Fallacies of Weak Induction

you had this question about what the difference between an enumerative generalization and a statistical syllogism is were the ones that you are confusing the most right and that's understandable because they're both articulating some sort of relationship between a general rule and a particular case right or something that worked several particular cases the difference between them is which way the argument goes a statistical syllogism starts with a key premise that is a general rule and then the rest of the argument is identifying that here's a particular case that fits the rule so let's apply the rule to the particular case the conclusion is going to be the application of that general rule to the particular case whereas in an enumerative generalization my conclusion is the general rule I'm going from a bunch of particular cases as my premises and I'm drawing a conclusion that says there for most days or B's or something like that right so it's this question that am i arguing from the general rule to a particular case or am i arguing from particular cases to the general rule I tend to think for some reason I don't know maybe this is like a holdover from like medieval metaphysics maybe I just read too much philosophy I tend to think of it is it like an up-or-down sort of thing the general rules up here particular cases are down here on the ground so are you arguing down from the general rule to the particular case or are you arguing up and the argument by analogy argue sideways on the ground we don't even mess with the general rules at all yes but does the yeah so does that arguments say everybody loved it therefore it's a hit or are we saying because the people who sent in the surveys liked it therefore everybody loved it aka it's a hit does that make sense so if we say everybody loved it to then say it's a hit isn't an application of the general rule everybody loved it to a particular case it almost seems like it's just a it's another way of saying that everybody loved it what makes something a hit as a product if everybody loves it right so yeah maybe there's a little bit of confusion there it seemed like what was making that argument tick was to say we got all of these survey responses they all said they loved it therefore everybody loves it everybody who submitted the survey loves it therefore everybody loves it that's a generalization right and it's in fact it's a sketchy one too because we think that the people who submit the survey the survey was included on the product so first of all you've already selected only for people who have already bought the product second of all there may be your sample is biased because who's gonna send in a survey from I got it do you guys ever if you find a survey on your products that you buy do you fill them out and send them in I don't unless I feel really strongly right so yeah maybe there's a little bias in the sampling there as well so so yeah it's not particularly good argument and it seems like it's a generalization generalizing from the people who responded to the survey to everybody okay anything else today we're talking about fallacies again maybe for yeah one of the lesson we might check back in on this again but we're kind of gonna cover almost all the ground in these fad fallacy files so far we've done these for different families of fallacies we started out talking about formal fallacies what makes a fallacy if what we actually this before we even get into what makes a fallacy formal fallacy what's a fallacy yeah they're do you guys reads good a bad argument that at first glance looks better than it actually is exactly so it's not just a bad argument it's like a sneaky bad argument right and all these fallacies are there kind of masquerading as better than they actually are and if you're not really careful you won't catch it you're not paying attention you won't catch it so formal fallacies are bad arguments they're sneaky in some sort of way what makes a fallacy a formal fallacy for example one of the formal fallacies that we discussed was affirming the consequent where I have an argument that goes if a then B be there for a and we said that's actually not a very good argument and it's a little bit sneaky because it looks a little bit like a good argument what makes that argument a formal fallacy as opposed to some other sort of fallacy I'll give you a hint yeah or what is the when we talk about formal logic and even you know like what makes formal logic formal to focus on the form of the argument the structure of the argument rather than its content is that were you gonna say something like that yeah so there's something about there's something gone wrong with the form or the structure of the argument what's wrong with if a then B B therefore a is that or if you just kind of switch some things around that would work if it was if a then B a therefore B piece-of-cake that's a good that's a valid argument at least right that's modus ponens if a then B be there for a with structural form is just a little bit off that's affirming the consequent and all of my formal fallacies are like that it's something that's wrong with the structural form not with the content it resembles a common valid argument but we've moved some of the pieces around and that's what makes it not a good argument and also a little bit sneaky what about fallacies of relevant that's maybe like so obvious as to not warrant a serious question what makes fallacies of relevance fallacies of relevance the premises are not particularly relevant to the conclusion being drawn maybe this will be more interesting to remind me what were some of the fallacies of relevance that we discussed what are some examples of fallacies of relevance ad hominem is one yeah when we're talking about the person's character is not relevant to the conclusion that's being drawn you should get off the swings no I shouldn't because you're a poopoo head wait a minute like whether or not a poopoo head is not