A Philosopher's Blog

Philosophical Essays on Many Subjects

fallacy

COVID-19 & Critical Thinking: Assessing Claims

by 1 Comment

Critical thinking can save your life, especially during a pandemic of viruses, disinformation and misinformation. Laying aside all the academic jargon, critical thinking is the rational assessment of a claim in order to determine whether you should accept a claim as true, reject it as false or suspend judgment about the claim. People often forget that they have the option to suspend judgment—in a time of misinformation and disinformation this can sometimes be the best option.

Brains!
Image Credit

Suppose that you see a post on Facebook claiming that drinking alcohol will reduce your chances of getting sick, you see a tweet about how gargling with bleach can kill the virus,  or you hear President Trump extoling the virtues of hydroxychloroquine as a treatment for the virus. How can you rationally assess these claims if you are not a medical expert? Fortunately, critical thinking can help you here, even if you got most of your medical knowledge from watching Grey’s Anatomy.

When you get a claim that is worth assessing, the first step is to run it against your own observations and see if it matches them. If it does not, then this is a mark against it. If it does, that is a plus. Take the bleach claim as an example. If you go look at a bottle of bleach you will observe that it has clear safety warnings. While it will probably kill viruses it contacts, the warning label also indicates that it will also hurt you. Hence, the rational assessment of the claim that gargling bleach is a good way to protect yourself against the virus will reveal that this is not true. While your own observations are a good check on claims, they are obviously not infallible—so it is wise to critically consider their reliability. But do not gargle with bleach.

The second step, which usually happens automatically, is to test the claim against your background information. Your background information is all the stuff you have learned over the years. When you get a claim worth testing, you match it up against your background information to get a rough assessment of its initial plausibility—how likely it seems to be true on first consideration. This initial plausibility can obviously be adjusted as you investigate more. As an example, consider the claim about alcohol’s effect on the virus. On the one hand, you probably learned that alcohol can be used to sterilize things—so that raises the plausibility of the claim. But you probably have not heard of people protecting themselves successfully from the flu or cold (which are also caused by viruses) by drinking alcohol. Also, you probably have in your background information the fact that the alcohol used to sterilize things is poisonous and that the alcohol your can safely drink is not used in this manner. So, the rational thing to do would be to take the claim about alcohol to be probably false.

One obvious problem here is that everyone’s background information is chock full of false beliefs. From my own experience, I know that I have believed many false things—so I infer I still believe false things. I just do not know which ones are false—if I did, I would stop believing them. Because of our fallibility, this method has a serious flaw: you could be accepting or rejecting a claim because of a false belief in your background information. This is why it is a good idea to assess your beliefs and weed out the bad ones—you can only be rationally confident of your assessment of a claim to the degree that you can be rationally confident that the background information you are using is correct. The more you know, the better you will be at making such assessments—so learning is a good thing.

While having false beliefs can cause errors in assessing claims, people are also impacted by biases and fallacies. Since there is a multitude of both, I will only briefly discuss a few that are especially relevant during this pandemic. People tend to be biased in favor of their group, be it their religion, political party or sports team. This leads people to tend to believe claims made by members of their group, which fuels the group think fallacy: believing that a claim is true because someone in your group made the claim and you are proud of your group. This can also be seen as a version of the appeal to belief fallacy in which one believes that a claim is true because their group believes that it is true. While the virus kills across party lines, the pandemic has become politicized. Because of this, people who have strong partisan feelings will tend to believe what their side says and disbelieve the other side—but this is bad logic. As such, making rational assessments in the pandemic (or anytime) requires taking the effort to set aside such biases and consider the claim as objectively as possible. This is a hard thing for some people to do, but your life depends on it in this time of misinformation and disinformation.

