Category: Fallacies

 

This is from my book 110 Fallacies.

Also Known as: Misuse of Authority, Irrelevant Authority, Questionable Authority, Inappropriate Authority, Ad Verecundiam

Description:

The fallacious Appeal to Authority is a fallacy of standards rather than a structural fallacy. A fallacious Appeal to Authority has the same form as a strong Argument from Authority. As such, determining when this fallacy occurs is a matter of assessing an Argument from Authority to see if it meets the standards presented below. The general form of the reasoning is as follows:

 

Premise 1: Person A is (claimed to be) an authority on subject S.

Premise 2: Person A makes claim C about subject S.

Conclusion: Therefore, C is true.

 

This reasoning is fallacious when person A is not qualified to make reliable claims in subject S. In such cases the reasoning is flawed because the fact that an unqualified person makes a claim does not provide any justification for the claim. The claim could be true, but the fact that an unqualified person made the claim does not provide any rational reason to accept the claim as true.

When a person falls prey to this fallacy, they are accepting a claim as true without having adequate evidence. More specifically, the person is accepting the claim because they erroneously believe the person making the claim is an expert. Since people tend to believe people they think are authorities this fallacy is common one.

Since this sort of reasoning is fallacious only when the person is not a legitimate authority in a particular context, it is necessary to provide the standards/criteria for assessing the strength of this argument. The following standards provide a guide to such an assessment:

 

1. The person has sufficient expertise in the subject matter in question.

Claims made by a person who lacks the needed degree of expertise to make a reliable claim are not well supported. In contrast, claims made by a person with the needed expertise will be supported by the person’s competence in the area.

Determining whether a person has the needed degree of expertise can be very difficult. In academic fields (such as philosophy, engineering, and chemistry), a person’s formal education, academic performance, publications, membership in professional societies, papers presented, awards won and so forth can all be reliable indicators of expertise. Outside of academic fields, other standards will apply. For example, having sufficient expertise to make a reliable claim about how to tie a shoelace only requires the ability to tie the shoelace. Being an expert does not always require having a university degree. Many people have high degrees of expertise in sophisticated subjects without having ever attended a university. Further, it should not be assumed that a person with a degree must be an expert.

What is required to be an expert is often a matter of debate. For example, some people claim expertise because of a divine inspiration or a special gift. The followers of such people accept such credentials as establishing the person’s expertise while others often see these self-proclaimed experts as deluded or even as charlatans. In other situations, people debate rationally over what sort of education and experience is needed to be an expert. Thus, what one person may take to be a fallacious appeal another person might take to be a well-supported line of reasoning.

2. The claim being made by the person is within their area(s) of expertise.

A person making a claim outside of their area(s) of expertise should not be considered an expert in that area. So, that claim is not backed expertise and should not be accepted based on an Appeal to Authority.

Because of the vast scope of human knowledge, it is impossible for a person to be an expert on everything or even many things. So, an expert will only be an expert in certain subject areas. In most other areas they will have little or no expertise. Thus, it is important to determine what subject a claim falls under.

Expertise in one area does not automatically confer expertise in another area, even if they are related. For example, being an expert physicist does not make a person an expert on morality or politics. Unfortunately, this is often overlooked or intentionally ignored. In fact, advertising often rests on a violation of this condition. Famous actors and sports heroes often endorse products that they are not qualified to assess. For example, a person may be a famous actor, but that does not automatically make them an expert on cars or reverse mortgages.

3. There is an adequate degree of agreement among the other experts in the subject in question.

If there is significant legitimate dispute between qualified experts, then it will be fallacious to make an Appeal to Authority using the disputing experts. This is because for almost any claim being made by one expert there will be a counterclaim made by another expert. In such cases an Appeal to Authority would tend to be futile. In such cases, the dispute must be settled by consideration of the issues under dispute. Since all sides in such a dispute can invoke qualified experts, the dispute cannot be rationally settled by an Argument from Authority.

There are many fields in which there is significant reasonable dispute. Economics, ethics, and law are all good examples of such disputed fields. For example, trying to settle an ethical issue by appealing to the expertise of one ethicist can easily be countered by pointing to an equally qualified expert who disagrees.

