Poisoning the Well

Description:

This sort of “reasoning” involves trying to discredit what a person might later claim by presenting unfavorable information (be it true or false) about the person. This “argument” has the following form:

1. Unfavorable information (be it true or false) about person A is presented.

2. Therefore any claims person A makes will be false.

This sort of “reasoning” is obviously fallacious.The person making such an attack is hoping that the unfavorable information will bias listeners against the person in question and hence that they will reject any claims he might make. However, merely presenting unfavorable information about a person (even if it is true) hardly counts as evidence against the claims he/she might make. This is especially clear when Poisoning the Well is looked at as a form of ad Hominem in which the attack is made prior to the person even making the claim or claims. The following example clearly shows that this sort of “reasoning” is quite poor.

Example #1

“Don’t listen to him, he’s a scoundrel.”

Example #2

“Before turning the floor over to my opponent, I ask you to remember that those who oppose my plans do not have the best wishes of the university at heart.”

Example #3

You are told, prior to meeting him, that your friend’s boyfriend is a decadent wastrel. When you meet him, everything you hear him say is tainted.

Example #4

Before class

Bill: “Boy, that professor is a real jerk. I think he is some sort of Eurocentric fascist.”

Jill: “Yeah.”

During Class:

Prof. Jones: “…and so we see that there was never any ‘Golden Age of Matriarchy’ in 1895 in America.”

After Class:

Bill: “See what I mean?”

Jill: “Yeah. There must have been a Golden Age of Matriarchy, since that jerk said there wasn’t.”

Personal Attack

Also Known as: Ad Hominem Abusive

Description:

A personal attack is committed when a person substitutes abusive remarks for evidence when attacking another person’s claim or claims. This line of “reasoning” is fallacious because the attack is directed at the person making the claim and not the claim itself. The truth value of a claim is independent of the person making the claim. After all, no matter how repugnant an individual might be, he or she can still make true claims.

Not all ad Hominems are fallacious. In some cases, an individual’s characteristics can have a bearing on the question of the veracity of her claims. For example, if someone is shown to be a pathological liar, then what he says can be considered to be unreliable. However, such attacks are weak, since even pathological liars might speak the truth on occasion.

In general, it is best to focus one’s attention on the content of the claim and not on who made the claim. It is the content that determines the truth of the claim and not the characteristics of the person making the claim.

Example #1

In a school debate, Bill claims that the President’s economic plan is unrealistic. His opponent, a professor, retorts by saying “the freshman has his facts wrong.”

Example #2

“This theory about a potential cure for cancer has been introduced by a doctor who is a known lesbian feminist. I don’t see why we should extend an invitation for her to speak at the World Conference on Cancer.”

Example #3

“Bill says that we should give tax breaks to companies. But he is untrustworthy, so it must be wrong to do that.”

Example #4

“That claim cannot be true. Dave believes it, and we know how morally repulsive he is.”

Example #5

“Bill claims that Jane would be a good treasurer. However I find Bill’s behavior offensive, so I’m not going to vote for Jill.”

Example #6

“Jane says that drug use is morally wrong, but she is just a goody-two shoes Christian, so we don’t have to listen to her.”

Example #7

Bill: “I don’t think it is a good idea to cut social programs.”

Jill: “Why not?”

Bill: “Well, many people do not get a fair start in life and hence need some help. After all, some people have wealthy parents and have it fairly easy. Others are born into poverty and…”

Jill: “You just say that stuff because you have a soft heart and an equally soft head.”

Peer Pressure

Description:

Peer Pressure is a fallacy in which a threat of rejection by one’s peers (or peer pressure) is substituted for evidence in an “argument.” This line of “reasoning” has the following form:

1. Person P is pressured by his/her peers or threatened with rejection.

2. Therefore person P’s claim X is false.

This line of “reasoning” is fallacious because peer pressure and threat of rejection do not constitute evidence for rejecting a claim. This is especially clear in the following example:

Joe: “Bill, I know you think that 1+1=2. But we don’t accept that sort of thing in our group.”

Bill: “I was just joking. Of course I don’t believe that.”

It is clear that the pressure from Bill’s group has no bearing on the truth of the claim that 1+1=2.

