philosophy of science

Sandra Blakeslee discusses a new book about the process of science: Ignorance: How It Drives Science, by Stuart Firestein ("To Advance, Search for a Black Cat in a Dark Room").

Dr. Firestein got the idea for his book by teaching a course on cellular and molecular neuroscience, based on a 1,414-page textbook that, at 7.7 pounds, weighs more than twice as much as a human brain. He eventually realized that his students must think that pretty much everything in neuroscience is known. “This could not be more wrong,” he writes. “I had, by teaching this course diligently, given the students the idea that science is an accumulation of facts.

“When I sit down with colleagues over a beer at a meeting, we don’t go over facts,” Dr. Firestein writes. “We don’t talk about what’s known. We talk about what we’d like to figure out, about what needs to be done.”

Lurking here is some insight about the process of deciding who gets to do what (and gets funded for it). To be willing to grant money to a project, there is a trade-off between admitting that the answer is unknown, and admitting that the process has a good likelihood of successful outcome. Ignorance has a dual role here: the grantor must admit a certain amount of ignorance, while the prospective grantee must define ignorance in an incredibly narrow way (and ideally demonstrate that it's not ignorance after all).

In some sense, becoming successful at funding your work requires solving an intricate communication problem where the subject is ignorance.

I'm a little concerned about the idea (mentioned in the review) of an entire semester-long course titled, "Ignorance". Don't the students get enough about ignorance after one or two class sessions?

Jonah Lehrer reports on what happens when scientists see the unexpected:

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 description of Kevin Dunbar's work is interesting -- he's a "cognitive scientist" but the work is almost anthropology in the context of scientific labs.

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.

As described in the story, the process of science is like a big noise filter, where theoretically unexpected results are systematically eliminated. I will note the positive aspect: when we find an unexpected result repeatedly, our confidence that it is signal and not noise is vastly higher. So all these attempts to squelch the unexpected create a mental environment in which we can sometimes recognize it.

Sometimes. But as Lehrer describes, humans are good at conforming their mental world to the expected. Strangest line: "the Aristotelian video with the aberrant balls."