The Slippery Slope Fallacy: How to Spot Unreasonable Assumptions

High school student David wants to spend the weekend with his friends, but his mom won’t let him.

“You have to study on Saturdays,” she insists. “If you don’t, your grades will suffer, you won’t get into a good university, and you’ll end up flipping burgers for the rest of your life!”

This is a prime example of the slippery slope fallacy: assuming that a relatively small first step will lead to a chain of events that eventually culminates in a significant, usually negative, outcome.

In other words, you assume that if A occurs, then B will follow, and if B occurs, then C will follow. And since C is something you really don’t want, you shouldn’t allow A to happen.

Some slippery slopes are real, but often they’re not, and that’s when we’ve got a slippery slope fallacy on our hands. To analyze this kind of reasoning, we need to examine each link in the chain.

Let’s assign some rough probability estimates to every assumption David’s mom is making. She’s saying that, if he doesn’t study on Saturdays:

A: “Your grades will suffer.” It’s possible but not very likely. A lot of students get good grades without studying on weekends. Let’s give this a 5 percent probability estimate.

B: “You won’t get into a good university.” That depends on what counts as a good university. David could also be eligible for non-academic scholarships. We’ll give this a probability of, say, 10 percent.

C: “You’ll end up flipping burgers for the rest of your life.” This is obviously the weakest link in the chain. It’s really nothing but wildly pessimistic speculation. It gets a probability of 0.1 percent.

As you can see, every link in the chain is weak. And the chain as a whole compounds those weaknesses. Here’s how the math works out:

.05 x .10 x .001 = There’s a 0.0005 percent risk that David’s mom’s assumption is correct. Not a very slippery slope.

Of course, it’s very difficult to predict the likelihood of a complex chain reaction. We can’t know if our probability numbers are accurate. But a rough guesstimate can still provide a useful hint about the likelihood of a chain of events.

So when you come across slippery slope assumptions, tease out the links in the chain and ask yourself how likely each of them is to be true. Then keep these two things in mind:

  1. The chain is only as strong as its weakest link. If you spot just one weak claim, the entire line of reasoning is also weak.
  2. Weaknesses in the links have a compounding effect. The strength of the whole chain is almost always even weaker than its weakest link.

Be skeptical of hypothetical chain reactions, and you’ll be much less vulnerable to falling for slippery slope reasoning.