It should be noted that loyalty to a group and the need to belong can give people very strong reasons to conform to the views and positions of those groups. Further, from a practical standpoint we must often compromise our beliefs in order to belong to groups. However, this feeling of loyalty or the need to belong simply do not constitute evidence for a claim.

Example #1

Bill says that he likes the idea that people should work for their welfare when they can. His friends laugh at him, accuse him of fascist leanings, and threaten to ostracize him from their group. He decides to recant and abandon his position to avoid rejection.

Example #2

Bill: “I like classical music and I think it is of higher quality than most modern music.”

Jill: “That stuff is for old people.”

Dave: “Yeah, only real sissy monkeys listen to that crap. Besides, Anthrax rules! It Rules!”

Bill: “Well, I don’t really like it that much. Anthrax is much better.”

Example #3

Bill thinks that welfare is needed in some cases. His friends in the Young Republicans taunt him every time he makes his views known. He accepts their views in order to avoid rejection.

Misleading Vividness

Description:

Misleading Vividness is a fallacy in which a very small number of particularly dramatic events are taken to outweigh a significant amount of statistical evidence. This sort of “reasoning” has the following form:

1. Dramatic or vivid event X occurs (and is not in accord with the majority of the statistical evidence) .

2. Therefore events of type X are likely to occur.

This sort of “reasoning” is fallacious because the mere fact that an event is particularly vivid or dramatic does not make the event more likely to occur, especially in the face of significant statistical evidence.

People often accept this sort of “reasoning” because particularly vivid or dramatic cases tend to make a very strong impression on the human mind. For example, if a person survives a particularly awful plane crash, he might be inclined to believe that air travel is more dangerous than other forms of travel. After all, explosions and people dying around him will have a more significant impact on his mind than will the rather dull statistics that a person is more likely to be struck by lightning than killed in a plane crash.

It should be kept in mind that taking into account the possibility of something dramatic or vivid occurring is not always fallacious. For example, a person might decide to never go sky diving because the effects of an accident can be very, very dramatic. If he knows that, statistically, the chances of the accident are happening are very low but he considers even a small risk to be unacceptable, then he would not be making an error in reasoning.

Example #1

Bill and Jane are talking about buying a computer.

Jane: “I’ve been thinking about getting a computer. I’m really tired of having to wait in the library to write my papers.”

Bill: ‘What sort of computer do you want to get?”

Jane: “Well, it has to be easy to use, have a low price and have decent processing power. I’ve been thinking about getting a Kiwi Fruit 2200. I read in that consumer magazine that they have been found to be very reliable in six independent industry studies.”

Bill: “I wouldn’t get the Kiwi Fruit. A friend of mine bought one a month ago to finish his master’s thesis. He was halfway through it when smoke started pouring out of the CPU. He didn’t get his thesis done on time and he lost his financial aid. Now he’s working over at the Gut Boy Burger Warehouse.”

Jane: “I guess I won’t go with the Kiwi!”

Example #2

Joe and Drew are talking about flying.

Joe: “When I was flying back to school, the pilot came on the intercom and told us that the plane was having engine trouble. I looked out the window and I saw smoke billowing out of the engine nearest me. We had to make an emergency landing and there were fire trucks everywhere. I had to spend the next six hours sitting in the airport waiting for a flight. I was lucky I didn’t die! I’m never flying again.”

Drew: “So how are you going to get home over Christmas break?”

Joe: “I’m going to drive. That will be a lot safer than flying.”

Drew: “I don’t think so. You are much more likely to get injured or killed driving than flying.”

Joe: “I don’t buy that! You should have seen the smoke pouring out of that engine! I’m never getting on one of those death traps again!”

Example #3

Jane and Sarah are talking about running in a nearby park.

Jane: “Did you hear about that woman who was attacked in Tuttle Park?”

Sarah: “Yes. It was terrible.”

Jane: “Don’t you run there every day?”

Sarah: “Yes.”

Jane: ‘How can you do that? I’d never be able to run there!”

Sarah: “Well, as callous as this might sound, that attack was out of the ordinary. I’ve been running there for three years and this has been the only attack. Sure, I worry about being attacked, but I’m not going give up my running just because there is some slight chance I’ll be attacked.”

Sarah: “That is stupid! I’d stay away from that park if I was you! That woman was really beat up badly so you know it is going to happen again. If you don’t stay out of that park, it will  happen to you!”

