Clarifying Scientific Concepts Part 13: Pseudoscience

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
• Seeks simple and robust methods
• Leverages probabilistic reasoning and acknowledges 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.

• Pseudoscience