Since pandemics are terrifying and people want to have hope, it is also important to be on guard against the poor logic of appeal to fear/scare tactics and wishful thinking. An appeal to fear occurs when a person accepts a claim as true because of fear rather than having actual evidence or reasons to do so. Something that provides good reasons can be scary—but if the only “reason” to accept a claim is fear, then the fallacy is committed. To illustrate, the virus is scary because it can kill you. This does give you a good reason to take precautions against it—so reasoning that because it is deadly, you should be careful would not be an error. But if someone believes that bleach will protect them because they have been scared into accepting this, then they are a victim of the fallacy (and bleach). In addition to fear, there is also hope.

Wishful thinking is a classic fallacy in which a person believes a claim because they want it to be true (or reject a claim because they want it to be false). Since there is currently no vaccine or cure for the virus, it is natural for people to engage in wishful thinking—to believe claims simply because they want them to be true. For example, a person might think that they will not get sick from the virus out of wishful thinking—which can be very dangerous to themselves and others. As another example, a person might believe that drinking alcohol will protect them from the virus because they want it to be true; but this is not true. The defense against wishful thinking is not to give up hope, but to not let false hope make you believe things without evidence. This can be hard to do—these are difficult times and objectively considering claims can lead to disappointment. But wishful thinking can get you and others killed—so keep hold of hope, but do not let false hope blind you. In the next essay, I will discuss how to assess experts and alleged experts.

Stay safe.

My Amazon Author Page

My Paizo Page

My DriveThru RPG Page

Follow Me on Twitter

Is Trump a Tyrant? IV: Red Herring & Two Bad

by 16 Comments

As this was being written, it was announced that the G-7 summit would be held at Trump’s Miami golf resort. Once again, his defenders have been tasked with explaining why this obvious exploitation of his office and clear violation of the emoluments clause is actually perfectly normal and fine. This adds yet another example in support of the claim that Trump is a tyrant. Trump will simply enrich himself and his family at the expense of the public while providing nothing for the public good. This is a clear case of tyrannical behavior. Now back to the discussion of fallacious responses to the argument by definition that Trump is a tyrant.

Image Credit

Since the Red Herring fallacy is so common, it is no surprise that Trump’s defenders press it into service. A Red Herring is a fallacy in which an irrelevant topic is presented in order to divert attention from the original issue. The basic idea is to “win” an argument by leading attention away from the argument and to another topic. This sort of “reasoning” has the following form:

1. Topic A is under discussion.

2. Topic B is introduced under the guise of being relevant to topic A (when topic B is not relevant to topic A).

3. Topic A is abandoned.

This sort of “reasoning” is fallacious because merely changing the topic of discussion hardly counts as an argument against a claim. This fallacy is often used in conjunction with the similar Two Bad fallacy. This fallacy has the following form:

1. Premises 1: A has done X, which is bad.

2.  Premise 2: A (or a defender of A) points out that B has also done X.

3. Conclusion: A doing X was not bad.

This reasoning is fallacious because the fact that someone else has done the same thing does not make it not bad. This fallacy is like Two Wrongs; in Two Wrongs the “reasoning” is that something wrong is not wrong if someone else would or has done it to you. The difference is that this fallacy does not require that the other person would or has done the action to you. It is also somewhat like Common Practice, which justifies something by asserting it is commonly done. The difference is that Two Bad does not involve saying that the practice is common, just that someone else did it as well.

So, how do Trump and Trump’s defenders use these fallacies to try to defend Trump? To illustrate, I will use the famous Obama Netflix example. Trump is understandably enraged at the Mueller Report—it details his many crimes and misdeeds while carefully asserting that a sitting president cannot be indicted. While the report had but little impact beyond enraging Trump, he has endeavored to distract attention from it to someone else—specifically he has called for an investigation of President Obama for his book deal and Netflix deal. Looked at as a Red Herring, this is simply an effort to switch the subject from Trump’s massive self-enriching corruption to Obama’s profiting from his time in office.