Middle Ground

Also Known as: Golden Mean Fallacy, Fallacy of Moderation

Description:

This fallacy is committed when it is assumed that the middle position between two extremes must be correct simply because it is the middle position. this sort of “reasoning” has the following form:

1. Position A and B are two extreme positions.

2. C is a position that rests in the middle between A and B.

3. Therefore C is the correct position.

This line of “reasoning” is fallacious because it does not follow that a position is correct just because it lies in the middle of two extremes. This is shown by the following example. Suppose that a person is selling his computer. He wants to sell it for the current market value, which is $800 and someone offers him $1 for it. It would hardly follow that $400.50 is the proper price.

This fallacy draws its power from the fact that a moderate or middle position is often the correct one. For example, a moderate amount of exercise is better than too much exercise or too little exercise. However, this is not simply because it lies in the middle ground between two extremes. It is because too much exercise is harmful and too little exercise is all but useless. The basic idea behind many cases in which moderation is correct is that the extremes are typically “too much” and “not enough” and the middle position is “enough.” In such cases the middle position is correct almost by definition.

It should be kept in mind that while uncritically assuming that the middle position must be correct because it is the middle position is poor reasoning it does not follow that accepting a middle position is always fallacious. As was just mentioned, many times a moderate position is correct. However, the claim that the moderate or middle position is correct must be supported by legitimate reasoning.

Example #1

Some people claim that God is all powerful, all knowing, and all good. Other people claim that God does not exist at all. Now, it seems reasonable to accept a position somewhere in the middle. So, it is likely that God exists, but that he is only very powerful, very knowing, and very good. That seems right to me.

Example #2

Congressman Jones has proposed cutting welfare payments by 50% while Congresswoman Shender has proposed increasing welfare payments by 10% to keep up with inflation and cost of living increases. I think that the best proposal is the one made by Congressman Trumple. He says that a 30% decrease in welfare payments is a good middle ground, so I think that is what we should support.

Example #3

A month ago, a tree in Bill’s yard was damaged in a storm. His neighbor, Joe, asked him to have the tree cut down so it would not fall on Joe’s new shed. Bill refused to do this. Two days later another storm blew the tree onto Joe’s new shed. Joe demanded that Joe pay the cost of repairs, which was $250. Bill said that he wasn’t going to pay a cent. Obviously, the best solution is to reach a compromise between the two extremes, so Bill should pay Joe $125.

Ignoring a Common Cause

Also Known as: Questionable Cause

Description:

This fallacy has the following general structure:

1) A and B are regularly connected (but no third, common cause is looked for).

2) Therefore A is the cause of B.

This fallacy is committed when it is concluded that one thing causes another simply because they are regularly associated. More formally, this fallacy is committed when it is concluded that A is the cause of B simply because A and B are regularly connected. Further, the causal conclusion is drawn without considering the possibility that a third factor might be the cause of both A and B.

In many cases, the fallacy is quite evident. For example, if a person claimed that a person’s sneezing was caused by her watery eyes and he simply ignored the fact that the woman was standing in a hay field, he would have fallen prey to the fallacy of ignoring a common cause. In this case, it would be reasonable to conclude that the woman’s sneezing and watering eyes was caused by an allergic reaction of some kind. In other cases, it is not as evident that the fallacy is being committed. For example, a doctor might find a large amount of bacteria in one of her patients and conclude that the bacteria are the cause of the patient’s illness. However, it might turn out that the bacteria are actually harmless and that a virus is weakening the person, Thus, the viruses would be the actual cause of the illness and growth of the bacteria (the viruses would weaken the ability of the person’s body to resist the growth of the bacteria).

As noted in the discussion of other causal fallacies, causality is a rather difficult matter. However, it is possible to avoid this fallacy by taking due care. In the case of Ignoring a Common Cause, the key to avoiding this fallacy is to be careful to check for other factors that might be the actual cause of both the suspected cause and the suspected effect. If a person fails to check for the possibility of a common cause, then they will commit this fallacy. Thus, it is always a good idea to always ask “could there be a third factor that is actually causing both A and B?”

Example #1

One day Bill wakes up with a fever. A few hours later he finds that his muscles are sore. He concludes that the fever must have caused the soreness. His friend insists that the soreness and the fever are caused by some microbe. Bill laughs at this and insists that if he spends the day in a tub of cold water his soreness will go away.

