From the moment humans came to realize if they didn’t eat they would die (or at least be hungry), the law of cause and effect became a reality. Since then, people have been applying this law to the world around them to explain why things happen. One way that people try to apply cause and effect is by observing things that happen sequentially and assuming that whatever came first caused what came next. While this might be true sometimes, this reasoning is called faulty causality.
Faulty Causality Definition
Faulty causality is the inaccurate assumption that one thing caused another to happen, based solely on the fact that one came before the other. Also translated from the Latin term post hoc, ergo propter hoc, which means “after this, therefore because of this,” faulty causality is a logical fallacy.
A logical fallacy, also known as a rhetorical fallacy, is a failure in reasoning which results in an unsound argument. There are many kinds of logical fallacies, but the result of each is flawed reasoning. Even if the outcome of a line of reasoning is accurate, the argument is invalid if it contains a logical fallacy somewhere along the way.
The argument is not always false—sometimes there is a positive causal relationship—but the argument's reasoning is faulty. Faulty causality is one of a few false cause, or questionable cause, fallacies. This is a group of rhetorical or logical fallacies that contain an error in the causal connection between two or more things. The others are:
Reverse causation, which is the incorrect belief or assumption that X causes Y when in reality, Y causes X.
Confounding causation, also known as simultaneity and cum hoc, ergo propter hoc (meaning “with this, therefore because of this”). This is when two or more things happen at the same, time and someone believes one of them is causing the other(s) to happen.
In all cases of questionable cause, people tend to notice that two things are connected in some way, and they jump to the conclusion that it must be causation. The truth is that, more often than not, these things simply share a correlation.
Correlation is a relationship where two things share a connection and move in coordination with each other.
An example of correlation is the relationship between time spent watching TV and exam scores. As students spend more time watching TV, they tend to receive lower exam scores. This doesn’t mean watching TV causes poor academic performance.
You may have heard the term correlation does not imply causation. All this means is that a connection does not equal causation; simply because two things are connected doesn’t mean one causes the other to happen. Correlation must be tested in specific, rigorous ways to prove causation. You can’t simply say something was the cause of something else without significant proof.
An example of faulty causality is hearing thunder in the distance, noticing it started to rain, and assuming that thunder causes rain. Most people understand that the relationship between thunder and rain is not a causal one, but faulty causality is not always that easy to spot.
Faulty Causality Examples
Here are some more examples of the use of faulty causality to explain things that are correlated. Notice how each argument sounds logical, and how difficult it might be to oppose it unless you attack the questionable causal connection.
Many heroin addicts used marijuana before they tried heroin. Clearly, marijuana causes heroin abuse.
This argument sees the connection between marijuana and heroin use and blames marijuana for heroin addiction. However, isn’t it possible that there are more factors at play? Isn’t it possible that the same population would still try heroin even if marijuana wasn’t available?
Daphne Du Maurier's Gothic novel, Rebecca (1938), is a ghost story without a real ghost. The memory of the deceased Rebecca haunts the lives of her husband, Maxim, and his new wife.
Rebecca has won... Rebecca has kept us apart all this time. (Ch. 17)
Maxim blames the failure of his new marriage on his dead wife. While it's true the memory of her caused strife, is it logical or fair to blame their downward spiral on Rebecca? Or is it possible that they made some mistakes with regard to communication and openness? This is a case of faulty causality; it's easier to blame a dead woman for causing his marriage to fail rather than to examine his own actions and shortcomings.
Effects of Faulty Causality
Logical fallacies often appear correct or appeal to people’s desire for a particular conclusion to be right. As a result, these errors in logic can seduce people into believing they are true. Faulty causality is no exception.
Fig. 1 - It wouldn't be unusual to hear an example of faulty causality in a variety of professional settings.
Questionable cause fallacies are known to generate superstitions among people.
A superstition is a belief in supernatural causation leading to real-world consequences.
You may be familiar with a brand of superstition that says, “If I _______, then _______ will happen.”