relevant to whether or not you should get off the swings so yeah ad hominem fallacy that's why it's not a very good argument sometimes bring in the argument to the character is relevant but when it's not we've committed this fallacy and that's what makes it sneaky sometimes it's relevant sometimes it's not some other fallacies of relevance that we discussed yes Adam is recording which is an appeal to pity right when we say that like yeah your sadness is not relevant to whether or not I should do this or something else yeah anything else yes at baculum which is it's a threat right an appeal to force yeah exactly so yeah the fact that you're bigger and stronger than me is not relevant to whether or not you're yeah ad populum similar the fact that an idea is like widely believed is not necessarily relevant to whether or not it's true any others and we got an idea right these are these are all fallacies of relevance fallacies of presumption include things like ooh how are we doing with this what are some examples of fallacies of presumption yes yeah false dilemmas a fallacy of presumption where I'm assuming that I only have these two options in an either/or premise like you're either with us or you're with the terrorists right and that assumption is what kind of like gets me to a point where I can make some very powerful good seeming arguments or seemingly good arguments when in fact I've made this society sumption in the backdoor and it makes the argument weaker than it actually seems or actually reeker than it seems begging the question another fallacy of presumption where what's being presumed or assumed in this case is that the conclusion is already true I assume the conclusion is true in order to give you reasons to believe that the conclusion is true no that's not how that works that's a bad argument fallacies of ambiguity include all of those cases where I have kind of like mushy vague ambiguous sorts of terminology or sentence structure we discussed equivocation as one yeah Amin you got another equivocation and fib Li was is one that's similar to equivocation equivocation is about when the word meaning is a little bit ambiguous when it changes throughout the argument and amphibole is about ambiguous sentence structure can remember some of these examples like I shot an elephant in my pajamas and what was the elephant doing in your pajamas kind of thing right yeah there are no words that are ambiguous there it's the sentence structure that's a little ambiguous what a fallacy of composition fallacy of division also a fallacy of ambiguity all right so those are the four families that we've already discussed today we're gonna be talking about fallacies of weak induction and surprise surprise all of these involve inductive arguments gone wrong there's going to be one family that I'm just going to kind of gesture towards because we haven't started talking about these arguments yet and the reason why we haven't started talking about them just yet is I'm not 100% convinced that they're actually inductive arguments they're definitely likely inferences but they may be a different class of likely inferences than induction but and we'll go ahead and toss them into this family fallacies of weak induction because they all involve some sort of likely inference that's not as strong as it seems like it is the first few that we're gonna look at are gonna be kind of obvious mostly just because we've kind of we've covered this territory already when talking about what makes inductive arguments work well a lot of these fallacies are just going to be yeah it's an inductive argument that's not done well for example hasty generalization a hasty generalization is an enumerative generalization that's just not done very well I a make my generalization too hastily too quickly on too little evidence or on not good enough evidence my sample size is too small my sample is biased I'm skipping to my general rule before I've actually offered actually compelling evidence that that general rule is the sort of thing that I should be confident in for example after the debate the reporter interviewed ten people and asked them to discuss their impressions seven of those ten thought the incumbent one one was undecided two thought the Challenger one looks like the incumbent is more popular with the people how could an argument is that not very yeah not very good and why because I'm trying to generalize from ten people to all Americans and that's just too small of a sample size we get why that's not a good argument we get way we would call it a hasty generalization it's an attempt to make a generalization on too little evidence compare that to accident sometimes known as a sweeping generalization and that might be easy to confuse these two just like it's easy to confuse statistical syllogism and a generalization if we can think of hasty generalization as an enumerative generalization gone wrong we can think of sweeping generalization or the fallacy of accident as a statistical syllogism gone wrong starts out without that's kind of of the form most azar bees and where it goes wrong is that it just seems not sensitive enough to the possibility that the case that we're applying this general rule to is an exception to the rule rather than something that fits the rule for example I think it's not controversial to say that if you let somebody borrow something they should return it when you ask for it back before we go through any more of that argument does that seem like a reasonable sort of thing to say if you let somebody borrow something when you ask for it back they should give it back if they don't give it back when you ask for it back they're not really borrowing it anymore it seems like they've stolen it okay fair enough I lent Brian my pistol last week but now I'm angry at my neighbor and I want the pistol back so I can threaten my neighbor Brian should totally give me my pistol back I agreed with that general rule at the beginning but I don't know about