- by Stuart Firestein
It offers several insights on how to ask effective questions.
Here are some text that I highlighted in the book:
James Clerk Maxwell, perhaps the greatest physicist between Newton and Einstein, advises that “Thoroughly conscious ignorance is the prelude to every real advance in science.”
There are cases where knowledge, or apparent knowledge, stands in the way of ignorance. The luminiferous ether of late 19th-century physics is an example.
Almost everyone believes that the tongue has regional sensitivities—sweet is sensed on the tip, bitter on the back, salt and sour on the sides. Pictures of “tongue maps” continue to appear not only in popular books on taste and cooking but in medical textbooks as well. The only problem is that it’s not true. The whole thing arose from the mistranslation of a German physiology textbook by a Professor D. P. Hanig, who claimed that his very anecdotal experiments showed that parts of the tongue were slightly more or slightly less sensitive to the four basic tastes. Very slightly as it has turned out when the experiments are done more carefully (you can try this on your own tongue with some salt and sugar, for example).
David Hilbert was probably the most successful at this game. In the talk that followed that opening comment in August 1900, he outlined 23 crucial problems for mathematics to solve in the next century. These problems, now known eponymously as the Hilbert problems, dominated mathematical research throughout the 20th century.
The result is that slightly more than a century later 10 of the 23 problems have been solved to the satisfaction of a consensus, the others being partially solved, unsolved, or now considered unsolvable.
When I ask Columbia University mathematician Maria Chudnovsky, who works in a very specialized area called Perfect Graph Theory (which by the way has nothing to do with the graphs you and I are familiar with), she says that a question is interesting if it leads somewhere and is connected to other questions.
The desire to measure more accurately drives technology and innovation, resulting in new microscopes with more resolution, new colliders with more smashing power, new detectors with more capturing capability, new telescopes with more reach.
This strategy, of using smaller questions to ask larger ones, is, if not particular to science, one of its foundations. In scientific parlance this is called using a “model system.”
“What are you thinking about these days, Albert?” “What are the problems you are working on?” “What are the new questions that physicists are asking now that the universe is relativistic, whatever that means?” “What are the loose ends?”
Here are some examples of what have turned out to be good questions in my class:
- Do you think things are unknowable in your field? What?
- What are the current technological limits in your work? Can you see solutions?
- Where are you currently stuck?
- How do you talk about what you don’t know?
- What was the main thrust of your last grant proposal?
- What will be the main thrust of your next grant proposal?
- Is there something you would like to work on knowing but can’t? Because of technical limitations? Money, manpower?
- What was the state of ignorance in your field 10, 15, or 25 years ago, and how has that changed?
- Are there data from other labs that don’t agree with yours?
- How often do you guess?
- Are you often surprised? When?
- Do things come undone?
- What questions are you generating?
- What ignorance are you generating?
This led Pfungst to the realization that Hans had to be getting some cue from the person, and by careful observation—of the person, not the horse—he found that people would tense the muscles of their body and face at the beginning of Hans’s answer and release the tension when he arrived at the correct hoof tap.
The method that scientists use to control for these Clever Hans effects, as they have come to be known, is the “double blind.” That is, either the experimenter cannot know the correct answer or she cannot be available to the subject. The experimenter herself cannot be trusted to hide the correct answer because she will give it away involuntarily.
In one of the great stories of serendipity in science, precisely this noise was discovered by two scientists at Bell Labs while they were trying to get rid of a troubling and persistent hum that plagued a new radio-telescope instrument they were testing. That hum was not a fault in the instrument but the cosmic background radiation left behind by the Big Bang:—a 13.7-billion-year-old fossil. What this fossil shows is a bit curious and leads to a conundrum in cosmology. The universal hum, the cosmic background radiation (CMB), is nearly the same in all directions.
Using perhaps the polar opposite of the theoretical approach, he nonetheless has come to a similar conclusion that motor systems are the improbable key to understanding how the brain works. Two of his mantras are that “Plants don’t have nervous systems, because they don’t go anywhere” and “The reason to exist is to act.”
The answer, or at least the partial answer, is that Parkinson’s patients, those in the earlier less debilitating stages of the disease, believe that they are moving at the correct speed; they are simply wrong about that. If you yell “Fire!” in a room full of these type of Parkinson’s patients, they will beat you to the door. They can move just fine; they “choose” to go slowly. But why have they made this choice? You might think you could just ask them, but that won’t work. They are unable to self-report on this. While they recognize they are moving slower than other people, and may even be embarrassed by it, they don’t really know why they are moving more slowly than they could, so you can’t just ask them. This is an example of why the brain is so poor an instrument for understanding how it works—at least through introspection. You can think about it all you want, and you will never get access to what your brain is doing computationally at any given moment. You only have access to a result, a behavior or a perception, that could have been reached in numerous indistinguishable ways. By the way, you are no more able to self-report why you have chosen the speed at which you walk or grasp for objects than a Parkinson’s patient.
Clearly what we need is a crash course in citizen science—a way to humanize science so that it can be both appreciated and judged by an informed citizenry. Aggregating facts is useless if you don’t have a context to interpret them, and this is even true for most scientists when faced with information outside their particular field of expertise.