While it is true that Obama has profited nicely from the book deal and will presumably profit from his Netflix deal, these are irrelevant to the issue of whether Trump is engaged in corruptly enriching himself. Trump’s approach can also be seen as a False Equivalence as well: while Obama is profiting from his book deal and will profit from the Netflix deal, both of these are legal and within the moral norms (Bush also signed a book deal). More importantly, while Obama is profiting from being president, he is doing so while he is no longer in office. While there are moral concerns with exploiting past office in this manner, these concerns pale in comparison with corruption while in office. Hence, this is just another attempt at a False Equivalency.

Trump and his defenders can also be seen as attempting a Two Bad here as well; by pointing to Obama’s deals, Trump can try to assert that his financial exploitation of the office for his and his family’s enrichment is not bad. His “logic” would be that his deals are not bad because Obama also did deals that were bad. Even if Obama’s deals were morally wrong, it would obviously not follow that Trump’s corruption is not bad. As such, trying to defend Trump against a charge of tyranny by asserting that other people do bad things as well would commit either a Red Herring or a Two Bad (or both). Thus, this defense has no logical merit. This is not to deny that other people do bad things or assert that there is nothing wrong with people exploiting their office after they leave—but those are utterly different matters.

My Amazon Author Page

My Paizo Page

My DriveThru RPG Page

Follow Me on Twitter

Trump & the Leave It Fallacy

by 9 Comments

When it comes to persuasion, logic is one of the weaker tools. This is because the end of logic is truth, not making people believe something—that is the end of persuasion. While the land of logic is a foreign realm to Trump, he seems to have an instinct for using fallacies and rhetoric to persuade people. This has served him well—rhetoric makes the masses clap, logic makes them nap.

Image Credit

While Trump enjoys the classic fallacies, such as the scare tactic and the general ad hominen attack, he recently made use of a subclass of the ad hominem known to some as the “ergo decedo” (“therefore leave”) and called by Copi the “traitorous critic fallacy.” Since there is no international bureau of fallacy naming, I will call it the “leave it” fallacy.

The Leave It fallacy is a type of ad hominem because it involves rejecting a person’s claim because the “evidence” against a person’s claim is an irrelevant attack on the person. There are two things that distinguish the Leave It fallacy. First, the person is attacked because they are being critical of something. This attack typically takes the form of asserting that the critic is motivated by a secret association or agreement with a disliked group. Second, rather than refuting the criticism, the attacker only tells the target to “leave.” As such, the fallacy has the following general form:

Premise 1. Person A makes critical claim X about Y.

Premise 2. Person B attacks A (usually for an alleged association/agreement with a disliked group G) and says that if A does not like X about Y, then they should leave Y (usually for G).

Conclusion:  Therefore, X is false.

This argument is a fallacy because simply attacking a person and telling them to leave does not prove that their criticism is false. The fallacy draws much of its psychological power from the cognitive bias of groupthink (the tendency to try to minimize conflict and form a consensus by suppressing dissent and avoiding outside influences) and the ingroup bias (the tendency to see one’s own group as superior and outsiders as inferior). Someone who is critical of a group can easily be cast as a threat and hence people in that group can be motivated to reject that criticism out of anger and dislike. These biases do not, of course, have any logical weight.

The defense against this fallacy is to try to reason through any negative feelings one might have and ask if any relevant refutation of the criticism has been offered. If it has not, then the “argument” gives no reason to reject that criticism. This does not mean that the criticism is therefore true—it just means the fallacy does not provide any reason to reject it.

Care should be taken to not confuse the Leave It fallacy with the False Dilemma “love it or leave it.” The idea in this false dilemma is that one has just two options: to love something (typically a country) utterly and never criticize it or leave it. There are obviously many other options. The difference between the two is that the Leave It fallacy involves using an attack on the person to “argue” that their criticism is false while the False Dilemma “love it or leave it” is intended to silence criticism by wrongly asserting that one has only the two choices. It can often be hard to distinguish the two because people often combine them and those attempting these fallacies often do not know what they are doing themselves. Now back to Trump.