you are you not entirely convinced that Brian should give me my pistol back maybe what we want to say is usually when you let somebody borrow something when you ask for it back they should give it back there are some exceptions to the rule what sources of exceptions well that looks like a pretty good case actually when giving it back would lead to some sort of harmful consequence right that general rule is one that applies most of the time but it doesn't apply every time and this argument just seems to be oblivious to or insensitive to the possibility that there are exceptions to the rule and that the case in question is precisely one of the cases that the exceptional case that like the exception to the rule is exceptional for right all right so this is a statistical syllogism gone wrong starts with a general rule applies that general rules for a particular particular case and does so with an insensitivity as to whether or not the particular case really does fit the rule or should count as an exception to it slothful induction which is this one's new we haven't really talked about this one just yet and it's kind of maybe an important thing to mention slothful induction refers to a failure to make an inductive leap when the inductive leak is actually really well supported and maybe you know somebody like this here's my friend Roberto who has had five car accidents in the past six months and he was driving and every single one of them and I say hey Roberto you should probably be a little bit more careful when you drive Roberto says ah that's just a coincidence that I had five accidents in six months just bad luck do you know anybody like this like bad keeps happening to them and you're like this seems like a pattern they're like dad it's not a pattern it's just bad luck they're not being reasonable there's ample evidence for them to identify that there's some sort of reliable pattern going on and they're just saying like no I don't think there is a pattern this is fallacious one of the things that makes it tricky is that it's true that no sort of inductive inference is ever going to be absolutely certain there's always going to be a possibility that there is no real pattern that it is a coincidence that it is just bad luck that's always a possibility in any kind of inductive argument but that doesn't mean that it's a probability it doesn't mean that it's a reasonable sort of thing to assume so it's trading on this idea that somehow like being cautious is wise and prudent when we can see that sometimes being too cautious is a really really bad idea when there's ample evidence that like there's a pattern going on in somebody's just like god I don't believe it you're like you're just not being reasonable weak analogy should be pretty straightforward what makes an analogy work when they're compelling relevant similarities between the two analog cases what makes it not work when those similarities aren't particularly relevant or when there are relevant differences that are being ignored here's an interesting case that actually the last section had trouble parsing this one and trying to figure out what was actually wrong with it while it's true that the chemical chlordane which has found that many insecticides has been shown to cause cancer it seems a bit rash to say that we should ban its use after all automobiles are responsible for tens of thousands of death each year but nobody seems to think that we should ban cars is it clear that this is an argument by analogy and the two things that are being compared to our cars and insecticides with chlordane chlordane is a chemical right not Claire Danes she's an actress chlordane did I just show my age do you guys even know who Claire Danes is okay good what's similar between these two cases they both kill people all right there's a similarity is that the only relevant similarity maybe there are some other similarities is that similarity relevant to the conclusion that I'm drawing a little bit yeah it's like it's it should be part of the conversation right if I'm like are these two things comparable with respect to whether or not we should ban them and somebody says well they both kill people and we'll be like whether or not something kills people is probably something we want to think about when we're deciding whether or not to ban something all right good relevant similarity are there relevant dissimilarities here yes what are they yeah what's the job that they do ones transporting people the other ones killing bugs so that people can eat but that's pretty important I suppose that's true yeah so we say not all insecticides have chlordane we're just talking about ban and the ones that do contain chlorine if you ban those you would still have some other insecticides you could engage in other sorts of farming practices where you don't use any insecticides at all maybe they might be a little more expensive they might not be as effective but you can do it in a way that doesn't kill people perhaps yeah would we say this well this is an argument by analogy so it's not necessarily gonna be utilitarian but sure the difference might be different sorts of utility right yeah that's right they both have benefits and harms but the balance is different for them yeah okay so what about the cars are there alternative ways to get around town besides a car but they're maybe not as effective we could say that about insecticides as well what other sorts of relevant differences might there be here so yeah so we've identified some good ones one that like we could ban the insecticides and still be able to grow our crops whereas if we banned cars it might be hard and this might depend on what city you live in right like you can walk you can ride a bike but I don't know like if you live in High Point and work in Greensboro and go to school in winston-salem you gonna bike everywhere you gonna take the bus everywhere maybe you need a car right also consider this is there a way of using those chlordane