This is a fantastic article about the science of science. It's worth printing and reading at your leisure.
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.The sad part is that many scientists abandon the unexpected data in order to continue searching for what they expected.
4 comments:
Experiments rarely tell us what we expect. That's the dirty secret of science
Not sure how I feel about this article ... I agree with the idea that humans can make subjective decisions about results, but ultimately the true objective science will prove them wrong. My comments below.
"Experiments rarely tell us what we expect. That's the dirty secret of science."
I object to this statement. This is not a secret. This IS science. If we expected it, it is not real research.
"The fact is, we carefully edit our reality, searching for evidence that confirms what we already believe."
Not true, per se. We try to find similarities with reality so it makes sense to us. Otherwise, unexplained (not unexpected data, as the author uses) is hard to ... well ... explain!
In addition, the author seems to do a horrible job explaining the two balls falling. He describes them by size, not mass. Unless you think in mass, there is no way to know if the students were wrong or not. They different sizes could be different masses. Or not. The author does not make a clear distinction.
I do like his "Seek Out the Ignorant" step. I use this often. If you can explain it to the "ignorant," you likely understand it.
With all my negative comments about the article, I do think there is a lot of narrow-minded scientists out there. Also, group meetings with a diverse background of individuals is the best way to learn. In my experience, business does a better job at this than academia. Unfortunately, nowadays business does not try to solve problems that take too long, as we can't "afford" the time/money. Thus, having both business and academia is good for the world.
This article sort of reminds me of my favorite quote: "Fail forward fast." Gavin Newsom used it at a Berkeley graduation. Not sure it was his, but I like to think about it when I and "failing" at science.
Thanks for the comments A.J. I liked the article quite a bit, but I understand your criticism, particularly with regard to the mass of the two balls.
The crux of the article seemed to be that breakthroughs can be missed because of those subjective assumptions. There may not be an opportunity for objective science to prove them wrong if the "mistakes" never see the light of day.
Don't you formulate a hypothesis before embarking on research? It seems like you would need that framework in order to prove or disprove something. Human beings do tend to favor those conclusions that jive with their perceptions of the world.
I also love the article because I also think it helps explain how the Global Warming consensus was reached. Looking at the leaked e-mails, which we both agree are not likely the result of a conspiracy, there seemed to be an effort to make research conform with either the models or previous research. There is very little incentive to buck the conventional view.
Of course, I am far from objective myself on that count!
I agree. You do formulate a hypothesis. That is where the subjectivity comes in. And everyone likes to hypothesize right, so that is likely where the global weirdening models run into trouble. I just hope people do not misread this article to think science is flawed, when in fact it is people. I liken it to the quote "guns do not kill people, people kill people." Just that, "science does not misrepresent the nature of things, people misrepresent the science."
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