Trump recently attacked Democratic Congresswomen with this fallacy, “arguing” that their criticisms of America are wrong “because” they are “from countries whose governments are a complete and total catastrophe, the worst, most corrupt and inept anywhere in the world” and they should go back to these countries.  Trump’s “logic” seems to be this:

Premise 1: The Democratic Congresswomen criticized the United States.

Premise 2: The women are from “from countries whose governments are a complete and total catastrophe, the worst, most corrupt and inept anywhere in the world” and they should go back where they came from.

Conclusion: The Democratic Congresswomen criticisms are not true.

Presented in this manner, the fallacy is even more evident: there is no connection between the premises and the conclusion; Trump is merely attacking the Congresswomen and telling them to leave. While having nothing to do with the fallacy, it is worth noting that all four of the Congresswomen Trump attacks are American citizens and three of them were born in the United States. Some might thus say that Trump is not wrong when he says that they come from a country with a government that is “a complete and total catastrophe, the worst, most corrupt and inept anywhere in the world”—that is, the Trump administration.

In closing, it must be noted that the fact that Trump’s attack on the Congresswomen was fallacious does not prove that their critical claims about the United States are true—that does not follow. Their claims must stand or fall on their own merits.

My Amazon Author Page

My Paizo Page

My DriveThru RPG Page

Follow Me on Twitter

Philosophy & My Old Husky I: Post Hoc & Anecdotal Evidence

by 2 Comments

dogpark065My Siberian husky, Isis, joined the pack in 2004 at the age of one. It took her a little while to realize that my house was now her house—she set out to chew all that could be chewed, presumably as part of some sort of imperative of destruction. Eventually, she came to realize that she was chewing her stuff—or so I like to say. More likely, joining me on 8-16 mile runs wore the chew out of her.

As the years went by, we both slowed down. Eventually, she could no longer run with me (despite my slower pace) and we went on slower adventures (one does not walk a husky; one goes adventuring with a husky). Despite her advanced age, she remained active—at least until recently. After an adventure, she seemed slow and sore. She cried once in pain, but then seemed to recover. Then she got worse, requiring a trip to the emergency veterinarian (pets seem to know the regular vet hours and seem to prefer their woes to take place on weekends).

The good news was that the x-rays showed no serious damage—just indication of wear and tear of age. She also had some unusual test results, perhaps indicating cancer. Because of her age, the main concern was with her mobility and pain—as long as she could get about and be happy, then that was what mattered. She was prescribed an assortment of medications and a follow up appointment was scheduled with the regular vet. By then, she had gotten worse in some ways—her right foot was “knuckling” over, making walking difficult. This is often a sign of nerve issues. She was prescribed steroids and had to go through a washout period before starting the new medicine. As might be imagined, neither of us got much sleep during this time.

While all stories eventually end, her story is still ongoing—the steroids seemed to have done the trick. She can go on slow adventures and enjoys basking in the sun—watching the birds and squirrels, willing the squirrels to fall from the tree and into her mouth.

While philosophy is often derided as useless, it was actually very helpful to me during this time and I decided to write about this usefulness as both a defense of philosophy and, perhaps, as something useful for others who face similar circumstances with an aging canine.

Isis’ emergency visit was focused on pain management and one drug she was prescribed was Carprofen (more infamously known by the name Rimadyl). Carprofen is an NSAID that is supposed to be safer for canines than those designed for humans (like aspirin) and is commonly used to manage arthritis in elderly dogs. Being a curious and cautious sort, I researched all the medications (having access to professional journals and a Ph.D.  is handy here). As is often the case with medications, I ran across numerous forums which included people’s sad and often angry stories about how Carprofen killed their pets. The typical story involved what one would expect: a dog was prescribed Carprofen and then died or was found to have cancer shortly thereafter. I found such stories worrisome and was concerned—I did not want my dog to be killed by her medicine. But, I also knew that without medication, she would be in terrible pain and unable to move. I wanted to make the right choice for her and knew this would require making a rational decision.