No field has complete agreement, and some degree of dispute is acceptable. How much is acceptable is, of course, a matter of debate. Even a field with a great deal of dispute might contain areas of significant agreement. In such cases, an Argument from Authority could be a good argument. For example, while philosophers disagree on most things, there is a consensus among the experts about basic logic. As such, appealing to the authority of an expert on logic in a matter of logic would generally be a strong Argument from Authority.

When it comes to claims that most of the qualified experts agree on, the rational thing for a non-expert to do is to accept that the claim is probably true. After all, a non-expert is not qualified to settle to question of which experts are correct and the majority of qualified experts is more likely to be right than the numerical minority. Non-experts often commit this fallacy because they wrongly think that because they prefer the claim of the minority of experts, it follows that those experts must be right.

4. The person in question is not significantly biased.

If an expert is significantly biased, then the claims they makes will be less credible. So, an Argument from Authority based on a biased expert will tend to be fallacious. This is because the evidence will usually not justify accepting the claim.

Experts, being people, are vulnerable to biases and prejudices. If there is evidence that a person is biased in some manner that would affect the reliability of their claims, then an Argument from Authority based on that person is likely to be fallacious. Even if the claim is true, the fact that the expert is biased weakens the argument. This is because there would be reason to believe that the expert might not be making the claim because they have carefully considered it using their expertise. Rather, there would be reason to believe that the claim is being made because of the expert’s bias or prejudice.

No person is completely objective. At the very least, a person will be favorable towards their own views (otherwise they would not hold them). Because of this, some degree of bias must be accepted, provided it is not significant. What counts as a significant degree of bias is open to dispute and can vary a great deal from case to case. For example, many people would probably suspect that doctors who were paid by tobacco companies to research the effects of smoking would be biased while other people might believe (or claim) that they would be able to remain objective.

5. The area of expertise is a legitimate area or discipline.

Certain areas in which a person may claim expertise may have no legitimacy or validity as areas of knowledge. Obviously, claims made in such areas tend to lack credibility.

What counts as a legitimate area of expertise can be difficult to determine. However, there are cases which are clear cut. For example, if a person claimed to be an expert at something they called “chromabullet therapy” and asserted that firing painted rifle bullets at a person would cure cancer it would not be unreasonable to accept their claim based on their “expertise.” After all, their expertise is in an area which has no legitimate content. The general idea is that to be a legitimate expert a person must have mastery over a real field or area of knowledge.

As noted above, determining the legitimacy of a field can often be difficult. In European history, various scientists had to struggle with the Church and established traditions to establish the validity of their disciplines. For example, experts on evolution faced an uphill battle in getting the legitimacy of their area accepted.

A modern example involves psychic phenomenon. Some people claim that they are certified “master psychics” and that they are experts in the field. Other people contend that their claims of being certified “master psychics” are simply absurd since there is no real content to such an area of expertise. If these people are right, then anyone who accepts the claims of these “master psychics” are victims of a fallacious Appeal to Authority.

6. The authority in question must be identified.

A common variation of the typical Appeal to Authority fallacy is an Appeal to an Unnamed Authority. This fallacy is Also Known as an Appeal to an Unidentified Authority.

This fallacy is committed when a person asserts that a claim is true because an expert or authority makes the claim, but the person does not identify the expert. Since the expert is not identified, there is no way to tell if the person is an expert. Unless the person is identified and has his expertise established, there is no reason to accept the claim on this basis.

This sort of reasoning is not unusual. Typically, the person making the argument will say things like “I have a book that says…”, or “they say…”, or “the experts say…”, or “scientists believe that…”, or “I read in the paper..” or “I saw on TV…” or some similar statement. in such cases the person is often hoping that the listener(s) will simply accept the unidentified source as a legitimate authority and believe the claim being made. If a person accepts the claim simply because they accept the unidentified source as an expert (without good reason to do so), he has fallen prey to this fallacy.

 

Non-Fallacious Arguments from Authority

Not all Arguments from Authority are fallacious. This is fortunate since people must rely on experts. No one person can be an expert on everything, and people do not have the time or ability to investigate every single claim themselves.

