Clarifying Scientific Concepts
There is a lot of confusion, propagated by various media sources, around fundamental scientific concepts and terminology. Colloquial uses of terms such as "theory" or "hypothesis" tend to distort the actual meanings of these terms. Scientific concepts can become trivialized as well; "your 'theory' is just as good as my 'theory'". I want to clarify some of this terminology because constant misuse simply confuses everyone, making it harder to distinguish between competing sources of information on social media platforms.
Science and Pseudo-Science
Demarcating science from non-science is quite difficult. There are obvious exemplars of pseudo-science and many prototypical examples of real science but there haven't been any necessary and sufficient conditions identified that can be used to categorize any particular example into a clearly defined bucket. Nevertheless, there are common features shared across many disciplines we deem scientific. These attributes form clusters; examples on the peripheries become harder to classify because they share features with canonical examples of pseudoscience. If you are familiar with Wittgenstein's notion of family resemblance then this might make sense to you. You can also think about it in terms of network clustering. In the diagram below, you can think of the edges between nodes as defining some common relation and distance measuring some degree of closeness.
A two dimensional view might look something like this:
In the middle of the large cluster we might consider a discipline like physics and towards the periphery of the cluster we could consider something like psychology, sociology, and economics. The green cluster could represent a pseudo-scientific category containing things like intelligent design. The thing to note with both visualizations is that there aren't a global set of definable features that can distinguish any two disciplines. We cannot construct a list containing all of the essential features that could exclude non-sciences without running into problems. For example, a pillar of modern sciences is the experiment. Theoretical physics, however, typically does not conduct experiments. Does this mean we exclude it from being a science? That would be absurd. Similarly, Geological sciences typically do not engage in any a-priori theorizing. A common practice of modern science is establishing some sort of theory to explain observations. Does this mean geology is not a science? That too, would be absurd.
These examples immediately make it obvious that, when discussing what is science, we have to consider that "science" is a term referring to a broad class of related types of disciplines. Something can be more or less scientific, exemplifying the fact that "science" is somewhat of a graded concept. This implies that there are qualities or properties by which we can evaluate any particular knowledge claim as science or not. I've shifted away from classifying disciplines as a whole to individual claims because we might run into the same problem when attempting to classify an entire discipline as scientific. For example, there are many knowledge claims coming out of the psychological literature that do not exhibit properties we consider scientific. It's also possible that for any given knowledge claim, some of the properties might not be exhibited. Nevertheless, this does not imply that all claims coming out of psychology are pseudo-scientific. This is also true of some of the more canonical examples of science. Therefore, we must consider the rate at which claims originating from any discipline exhibit scientific qualities. This will prevent us from a-prior labeling knowledge claims as pseudo-scientific simply based on the discipline they come from.
Here is a list of some qualities I think that can be used when considering whether a claim is scientific. I do not claim this list to be exhaustive. Also, the order does not matter at this point. This is not to say that all qualities are of equal importance. I think that would be false.
- Makes predictions or retrodictions
- Is testable
- Is replicable
- Systematically records observations
- Capable of verifiability and validation
- Acknowledges the boundaries of its explanatory breadth
- Self corrective and reflective
- Maintains are fair degree of precision and clarity with its terminology
- Is falsifiable
- Has an empirical basis
- Is reproducible
- Is internally coherent and logically consistent
- Strives for impartiality and objectivity
- Has a sufficient degree of generalizability
- Can be subject to scrutiny within a broader community of peer review
- Uses concepts that can be measured or quantified
- Subject to revision in light of new findings
- Is transparent with it's methodology
- Is rigorous
- Seeks disconfirmation along with confirmation
- Is communicable
- Seeks to provide causal explanations
- Highly critical during design and analysis phase
- Critically assess methods, assumptions, and interpretations of results
- Uses mathematical models and simulation methods
- Is simple and robust
- Is probabilistic and should acknowledge the uncertainty of it's conclusions
- Does not rely on authority unless it's a claim that is taken to be true within the community
- Considers alternative hypotheses
- Seeks convergent validity through multiple information sources and different methods
There are probably more I am not considering but I think this is not a bad start. I am partial to mathematical modeling but acknowledge that there are disciplines such as Anthropology that are scientific but might not emphasize mathematical modeling. Also, not all knowledge claims must come from a mathematical model. Nevertheless, scientific disciplines tend to use models because they help us check our assumptions against reality. Another consideration is that a claim might not be testable at this point in time, but technological innovations in the future can make it become testable. The fact that something isn't immediately testable due to technical constraints does not make it unscientific. I would say that it's unscientific if, in principle, it cannot be tested. If there is no conceivable way to test the claim, then it is not testable. Again, these are qualities that claims should strive for if we want to consider them scientific.