insecticides properly that doesn't kill people or is it just using a properly means spray it on the plants and if you sprayed it on the plants now the now the crops are gonna be poisonous to the people who eat them if you operate a car if everybody who operates a car does so responsibly can we bring down the number of deaths yeah so that might be an important difference between the two that one of the reasons why we accept car deaths is because we still are holding out this hope that like maybe if people drive responsibly we can keep this down we don't really have that option with the insecticides there's also the issue of the public isn't necessarily aware that what they're eating might give them cancer whereas if you get in the car are we all fairly cognizant of the fact that you're taking a little bit of a risk every time you drive or ride in the car okay there are some differences here and there are important ones and to the extent that there are important relevant dissimilarities between these two analogue cases that makes this analogy a weak analogy appeal to unqualified Authority is a fallacy that refers to Oh whenever it is that I say that somebody's testimony is trustworthy because they are an expert because they have some sort of authority or access to information that's better than other people and this can be a very good argument sometimes people will say any appeal to Authority is fallacious those people are crazy because I don't know about you but like I believe I totally believe that carbon has six protons even though I've never checked myself do you believe this as well carbon has six protons you might even be like I'm like you say so look it up on your phone if you want this Carbon has six protons and why do you believe that is it because you trust the people who say so because they seem like they know that sort of thing if the meteorologists tell you that it's gonna rain tomorrow and I say alright so I think it's gonna rain him on it so he's like oh it just cuz the people who are experts say so you'd be like yeah that's exactly why I think so and we could say like why I got my friend over here he says it's not gonna rain we might say like well why should I trust him like cuz he's got a cool haircut he's a good dancer no that's not relevant right so one of the reasons so this could be classified by the way as a fallacy of relevance where we could say like you might have some expertise or you might have some authority but it's just not related to what we're talking about or we could talk about it as a fallacy of induction because a lot of times when we talk about an appeal to Authority we're doing so on the basis of somebody's got a track record right people who have that sort of background knowledge tend to be right more often than not when they talk about the things that are relevant to the background knowledge that they have or they might actually have a track record will say like this meteorologist has been predicting the weather for ten years and he's right more often than he's wrong or she's right more often than she's wrong therefore there's a pattern I expect the pattern to persist this is an inductive leap that I'm making but when the authority that's being appealed to is just not relevant to the conclusion that's being drawn clearly we get into trouble so our example here Kim says I'm concerned about the amount of gluten that we been eating and Daniel says why do you have celiac disease or something and Tim says no but dr. Elizabeth on TV says that gluten can be dangerous for anyone and Daniel says dr. Elizabeth what does she eat like some sort of gastroenterologist somebody who specializes in digestive issues and Tim says no she has a doctorate in English literature but she's super smart you should totally check her out why is dr. Elizabeth not trustworthy on this issue yeah her her disciplinary expertise is not relevant to the conclusion that's being drawn and this is what makes it fallacious and my guess is you've seen something like this before lots of people like go on the radio or go on TV and they're like Oh dr. so-and-so dr. so-and-so how impressive like doctor of what what sort of expertise do they have I want to pay attention that sort of thing the gamblers fallacy there's a nice little inductive fallacy the gamblers fallacy is tricky because it seems like it plays on something that is a like a good premise to work on something we might talk about as laws a law of averages or laws of large numbers or something like this if I flip a coin like an ordinary fair coin just a quarter that I pulled out of my pocket if I flip it five hundred times in a row what do you think like how many of those times are gonna come up heads and how many of them are gonna be tails ballpark quarter flip 500 times in a row this is not a brain buster folks let's back this up what are the odds on any one coin toss 5050 right which means 500 times in a row probably gonna get somewhere in the ballpark of 250 heads 250 tails that's a reasonable thing to expect because the odds are 50/50 for every one toss if I have been on a streak if I flip a quarter 10 times in a row and it came up heads every time do you feel like maybe the next one is probably going to be tails yeah it feels like you're overdue yeah because eventually it's going to balance out right yeah this is what this fallacy praise this expectation that's like that streak is unnaturally strong it's got a break it's probably going to break this time the fact of the matter is though for any one coin toss the odds are 50/50 and this quarter doesn't remember the past like those past events have no influence on how this particular coin toss is going to turn out so just because I flip the coin 10 heads in a row does not mean that the next one is probably going to be tails doesn't mean that the next one is probably going to be heads either although 10 times in row you might start to be suspicious that like maybe this is not a fair coin maybe it's weighted funny you