My regular vet decided to go with the steroid option, one that also has the potential for side effects—complete with the usual horror stories on the web. Once again, it was a matter of choosing between the risks of medication and the consequences of doing without. In addition to my research into the medication, I also investigated various other options for treating arthritis and pain in older dogs. She was already on glucosamine (which might be beneficial, but seems to have no serious side effects), but the web poured forth an abundance of options ranging from acupuncture to herbal remedies. I even ran across the claim that copper bracelets could help pain in dogs.

While some of the alternatives had been subject to actual scientific investigation, the majority of the discussions involved a mix of miracle and horror stories. One person might write glowingly about how an herbal product brought his dog back from death’s door while another might claim that after he gave his dog the product, the dog died because of it. Sorting through all these claims, anecdotes and studies turned out to be a fair amount of work. Fortunately, I had numerous philosophical tools that helped a great deal with such cases, specifically of the sort where it is claimed that “I gave my dog X, then he got better/died and X was the cause.” Knowing about two common fallacies is very useful in these cases.

The first is what is known as Post Hoc Ergo Propter Hoc (“after this, therefore because of this”).  This fallacy has the following form:

 

  1. A occurs before B.
  2. Therefore A is the cause of B.

 

This fallacy is committed when it is concluded that one event causes another simply because the proposed cause occurred before the proposed effect. More formally, the fallacy involves concluding that A causes or caused B because A occurs before B and there is not sufficient evidence to actually warrant such a claim.

While cause does precede effect (at least in the normal flow of time), proper causal reasoning, as will be discussed in an upcoming essay, involves sorting out whether A occurring before B is just a matter of coincidence or not. In the case of medication involving an old dog, it could entirely be a matter of coincidence that the dog died or was diagnosed with cancer after the medicine was administered. That is, the dog might have died anyway or might have already had cancer. Without a proper investigation, simply assuming that the medication was the cause would be an error. The same holds true for beneficial effects. For example, a dog might go lame after a walk and then recover after being given an herbal supplement for several days. While it would be tempting to attribute the recovery to the herbs, they might have had no effect at all. After all, lameness often goes away on its own or some other factor might have been the cause.

This is not to say that such stories should be rejected out of hand—it is to say that they should be approached with due consideration that the reasoning involved is post hoc. In concrete terms, if you are afraid to give your dog medicine she was prescribed because you heard of cases in which a dog had the medicine and then died, you should investigate more (such as talking to your vet) about whether there really is a risk of death. As another example, if someone praises an herbal supplement because her dog perked up after taking it, then you should see if there is evidence for this claim beyond the post hoc situation.

Fortunately, there has been considerable research into medications and treatments that provide a basis for making a rational choice. When considering such data, it is important not to be lured into rejecting data by the seductive power of the Fallacy of Anecdotal Evidence.

This fallacy is committed when a person draws a conclusion about a population based on an anecdote (a story) about one or a very small number of cases. The fallacy is also committed when someone rejects reasonable statistical data supporting a claim in favor of a single example or small number of examples that go against the claim. The fallacy is considered by some to be a variation on hasty generalization.  It has the following forms:

Form One

  1. Anecdote A is told about a member (or small number of members) of Population P.
  2. Conclusion C is drawn about Population P based on Anecdote A.

For example, a person might hear anecdotes about dogs that died after taking a prescribed medication and infer that the medicine is likely to kill dogs.

Form Two

  1. Reasonable statistical evidence S exists for general claim C.
  2. Anecdote A is presented that is an exception to or goes against general claim C.
  3. Conclusion: General claim C is rejected.

