I fall on that french article
which is fantastic, and is a translation of that wired article:
a must to read about how science really works.
It all started with the sound of static. In May 1964, two astronomers at Bell Labs, Arno Penzias and Robert Wilson, were using a radio telescope in suburban New Jersey to search the far reaches of space. Their aim was to make a detailed survey of radiation in the Milky Way, which would allow them to map those vast tracts of the universe devoid of bright stars. This meant that Penzias and Wilson needed a receiver that was exquisitely sensitive, able to eavesdrop on all the emptiness. And so they had retrofitted an old radio telescope, installing amplifiers and a calibration system to make the signals coming from space just a little bit louder.
But they made the scope too sensitive. Whenever Penzias and Wilson aimed their dish at the sky, they picked up a persistent background noise, a static that interfered with all of their observations. It was an incredibly annoying technical problem, like listening to a radio station that keeps cutting out.
At first, they assumed the noise was man-made,
but the noise always remained, making it impossible to find the faint radio echoes they were looking for. Their telescope was a failure.
Kevin Dunbar is a researcher who studies how scientists study things — how they fail and succeed. In the early 1990s, he began an unprecedented research project: observing four biochemistry labs at Stanford University. Philosophers have long theorized about how science happens, but Dunbar wanted to get beyond theory. He wasn’t satisfied with abstract models of the scientific method — that seven-step process we teach schoolkids before the science fair — or the dogmatic faith scientists place in logic and objectivity. Dunbar knew that scientists often don’t think the way the textbooks say they are supposed to. He suspected that all those philosophers of science — from Aristotle to Karl Popper — had missed something important about what goes on in the lab. (As Richard Feynman famously quipped, “Philosophy of science is about as useful to scientists as ornithology is to birds.”) So Dunbar decided to launch an “in vivo” investigation, attempting to learn from the messiness of real experiments.
He ended up spending the next year staring at postdocs and test tubes: The researchers were his flock, and he was the ornithologist. Dunbar brought tape recorders into meeting rooms and loitered in the hallway; he read grant proposals and the rough drafts of papers; he peeked at notebooks, attended lab meetings, and videotaped interview after interview. He spent four years analyzing the data. “I’m not sure I appreciated what I was getting myself into,” Dunbar says. “I asked for complete access, and I got it. But there was just so much to keep track of.”
Dunbar came away from his in vivo studies with an unsettling insight: Science is a deeply frustrating pursuit. Although the researchers were mostly using established techniques, more than 50 percent of their data was unexpected. (In some labs, the figure exceeded 75 percent.) “The scientists had these elaborate theories about what was supposed to happen,” Dunbar says. “But the results kept contradicting their theories. It wasn’t uncommon for someone to spend a month on a project and then just discard all their data because the data didn’t make sense.” Perhaps they hoped to see a specific protein but it wasn’t there. Or maybe their DNA sample showed the presence of an aberrant gene. The details always changed, but the story remained the same: The scientists were looking for X, but they found Y.
How did the researchers cope with all this unexpected data? How did they deal with so much failure? Dunbar realized that the vast majority of people in the lab followed the same basic strategy. First, they would blame the method. The surprising finding was classified as a mere mistake; perhaps a machine malfunctioned or an enzyme had gone stale. “The scientists were trying to explain away what they didn’t understand,” Dunbar says. “It’s as if they didn’t want to believe it.”
The experiment would then be carefully repeated. Sometimes, the weird blip would disappear, in which case the problem was solved. But the weirdness usually remained, an anomaly that wouldn’t go away.
This is when things get interesting. According to Dunbar, even after scientists had generated their “error” multiple times — it was a consistent inconsistency — they might fail to follow it up. “Given the amount of unexpected data in science, it’s just not feasible to pursue everything,” Dunbar says. “People have to pick and choose what’s interesting and what’s not, but they often choose badly.” And so the result was tossed aside, filed in a quickly forgotten notebook. The scientists had discovered a new fact, but they called it a failure.
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.
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.
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 [lexicon]conversation[/lexicon], not solitude; a single bracing query was enough to turn scientists into temporary outsiders, able to look anew at their own work.
fantastic description of what LENR experience today, and have experience, and also what t do, and not to do about experiments.