should expect the next one to be 50/50 and this is the sort of thing that like people who gamble poorly get suckered into they say ah that slot machines do to payout hasn't won in a while nope it's brand-new odds every time you pull the lever the roulette wheel hasn't turned up black in a while I'm betting on black why why there are just as many black slots as red slots on the wheel the odds are 50/50 every time you spin it over time we would expect that it'll balance out but that tells me nothing about any one particular instance somebody brought up an example in the last section about taking a multiple-choice test have you ever been in this situation where it's just kind of like question 1 the answer is C question 2 the answer is C question 3 like 5 season a row does this kind of freak you out when that happens and if you get to like question number 6 and you're kind of like see looks like a tempting answer but also a looks like a tempting answer are you inclined to think like we're probably a right because 6 sees in a row that's insane ya know those previous questions have nothing to do with what the with the correct answer is on question 6 right so let's not falsely assume that past trends are relevant to future events in some genuinely random system that's the gamblers fallacy questions about that all right good old friends slippery slope have you heard of this one before this slippery slope fallacy this is a nice one it gets used an awful lot and again what's kind of tempting and compelling about it is that it does kind of trade on an idea that that there's some serious truth to it sometimes folks will refer to oh the boiling frog phenomenon have you heard of this boiling frog phenomenon I don't even know if this is actually true but sometimes people talk about if you drop a frog in boiling water that frog is gonna jump right out of the boiling water it's gonna be like no thank you if you put a frog in room-temperature water and turn the heat up raise the temperature about 10 degrees slowly the Frog will get used to it and then if you turn it up a little more the Frog will get used to that and turn up a little more the Frog will get used to that you can if you do it slowly enough people say uh again I don't know if this is actually true but is it true have you done this have you seen this a humane way to kill a front yet you just alright alright either way I fear that I fear that we're getting off track here so the idea here is and sometimes this is referred to as the camels nose problem as well that like if and we all know how pesky a camel can be when you're in your tent if the camel gets its nose into the tent yeah well pretty soon it's going to get its whole head into the tent and once it's got its head into it into the tent then its neck is probably next and then it'll get its shoulders in and pretty soon the whole camels in the tan - and who wants that right better to just stop the camel like don't even let it get its nose in the tent right and maybe there's something reasonable about this and maybe there's some truth to the idea that if you make changes slowly enough people beaking can become kind of acclimatized to the change where they're going to be more receptive to the next change and then if we do that one now they'll become more receptive to the next change and eventually we might get led down a path where at the beginning we would have said like I don't want to go there but by the end of it like we went in little steps where nobody objected to any of the particular steps does that make sense and that's the sort of thing that we want to be careful about because people do have this tendency that like once you've gotten used to something the next little step doesn't seem so bad anymore at the same time just because a whole series of steps lead someplace bad doesn't mean that the first step is necessarily a bad idea for example physician assisted suicide should not be allowed if we were to allow patients to voluntarily in their own life with the aid of a medical professional it's just a matter of time before those medical professionals start recommending euthanasia to patients we've gone from allowing people to say I want my doctor to help me die too now the doctors are recommending to some patients that maybe they should consider physician assisted suicide once we've gotten there it's a small step to ending the lives of patients who can't communicate about their willingness to die or lack thereof so somebody who just like they can't speak or their unconscious they're in a persistent vegetative state we're gonna say like we don't know whether they want it or not but we'll look at it what say okay that wasn't seem like good life will kill them whether they request it or not and once that happens what's the stop doctors from deciding to kill patients who don't want to die at all that would be unacceptable the only reasonable option here is to not start to down this road to begin with it's true can we see from the boiling frog perspective that like if we took one step and if we got used to that the next one wouldn't seem as bad and the next one wouldn't seem as bad but where this becomes fallacious is we might say something like that slope isn't really all that slippery I can maybe spot exactly where it goes from okay to not okay where do you guys think is the physician assisted suicide is that okay raise your hand if you think physician like if a patient wants to die and they can't do it themselves should they be able to get their physician to help them do it in the most humane and least painful way some people say yes not everybody there all right cool what about the next step do you think it's okay that doctors should be able to recommend this or at least propose it as an option for their patients we got a little bit less what about the third step where we don't know what the patient wants so let it will let the doctor be the judge and say like alright we're gonna end this patients life because they they