For example, the statistical evidence shows that the claim that glucosamine-chondroitin can treat arthritis is, at best, very weakly supported. But, a person might tell a story about how their aging husky “was like a new dog” after she starting getting a daily dose of the supplement. To accept this as proof that the data is wrong would be to fall for this fallacy. That said, I do give my dog glucosamine-chondroitin because it is cheap, has no serious side effects and might have some benefit. I am fully aware of the data and do not reject it—I am gambling that it might do my husky some good.

The way to avoid becoming a victim of anecdotal evidence is to seek reliable, objective statistical data about the matter in question (a vet should be a good source). This can, I hasten to say, can be quite a challenge when it comes to treatments for pets. In many cases, there are no adequate studies or trials that provide statistical data and all the information available is in the form of anecdotes. One option is, of course, to investigate the anecdotes and try to do your own statistics. So, if the majority of anecdotes indicate something harmful (or something beneficial) then this would be weak evidence for the claim. In any case, it is wise to approach anecdotes with due care—a story is not proof.

Threat Assessment I: A Vivid Spotlight

by Leave a Comment

When engaged in rational threat assessment, there are two main factors that need to be considered. The first is the probability of the threat. The second is, very broadly speaking, the severity of the threat. These two can be combined into one sweeping question: “how likely is it that this will happen and, if it does, how bad will it be?”

Making rational decisions about dangers involves considering both of these factors. For example, consider the risks of going to a crowded area such as a movie theater or school. There is a high probability of being exposed to the cold virus, but it is a very low severity threat. There is an exceedingly low probability that there will be a mass shooting, but it is a high severity threat since it can result in injury or death.

While humans have done a fairly good job at surviving, this seems to have been despite our amazingly bad skills at rational threat assessment. To be specific, the worry people feel in regards to a threat generally does not match up with the actual probability of the threat occurring. People do seem somewhat better at assessing the severity, though they are also often in error about this.

One excellent example of poor threat assessment is in regards to the fear Americans have in regards to domestic terrorism. As of December 15, 2015 there have been 45 people killed in the United States in attacks classified as “violent jihadist attacks” and 48 people killed in attacks classified as “far right wing attacks” since 9/11/2001.  In contrast, there were 301,797 gun deaths from 2005-2015 in the United States and over 30,000 people are killed each year in motor vehicle crashes in the United States.

Despite the incredibly low likelihood of a person being killed by an act of terrorism in the United States, many people are terrified by terrorism (which is, of course, the goal of terrorism) and have become rather focused on the matter since the murders in San Bernardino. Although there have been no acts of terrorism on the part of refugees in the United States, many people are terrified of refugees and this had led to calls for refusing to accept Syrian refugees and Donald Trump has famously called for a ban on all Muslims entering the United States.

Given that an American is vastly more likely to be killed while driving than killed by a terrorist, it might be wondered why people are so incredibly bad at this sort of threat assessment. The answer, in regards to having fear vastly out of proportion to the probability is easy enough—it involves a cognitive bias and some classic fallacies.

People follow general rules when they estimate probabilities and the ones we use unconsciously are called heuristics. While the right way to estimate probability is to use proper statistical methods, people generally fall victim to the bias known as the availability heuristic. The idea is that a person unconsciously assigns a probability to something based on how often they think of that sort of event. While an event that occurs often will tend to be thought of often, the fact that something is often thought of does not make it more likely to occur.

After an incident of domestic terrorism, people think about terrorism far more often and thus tend to unconsciously believe that the chance of terrorism occurring is far higher than it really is. To use a non-terrorist example, when people hear about a shark attack, they tend to think that the chances of it occurring are high—even though the probability is incredibly low (driving to the beach is vastly more likely to kill you than a shark is). The defense against this bias is to find reliable statistical data and use that as the basis for inferences about threats—that is, think it through rather than trying to feel through it. This is, of course, very difficult: people tend to regard their feelings, however unwarranted, as the best evidence—despite it is usually the worst evidence.

