This post is about a fallacy (a thinking error) called false cause.
I bet you know more about this fallacy than you think.
You’ve probably witnessed it, even if you didn’t realize it.
For example, imagine the following scenario:
Your friend drinks a brand of orange juice called Florida Smile on Tuesday.
And then on Wednesday they come down with a splitting headache.
Picture courtesy of Wikimedia.
And imagine further they argue, “Wow! That Florida Smile orange juice is horrible. It gave me the worse headache.
I’m never drinking it again.”
Now on the one hand, our friend’s claim makes some sense.
After all, they did drink orange juice. And they did come down with a headache the next day.
So maybe the orange juice did cause the headache.
But there’s a problem.
Our friend did indeed drink orange juice before he got the headache.
But he also did a hundred other things before he got his headache.
For instance . . .
He went to school.
And he listened to loud music while lifting weights when he got home.
He ate pizza and ice cream for dinner.
And he slept on a new pillow.
He tripped and fell down a few stairs when he was sleepy in the morning.
The point is that our friend did a lot of things before he got a headache.
And maybe one or more of them contributed to (or caused) his headache.
Or maybe none of them did.
Here’s a Good Rule to Remember: Correlation does not equal causation.
Just because two things are correlated or associated (A happens and then B happens), doesn’t mean that A caused B.
Now, it could be true that A causes B.
But mere correlation in time doesn’t prove it.
And in fact, if we assume that A caused B merely because A happened before B, we commit the fallacy of false cause.[1]
False cause is the reasoning error we make when we assume that A causes B simply because the two events are correlated or associated (in time, for example).
Here’s another Example:
Let’s say that I drive under a bridge called Peterson Bridge.
And immediately as I do so, my tire goes flat.
Picture courtesy of Wikimedia.
And imagine that I say, “I will never drive under Petersen Bridge again! It made my tire go flat.”
In this example we certainly realize that just because my tire goes flat as I drive under Peterson Bridge, it doesn’t mean the bridge caused my flat tire.
It could be any number of things causing my flat tire.
Perhaps I ran over a nail just as I drove under the bridge.
Or perhaps it was just bad luck.
The point is that if I assume that going under the bridge caused my flat tire, I commit the fallacy of false cause.
So, one way we commit false cause is to assume that correlation automatically equals causation.
But there’s another common way we commit the fallacy of false cause.
It is when we fail to realize that two factors that seemed causally connected are in fact caused by a third, related factor.
To illustrate this, let me give another, more complex example.
Let’s say a study finds a correlation, or an association, between eating ice cream and shark attacks.[2]
Now, this correlation seems weird.
Picture courtesy of Wikimedia.
After all, a lot of people eat ice cream on a regular basis and never suffer shark attacks.
Picture courtesy of Wikimedia.
But let’s say that you examine this study more in depth and here is what you discover:
More people eat ice cream in the summer because it’s warm.
And more people go swimming in the ocean in the summer when it’s warm.
So, since there are more people swimming in the ocean, the number of shark attacks goes up as well.
Thus, it turns out that there is, indeed, a correlation, an association, between eating ice cream and shark attacks.
But this correlation doesn’t mean that eating ice cream causes shark attacks.
That’s because correlation does not entail causation.
Rather, people eat more ice cream when the weather gets warmer.
They also swim in the ocean more frequently when the weather gets warmer.
Picture courtesy of Wikimedia.
And if you are going to get attacked by a shark, it’s going to be while you are you are swimming in the ocean.
So, eating and ice cream are correlated (or associated), but they are not causally connected to each other.
They are both caused by a third factor: hot weather.
So, we commit the false cause fallacy in this case because we assume that ice cream causes shark attacks.
And we do this because we fail to see that warm weather is the cause of both increased ice cream consumption and increased shark attacks.
(And note: Warm weather only causes shark attacks if it encourages people to visit the beach and swim in an ocean where sharks are present.)
So how do we avoid the fallacy of false cause?
How do we determine if two events are truly connected?
Well, first, we must observe many instances in which two events (a supposed cause and outcome) are indeed causally connected.
For instance, if we wanted to determine if Florida Smile does indeed cause headaches, one instance alone won’t prove this causal connection.
We must observe multiple instances over time.
Second, we need to look for negative instances the disprove our hypothesis.
For instance, with our hypothesis that drinking Florida Smile causes headaches, we should look for instances that disprove our hypothesis.
Third, we should examine whether the two factors we observe connect to a third factor.
For example, you might be aware of a recent causal claim in the news: Tylenol causes autism.
Recently the President and RFK Jr. suggested that women taking Tylenol during pregnancy is associated with autism.
