Skip to main content
Humanities LibreTexts

15.2.5: A Cautious Approach with an Open Mind

  • Page ID
    36294
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

    \( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\)

    ( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\)

    \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

    \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\)

    \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

    \( \newcommand{\Span}{\mathrm{span}}\)

    \( \newcommand{\id}{\mathrm{id}}\)

    \( \newcommand{\Span}{\mathrm{span}}\)

    \( \newcommand{\kernel}{\mathrm{null}\,}\)

    \( \newcommand{\range}{\mathrm{range}\,}\)

    \( \newcommand{\RealPart}{\mathrm{Re}}\)

    \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

    \( \newcommand{\Argument}{\mathrm{Arg}}\)

    \( \newcommand{\norm}[1]{\| #1 \|}\)

    \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

    \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\)

    \( \newcommand{\vectorA}[1]{\vec{#1}}      % arrow\)

    \( \newcommand{\vectorAt}[1]{\vec{\text{#1}}}      % arrow\)

    \( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vectorC}[1]{\textbf{#1}} \)

    \( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \)

    \( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \)

    \( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \)

    \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

    The scientific attitude is also a cautious one. If you are a good scientist, you will worry initially that perhaps your surprising new evidence shows only that something is wrong somewhere. You won't claim to have revolutionized science until you’ve made sure that the error isn't in the faulty operation of your own measuring apparatus. If a change of beliefs is needed, you will try to find a change with minimal repercussions; you won't recommend throwing out a cherished fundamental law when you can just as easily revise it by changing that constant from 23 to 24 so that it is consistent with all data, given the margin of error in the experiments that produced the data. The cautious scientific attitude recognizes these principles: Don't make a broader claim than the evidence warrants, and don't reject strongly held beliefs unless the evidence is very strong. In short, don't be wildly speculative.

    Scientists are supposed to think up reasonable explanations, but what counts as a reasonable explanation? An explanation that conflicts with other fundamental beliefs that science has established is initially presumed to be unreasonable, and any scientist who proposes such an explanation accepts a heavier than usual burden of proof. A related principle of good explanation is to not offer supernatural explanations until it is clear that more ordinary, natural explanations won't work.

    Exercise \(\PageIndex{1}\)

    What is the main mistake in the following reasoning?

    Yes, I've read the health warnings on those cigarette packs, but my uncle smokes, and he says he's never been sick a day in his life, so I'm going to continue smoking regularly.

    a. overemphasizing anecdotal evidence
    b. not having a cautious attitude about scientific revolutions
    c. not appreciating the need for independent verification
    d. overemphasizing unrepeatable phenomena
    e. pseudoprecision

    Answer

    Answer (a). The anecdote from the uncle should be given less weight than the warning on the pack. The warning came from statistical tests covering a wide variety of smokers.

    In assessing potential new beliefs─candidates for new knowledge─ scientists actively use what they already believe. They don't come into a new situation with a mental blank. When scientists hear a report of a ghost sighting in Amityville, they will say that the report is unlikely to be true. The basis for this probability assessment is that everything else in the scientists' experience points to there being no ghosts anywhere, and so not in Amityville, either. Because of this background of prior beliefs, a scientist will say it is more probable that the reporter of the Amityville ghost story is confused or lying than that the report is correct. Better evidence, such as multiple reports or a photograph, may prompt a scientist to actually check out the report, if Amityville isn't too far away or if someone provides travel expenses.

    Good scientists don't approach new data with the self-assurance that nothing will upset their current beliefs. Scientists are cautious, but they are also open to new information, and they don't suppress counterevidence, relevant evidence that weighs against their accepted beliefs. They do search for what is new; finding it is how they get to be famous. So the scientific attitude requires a delicate balance.

    Discovering Causes, Creating Explanations, and Solving Problems

    Contrary to what Francis Bacon recommended in 1600, clearing your head of the B.S. and viewing nature with an open mind is not a reliable way to discover the causes behind what you see. Unfortunately, there is no error-free way. Nevertheless, the discovery process is not completely chaotic. There are rules of thumb. For example, to discover a solution to a problem, scientists can often use a simple principle: Divide the problem into manageable components. This principle was used by the space program in solving the problem of how to travel to the moon. The manager of the moon program parceled out the work. Some scientists and engineers concentrated on creating a more powerful rocket engine; others worked on how to jettison the heavy, empty lower stages of the rocket; others designed the communication link between the Earth and the spaceship's computer; and still others created the robot mechanisms that could carry out the computer's commands during flight and after landing on the moon. In short: Divide and conquer.

    Another principle of scientific discovery says to assume that similar effects are likely to have similar causes. The history of medicine contains many examples of using this principle effectively. Several times before 1847, Doctor Ignaz Semmelweis of the General Hospital in Vienna, Austria had tried but failed to explain the alarming death rate of so many women who gave birth in his maternity ward. They were dying of puerperal fever, a disease with gruesome symptoms: pus discharges, inflammation throughout the body, chills, fever, delirious ravings. One day, a Dr. Kolletschka, who worked with Semmelweis, was performing an autopsy on a puerperal fever victim when a clumsy medical student nicked Kolletschka's arm with a scalpel. A few days later Kolletschka died with the same symptoms as the women who died of puerperal fever. Semmelweis suspected a connection. Perhaps these were similar effects due to a similar cause. And perhaps whatever entered Kolletschka via the student's scalpel was also being accidentally introduced into the women during delivery. Then Semmelweis suddenly remembered that the doctors who delivered the babies often came straight from autopsies of women who had died of puerperal fever. Maybe they were bringing infectious material with them and it somehow entered the bodies of women during delivery of their babies. Semmelweis's suggestion of blaming the doctors was politically radical for his day, but he was in fact correct that this disease, which we now call blood poisoning, was caused by doctors transferring infectious matter from the dead mothers on the dissecting tables to the living mothers in the delivery rooms. Semmelweis's solution was straightforward. Doctors must be required to wash their hands in disinfectant before delivering babies. That is one reason that today doctors wash their hands between visits to patients.

    A good method to use when trying to find an explanation of some phenomenon is to look for the key, relevant difference between situations in which the phenomenon occurs and situations in which it doesn't. Semmelweis used this method of discovery. You can use the same method to make discoveries about yourself. Suppose you were nauseous, then you vomited. You want to know why. The first thing to do is to check whether prior to your symptoms you ate something you'd never eaten before. If you discover there was something, it is likely to be the cause. Did you get those symptoms after eating raw tuna, but not after eating other foods? If so, you have a potentially correct cause of your problem. This sort of detective work is encoded in the box below.

    The rules of thumb we have just discussed can help guide scientific guessing about what causes what. There are a few other rules, some of which are specific to the kind of problem being worked on. Guessing is only the first stage of the discovery process. Before the guess can properly be called a discovery, it needs to be confirmed. This is the second stage, and one that is more systematic than the first, as we shall see.


    This page titled 15.2.5: A Cautious Approach with an Open Mind is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by Bradley H. Dowden.

    • Was this article helpful?