People are also misled about probability by various fallacies. One is the spotlight fallacy. The spotlight fallacy is committed when a person uncritically assumes that all (or many) members or cases of a certain class or type are like those that receive the most attention or coverage in the media. After an incident involving terrorists who are Muslim, media attention is focused on that fact, leading people who are poor at reasoning to infer that most Muslims are terrorists. This is the exact sort of mistake that would occur if it were inferred that most Christians are terrorists because the media covered a terrorist who was Christian (who shot up a Planned Parenthood). If people believe that, for example, most Muslims are terrorists, then they will make incorrect inferences about the probability of a domestic terrorist attack by Muslims.

Anecdotal evidence is another fallacy that contributes to poor inferences about the probability of a threat. This fallacy is committed when a person draws a conclusion about a population based on an anecdote (a story) about one or a very small number of cases. The fallacy is also committed when someone rejects reasonable statistical data supporting a claim in favor of a single example or small number of examples that go against the claim. This fallacy is similar to hasty generalization and a similar sort of error is committed, namely drawing an inference based on a sample that is inadequate in size relative to the conclusion. The main difference between hasty generalization and anecdotal evidence is that the fallacy anecdotal evidence involves using a story (anecdote) as the sample.

People often fall victim to this fallacy because stories and anecdotes tend to have more psychological influence than statistical data. This leads people to infer that what is true in an anecdote must be true of the whole population or that an anecdote justifies rejecting statistical evidence in favor of said anecdote. Not surprisingly, people most commonly accept this fallacy because they want to believe that what is true in the anecdote is true for the whole population.

In the case of terrorism, people use both anecdotal evidence and hasty generalization: they point to a few examples of domestic terrorism or tell the story about a specific incident, and then draw an unwarranted conclusion about the probability of a terrorist attack occurring. For example, people point to the claim that one of the terrorists in Paris masqueraded as a refugee and infer that refugees pose a great threat to the United States. Or they tell the story about the one attacker in San Bernardino who arrived in the states on a K-1 (“fiancé”) visa and make unwarranted conclusions about the danger of the visa system (which is used by about 25,000 people a year).

One last fallacy is misleading vividness. This occurs when a very small number of particularly dramatic events are taken to outweigh a significant amount of statistical evidence. 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 to the contrary.

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, mass shootings by domestic terrorists are vivid and awful, so it is hardly surprising that people feel they are very much in danger from such attacks. Another way to look at this fallacy in the context of threats is that a person conflates the severity of a threat with its probability. That is, the worse the harm, the more a person feels that it will occur.

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 this error in reasoning. This then becomes a matter of value judgment—how much risk is a person willing to tolerate relative to the severity of the potential harm.

The defense against these fallacies is to use a proper statistical analysis as the basis for inferences about probability. As noted above, there is still the psychological problem: people tend to act on the basis on how they feel rather than what the facts show.

Such rational assessment of threats is rather important for both practical and moral reasons. The matter of terrorism is no exception to this.  Since society has limited resources, rationally using them requires considering the probability of threats rationally—otherwise resources are being misspent. For example, spending billions to counter a miniscule threat while spending little on leading causes of harm would be irrational (if the goal is to protect people from harm). There is also the concern about the harm of creating fear that is unfounded. In addition to the psychological harm to individuals, there is also the damage to the social fabric. There has already been an increase in attacks on Muslims in America and people are seriously considering abandoning core American values, such as the freedom of religion and being good Samaritans.

In light of the above, I urge people to think rather than feel their way through their concerns about terrorism. Also, I urge people to stop listening to Donald Trump. He has the right of free expression, but people also have the right of free listening.

