Most logical fallacies have more to do with formal arguments and less to do with how we communicate with each other daily. There are simple words and ideas used in our everyday speech that have a significant impact on our interpretations, perceptions, and decision-making.

Listed below are a few of those terms. Understanding or reviewing these terms will give you a slight edge while watching the news, attending a meeting, or discussing world events with your loved ones. I chose these terms because I’m often involved in situations in which these definitions could come in handy.

Below are the terms I’ll cover. Feel free to skip ahead to what interests you.

Communication and Comprehension

• Interpretation
• Implication
• Indication
• Conjecture
• Expectation
• Context

Common Fallacies, Biases & Modes of Thinking

• Emotivism
• Stand Alone Complex
• Faulty Generalization
• Gambler’s Fallacy
• Anchoring
• Availability Bias
• Recency Bias
• Falsification
• Availability cascade
• Rates and Percentages

Understanding and Comprehension

Your interpretation is a translation of what you are presented into your paradigm. An interpretation is significantly different from facts, raw data, or objective reality because you add your meaning to the information being provided. Our interpretation influences almost every piece of information we receive from other human beings and the world around us.

The best example of an interpretation is interpreting words of one language into another. The exact terms, dialect, and tone differ significantly, leaving it up to the interpreter to ensure the audience receives the correct interpretation or representation of what the original speaker is attempting to convey. Interpretations also come into play when analyzing data. Many people interpret the data in many different ways.

An implication is an act of implying or inferring. To imply is to suggest without explicitly or directly stating. Many arguments come with implications. They are like hidden warriors, hiding out in the background but somehow inflicting significant harm. An implication is usually what someone wants you to know without telling you directly.

Implications lead your thought process to conclusions that seem to like your own, but they aren’t. If someone asks you, “What are the implications of what you are telling me?” This is usually a call to uncover what you mean. It’s an ask for you to state your intentions directly. One of the most dangerous implications is what is called implicit bias. Implicit bias is a preconceived notion that affects our understanding, actions, and decisions unconsciously. These biases are involuntary and usually exist beyond our awareness or intention.

An indication is closely related to an implication. The difference between an implication and an indication is that an implication usually exists in your head as a suggested idea. In contrast, an indication is a sign out in the world that has been recently discovered. An indication is a sign, suggestion, clue, or proof that points to a particular conclusion. It is NOT, however, direct evidence that proves something.

An inference is closely related to implications and indications but is more conclusive. If you “infer” something, you are drawing a conclusion based on available facts or observation.

Conjecture is an opinion or conclusion based on inconclusive or incomplete evidence or guesswork. Conjecture differentiates itself from indications in that indications are more concrete or trustworthy, while conjecture is simply guesswork.

• Imply — To suggest to without directly stating.
• Indicate — To point out with certainty based on available facts.
• Infer — To conclude based on available facts.
• Conjecture — a conclusion based on incomplete evidence.

An expectation is what you expect. Why is it important to critical thinking? Because our expectations frequently cloud our interpretation of facts and data. We expect something. Therefore we often seek to satisfy our expectations subconsciously. It is often said that expectations are at the root of most of the disappointment we experience in life. Expecting less may sound like a bad thing, but in reality, it is at the core of seeing things for what they are instead of what we want them to be. It’s good to understand expectations since expectations personal and professional anchor relationships.

Context refers to the circumstances in which something occurs. For example, the normal behavior of laugher can have entirely different meanings based on where it happens. Laugher in the context of a comedy means something entirely different than laughing at a funeral. It is important to have context for the things you see, hear and read online. You might say that you can’t understand what happens without looking at the context.

Common Fallacies, Biases & Modes of Thinking

Emotivism is my favorite on this list by far since it is a key driver of “rage-bait” online and elsewhere over the last decade, thereby affecting how we interpret world events. Emotivism effectively merges morality, ethics, and values into feelings, attitudes, and prescriptive action without an assessment or acknowledgment of a statement’s objective contents.

For example, the simple moral claim such as “That person did a bad thing” is not perceived as a critique of the bad thing that person did. It is perceived as an emotional repudiation of that person. A better way to say this is that the statement is interpreted as the messenger expressing a negative feeling and nothing objective or concrete.

Emotivism has become extremely prevalent online, especially within the realm of politics and public policy. Nuanced thoughts and opinions aren’t evaluated on their substance, quality or feasibility, but are perceived as emphatic, emotional expressions for or against an idea.