Example #2

Over the course of several weeks the leaves from the trees along the Wombat river fell into the water. Shortly thereafter, many dead fish were seen floating in the river. When the EPA investigated, the owners of the Wombat River Chemical Company claimed that is it was obvious that the leaves had killed the fish. Many local environmentalists claimed that the chemical plant’s toxic wastes caused both the trees and the fish to die and that the leaves had no real effect on the fish.

Example #3

A thunderstorm wakes Joe up in the middle of the night. He goes downstairs to get some milk to help him get back to sleep. On the way to the refrigerator, he notices that the barometer has fallen a great deal. Joe concludes that the storm caused the barometer to fall. In the morning he tells his wife about his conclusion. She tells him that it was a drop in atmospheric pressure that caused the barometer to drop and the storm.

Hasty Generalization

Also Known as: Fallacy of Insufficient Statistics, Fallacy of Insufficient Sample, Leaping to A Conclusion, Hasty Induction

Description:

This fallacy is committed when a person draws a conclusion about a population based on a sample that is not large enough. It has the following form:

1. Sample S, which is too small, is taken from population P.

2. Conclusion C is drawn about Population P based on S.

The person committing the fallacy is misusing the following type of reasoning, which is known variously as Inductive Generalization, Generalization, and Statistical Generalization:

1. X% of all observed A’s are B’s.

2. Therefore X% of all A’s are B’s.

The fallacy is committed when not enough A’s are observed to warrant the conclusion. If enough A’s are observed then the reasoning is not fallacious.

Small samples will tend to be unrepresentative. As a blatant case, asking one person what she thinks about gun control would clearly not provide an adequate sized sample for determining what Canadians in general think about the issue. The general idea is that small samples are less likely to contain numbers proportional to the whole population. For example, if a bucket contains blue, red, green and orange marbles, then a sample of three marbles cannot possible be representative of the whole population of marbles. As the sample size of marbles increases the more likely it becomes that marbles of each color will be selected in proportion to their numbers in the whole population. The same holds true for things others than marbles, such as people and their political views.

Since Hasty Generalization is committed when the sample (the observed instances) is too small, it is important to have samples that are large enough when making a generalization. The most reliable way to do this is to take as large a sample as is practical. There are no fixed numbers as to what counts as being large enough. If the population in question is not very diverse (a population of cloned mice, for example) then a very small sample would suffice. If the population is very diverse (people, for example) then a fairly large sample would be needed. The size of the sample also depends on the size of the population. Obviously, a very small population will not support a huge sample. Finally, the required size will depend on the purpose of the sample. If Bill wants to know what Joe and Jane think about gun control, then a sample consisting of Bill and Jane would (obviously) be large enough. If Bill wants to know what most Australians think about gun control, then a sample consisting of Bill and Jane would be far too small.

People often commit Hasty Generalizations because of bias or prejudice. For example, someone who is a sexist might conclude that all women are unfit to fly jet fighters because one woman crashed one. People also commonly commit Hasty Generalizations because of laziness or sloppiness. It is very easy to simply leap to a conclusion and much harder to gather an adequate sample and draw a justified conclusion. Thus, avoiding this fallacy requires minimizing the influence of bias and taking care to select a sample that is large enough.

One final point: a Hasty Generalization, like any fallacy, might have a true conclusion. However, as long as the reasoning is fallacious there is no reason to accept the conclusion based on that reasoning.

Example #1

Smith, who is from England, decides to attend graduate school at Ohio State University. He has never been to the US before. The day after he arrives, he is walking back from an orientation session and sees two white (albino) squirrels chasing each other around a tree. In his next letter home, he tells his family that American squirrels are white.

Example #2

Sam is riding her bike in her home town in Maine, minding her own business. A station wagon comes up behind her and the driver starts beeping his horn and then tries to force her off the road. As he goes by, the driver yells “get on the sidewalk where you belong!” Sam sees that the car has Ohio plates and concludes that all Ohio drivers are jerks.

Example #3

Bill: “You know, those feminists all hate men.”

Joe: “Really?”

Bill: “Yeah. I was in my philosophy class the other day and that Rachel chick gave a presentation.”

Joe: “Which Rachel?”