 

My Amazon Author Page

My Paizo Page

My DriveThru RPG Page

Follow Me on Twitter

The “Two Bads” Fallacy & Racism

by Leave a Comment

The murder of nine people in the Emanuel AME Church in South Carolina ignited an intense discussion of race and violence. While there has been near-universal condemnation of the murders, some people take effort to argue that these killings are part of a broader problem of racism in America. This claim is supported by reference to the well-known history of systematic violence against blacks in America as well as consideration of data from today. Interestingly, some people respond to this approach by asserting that more blacks are killed by blacks than by whites. Some even seem obligated to add the extra fact that more whites are killed by blacks than blacks are killed by whites.

While these points are often just “thrown out there” without being forged into part of a coherent argument, presumably the intent of such claims is to somehow disprove or at least diminish the significance of claims regarding violence against blacks by whites. To be fair, there might be other reasons for bringing up such claims—perhaps the person is engaged in an effort to broaden the discussion to all violence out of a genuine concern for the well-being of all people.

In cases in which the claims about the number of blacks killed by blacks are brought forth in response to incidents such as the church shooting, this tactic appears to be a specific form of a red herring. This fallacy in which an irrelevant topic is presented in order to divert attention from the original issue. The basic idea is to “win” an argument by leading attention away from the argument and to another topic.

This sort of “reasoning” has the following form:

  1. Topic A is under discussion.
  2. Topic B is introduced under the guise of being relevant to topic A (when topic B is actually not relevant to topic A).
  3. Topic A is abandoned.

In the case of the church shooting, the pattern would be as follows:

  1. The topic of racist violence against blacks is being discussed, specifically the church shooting.
  2. The topic of blacks killing other blacks is brought up.
  3. The topic of racist violence against blacks is abandoned in favor of focusing on blacks killing other blacks.

 

This sort of “reasoning” is fallacious because merely changing the topic of discussion hardly counts as an argument against a claim. In the specific case at hand, switching the topic to black on black violence does nothing to address the topic of racist violence against blacks.

While the red herring label would certainly suffice for these cases, it is certainly appealing to craft a more specific sort of fallacy for cases in which something bad is “countered” by bringing up another bad. The obvious name for this fallacy is the “two bads fallacy.” This is a fallacy in which a second bad thing is presented in response to a bad thing with the intent of distracting attention from the first bad thing (or with the intent of diminishing the badness of the first bad thing).

This fallacy has the following pattern:

  1. Bad thing A is under discussion.
  2. Bad thing B is introduced under the guise of being relevant to A (when B is actually not relevant to A in this context).
  3. Bad thing A is ignored, or the badness of A is regarded as diminished or refuted.

In the case of the church shooting, the pattern would be as follows:

  1. The murder of nine people in the AME church, which is bad, is being discussed.
  2. Blacks killing other blacks, which is bad, is brought up.
  3. The badness of the murder of the nine people is abandoned, or its badness is regarded as diminished or refuted.

This sort of “reasoning” is fallacious because the mere fact that something else is bad does not entail that another bad thing thus has its badness lessened or refuted. After all, the fact that there are worse things than something does not entail that it is not bad. In cases in which there is not an emotional or ideological factor, the poorness of this reasoning is usually evident:

Sam: “I broke my arm, which is bad.”
Bill: “Well, some people have two broken arms and two broken legs.”
Joe: “Yeah, so much for your broken arm being bad. You are just fine. Get back to work.”

What seems to lend this sort of “reasoning” some legitimacy is that comparing two things that are bad is relevant to determining relative badness. If a person is arguing about how bad something is, it is certainly reasonable to consider it in the context of other bad things. For example, the following would not be fallacious reasoning:

Sam: “I broke my arm, which is bad.”
Bill: “Some people have two broken arms and two broken legs.”
Joe: “That is worse than one broken arm.”
Sam: “Indeed it is.”
Joe: “But having a broken arm must still suck.”
Sam: “Indeed it does.”

Because of this, it is important to distinguish between cases of the fallacy (X is bad, but Y is also bad, so X is not bad) and cases in which a legitimate comparison is being made (X is bad, but Y is worse, so X is less bad than Y, but still bad).

%d bloggers like this: