What are the potential consequences and dangers of a slippery slope situation?

In debate or rhetoric, a slippery slope (also known as thin edge of the wedge, or the camel’s nose) is a classic form of argument, arguably an informal fallacy. A slippery slope argument states that a relatively small first step leads to a chain of related events culminating in some significant effect, much like an object given a small push over the edge of a slope sliding all the way to the bottom. The strength of such an argument depends on the warrant, i.e. whether or not one can demonstrate a process which leads to the significant effect. The fallacious sense of “slippery slope” is often used synonymously with continuum fallacy, in that it ignores the possibility of middle ground and assumes a discrete transition from category A to category B. Modern usage avoids the fallacy by acknowledging the possibility of this middle ground.

 

Slippery slope arguments

The argument takes on one of various semantical forms:

• In the classical form, the arguer suggests that making a move in a particular direction starts something on a path down a “slippery slope”. Having started down the metaphorical slope, it will continue to slide in the same direction (the arguer usually sees the direction as a negative direction, hence the “sliding downwards” metaphor).
• Modern usage includes a logically valid form, in which a minor action causes a significant impact through a long chain of logical relationships. Note that establishing this chain of logical implication (or quantifying the relevant probabilities) makes this form logically valid. The slippery slope argument remains a fallacy if such a chain is not established.
• Some claims lie in between the two. For example: “If we accept censorship on most disgusting material, the politicians may easily widen the area under censorship. This has happened often before too, with far-reaching consequences. Therefore, we should completely avoid the slippery slope of censorship.” This claim is not a fallacy: some people think that there is enough evidence for the claim to be probably true, some not.

 

Examples

Eugene Volokh’s Mechanisms of the Slippery Slope (PDF version) analyzes various types of such slippage. Volokh uses the example “gun registration may lead to gun confiscation” to describe six types of slippage:

• Cost-lowering: Once all gun-owners have registered their firearms, the government will know exactly from whom to confiscate them. Gun control opponents argue against limits on the sale of automatic attack weapons because the confiscation of sportsmen’s shotguns will soon follow. Meanwhile, government officials defend their inflexible enforcement of a regulation, even in circumstances that are obviously unfair, because allowing an exception would open the floodgates.
• Legal rule combination: Previously the government might need to search every house to confiscate guns, and such a search would violate the Fourth Amendment to the United States Constitution. Registration would eliminate that problem.
• Attitude altering: People may begin to think of gun ownership as a privilege rather than a right, and thus regard gun confiscation less seriously.
• Small change tolerance, colloquially referred to as the “boiling frog”: People may ignore gun registration because it constitutes just a small change, but when combined with other small changes, it could lead to the equivalent of confiscation.
• Political power: The hassle of registration may reduce the number of gun owners, and thus the political power of the gun-ownership bloc.
• Political momentum: Once the government has passed this gun law it becomes easier to pass other gun laws, including laws like confiscation.

Slippery slope can also be used as a retort to the establishment of arbitrary boundaries or limitations. For example, one might argue that rent prices must be kept to $1,000 or less a month to be affordable to tenants in an area of a city. A retort invoking the slippery slope could go in two different directions:

Once such price ceilings become accepted, they could be slowly lowered, eventually driving out the landlords and worsening the problem.

If a $1,000 monthly rent is affordable, why isn’t $1,025 or $1,050? By lumping the tenants into one abstract entity, the argument renders itself vulnerable to a slippery slope argument. A more careful argument in favor of price ceilings would statistically characterize the number of tenants who can afford housing at various levels based on income and choose a ceiling that achieves a specific goal, such as housing 80% of the working families in the area.

Sometimes a single action does indeed induce similar latter action. For example, judiciary decisions may set legal precedents.

 

The slippery slope as fallacy

The heart of the slippery slope fallacy lies in abusing the intuitively appreciable transitivity of implication, claiming that A leads to B, B leads to C, C leads to D and so on, until one finally claims that A leads to Z. While this is formally valid when the premises are taken as a given, each of those contingencies needs to be factually established before the relevant conclusion can be drawn. Slippery slope fallacies occur when this is not done—an argument that supports the relevant premises is not fallacious and thus isn’t a slippery slope fallacy.