Bill: “You know her. She’s the one that runs that feminist group over at the Women’s Center. She said that men are all sexist pigs. I asked her why she believed this and she said that her last few boyfriends were real sexist pigs.”

Joe: “That doesn’t sound like a good reason to believe that all of us are pigs.”

Bill: “That was what I said.”

Joe: “What did she say?”

Bill: “She said that she had seen enough of men to know we are all pigs. She obviously hates all men.”

Joe: “So you think all feminists are like her?”

Bill: “Sure. They all hate men.”

Guilt by Association

Also Known as: Bad Company Fallacy, Company that You Keep Fallacy

Description:

Guilt by Association is a fallacy in which a person rejects a claim simply because it is pointed out that people she dislikes accept the claim. This sort of “reasoning” has the following form:

1. It is pointed out that person A accepts claim P.

2. Therefore P is false

It is clear that sort of “reasoning” is fallacious. For example the following is obviously a case of poor “reasoning”: “You think that 1+1=2. But, Adolf Hitler, Charles Manson, Joseph Stalin, and Ted Bundy all believed that 1+1=2. So, you shouldn’t believe it.”

The fallacy draws its power from the fact that people do not like to be associated with people they dislike. Hence, if it is shown that a person shares a belief with people he dislikes he might be influenced into rejecting that belief. In such cases the person will be rejecting the claim based on how he thinks or feels about the people who hold it and because he does not want to be associated with such people.

Of course, the fact that someone does not want to be associated with people she dislikes does not justify the rejection of any claim. For example, most wicked and terrible people accept that the earth revolves around the sun and that lead is heavier than helium. No sane person would reject these claims simply because this would put them in the company of people they dislike (or even hate).

Example #1

Will and Kiteena are arguing over socialism. Kiteena is a pacifist and hates violence and violent people.

Kiteena: “I think that the United States should continue to adopt socialist programs. For example, I think that the government should take control of vital industries.”

Will: “So, you are for state ownership of industry.”

Kiteena: “Certainly. It is a great idea and will help make the world a less violent place.”

Will: “Well, you know Stalin also endorsed state ownership on industry. At last count he wiped out millions of his own people. Pol Pot of Cambodia was also for state ownership of industry. He also killed millions of his own people. The leadership of China is for state owned industry. They killed their own people in that square. So, are you still for state ownership of industry?”

Kiteena: “Oh, no! I don’t want to be associated with those butchers!”

Example #2

Jen and Sandy are discussing the topic of welfare. Jen is fairly conservative politically but she has been an active opponent of racism. Sandy is extremely liberal politically.

Jen: “I was reading over some private studies of welfare and I think it would be better to have people work for their welfare. For example, people could pick up trash, put up signs, and maybe even do skilled labor that they are qualified for. This would probably make people feel better about themselves and it would get more out of our tax money.”

Sandy: “I see. So, you want to have the poor people out on the streets picking up trash for their checks? Well, you know that is exactly the position David Count endorses.”

Jen: “Who is he?”

Sandy: “I’m surprised you don’t know him, seeing how alike you two are. He was a Grand Mooky Wizard for the Aryan Pure White League and is well known for his hatred of blacks and other minorities. With your views, you’d fit right in to his little racist club.”

Jen: “So, I should reject my view just because I share it with some racist?”

Sandy: “Of course.”

Example #3

Libard and Ferris are discussing who they are going to vote for as the next department chair in the philosophy department. Libard is a radical feminist and she despises Wayne and Bill, who are two sexist professors in the department.

Ferris: “So, who are you going to vote for?”

Libard: ‘Well, I was thinking about voting for Jane, since she is a woman and there has never been a woman chair here. But, I think that Steve will do an excellent job. He has a lot of clout in the university and he is a decent person.”

Ferris: “You know, Wayne and Bill are supporting him. They really like the idea of having Steve as the new chair. I never thought I’d see you and those two pigs on the same side.”

Libard: “Well, maybe it is time that we have a woman as chair.”

Genetic Fallacy

Description:

A Genetic Fallacy is a line of “reasoning” in which a perceived defect in the origin of a claim or thing is taken to be evidence that discredits the claim or thing itself. It is also a line of reasoning in which the origin of a claim or thing is taken to be evidence for the claim or thing. This sort of “reasoning” has the following form:

1. The origin of a claim or thing is presented.

2. The claim is true(or false) or the thing is supported (or discredited).

It is clear that sort of “reasoning” is fallacious. For example: “Bill claims that 1+1=2. However, my parents brought me up to believe that 1+1=254, so Bill must be wrong.”