In some cases, Arguments from Authority will be good arguments. For example, when a person goes to a skilled doctor and the doctor tells them that they have a cold, then the patient has good reason to accept the doctor’s conclusion. As another example, if a person’s computer is acting odd and their friend, who is a computer expert, tells them it is probably their hard drive then they have good reason to accept this claim.

What distinguishes a fallacious Appeal to Authority from a good Argument from Authority is that the argument effectively meets the six conditions discussed above.

In a good Argument from Authority, there is reason to believe the claim because the expert says the claim is true. This is because a qualified expert is more likely to be right than wrong when making claims within their area of expertise. In a sense, the claim is being accepted because it is reasonable to believe that the expert has tested the claim and found it to be reliable. So, if the expert has found it to be reliable, then it is reasonable to accept it as being true. Thus, the listener is accepting a claim based on the testimony of the expert.

It should be noted that even a good Argument from Authority is not an exceptionally strong argument. After all, a claim is accepted as true because a credible person says it is true. Arguments that deal directly with evidence relating to the claim itself will tend to be stronger.

 

Defense: The main defense against this fallacy is to apply the standards of the Argument from Authority when considering any appeal to authority important enough to be worth assessing. You should especially be on guard when you agree with the (alleged) expert and want to believe they are correct. While there are legitimate uses for claims by anonymous experts, the credibility of these claims rest on the expertise of the person reporting the claim. This is because the evidence for such a claim is the credibility and expertise of the person reporting it. That is, you are trusting that they are honestly reporting the claim and are qualified to assess that the anonymous expert is credible.

Example #1:

Bill: “I believe that abortion is morally acceptable. After all, a woman should have a right to her own body.”

Jane: ‘I disagree completely. Dr. Johan Skarn says that abortion is always morally wrong, regardless of the situation. He must be right, after all, he is a respected expert in his field.”

Bill: “I’ve never heard of Dr. Skarn. Who is he?”

Jane: “He’s that guy that won the Nobel Prize in physics for his work on cold fusion.”

Bill: “I see. Does he have any expertise in morality or ethics?”

Jane: “I don’t know. But he’s a world-famous expert, so I believe him.”

Example #2:

Kintaro: “I don’t see how you can consider Stalin to be a great leader. He killed millions of his own people, he crippled the Soviet economy, kept most of the people in fear and laid the foundations for the violence that is occurring in much of Eastern Europe.”

Dave: “Yeah, well you say that. However, I have a book at home that says that Stalin was acting in the best interest of the people. The millions that were killed were vicious enemies of the state and they had to be killed to protect the rest of the peaceful citizens. This book lays it all out, so it must be true.”

Example #3:

Actor: “I’m not a doctor, but I play one on the hit series ‘Bimbos and Studmuffins in the OR.’ You can take it from me that when you need a fast acting, effective and safe pain killer there is nothing better than MorphiDope 2000. That is my considered medical opinion.”

Example #4:

Sasha: “I played the lottery today and I know I am going to win something.”

Siphwe: “What did you do, rig the outcome?”

Sasha: “No, silly. I called my Super Psychic Buddy at the 1-900-MindPower number. After consulting his magic Californian Tarot deck, he told me my lucky numbers.”

Siphwe: “And you believed him?”

Sasha: “Certainly, he is a certified Californian Master-Mind Psychic. That is why I believe what he has to say. I mean, like, who else would know what my lucky numbers are?”

Example #5

Sam: “I’m going to get the Shingles vaccine based on my doctor’s advice.”

Ted: “Well, I saw this guy on YouTube who says that the vaccine has microchips in it. And that it causes autism.”

Sam: “Are they are doctor or scientist?”

Ted: “Well, I think he was a doctor once. He said something about getting his medical license revoked because They are out to get him and want to silence him.”

Sam: “Does he have any evidence for these claims?”

Ted: “Look, you can believe your doctor if you want, but don’t come crying to me when the microchips take over your brain and you catch autism.”

Sam: “You don’t catch autism.”

Ted: “Whatever.”

 

Description:

This fallacy occurs when someone uncritically rejects a prediction or the effectiveness of the responses to it when the predicted outcome does not occur:

Premise 1: Prediction P predicted outcome X if response R is not taken.

