Belief is a kind of blindness; and “dialogue” about your message with “diverse” people may foster new insight
The reason we’re so resistant to anomalous information — the real reason researchers automatically assume that every unexpected result is a stupid mistake — is rooted in the way the human brain works. Over the past few decades, psychologists have dismantled the myth of objectivity. The fact is, we carefully edit our reality, searching for evidence that confirms what we already believe. Although we pretend we’re empiricists — our views dictated by nothing but the facts — we’re actually blinkered, especially when it comes to information that contradicts our theories. The problem with science, then, isn’t that most experiments fail — it’s that most failures are ignored.
…dorsolateral prefrontal cortex, or DLPFC. It’s located just behind the forehead and is one of the last brain areas to develop in young adults. It plays a crucial role in suppressing so-called unwanted representations, getting rid of those thoughts that don’t square with our preconceptions. For scientists, it’s a problem.
There was a squirt of blood to the anterior cingulate cortex, a collar of tissue located in the center of the brain. The ACC is typically associated with the perception of errors and contradictions — neuroscientists often refer to it as part of the “Oh shit!” circuit — so it makes sense that it would be turned on when we watch a video of something that seems wrong.
…their DLPFCs kicked into gear and they quickly deleted the image from their consciousness. In most contexts, this act of editing is an essential cognitive skill. (When the DLPFC is damaged, people often struggle to pay attention, since they can’t filter out irrelevant stimuli.) However, when it comes to noticing anomalies, an efficient prefrontal cortex can actually be a serious liability. The DLPFC is constantly censoring the world, erasing facts from our experience. If the ACC is the “Oh shit!” circuit, the DLPFC is the Delete key. When the ACC and DLPFC “turn on together, people aren’t just noticing that something doesn’t look right,” Dunbar says. “They’re also inhibiting that information.”
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…Belief, in other words, is a kind of blindness
How to learn from failure
1 Check Your Assumptions
- Ask yourself why this result feels like a failure. What theory does it contradict? Maybe the hypothesis failed, not the experiment.
2 Seek Out the Ignorant
- Talk to people who are unfamiliar with your experiment. Explaining your work in simple terms may help you see it in a new light.
3 Encourage Diversity
- If everyone working on a problem speaks the same language, then everyone has the same set of assumptions.
4 Beware of Failure-Blindness
- It’s normal to filter out information that contradicts our preconceptions. The only way to avoid that bias is to be aware of it.
Just look at Einstein, who did much of his most radical work as a lowly patent clerk in Bern, Switzerland. According to Veblen’s logic, if Einstein had gotten tenure at an elite German university, he would have become just another physics professor with a vested interest in the space-time status quo. He would never have noticed the anomalies that led him to develop the theory of relativity.
There are advantages to thinking on the margin. 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.
Modern science is populated by expert insiders, schooled in narrow disciplines. Researchers have all studied the same thick textbooks, which make the world of fact seem settled. This led Kuhn, the philosopher of science, to argue that the only scientists capable of acknowledging the anomalies — and thus shifting paradigms and starting revolutions — are “either very young or very new to the field.” In other words, they are classic outsiders, naive and untenured. They aren’t inhibited from noticing the failures that point toward new possibilities.
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.
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.”
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 look easy.”
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
- Jonah Lehrer
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