A hypothesis is a possible explanation of something–an explanation that one has some reason to think may be correct. in the previous section, Theodor Bischoff’s test of the hypothesis that consciousness requires a physical connection between the brain and the rest of the nervous system was an early example of a scientific approach to the study of consciousness. Bischoff tested this hypothesis by attempting (and failing) to get the head of a guillotined prisoner to respond. Although gruesome, Bischoff’s study was scientific because it conformed to the following two scientific rules or precepts.
Scientific Precept #1: Claims must be tested empirically. Although you might not accept that Bischoff’s experiment was likely to provide adequate support for the hypothesis, his attempt to find supporting evidence illustrates the first major precept of science: claims must be tested by making direct observations of physical events. Empiricism is the doctrine that knowledge can be derived only from sensory experience — that is, from direct observations and measurements of events. Let’s say that someone claims that there are 23 students in a classroom. An empirical test of this claim must include a direct count. We would question the original claim if we counted a different number of people, say 24 students. We could not, however, immediately reject the original claim after just one count because, even though an empirical test was performed, the observer’s count may have been wrong: some people may have been hiding, the observer’s attention may have wavered, etc. Thus, empiricism also requires that observations be checked and rechecked to make sure they are accurate. Furthermore, regardless of how much care is taken, it still is possible that our observations and measurements are inaccurate. Nevertheless, the more times that similar observations are made, the greater the confidence we have that the results are accurate.
Scientific Precept #2: Claims are doubted until adequate supporting evidence has been collected. A person using a scientific approach does not accept a claim simply because someone says it’s true, even if that person says he is “absolutely certain.” You know that people may feel certain about something but still be wrong. If it’s important to know precisely how many students there are in a classroom, it would be unwise to accept without question the claim that the room contains 23 students. This illustrates a second precept of modern science: we must be skeptical of claims that have not be carefully tested. Skepticism is the doctrine that a claim should be doubted until adequate supporting evidence has been collected. This generally means that the claim has been tested by independent evaluators, most of whom have concluded that it is likely to be true. Once the evidence is considered adequate, the claim is accepted as “likely to be true.” Nevertheless, new evidence that conflicts with the claim should lead us to rethink whether the claim actually is true or not (see the example below).
A proper scientific approach must include both skepticism and empiricism (for more on skepticism and empiricism, see my blog post here). In science, a claim usually must be tested empirically a number of times by different researchers working in different places and with different assumptions about what the likely results will be. The more that this is done, the more confident we can be that the claim is likely to be true. For example, the geneticist Peter St. George-Hyslop has, for years, looked for genes associated with the development of Alzheimer’s Disorder. In talking about the recent discovery of a gene thought to be a cause of the disorder, St. George-Hyslop referred to the “Eureka (Aha!) Moment” — the point at which the increasing accumulation of supporting evidence finally tips a person over to accepting a claim as likely to be true:
The “Aha!” moment happens to different people at different times…. We are aware of little bits of data as they come out that say, “Yes, it’s real,” but not very strongly, so what you get is not really a eureka moment but something that is incremental. It starts out as “Uh-huh, but it’s probably a fluke,” to “Maybe it’s not a fluke,” to “This could be real, let me see what I can do to make it go away,” to “Well, it seems pretty robust, but there are still problems,” to “We’ve taken this as far as we can and we concede that there are many things to do on this story, but before we do too much more it needs to be put in the hands of some other people, with totally different data sets and totally different ways of analyzing things. and see if they get the same results.” (quoted in Halpern, 2005)
As you can see, a skeptical empiricist takes his or her time before finally accepting or rejecting a new claim. In the quoted passage, St. George-Hyslop mentioned several steps in this process that can be divided into three stages:
- Repeat initial observations more than once. This is because the initial observations may have occurred simply by chance or have been mistaken. For example, flipping a coin five times and getting five heads in a row suggests that the coin may be unfair. On the other hand, the results could have been a “fluke”: they could have occurred by chance. The best way to see if this is true is to flip the coin five more times in a row. If you get four heads and one tail, this provides a better reason to think that the coin really is unfair. If you need to be as certain as you can that the coin is unfair, then you’ll want to repeat these observations many times. If you get similar results each time, the coin probably really is unfair.
- Attempt to falsify the claim. This means that you try to determine if there is something else going on that makes the claim appear to be true when it actually is false. For example, perhaps you get a larger percentage of heads than tails because of the way you flip coins. How might you test this? You might flip other coins to see if you get the same result: most coins should come up heads 50% of the time; but if you don’t get this result with other coins, then it seems more likely that you are the source of the bias, not the coins. Let’s say that, when you flip other coins, you get about 50% heads. This suggests that your observations with the first coin probably had nothing to do with the way you flipped it, which supports the claim that the coin really is unfair.
- Get others to repeat the observations and attempt to falsify the claim. If the accuracy of the claim is important enough, then other people — preferably in different locations and with different attitudes about the possible truth of the claim — need to flip the coin over and over again. If they get results similar to yours, then you can feel confident that the claim is very likely to be true. On the other hand, if some or all of them get about 50% heads, then it is much more likely that there was something specific to you or to your location that caused the coin to incorrectly appear to be unfair. In this case, unknown factors (causes) probably made the claim appear to be correct when it actually was not. If the claim is important enough, you would begin to look for these other factors.
Going back to the example involving the number of students in a classroom, let’s say that, after performing 1000 counts, the “skeptical empiricist” got the following results:
# of Students
# of Counts
Table 1. The number of times that different numbers of students were counted (out of 1000 counts)
Given these results, the best conclusion to make is that we should accept the claim as virtually certain that there are 23 students in the classroom (and that mistakes probably had been made on nine of the counts).
Nevertheless, regardless of the number of times that 23 people are counted, a skeptical empiricist should never say that “the claim that 23 people are in the room has been proved.” Why? Because there is a very small possibility that a mistake was made each time she counted 23 people. Before you dismiss skeptical empiricists as obviously insane (“How many times do you need to repeat the count before you’ll agree that there are 23 people in this room?!?!”), you should read the next section. It is a very instructive example from the history of human-genetics research.
In the following video, the physicist, Richard Feynman, answers the question “what is science?” in a 1964 lecture.
NOTE TO MYSELF: SUGGEST INTERACTIVE COIN-TOSS ACTIVITY HERE.
Study Questions for Section 1-2
Note: As stated in the first section, it is important to answer the study questions in your own words. This is because writing answers in your own words requires that you give meaning to the material, which helps you to understand it better.
- If you tried to start your car and nothing happened, what would be a good hypothesis to test first?
- How would you define empiricism in your own words?
- What is an example from your own life of a time when you were being empirical when trying to solve a problem or answer a question?
- How would you define skepticism in your own words?
- What is an example from your own life of a time when you were being skeptical of a claim made by someone else? Why were you skeptical of the claim?
- Why should a skeptical empiricist never conclude that a claim has been proved to be true?
Practice Quiz for Section 1-2
Click HERE to find the details about the articles, books, etc., referred to in this section.