Premise 2: Response R was taken (based on prediction P).

Premise 3: X did not happen, so Prediction P was wrong.

Conclusion: Response R should not have been taken (or there is no longer a need to take Response R).

 

The error occurs because of a failure to consider the obvious: if there is an effective response to a predicted outcome, then the prediction will appear to be “wrong” because the predicted outcome will not occur.

While a prediction that turns out to be “wrong” is technically wrong, the error here is to uncritically conclude that this proves the response was not needed (or there is no longer any need to keep responding). The initial prediction assumes there will not be a response and is usually made to argue for responding. If the response is effective, then the predicted outcome will not occur, which is the point of responding. To reason that the “failure” of the prediction shows that the response was mistaken or no longer needed is thus a mistake in reasoning.

To use a silly analogy, imagine that we are in a car and driving towards a cliff. You make the prediction that if we keep going, we will go off the cliff and die. So, I turn the wheel and avoid the cliff. If backseat Billy gets angry and says that there was no reason to turn the wheel or that I should turn it back because we did not die in a fiery explosion, Billy is falling for this fallacy. After all, if we did not turn, then we would have probably died. And if we turn back too soon, then we will probably die. The point of turning is so that the predicted outcome of death will not occur.

A variation on this fallacy involves inferring the prediction was bad because it turned out to be “wrong”:

Premise 1: Prediction P predicted outcome X if response R is not taken.

Premise 2: Response R was taken based on prediction P.

Premise 3: X did not happen.

Conclusion: Prediction P was wrong about X occurring if response R was not taken.

 

While the prediction would be “wrong” in that the predicted outcome did not occur, this does not disprove the prediction that X would occur without the response. Going back to the car example, the prediction that we would die if we drove of the cliff if we do not turn is not disproven if we turn and then do not die. In fact, that is the result we want.

Since it lacks logical force, this fallacy gains its power from psychological force. Sorting out why something did not happen can be difficult and it is easier to go along with biases, preconceptions, and ideology than it is to sort out a complicated matter.

This fallacy can be committed in good faith out of ignorance. When committed in bad faith, the person using it is aware of the fallacy. The intent is often to use this fallacy to argue against continuing the response or as a bad faith attack on those who implemented or argued for the response. For example, someone might argue in bad faith that a tax cut was not needed to avoid a recession because the predicted recession did not occur after the tax cut. While the tax cut might have not been a factor, simply asserting that they were not needed because the recession did not occur would commit this fallacy.

 

Defense: To avoid inflicting this fallacy on yourself or falling for it, the main defense is to keep in mind that a prediction based on the assumption that a response will not be taken can turn out to be “wrong” if that response is taken. Also, you should remember that the failure of a predicted event to occur after a response is made to prevent it would count as some evidence that the response was effective rather than as proof it was not needed. But care should be taken to avoid uncritically inferring that the response was needed or effective because the predicted event did not occur.

 

Example #1

Julie: “The doctor said that my blood pressure would keep going up unless I improved my diet and started exercising.”

Kendra: “How is your blood pressure now?”

Julie: “Pretty good. I guess I don’t need to keep eating all those vegetables and I can stop going on those walks.”

Kendra: “Why?”

Julie: “Well, she was wrong. My blood pressure did not go up.”

Example #2

Robert: “While minority voters might have needed some protection long ago, I am confident we can remove all those outdated safeguards.”

Kelly: “Why? Aren’t they still needed? Aren’t they what is keeping some states from returning to the days of Jim Crow?”

Robert: “Certainly not. People predicted that would happen, but it didn’t. So, we obviously no longer need those protections in place.”

Kelly: “But, again, aren’t these protections what is keeping that from happening?”

Robert: “Nonsense. Everything will be fine.”

Example #3

Lulu: “I am so mad. We did all this quarantining, masking, shutting down, social distance and other dumb thing for so long and it is obvious we did not need to.”

Paula: “I didn’t like any of that either, but the health professionals say it saved a lot of lives.”

Lulu: “Yeah, those health professionals said that millions of people would die if we didn’t do all that stupid stuff. But look, we didn’t have millions die. So, all that was just a waste.”