Whenever I wear my lucky socks, I pass my exams.
The belief that a particular action—in this case, wearing a pair of socks—will cause something unrelated to happen is a case of faulty causation. There is no causal connection between these two things, but people appreciate a causal formula for things they can’t easily control.
Another consequence of faulty causality is simply arriving at incorrect conclusions. In the example with the lucky socks, if the student relies solely on wearing the socks to pass an exam—instead of, say, diligent study—they are likely to fail the exam. Their conclusion (i.e., wear the socks, pass the exam) is incorrect.
The medical community can be guilty of questionable causal logic at times. This is because medicine is constantly looking for the causes of health problems, and in an effort to bring relief to people, some medical professionals have been known to claim a causal relationship where there was none. This results in misdiagnoses, which can have serious implications for patients.
In The Yellow Wallpaper (1892) by Charlotte Perkins Gilman, the protagonist, Jane, is diagnosed by her physician-husband as suffering a “slight hysteria.” He prescribes a rest cure, which means she is isolated in a single room of a house with no social interaction. In reality, she was likely experiencing postpartum depression but is driven truly mad by her husband’s “cure.”
This is an example of misdiagnosis due to a false causal assumption (and outdated medical methods). John, the husband in The Yellow Wallpaper, believes a mild hysteria is the cause of his wife’s anxiety, and she will be cured with rest. Because of his failure to properly identify the true cause of her depression, he drives her to insanity.
Faulty Causal Reasoning
Faulty causal reasoning typically starts with the desire to find a reason why things happen; most people want to feel like they have the answers to the question, “Why?”
In the search to identify an answer, someone might look to whatever happened just prior to the effect to provide a cause.
When two events only have time as a common factor, there is no causal connection.
The truth is that whenever event A happens just before event B, this is a good starting place to begin investigating a causal relationship. However, that’s all it is—a starting place. The average person doesn’t have enough time or data to conduct the necessary research, which is why many people fall back on faulty causal reasoning as a rhetorical crutch. “It can’t be coincidence,” they might say. It’s easier to deny the possibility of a coincidence than to pursue the course of proving causation.
This is a case of faulty inductive reasoning.
Inductive reasoning is the process of forming a broad generalization from specific observations.
Inductive reasoning tries to establish generalized concepts based on a limited body of evidence. People use inductive reasoning all the time without realizing it. Faulty causal reasoning is a misstep in induction.
If you wake up to wet streets one morning, you might assume that overnight rain caused the pavement to be wet. This is inductive reasoning. However, it’s also possible that the city came through and cleaned the streets or a fire hydrant burst.
Difference Between Faulty Analogy and Faulty Causality
Another mistake in inductive reasoning is faulty analogy. While faulty causality believes that A causes B simply because it follows A, faulty analogy is a different type of logical fallacy.
Faulty analogy is a false connection between two things, which makes the mistake that they are alike in all ways simply because they have one thing in common.
Fig. 2 - "It's like comparing apples and oranges" is a popular saying that illustrates the trouble of faulty analogies.
Both faulty analogy and faulty causation are informal logical fallacies—which means the error is due to the content or context of the argument, not the way it was formed—but faulty analogy is based on comparison.
The universe functions systematically, like a watch.
A watch has a maker.
Therefore, the universe has a maker.
This is a faulty analogy known as the "watchmaker analogy." For an analogy to be true, the things you’re comparing must be alike in several significant ways. Unfortunately, a watch and the universe do not share many significant similarities, so to compare them in this light is a logical fallacy.
Faulty Causality - Key Takeaways
- Faulty causality is the inaccurate assumption that one thing caused another to happen, based solely on the fact that one came before the other.
- People tend to find causation between things that are simply correlated.
- Causation must be proved through rigorous tests and research.
- People tend to deny the possibility of coincidence than pursue the course of proving causation.
- Faulty causality is an informal logical fallacy, which means it is an error in logic due to the content or context of the argument, not the way it was formed.
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