Throughout the rest of this blog post I'll touch on some of these concepts. I just wanted to initially get this out of the way because many people are confused about which claims are genuinely scientific.
Theories and Scientific Theories
I am not going to focus on any particular theory. Rather, I want to distinguish the concept from related concepts and show instances where information sources bastardize the term.
Theory and Observation
Theoretical Virtues
What counts as a "good" explanation in scientific inquiry? Why is simplicity considered desirable? We will look at an attempt to systematize theoretical virtues.
Evidence and Empirical Evidence
What distinguishes a detective who uses evidence from the scientist who uses "empirical evidence" when engaged in empirical research?
Scientific Measurement
In terms of "what is a science", if a claim is not measurable in principle, I think this significantly reduces the ability to call it "scientific".
Scientific Representation and Models in Science
How do scientists represent the target system they are studying?
Analysis
This is a mental activity at the core of all scientific research.
Mechanisms in Science
The act of identifying mechanistic cause and effect relations.
Scientific and Mathematical Modeling
Models are quite frequently used in science and might be one of the most fundamental features.
Data and Statistics
Simply put, this is also a cornerstone of modern science. We will look at the Philosophy of Statistics, Bayesian Epistemology, and other interpretations of probability.
Scientific Objectivity
Whether or not the practice of science can be truly objective is not the purpose of this section. Rather, I'd like to discuss various methods it uses to maintain alignment with the standard, and how built in mechanisms self correct when deviations from the ideal occur.
Scientific Discovery
What constitutes a scientific discovery? With the constant barrage of "new discoveries" flooding the media, how do we make sense of what is going on?
Scientific Explanation
What does it mean when someone says "Science has explained something"?
Scientific Reduction
What is the role of reduction in explanation? When larger systems are explained in terms of something more fundamental, what exactly are we accomplishing?
The Role of Hypothesizing and Confirmation
"Hypothesis" is a frequently bastardized term. Confirmation, and its counterpart disconfirmation, are also incredibly misunderstood by the general public.
Computer Simulation and Indirect Methods of Discovery
The advent and proliferation of computing, programming languages, and software has undoubtedly had a significant impact on the way science is carried out. Simulation modeling is now quite indispensable within the toolkit of the modern scientist. I would go so far to say that you simply cannot do modern science without the aid of a computer in one form or another.
Scientific Research and Big Data
A corollary to the prior section, data driven methods are also becoming quite prolific in many domains. The general public is grossly incompetent when it comes to understanding the nuances of collection, storage, governance, processing, transmission, provenance, and utility of data for inquiry. And yet, this has been a massive pillar in many of the advances in the past few decades. People generally do not have a clue why big data is so valuable, what can be done with it, and to whom. They are unaware that their digital footprint can be used to yield a fairly accurate picture of their beliefs and preferences, which can then be used for predictive analytics. They are also unaware of the value it provides to scientific researchers.
Scientific Underdetermination, Fallibilism, and Uncertainty
Many people are interested in science because of a "debunking" attitude rather than one of genuine curiosity. Because of this, they expect some sort of infallibility, so they can use conclusions from science to beat their opponent in an argument. They then become frustrated when they find out something they held to be true should have been tentative at best. Science is always in the process of revising itself and really is not concerned with the platonic conception of truth.