Picture courtesy of Wikimedia.
Fox News notes that “Speaking from the White House on Monday, the president said that Tylenol taken during pregnancy ‘can be associated with a very increased risk of autism’.”
And as a result, the President and RFK urged women not to take Tylenol during pregnancy unless absolutely necessary.
It appears the President was making a causal claim.
Their claims are based on various studies that do indeed suggest a correlation between Tylenol dosage during pregnancy and autism.
For instance, you can see a list of a studies indicating a correlation on the White House web site here.
The articles note that this correlation is most pronounced with “frequent or prolonged” usage of Tylenol.
But in the case of Tylenol and autism, as with all causal claims, it’s important to remember that correlation (association) doesn’t entail causation.
And it’s important to consider that there could be other factors–for instance an underlying illness, stressors, or other factors–that correlate with Tylenol use, especially significant Tylenol use.
For instance, Dr. Zeyan Liew of Yale School of Public Health notes, “There might be other factors related to acetaminophen use, such as fevers (which are known to cause increased rates of neurodevelopmental delays).”
And, in fact, one reason medical doctors have permitted Tylenol use in pregnancy is because it is the safest over-the-counter drug for lowering fevers, as prolonged fevers are certainly dangerous in pregnancy.
A study by Harvard, which the White House posted on its press release site regarding Tylenol and autism, states,
“The researchers noted that while steps should be taken to limit acetaminophen use, the drug is important for treating pain and fever during pregnancy, which can also harm the developing fetus.
High fever can raise the risk of neural tube defects and preterm birth. We recommend judicious acetaminophen use—lowest effective dose, shortest duration—under medical guidance, tailored to individual risk-benefit assessments, rather than a broad limitation.”
About a possible association between Tylenol and autism, a primary author of this paper, Bacarelli, argues, “That association is strongest when acetaminophen is taken for four weeks or longer.”
This stronger four-week association suggests that there may be an underlying cause—a third factor—which causes increased Tylenol usage and may also correlate to autism.
A John Hopkins study, which the White House posted on its website, suggests this as well.
Picture courtesy of Unsplash.
For instance, researcher Xioban Wang writes in this article that “researchers found consistent associations between the drug and the disorders across a variety of other factors that correlate with ADHD and autism spectrum disorder diagnoses, such as maternal BMI, preterm birth, child sex, and reports of maternal stressors and substance use.”
The possible association between drug use and autism to other factors like maternal BMI and preterm birth, seems to prompt Wang to conclude, “although the study found a consistent association between biomarkers of acetaminophen and its metabolites in cord blood and child risk of ADHD and autism spectrum disorder, it should not be interpreted that the Tylenol use causes these disorders.”
People are especially concerned about the Tylenol and autism link because of apparent rising rates of autism in the U.S.
For instance, an article from John Hopkins University notes that in the U.S., autism diagnoses have increased 300% in the last 20 years.
However, is an epidemic of autism causing increased autism diagnoses rates? Or is there another cause for increased diagnosis rates?
Autism researcher Christine-Ladd Acosta notes that the increase in autism diagnoses are due to an expanded definition of autism and because more parents are seeking help for their children exhibiting potential autism symptoms.
Both causal factors are, in fact, good news.
That is because the more help children on the autism spectrum receive early on in their life, the more they benefit.
Picture courtesy of Unsplash.
In addition, Acosta makes another important point.
She notes that the rates of diagnosis for people with severe autism, those “needing 24-hour-a-day support and care from a caregiver” who “often have very limited verbal communication skills, or have intellectual disability” have changed very minimally if at all in the last 10 years.
This fact also suggests that expanding the definition of autism (along with parents seeking out more help for their children with autism) drives the increasing rates in autism.
This rather than, for example, an epidemic of autism, seems to be the cause of the increase in diagnosis rates.
It is important to be careful about causal claims.
When we identify actual causes, it helps us solve problems.
But when we commit the fallacy of false cause, it makes it more difficult to solve problems.
In the case of Tylenol and autism, we commit false cause when we assume that there is a simple causal link between taking one or two Tylenol and increased autism rates, for example.
We think more carefully, however, when we note that a variety of factors correlate with autism.
Therefore, establishing causality takes care and precision.
In addition, it is important to note that expanding the definition of autism allows more children with autism to receive a diagnosis and receive early help and intervention.
It significantly improves the social interaction of children diagnosed with autism.
This expanded definition may increase diagnosis rates of autism, but it helps children with autism more in the long-run.
You might also like this post: The Cause of Inflation.
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For further reading, you might be interested in these three books I have written (or co-written) to help people develop good thinking habits.
