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  • SPEAKER 1: The last content fallacy

  • that we're going to look at is slippery slope.

  • Here's a pretty extreme example of a slippery slope fallacy.

  • A high school kid's mom insists that she study on Saturdays.

  • Why?

  • Because if she doesn't study on Saturdays,

  • her grades will suffer, and she won't graduate high school

  • with honors.

  • And if she doesn't graduate with honors,

  • then she won't be able to get into the university

  • of her choice.

  • And, well, the rest isn't clear, but the result of all this

  • is that she'll end up flipping burgers

  • for the rest of her life.

  • And surely, she doesn't want that,

  • so she better darn well get serious and study.

  • I've actually heard a version of this discussion between two

  • wealthy mothers who were talking about which preschool

  • to send their kids to.

  • The gist was that if they didn't get their kid

  • into a prestigious preschool, then

  • they'd be disadvantaged from that point

  • forward in ways that could ultimately threaten

  • their future life prospects.

  • So this was not a decision to be taken lightly.

  • I did not envy those kids.

  • Here's the schematic form of a slippery slope argument.

  • It's a series of connected conditional claims

  • to the effect that if you assume that A is true

  • or allow A to occur, then B will follow.

  • And if B follows, then C will follow, and if C follows,

  • then D will follow.

  • But D is something nasty that we all want to avoid.

  • So the conclusion is that if we want to avoid D,

  • we need to reject A, or not allow A to happen.

  • Now, note that as stated, the logic of this argument is fine.

  • In fact, this is a valid argument form

  • that we've seen before.

  • We've called it hypothetical syllogism,

  • or reasoning in a chain with conditionals.

  • Slippery slopes are fallacious only if the premises

  • are false or implausible.

  • Everything turns on whether these conditional relationships

  • hold.

  • Sometimes, they do.

  • And if they do, it's not a fallacy.

  • But very often, they don't.

  • And when they don't, we've got a slippery slope fallacy.

  • Now, there's a caveat to this way

  • of analyzing slippery slopes.

  • It's usually the case that slippery slope arguments

  • aren't intended to be valid-- that is, they're not intended

  • to establish that the dreaded consequence will follow

  • with absolute certainty.

  • Usually the intent is to argue that if you assume A,

  • then D is very likely to follow.

  • So what's being aimed for is really a strong argument.

  • And that means we shouldn't really

  • be reading the conditional claims as strict conditionals

  • with every link in the chain following

  • with absolute necessity.

  • We should be asking ourselves, how likely is it

  • that D will follow if A occurs?

  • If it's very likely, then the logic is strong.

  • If not, then it's weak.

  • So in a sense, we're evaluating the logic of the argument.

  • But it turns out that in cases like this,

  • the strength of the logic turns on the content of the premises.

  • So in the end, we are evaluating the plausibility

  • of premises, which makes this a content fallacy, and not

  • a logical or formal fallacy.

  • For our example, the chain of inferences looks like this.

  • Now, this argument is obviously bad at every stage

  • of the reasoning.

  • It's possible that not studying on Saturdays

  • could make a difference to whether the student gets

  • on the honor roll, but there's no evidence

  • that this is likely.

  • Yes, if you're not on the honor roll, then

  • maybe this will affect your chances

  • of getting into a top university.

  • But without specifying what counts as a top university,

  • one of the factors may or may not

  • be operating-- like, for example, whether the student is

  • a minority or an athlete.

  • They might be eligible for non-academic scholarships

  • of various kinds.

  • Then it's impossible to assess the chances in this case.

  • The last move, from failing to get into a top university

  • to flipping burgers for a living,

  • is obviously the weakest link in the chain.

  • This is just widely pessimistic speculation with nothing

  • to support it.

  • So each link in the chain is weak, and the chain as a whole

  • simply compounds those weaknesses.

  • By saying this, we're saying that premises 1, 2, and 3 are

  • not plausible, and so the inference from A to D

  • is not possible.

  • We have no reason to think that this slope is not slippery.

  • Now, there's another obvious way that one can attack

  • a slippery slope argument.