Paula: “Maybe doing all that was why more people didn’t die.”

Lulu: “That is what they want you to think.”

 

Since I often reference various fallacies in blog posts I decided to also post the fallacies. These are from my book 110 Fallacies.

Description:

This fallacy is committed when a person places unwarranted confidence in drawing a conclusion from statistics that are unknown.

 

Premise 1: “Unknown” statistical data D is presented.

Conclusion: Claim C is drawn from D with greater confidence than D warrants.

 

Unknown statistical data is just that, statistical data that is unknown. This data is different from “data” that is simply made up because it has at least some foundation.

One type of unknown statistical data is when educated guesses are made based on limited available data. For example, when experts estimate the number of people who use illegal drugs, they are making an educated guess. As another example, when the number of total deaths in any war is reported, it is (at best) an educated guess because no one knows for sure exactly how many people have been killed.

Another common type of unknown statistical data is when it can only be gathered in ways that are likely to result in incomplete or inaccurate data. For example, statistical data about the number of people who have affairs is likely to be in this category. This is because people generally try to conceal their affairs.

Obviously, unknown statistical data is not good data.  But drawing an inference from unknown data need not always be unreasonable or fallacious. This is because the error in the fallacy is being more confident in the conclusion than the unknown data warrants. If the confidence in the conclusion is proportional to the support provided by the evdience, then no fallacy would be committed.

For example, while the exact number of people killed during the war in Afghanistan will remain unknown, it is reasonable to infer from the known data that many people have died. As another example, while the exact number of people who do not pay their taxes is unknown, it is reasonable to infer that the government is losing some revenue because of this.

The error that makes this a fallacy is to place too much confidence in a conclusion drawn from unknown data. Or to be a bit more technical, to overestimate the strength of the argument based on statistical data that is not adequately known.

This is an error of reasoning because, obviously enough, a conclusion is being drawn that is not adequately justified by the premises. This fallacy can be committed in ignorance or intentionally committed.

Naturally, the way in which the statistical data is gathered also needs to be assessed to determine whether other errors have occurred, but that is another matter.

 

Defense: The main defense against this fallacy is to keep in mind that inferences drawn from unknown statistics need to be proportional to the quality of the evidence. The error, as noted above, is placing too much confidence in unknown statistics.

Sorting out exactly how much confidence can be placed in such statistics can be difficult, but it is wise to be wary of any such reasoning. This is especially true when the unknown statistics are being used by someone who is likely to be biased. That said, to simply reject claims because they are based on unknown statistics would also be an error.

 

Example #1

“Several American Muslims are known to be terrorists or at least terrorist supporters. As such, I estimate that there are hundreds of actual and thousands of potential Muslim-American terrorists. Based on this, I am certain that we are in grave danger from this large number of enemies within our own borders.”

Example #2

“Experts estimate that there are about 11 million illegal immigrants in the United States. While some people are not worried about this, consider the fact that the experts estimate that illegals make up about 5% of the total work force. This explains that percentage of American unemployment since these illegals are certainly stealing 5% of America’s jobs. Probably even more, since these lazy illegals often work multiple jobs.”

Example #3

Sally: “I just read an article about cheating.”

Jane: “How to do it?”

Sally: “No! It was about the number of men who cheat.”

Sasha: “So, what did it say?”

Sally: “Well, the author estimated that 40% of men cheat.”

Kelly: “Hmm, there are five of us here.”

Janet: “You know what that means…”

Sally: “Yes, two of our boyfriends are cheating on us. I always thought Bill and Sam had that look…”

Janet: “Hey! Bill would never cheat on me! I bet it is your man. He is always given me the eye!”

Sally: ‘What! I’ll kill him!”

Janet: “Calm down. I was just kidding. I mean, how can they know that 40% of men cheat? I’m sure none of the boys are cheating on us. Well, except maybe Sally’s man.”

Sally: “Hey!”

Example #4

“We can be sure that most, if not all, rich people cheat on their taxes. After all, the IRS has data showing that some rich people have been caught doing so. Not paying their fair share is exactly what the selfish rich would do.”