The Stand Alone Complex is an alternative to nefarious conspiracies. Sometimes what seems to be conspiracy can be something a little less ominous, still bad, but less ominous. The Stand-Alone complex can be described as a phenomenon in which individuals’ behavior or actions creates a seemingly concentrated effort on a large scale. However, the individual events and actions are unconnected, with all individuals acting on their own accord without coordination or communication.

Faulty Generalization is a conclusion made about the whole or a population-based on observing one or a few instances of a phenomenon. An example of a faulty generalization is one person observing a few dogs eating broccoli. Therefore the person concludes that ALL dogs eat broccoli.

The gambler’s fallacy is the belief that if a particular event occurs more frequently than normal during the past, then it is less OR more likely to happen in the future or vice versa. The gambler’s fallacy can easily be confused with a regression to the mean, which states that if an extreme phenomenon arises as an outlier, a future phenomenon will be closer to the mean, average, or “normal.”

For example, if an NFL wide receiver catches five touchdowns in his last two games while posting a career average of one touchdown per game, it is reasonable to expect the wide receiver to be closer to one touchdown the next game. It would seem as though both gambler’s fallacy and a regression to the mean will predict a bad game the following week. The difference between the two is the frame of reference. Regression to mean states that things will return to the mean, using the mean as a reference point. The gambler’s fallacy uses the last two games as a reference point, not considering the mean over time.

The gambler’s fallacy is a form of Anchoring, a cognitive bias in which an individual uses an initial piece of information as a reference point or anchor for making decisions when the initial piece of information has equal or lesser value than all other pieces of information. One of the most prevalent uses of Anchoring is with salary negotiations. A common bargaining tool is to “anchor” the negotiations with an excessive number so that the number you want seems more palatable to the opposing party.

Anchoring is also a form of Availability bias and closely related to Recency bias. An availability bias is a mental shortcut that relies on readily available or more potent information or insights within a person’s mind when evaluating a specific topic, concept, method, or decision. The gambler’s fallacy is a recency bias. A recency bias places more weight on information recently encoded in memory than properly accessing information for its stand-alone value.

Falsification is the cornerstone of modern science and is the current distinction between pseudo-science and real science. Falsification asks the simple question: “Can a statement or hypothesis be contradicted by evidence.” The vast majority of people believe that “science,” as we know it today, is about proving a hypothesis “true.” While this is a good start, the problem with proving something true is that you open yourself up to many fallacies, errors, and biases, especially on a large scale. You are only one person, your ability to prove a statement universally true is minimal. Falsification seeks to prove something “false” instead of proving it true. If it can’t be proven false, then it stands…until it can be proven false.

The availability cascade is a landmine when it comes to marketing and the news media. The availability cascade is defined as a self-reinforcing process in which a collective belief gains more and more plausibility through its increasing repetition through public discourse. The more you hear something, the more your mind becomes comfortable with the idea or ideology. This a common tool when it comes to propaganda and narratives pushed via the mainstream. Most people operate with the assumption that mainstream media or television, in general, is trustworthy, thereby arbitrarily absorbing information and paradigms circulating without scrutiny or push back.

Lastly, you may be asking, why are rates and percentages on this list? Well, with the onset of COVID-19, we have had a front-row seat to how we understand and interpret numbers. MSNBC writer and editor Hayes Brown wrote a pretty interesting piece on how we as humans dont understand large numbers in his piece The Covid death toll is too big for Americans’ brains to handle. I agree 100% with the premise. We actually do not comprehend and very little use for usually large numbers. However, his conclusion is suspect. If we can not properly comprehend large numbers, what is the difference between 200,000, 300,000, 400,000, and 500,000? When placed side by side, we can easily say that 500,000 is greater than 200,000. But what if I were standing in front of you and I said, “300,000 people have died!!!!” How significant is that number?

When stated alone without context, your brain has two choices, look into this further or take the emotional bait based on your fear of death.

Hayes is correct. Without context, we can not properly ascertain the significance of a large number. However, there is something we can effectively comprehend, that is, percentages and ratios.

Considering the number of COVID-19 deaths, around 500,000, we can do the math and compare this to the United States population, which is somewhere around 330,000,000, and you will get the percentage of 0.0015% who have died in the US. That is FAR less than 1% of people who have died from COVID-19 in the US. You can take these numbers further and compare them to death rates and infection rates of other diseases and conditions, and you’ll arrive at conclusions that are quite dissimilar to the mainstream narrative.

Yes, numbers can be less sensitive to individual suffering, but when they involve public policy and narrative that affect the masses, it is irresponsible to disregard these numbers. Any number can be conceived as “large,” but we can begin to understand their real-world implications and consequences with points of reference.