Scientific Pluralism
Given all of the above, it should be clear that science is inherently pluralistic.
Scientism
Can someone dogmatically adhere to science at the expense of other lines of inquiry? We will look at Six Signs of Scientism to answer this question.
Conclusion: The Richard Feynman Lectures
I've always found Feynman to be an excellent science communicator. So to wrap this up, lets have a look at his famous lecture on the scientific method:
Richard Feynman on Scientific Method (1964) | After noise reduction
Now, I'm going to discuss how we would look for a new law. In general, we look for a new law by the following process. First, we guess it.
Then we-- well, don't laugh. That's really true. Then we compute the consequences of the guess to see what-- if this is right, if this law that we guessed is right, we see what it would imply, and then we compare those computation results to nature. Or we say, compare to experiment or experience. Compare it directly with observation to see if it works.
If it disagrees with experiment, it's wrong. And that simple statement is the key to science. It doesn't make a difference how beautiful your guess is. It doesn't make a difference how smart you are, who made the guess, or what his name is, if it disagrees with experiment, it's wrong. That's all there is to it.
It's therefore not unscientific to take a guess, although many people who are not in science think it is. For instance, I had a conversation about flying saucers some years ago with laymen.
Because I'm scientific. I know all about flying saucers. So I said, I don't think there are flying saucers. So the other-- my antagonist said, is it impossible that there are flying saucers? Can you prove that it's impossible? I said, no, I can't prove it's impossible. It's just very unlikely.
That, they say, you are very unscientific. If you can't prove an impossible, then why-- how can you say it's likely, that it's unlikely? Well, that's the way-- that it is scientific. It is scientific only to say what's more likely and less likely, and not to be proving all the time possible and impossible.
To define what I mean, I finally said to them, listen, I mean that from my knowledge of the world that I see around me, I think that it is much more likely that the reports of flying saucers are the result of the known irrational characteristics of terrestrial intelligence, rather than the unknown rational effort of extraterrestrial intelligence.
It's just more likely, that's all. And it's a good guess. And we always try to guess the most likely explanation, keeping in the back of the mind the fact that if it doesn't work, then we must discuss the other possibilities.
There was, for instance, for a while a phenomenon we called superconductivity. It still is a phenomenon, which is that metals conducts electricity without resistance at low temperatures. And it was not at first obvious that this was a consequence of the known laws with these particles. But it turns out that it has been thought through carefully enough, and it's seen, in fact, to be a consequence of known laws.
There are other phenomena, such as extrasensory perception, which cannot be explained by this known knowledge of physics here. And it is interesting, however, that that phenomenon has not been well established, and--
--that we cannot guarantee that it's there. So if it could be demonstrated, of course, that would prove that the physics is incomplete. And therefore, it's extremely interesting to physicists whether it's right or wrong. And many, many experiments exist which show it doesn't work.
The same goes for astrological influences. If that were true, that the stars could affect the day that it was good to go to the dentist, then-- it's in America we have that kind of astrology-- then it would be wrong. The physics theory would be wrong, because there's no mechanism understandable in principle from these things that would make it go. And that's the reason that there's some skepticism among scientists with regard to those ideas.
Now, you see, of course, that with this method, we can disprove any definite theory. We have a definite theory, a real guess from which you can really compute consequences which could be compared to experiment, and in principle, we can get rid of any theory. You can always prove any definite theory wrong. Notice, however, we never prove it right.
Suppose that you invent a good guess, calculate the consequences, and discover every consequence that you calculate agrees with the experiment. Your theory is then right? No, it is simply not proved wrong. Because in the future, there could be a wider range of experiments, you compute a wider range of consequences, and you may discover, then, that the thing is wrong.
That's why laws like Newton's laws for the motion of planets lasts such a long time. He guessed the law of gravitation, calculated all kinds of consequences for the solar system and so on, compared them to experiment, and it took several hundred years before the slight error of the motion of Mercury was developed.