can't say no who thinks that one's okay maybe that's where we draw the line right maybe we say step one and step two or fine and somebody's like what's of stop us from going to step three and like we are we're all to stop us we're all deciding right now we'll do steps one and two but not step three that's where it goes from okay - not okay yeah and we might also point out that like step a version of step three already does happen yeah if it's withholding care if like if we're just kind of saying like we don't know what their wishes are they don't have a DNR but they don't also say like do whatever you can to like save me and they're comatose or they're in a persistent vegetative state we might pull the plug and a lot of people seem to think that like yeah that's one thing but making a positive intervention instead of just withholding care to like maybe give them an injection that's gonna stop their heart that's a different thing altogether and we might make we might make those discrete steps in this - we might say pulling the plug withholding care and we like that ones okay well what about positive interventions do we go that one's different than not okay and somebody might say the difference between the two is not very clear once we agree to one we might be inclined to agree to the other and we can say thanks for pointing that out we'll be careful about that we'll make sure that we don't slip just because the slope is slippery doesn't mean you're going to slip you can be mindful of the slipperiness and say like alright here's where we're gonna cut it off maybe we'll all sign a pledge that like we'll only go to step two no further and then once we get there we might say lagoon we want to go to step three yes morally relative do you mean do you mean that people are going to disagree about it ah I can think of a really really pretty like a very clear reason for why steps 1 & 2 are very very different than step 3 steps 1 & 2 allow the patient to make their own decisions step 3 doesn't let the patient make their own decision and that's maybe the most important part like I'm respecting the patient's autonomy in steps 1 & 2 but not in step 3 yes it is yes yeah if we if we start with any form of gun control then pretty soon the government's gonna come and take all your guns so no gun control at all you're like woah woah woah that's clearly a slippery slope argument yeah the slippery slope argument is saying and do we get like why it's called slippery slope it's saying like take one step on that slippery slope and pretty soon you're like sliding all the way down it because it's so slippery and some slopes are slippery and we should definitely be careful about them the structure of this fallacious argument is to say that because the end of the series of steps is unacceptable you shouldn't even take the first step and sometime why this is tricky is sometimes that's a reasonable sort of thing to say we shouldn't take the first step because it's going to be very difficult for us to stop ourselves from sliding from that first step all the way to the last one which we can all agree is unacceptable but if we can point out that like it's possible to not slide all the way down if we can say like here's a clear place to cut it off then it seems like that argument shouldn't necessarily be compelling here's another reason that's more about kind of like induction more like more kind of directly targeting induction especially the mathematical and statistical aspects of induction that relates to slippery slopes as well so let's kind of strip away any of like the content in this example let's just say I'm gonna take step a step B step C and step D and let's say that looking at step a and we're wondering like what are the chances that we think that like people are going to want to take step a and we'll say there's a 90% chance that people are gonna want to take step a and once they've taken step a how likely is it that we think that folks are gonna want to take step B and we say there's a 90% chance once they've taken step a folks are gonna want to take step B once they've taken step B what are the chances that they're gonna want to take step C mostly if there's a 90% chance that they'll take step C once they've done that what's the chance about step D what do you think 90% chance 90% chance they'll take step D all those chances looked really likely right each of those steps looked incredibly likely is there a 90% chance that we'll go all the way through yeah it's not quite but it's a yeah it's definitely bad statistics 90% chance of taking one step and then a 90% chance of the next step and then the next step is 90% chance and then the next step is night what's the chances of doing all four steps how would you determine this 90 percent times 90 percent times 90 percent times 90 percent which is 9 it's not 9 times 4 it's 9 x 9 x 9 x 9 65% chance yet there's a 65% chance of doing all 4 of the steps do we see how that looked way more likely than it actually is that looked like each of those steps was very likely but doing them all in a row considerably less likely 65% chance is a better chance than not but maybe not enough to be super confident in depending on what's on the line so this is a more of a statistical approach to the problem that's going on in a slippery slope it's that we somehow think that because each of the steps is probable that the whole concatenation of steps is also probably no that's not how probabilities work it's not how math works that's our friend slippery slope last but not least false cause fallacy false cause fallacy because we're running a little short on time I'm only gonna gesture vaguely this because we haven't started talking about causal arguments at all and that's what we're doing next week we're gonna talk about arguments where we say I think that this thing is causing this other thing and that's my conclusion they're growing we're gonna wonder like what sorts of premises are gonna make that sort of conclusion