Range - David Epstein Page 0,47

about impromptu meetings. The surface features of the labs were very different. One had dozens of members, others were small. A few were all men, one was all women. All had international reputations.

The weekly lab meetings made the most interesting viewing. Once a week, the entire team came together—lab director, grad students, postdoctoral fellows, technicians—to discuss some challenge a lab member was facing. The meetings were nothing like the heads-down, solitary work in stereotypical portrayals of scientists, huddled over their test tubes. Dunbar saw free-flowing and spontaneous exchange. Ideas were batted back and forth, new experiments proposed, obstacles discussed. “Those are some of the most creative moments in science,” he told me. So he recorded them.

The first fifteen minutes could be housekeeping—whose turn it was to order supplies, or who had left a mess. Then the action started. Someone presented an unexpected or confusing finding, their version of Kepler’s Mars orbit. Prudently, scientists’ first instinct was to blame themselves, some error in calculation or poorly calibrated equipment. If it kept up, the lab accepted the result as real, and ideas about what to try and what might be going on started flying. Every hour of lab meeting Dunbar recorded required eight hours of transcribing and labeling problem-solving behaviors so that he could analyze the process of scientific creativity, and he found an analogy fest.

Dunbar witnessed important breakthroughs live, and saw that the labs most likely to turn unexpected findings into new knowledge for humanity made a lot of analogies, and made them from a variety of base domains. The labs in which scientists had more diverse professional backgrounds were the ones where more and more varied analogies were offered, and where breakthroughs were more reliably produced when the unexpected arose. Those labs were Keplers by committee. They included members with a wide variety of experiences and interests. When the moment came to either dismiss or embrace and grapple with information that puzzled them, they drew on their range to make analogies. Lots of them.

For relatively straightforward challenges, labs started with analogies to other, very similar experiments. The more unusual the challenge, the more distant the analogies, moving away from surface similarities and toward deep structural similarities. In some lab meetings a new analogy entered the conversation every four minutes on average, some of them from outside of biology entirely.

In one instance, Dunbar actually saw two labs encounter the same experimental problem at around the same time. Proteins they wanted to measure would get stuck to a filter, which made them hard to analyze. One of the labs was entirely E. coli experts, and the other had scientists with chemistry, physics, biology, and genetics backgrounds, plus medical students. “One lab made an analogy drawing on knowledge from the person with a medical degree, and they figured it out right there at the meeting,” Dunbar told me. “The other lab used E. coli knowledge to deal with every problem. That didn’t work here so they had to just start experimenting for weeks to get rid of the problem. It put me in an awkward position because I had seen the answer in another lab’s meeting.” (As part of the conditions of the study, he was not allowed to share information between labs.)

In the face of the unexpected, the range of available analogies helped determine who learned something new. In the lone lab that did not make any new findings during Dunbar’s project, everyone had similar and highly specialized backgrounds, and analogies were almost never used. “When all the members of the laboratory have the same knowledge at their disposal, then when a problem arises, a group of similar minded individuals will not provide more information to make analogies than a single individual,” Dunbar concluded.

“It’s sort of like the stock market,” he told me. “You need a mixture of strategies.”

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The trouble with courses of study like Northwestern’s Integrated Science Program, which impart a broad mixture of strategies, is that they may require abandoning a head start toward a major or career. That is a tough sell, even if it better serves learners in the long run.

Whether it is the making-connections knowledge Lindsey Richland studied, or the broad concepts that Flynn tested, or the distant, deep structural analogical reasoning that Gentner assessed, there is often no entrenched interest fighting on the side of range, or of knowledge that must be slowly acquired. All forces align to incentivize a head start and early, narrow specialization, even if that is a poor