It should be noted that there are some cases in which the origin of a claim is relevant to the truth or falsity of the claim. For example, a claim that comes from a reliable expert is likely to be true (provided it is in her area of expertise).

Example #1

“Yeah, the environmentalists do claim that over-development can lead to all kinds of serious problems. But we all know about those darn bunny huggers and their silly views!.”

Example #2

“I was brought up to believe in God, and my parents told me God exists, so He must.”

Example #3

“Sure, the media claims that Senator Bedfellow was taking kickbacks. But we all know about the media’s credibility, don’t we.”

Gambler’s Fallacy

Description:

The Gambler’s Fallacy is committed when a person assumes that a departure from what occurs on average or in the long term will be corrected in the short term. The form of the fallacy is as follows:

1. X has happened.

2. X departs from what is expected to occur on average or over the long term.

3. Therefore, X will come to an end soon.

There are two common ways this fallacy is committed. In both cases a person is assuming that some result must be “due” simply because what has previously happened departs from what would be expected on average or over the long term.

The first involves events whose probabilities of occurring are independent of one another. For example, one toss of a fair (two sides, non-loaded) coin does not affect the next toss of the coin. So, each time the coin is tossed there is (ideally) a 50% chance of it landing heads and a 50% chance of it landing tails. Suppose that a person tosses a coin 6 times and gets a head each time. If he concludes that the next toss will be tails because tails “is due”, then he will have committed the Gambler’s Fallacy. This is because the results of previous tosses have no bearing on the outcome of the 7th toss. It has a 50% chance of being heads and a 50% chance of being tails, just like any other toss.

The second involves cases whose probabilities of occurring are not independent of one another. For example, suppose that a boxer has won 50% of his fights over the past two years. Suppose that after several fights he has won 50% of his matches this year, that he his lost his last six fights and he has six left. If a person believed that he would win his next six fights because he has used up his losses and is “due” for a victory, then he would have committed the Gambler’s Fallacy. After all, the person would be ignoring the fact that the results of one match can influence the results of the next one. For example, the boxer might have been injured in one match which would lower his chances of winning his last six fights.

It should be noted that not all predictions about what is likely to occur are fallacious. If a person has good evidence for his predictions, then they will be reasonable to accept. For example, if a person tosses a fair coin and gets nine heads in a row it would be reasonable for him to conclude that he will probably not get another nine in a row again. This reasoning would not be fallacious as long as he believed his conclusion because of an understanding of the laws of probability. In this case, if he concluded that he would not get another nine heads in a row because the odds of getting nine heads in a row are lower than getting fewer than nine heads in a row, then his reasoning would be good and his conclusion would be justified. Hence, determining whether or not the Gambler’s Fallacy is being committed often requires some basic understanding of the laws of probability.

Example #1

Bill is playing against Doug in a WWII tank battle game. Doug has had a great “streak of luck” and has been killing Bill’s tanks left and right with good die rolls. Bill, who has a few tanks left, decides to risk all in a desperate attack on Doug. He is a bit worried that Doug might wipe him out, but he thinks that since Doug’s luck at rolling has been great Doug must be due for some bad dice rolls. Bill launches his attack and Doug butchers his forces.

Example #2

Jane and Bill are talking:

Jane: “I’ll be able to buy that car I always wanted soon.”

Bill: “Why, did you get a raise?”

Jane: “No. But you know how I’ve been playing the lottery all these years?”

Bill: “Yes, you buy a ticket for every drawing, without fail.”

Jane: “And I’ve lost every time.”

Bill: “So why do you think you will win this time?”

Jane: “Well, after all those losses I’m due for a win.”

Example #3

Joe and Sam are at the race track betting on horses.

Joe: “You see that horse over there? He lost his last four races. I’m going to bet on him.”

Sam: ‘Why? I think he will probably lose.”

Joe: “No way, Sam. I looked up the horse’s stats and he has won half his races in the past two years. Since he has lost three of his last four races, he’ll have to win this race. So I’m betting the farm on him.”

Sam: “Are you sure?”

Joe: “Of course I’m sure. That pony is due, man…he’s due!”