Slippery Slope Fallacy: Meaning and Examples

The slippery slope fallacy is claiming that one step will set off a chain of events ending in disaster, without giving enough evidence that the chain will actually happen (UNC Writing Center). The Internet Encyclopedia of Philosophy names the flaw: the arguer exaggerates how likely the final, unacceptable step is (IEP). Not every slippery slope argument is a fallacy, though. Some chains of consequences are real, and the argument is only as strong as the support for each link.

What the slippery slope fallacy is

The UNC Writing Center describes the arguer as assuming that once we take a first step, we won’t be able to stop partway down (UNC). Purdue OWL puts it as a pattern: if A happens, then through a series of small steps B, C and so on, Z will happen too, so if we don’t want Z, we can’t allow A. In doing so, it says, the argument basically equates A and Z (Purdue OWL).

The Stanford Encyclopedia of Philosophy gives a similar definition: from a starting point, a series of incremental inferences arrives at an undesirable conclusion, and the starting point is rejected because of it (SEP). Matthew Knachel’s logic textbook files it as a fallacy of weak induction, an argument about causes whose reasons are too weak to support the conclusion (Knachel). Our list of logical fallacies shows where it sits among the others.

How a slippery slope argument works

The IEP sets out the basic form: step 1 often leads to step 2, step 2 often leads to step 3, and so on, until the chain reaches a step that’s unacceptable. That final step is then used as a reason to reject step 1 (IEP).

The trouble usually hides in the middle. Each “often leads to” is a claim that needs support, and a long chain of weak links gets weaker as it goes. The UNC handout’s example argues that allowing animal experimentation will start a slide toward the end of civilization. Its rebuttal is simple: animal experimentation has been legal for some time, and civilization hasn’t ended, so the chain is hardly inevitable (UNC).

Types of slippery slope arguments

Scholars don’t all define the slippery slope the same way. Knachel treats it as a claim about causes (Knachel), while the IEP says the chain can run through causes or through reasoning, and calls the causal version the Domino Fallacy (IEP). Philosopher Douglas Walton, who the SEP says has written more about fallacies than anyone else (SEP), takes a broader view. In a 2015 paper in Informal Logic, he notes that his 1992 book distinguished four types, depending on what moves the argument forward (Walton, 2015):

• Causal: one event is said to cause the next, and so on down the line.
• Precedent: allowing one exception to a rule sets a precedent for similar cases, which leads to more, until the result is intolerable.
• Vagueness (Walton also calls it the linguistic type): a vague term with no sharp boundary lets each small step seem no different from the last.
• Full: a combination of features from the other three.

Walton’s 2015 paper also argues that what makes a slope “slippery” is a gray area with no clear stopping point, combined with a loss of control once you’re in it. The person taking the first step thinks they can stop at any point, which is true at first but stops being true at a point they can’t predict (Walton, 2015).

Examples of the slippery slope fallacy

These are made-up illustrations of the pattern.

At home: “If we let him have dessert tonight, he’ll expect it every night, then he’ll refuse vegetables, and before long he’ll have no healthy habits at all.” One dessert is doing a lot of work here, and nothing shows any later step would follow.

At work: “If we let one person work from home on Fridays, everyone will want it, then no one will come in, and the company will fall apart.” Nobody shows that any of these steps would happen, and there are obvious places to stop along the way, like a written policy.

In a local debate: “If the town allows one food truck downtown, soon the streets will be lined with them, the restaurants will all close, and downtown will be dead.” The argument jumps from one permit to the collapse of a business district.

A precedent version: “If we excuse one late assignment for a sick student, we’ll have to excuse every late assignment for any reason.” This one runs on precedent rather than causes. Whether it holds depends on whether a reasonable line, such as a doctor’s note, can be drawn.

When a slippery slope argument isn’t a fallacy

Knachel says plainly that genuine slippery slopes exist, meaning causal chain reactions that really can’t be stopped. The fallacy, he says, is claiming the chain can’t be stopped without good reasons to believe it (Knachel). The IEP agrees that the same form shows up in good and bad arguments, and that an argument’s quality depends on how strong the probabilities are at each step, which depends on its content and not just its form (IEP).

Walton makes the case in more detail. He notes that logic textbooks usually list the slippery slope under fallacies while occasionally conceding it isn’t always one. His 2015 paper presents an example that strongly appears reasonable: a father warning his daughter that trying a drug such as heroin can become habit-forming and lead to addiction (Walton, 2015). On his view, these arguments are defeasible. They hold tentatively and can be defeated by critical questions or counterarguments.

Psychology research points the same way. Ulrike Hahn and Mike Oaksford argue that the classic fallacies are argument forms whose strength varies with their content. They tested a Bayesian account of argument strength on three of them, including the slippery slope, and found that people’s judgments were affected by the factors that account predicts (Hahn and Oaksford, 2007). On this approach, the SEP explains, a fallacy is an argument with a low probability, which makes strength a matter of degree (SEP).

A follow-up study by Adam Corner, Hahn and Oaksford notes that slippery slope arguments have a bad philosophical reputation but are widely used and often accepted in legal, political and ethical settings. Across three experiments, they found that probability affected how strong people judged these arguments to be. When the start and end of a slope were more similar, people were more likely to see them as belonging to the same category, and the argument seemed stronger (Corner, Hahn and Oaksford, 2011). One of their examples: if voluntary ID cards are accepted, compulsory ID cards will follow. They comment that this becomes more likely if the cards prove to be an effective security measure (Walton, 2015).

How to spot and respond to a slippery slope

UNC’s advice for your own writing is to check any chain of consequences and make sure each one is reasonable (UNC). The same checks work on other people’s arguments:

• Write out every step between the first action and the final outcome. Compressed versions that jump straight from A to Z hide the weakest links.
• Ask what evidence supports each “and then.” If the answer is “it just will,” that’s the gap.
• Look for a stopping point. Walton calls one of the most important questions whether a bright line can be drawn in the gray zone to stop the slide (Walton, 2015).
• Check the track record. UNC’s animal-testing rebuttal works because the first step already happened and the disaster didn’t (UNC).

Be careful about the label, too. Walton warns that people often call any argument about bad consequences a “slippery slope,” and the label alone can put the other side on the defensive (Walton, 2015). Before calling it a fallacy, make sure there really is a chain, and that the person is claiming more certainty than the evidence gives. Restate their chain fairly, too, so you don’t slip into a straw man while answering it.