reasonable and here are some of the mistakes that we can make when we make those sorts of arguments I can engage in what's known as a post hoc ergo propter hoc fallacy literally this means after which therefore because of which this is a great example that demonstrates just how silly it is to say that just because one thing happens after another it must have been caused by the first thing every morning my neighbor's rooster crows and then about 30 minutes later the Sun rises I think it's safe to assume that the rooster is causing the Sunter not necessarily right okay so here's one where we can confuse cause and effect that just because two things seem to happen coincidentally just because they tend to come together and maybe they are even causally related to one another I don't necessarily know that a is causing B or B is causing a right I don't necessarily know which direction the causation runs we'll talk about that a little bit next week and like whether it whether or not we can try to figure out which way that causation runs the common cause fallacy is when I notice that two things seem to be causally linked and therefore I think that one is a cause of the other or the other is the cause of the one when in fact what's going on is there some third thing that's causing them both a nice example of this is when we're talking about disease symptoms so first I got a fever and then later I started getting these blisters all over my skin I think the fever caused the blisters this is not like the rooster making the Sun crow up nests what Sun come up the rooster crowing making the Sun come up maybe it is similar to that actually is the fever causing the blisters are the blisters causing the fever are they causally related at all is there a virus that's causing both the fever and the blisters that's what it is right they have some common cause they're not one is not causing the other they're both caused by some third thing and that's not least we can talk about a complex cause fallacy this involves reducing kind of oversimplifying some kind of causal phenomenon to just saying like there's one thing that's causing the effect when the truth is most of the times when something is caused there are a whole bunch of contributing causes all coming together to make the effect happen right if you hadn't been trying to cross the street then you wouldn't have been hit by that car so I think that we can safely say that you are responsible for this accident and not the driver yes you're causing the street was a contributing factor perhaps the driver talking on their phone while driving was another contributing factor and maybe a more important one when we're attributing responsibility right okay those are all false cause fallacy they're a member of the bigger family of fallacies of weak induction which are just you know another family of all the fallacies that we've been discussing in general you've got a worksheet we are down to zero time left would you mind hanging on just for a second so we can go through just a couple of these worksheet questions because the homework is gonna be really really similar okay so take a look at number one see if you can identify what fallacy is being committed there and what family it belongs to what do you think you got an answer was that too fast repeated studies have shown that men are on average physically stronger than women are on average is that true I think that's fairly safe to say and I like I don't want to seem like sexist or something but I think this is a biological fact Stephen Hawking's a man and Venus Williams is a woman therefore I think it's safe to conclude that Stephen Hawking is probably physically stronger than Venus Williams what's going on there I started out with a general rule about men on average being stronger than women on average that general rule is fine does it have exceptional cases am I somehow assuming that Stephen Hawking and Venus Williams are not exceptional cases so I'm applying a general rule without sensitivity to whether or not the case in question is an exception to the rule or fits the rule which fallacy is that accident ache a sweeping generalization right this is a badly done statistical syllogism and that is a sweeping generalization fallacy belongs to the fallacy of weak induction family let's look at number two real quick and then then we'll all start our weekends my friend takes the city bus to school every day and it usually takes about ten minutes to get from his house to campus I drive to work every day and it also takes me about ten minutes to get home from campus to get from home to campus we all know that the city buses don't break the speed limit so you can see officer I can't have been speeding as I was probably going just as fast as the city buses what kind of argument is this trying to be it's an analogy yeah it's tempting to be an analogical induction are there similarities between the two cases yeah hmm my friend goes on the bus and doesn't break the speed limit it takes him ten minutes I take ten minutes to therefore I must not have been breaking the speed limit that might be irrelevant similarly what's the important relevant difference that might be overlooked here the distance between my house and the campus and my friends house and the campus right yeah okay if I live twice as far away from him if I'm gonna make that in the same amount of time I'm gonna go twice as fast and possibly break the speed limit that makes it a bad analogy a weak analogy which is a member of the family of fallacies of weak induction your homework is going to be similar to this it'll be multiple choice I'll hit you with an argument I'll ask you which fallacy is being committed and so good luck with that and good luck with the argument analysis draft number one and enjoy your weekend

Channel: Adam Rosenfeld

Views: 1,041

Keywords: Critical Thinking, Fallacies, Fallacies of Weak Induction

Id: X1SN3xBTSYw

Length: 44min 35sec (2675 seconds)

Published: Mon Jul 16 2018