  • You might be willing to grant that the slope is slippery

  • but deny that what awaits at the bottom of the slope

  • is really all that bad.

  • This would be to challenge premise 4,

  • the not D. Not D says that D is objectionable in some way,

  • that we don't want to accept D. But this

  • might be open to debate.

  • Put away to the bottom of the slope

  • is "and" then you die a painful death,"

  • or "and then all our civil rights are taken away."

  • And sure, just about everyone is going

  • to agree that that's a bad outcome.

  • But it's not as obvious that everyone

  • will find flipping burgers objectionable,

  • or whatever this notion stands for-- working in the service

  • industry, or working in a low-paying job or whatever.

  • What's important in evaluating a slippery slope argument

  • is that the intended audience of the argument

  • finds the bottom of the slope objectionable.

  • So this is another way to criticize a slippery slope

  • argument-- by arguing that the outcome of this chain of events

  • really isn't as objectionable as the arguer would

  • like you to think.

  • So just to summarize what we've said so far--

  • there are two ways of challenging a slippery slope

  • argument.

  • The first one is to challenge the strength

  • of the conditional relationships that the argument relies on.

  • When people say that a slippery slope argument is fallacious,

  • they usually mean that the chain of inferences is weak.

  • By the way, I hope it's clear that slippery slope

  • arguments don't have to have only three links.

  • My argument schema could've been longer or shorter.

  • Now, second, you can also challenge a slippery slope

  • argument by challenging the objectionableness of whatever

  • lies at the end of the chain.

  • If it's not obvious to the intended audience

  • that this is actually a bad thing,

  • then the argument will fail to persuade, regardless of how

  • slippery the slope may be.

  • Before wrapping up, I'd like to make a few points

  • about assessing the plausibility of conditional chains.

  • Fallacious slippery slope arguments

  • often succeeded at persuading their audience

  • because people misjudge the strength

  • of the chain of inferences.

  • They're prone to thinking that the chain is stronger

  • than it actually is.

  • It's important to realize two things.

  • First, a chain of conditional inferences

  • is only as strong as its weakest link.

  • The weakest conditional claim-- the one that

  • is least likely to be true-- is the one that sets the upper

  • bound on the strength of the chain as a whole.

  • So even if some of the inferences in the chain

  • are plausible, the chain itself is only

  • as strong as the weakest inference.

  • Second, weaknesses in the links have a compounding effect,

  • so the strength of the whole chain

  • is almost always much weaker than the weakest link.

  • To see why this is so, you can think of conditional claims

  • as probabilistic inferences.

  • If A is true, then B follows with some probability,

  • and this probability is usually less than one,

  • or less than 100%.

  • So the probability of D following

  • from A, the probability of the whole inference,

  • is actually a multiplicative product

  • of the probabilities of each of the individual links.

  • Now, the odds of a coin landing heads on a single toss

  • is one half, or 50%.

  • The odds of a coin landing heads twice

  • in a row is one half times one half, or one quarter,

  • which is 25%.

  • Conditional inferences compound in a similar way.

  • So if the odds for each link in the chain were,

  • let's say, 90%, then the odds of the whole chain being true,

  • of D actually following from A, would only be 0.73, or 73%,

  • and this number would go down further

  • with each additional link in the chain.

  • People in general are very bad at estimating

  • compound probabilities and will tend to overestimate them.

  • Here's the calculation if one of the links

  • is weaker than the rest-- say, 0.6, or 60%.

  • The probability of D following from A

  • actually drops below 50%, a very weak inference.

  • But very few people will read the probabilities this way.

  • Their attention will focus on the highly probable bits

  • of the story, and their estimate of the overall odds

  • will be anchored to these bits, especially if they're

  • either at the very beginning or the very end of the chain,

  • since these make the biggest impression.

  • So human beings in general are quite

  • vulnerable to slippery slope reasoning,

  • and knowing these facts should motivate

  • you to be more critical when you encounter

  • these kinds of arguments.

SPEAKER 1: The last content fallacy

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B1 中級 美國腔

謬論。滑坡 (Fallacies: Slippery Slope)

  • 22 1
    Keira Wang 發佈於 2021 年 01 月 14 日
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