Often proponents of a “slippery slope” contention propose a long series of intermediate events as the mechanism of connection leading from A to B. The “camel’s nose” provides one example of this: once a camel has managed to place its nose within a tent, the rest of the camel will inevitably follow. In this sense the slippery slope resembles the genetic fallacy, but in reverse.

As an example of how an appealing slippery slope argument can be unsound, suppose that whenever a tree falls down, it has a 95% chance of knocking over another tree. We might conclude that soon a great many trees would fall, but this is not the case. There is a 5% chance that no more trees will fall, a 4.75% chance that exactly one more tree will fall (and thus a 9.75% chance of 1 or fewer additional trees falling), and so on. There is a 92.3% chance that 50 or fewer additional trees will fall. The expected value of trees that will fall is 20. In the absence of some momentum factor that makes later trees more likely to fall than earlier ones, this “domino effect” approaches zero probability.

This form of argument often provides evaluative judgments on social change: once an exception is made to some rule, nothing will hold back further, more egregious exceptions to that rule.

Note that these arguments may indeed have validity, but they require some independent justification of the connection between their terms: otherwise the argument (as a logical tool) remains fallacious.

The “slippery slope” approach may also relate to the conjunction fallacy: with a long string of steps leading to an undesirable conclusion, the chance of all the steps actually occurring in sequence is less than the chance of any one of the individual steps occurring alone.

 

Supporting analogies

Several common analogies support slippery slope arguments. Among these are analogies to physical momentum, to frictional forces and to mathematical induction.

 

Momentum or frictional analogies

In the momentum analogy, the occurrence of event A will initiate a process which will lead inevitably to occurrence of event B. The process may involve causal relationships between intermediate events, but in any case the slippery slope schema depends for its soundness on the validity of some analogue for the physical principle of momentum. This may take the form of a domino theory or contagion formulation. The domino theory principle may indeed explain why a chain of dominos collapses, but an independent argument is necessary to explain why a similar principle would hold in other circumstances.

An analogy similar to the momentum analogy is based on friction. In physics, the static co-efficient of friction is always greater than the kinetic co-efficient, meaning that it takes more force to make an object start sliding than to keep it sliding. Arguments that use this analogy assume that people’s habits or inhibitions act in the same way. If a particular rule A is considered inviolable, some force akin to static friction is regarded as maintaining the status quo, preventing movement in the direction of abrogating A. If, on the other hand, an exception is made to A, the countervailing resistive force is akin to the weaker kinetic frictional force. Validity of this analogy requires an argument showing that the initial changes actually make further change in the direction of abrogating A easier.

 

Induction analogy

Another analogy resembles mathematical induction. Consider the context of evaluating each one of a class of events A1, A2, A3,…, An (for example, is the occurrence of the event harmful or not?). We assume that for each k, the event Ak is similar to Ak+1, so that Ak has the same evaluation as Ak+1.

Therefore every An has the same evaluation as A’1.

For example, the following arguments fit the slippery slope scheme with the inductive interpretation

If we grant a building permit to build a religious structure in our community, then there will be no bound on the number of building permits we will have to grant for religious structures and the nature of this city will change. This argument instantiates the slippery slope scheme as follows: Ak is the situation in which k building permits are issued. One first argues that the situation of k permits is not significantly different from the one with k + 1 permits. Moreover, issuing permits to build 1000 religious structures in a city of 300,000 will clearly change the nature of the community.

In most real-world applications such as the one above, the naïve inductive analogy is flawed because each building permit will not be evaluated the same way (for example, the more religious structures in a community, the less likely a permit will be granted for another).

 

Measuring the slippery slope

When a principle is based on direct proportion and the circumstance cannot be made to fit that principle, then the discrepancy is taken as indication of failure. The impression becomes pessimistic when there is continual failure at meeting the ideal principle, such as in a democratic or justice context. To overcome the pessimism that appears when sliding on the slippery slope of injustice, one requires a measurement of discrepancy. Then successive efforts can be compared and the slippery illusion dispelled. Scientists have used hyperbolic coordinates in technical work to deal with parameters similar to those giving the slippery slope scenario.