During all that time, the theory had been failed to be proved wrong, and could be taken to be temporarily right. But it can never be proved right, because tomorrow's experiment may succeed in proving what you thought was right wrong. So we never are right. We can only be sure we're wrong. However, it's rather remarkable that we can last so long. I mean, have some idea which will last so long.
I must also point out to you that you cannot prove a vague theory wrong. If the guess that you make is poorly expressed and rather vague, and the method that you used for figuring out the consequences is rather a little vague-- you're not sure. You say, I think everything is because it's all due to [INAUDIBLE], and [INAUDIBLE] do this and that, more or less. So I can sort of explain how this works. Then you see that that theory is good, because it can't be proved wrong.
If the process of computing the consequences is indefinite, then with a little skill, any experimental result can be made to look like-- or an expected consequence. You're probably familiar with that in other fields. For example, A hates his mother. The reason is, of course, because she didn't caress him or love him enough when he was a child. Actually, if you investigate, you find out that as a matter of fact, she did love him very much, and everything was all right. Well, then, it's because she was overindulgent when he was [INAUDIBLE]. So by having a vague theory--
--it's possible to get either result.
Now, wait. Now, the cure for this one is the following. It would be possible to say, if it were possible to state ahead of time how much love is not enough, and how much love is overindulgent exactly, and then there would be a perfectly legitimate theory against which you can make tests. It is usually said when this is pointed out how much love is and so on, oh, you're dealing with psychological matters, and things can't be defined so precisely. Yes, but then you can't claim to know anything about it.
Now, I want to concentrate for now on-- because I'm a theoretical physicist, and more delighted with this end of the problem-- as to what goes-- how do you make the guesses? Now, it's strictly, as I said before, not of any importance where the guess comes from. It's only important that it should agree with experiment, and that it should be as definite as possible.
But, you say, that is very simple. We set up a machine-- a great computing machine-- which has a random wheel in it that makes a succession of guesses. And each time it guesses a hypotheses about how nature should work, computes immediately the consequences, and makes a comparison to a list of experimental results it has at the other end. In other words, guessing is a dumb man's job.
Actually, it's quite the opposite, and I will try to explain why.
The first problem is how to start. You see how I start? I'll start with all the known principles. But the principles that are all known are inconsistent with each other, so something has to be removed. So we get a lot of letters from people. We're always getting letters from people who are insisting that we ought to make holes in our guesses as follows. You see, you make a hole to make room for a new guess.
Somebody says, do you know, people always say space is continuous. But how do you know when you get to a small enough dimension that there really are enough points in between? It isn't just a lot of dots separated by a little distance.
Or they say, you know those quantum mechanical amplitudes you told me about? They're so complicated and absurd. What makes you think those are right? Maybe they aren't right. I get a lot of letters with such content.
But I must say that such remarks are perfectly obvious and are perfectly clear to anybody who is working on this problem, and it doesn't do any good to point this out. The problem is not what might be wrong, but what might be substituted precisely in place of it. If you say anything precise, for example, in the case of a continuous space. Suppose the precise composition is that space really consists of a series of dots only, and the space between them doesn't mean anything, and the dots are in a cubic array, then we can prove that immediately is wrong. That doesn't work.
You see, the problem is not to make-- to change, or to say something might be wrong, but to replace it by something. And that is not so easy. As soon as any real definite idea is substituted, it becomes almost immediately apparent that it doesn't work.
Secondly, there's an infinite number of possibilities of these simple types. It's something like this. You're sitting, working very hard. You work for a long time trying to open a safe. And some Joe comes along who hasn't-- doesn't know anything about what you're doing or anything, except that you're trying to open a safe.
He says, you know, why don't you try the combination 10, 20, 30? Because you're busy. You tried a lot of things. Maybe you already tried 10, 20, 30. Maybe you know that the middle number is already 32 and not 20. Maybe you know that as a matter of fact, this is a five-digit combination. There we go.
So these letters don't do any good, and so please don't send me any letters trying to tell me how the thing is going to work. I read them to make sure--
--that I haven't already thought of that. But it takes too long to answer them, because they're usually in the class, try 10, 20, 30.
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