.
which people publicly present their data.”
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.
But not every lab meeting was equally effective. Dunbar tells the
story of two labs that both ran into the same experimental problem: The
proteins they were trying to measure were sticking to a filter, making
it impossible to analyze the data. “One of the labs was full of people
from different backgrounds,” Dunbar says. “They had biochemists and
molecular biologists and geneticists and students in medical school.”
The other lab, in contrast, was made up of E. coli experts. “They knew more about E. coli
than anyone else, but that was what they knew,” he says. Dunbar watched
how each of these labs dealt with their protein problem. The E. coli
group took a brute-force approach, spending several weeks methodically
testing various fixes. “It was extremely inefficient,” Dunbar says.
“They eventually solved it, but they wasted a lot of valuable time.”
Sounds like an industry trade meeting…
The diverse lab, in contrast, mulled the problem at a group meeting.
None of the scientists were protein experts, so they began a
wide-ranging discussion of possible solutions. At first, the
conversation seemed rather useless. But then, as the chemists traded
ideas with the biologists and the biologists bounced ideas off the med
students, potential answers began to emerge. “After another 10 minutes
of talking, the protein problem was solved,” Dunbar says. “They made it
Now THAT sounds more like a mastermind meeting.
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
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.”