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Critical Thinking and Decision Making, Main Sources [CT] W. Hughes, J.…

- - - - Ambiguity An ambiguous statement has two or more distinct but precise interpretations.
        
        Syntactic Ambiguity (also Amphiboly) The ambiguity is caused by the word order or grammatical construction of the statement.
        
        Equivocation An Informal Fallacy where the same word or expression is used multiple times in the same argument, but given different interpretations. The fundamental problem with equivocations is the entanglement of two or more separate arguments. A strategy for dealing with equivocations:
        
        Distinguish the different meanings of ambiguous expressions.
        
        For each meaning, restate the argument so that the expression has the same meaning in all the premises and conclusion.
        
        Evaluate the resulting arguments separately.
        
        Semantic Ambiguity (also Referential Ambiguity and Lexical Ambiguity) The ambiguity is caused by a word which can have different meanings.
      - Vagueness An expression is vague when there is no precise boundary between the cases to which it correctly applies and the case to which it incorrectly applies. If there is no precise boundary between cases of correct application and cases of incorrect application, then a minuscule difference will not change whether or not we have a case of correct or incorrect application. The problem is that a series of minuscule differences can amount to a large difference.
        
        Argument from the Heap (also Sorites Argument, Sorites Paradox, Paradox of the Heap) a philosophical paradox that arises from the vagueness of certain terms or concepts. It highlights the difficulty in establishing a precise boundary between cases of correct and incorrect application of a term or concept, especially when a series of minuscule differences can accumulate into a significant difference. The paradox is often illustrated using a heap of sand. If you remove one grain of sand from the heap, it remains a heap. However, if you continue to remove one grain of sand at a time, at some point, the heap will no longer be considered a heap. The problem lies in determining the exact point at which this transition occurs. The Argument from the Heap demonstrates the challenges in establishing clear boundaries for vague concepts and the potential for ambiguous reasoning or manipulation of terms in an argument. A type of Slippery Slope Fallacy
    - - Essentialist Define a term by describing its essential attributes or qualities.
      - Lexical (also Reportive) The standard common usage of the term given in dictionaries.
      - Ostensive A type of definition in which a concept or object is demonstrated or pointed out through direct observation or demonstration.
      - Stipulative A more precise definition that assigns a specific meaning to a term, often in a technical or specialised context. Stipulative definitions do not necessarily reflect common usage or prior understanding of a term, but rather establish a new meaning for the term in a particular context. Used to reduce Vagueness.
    - - Irrational Techniques of Persuasion
        
        Persuasive Definition (also Persuasive Redefinition, Definist Fallacy) a more specific tactic where a term or concept is redefined with the intent to influence an audience's opinion or subtly convey a particular point of view. The redefinition often carries strong emotional connotations and is designed to sway the listener's perception of the topic at hand. The main objective of a persuasive definition is to promote a specific stance or belief.
        
        Loaded Terms Words or phrases that are chosen for their emotional impact or suggestive power. They often carry strong positive or negative connotations and are used to provoke an emotional response from the audience or to frame an argument in a specific way. Loaded terms can be used to manipulate the listener's perception, encourage certain conclusions, or even discredit an opposing viewpoint.
        
        Humpty Dumptying This practice involves changing or manipulating the meaning of words to suit one's own agenda or to win an argument. It often involves redefining terms, using ambiguous language, or exploiting semantic confusion to assert one's position. The primary goal of Humpty Dumptying is to dominate a conversation or gain an upper hand in a debate by controlling the meaning of words.
  - - - Warrant A type of Premise that asserts a rule or principle which connects the Grounds to the Claim.
        Example: Urinary tract infections are normally treated with antibiotics
      - Backing The general body of knowledge from which the Warrant has been derived. In practise for most arguments the backing is assumed and rarely stated explicitly.
        Example: Medical trials have demonstrated that antibiotics are an effective treatment for urinary tract infections
      - Grounds A type of Premise which asserts facts or evidence in support of the Claim.
        Example: The patient has a urinary tract infection
      - Modalities Any Qualifying Phrases (Guarding) associated with the claim.
      - Claim A Proposition which we are asked to believe is true on the basis of a supporting argument
        Example: The patient requires treatment with antibiotics
      - Rebuttals Any expectations or circumstances where the claim might not hold true.
        Example: Unless the person is allergic to antibiotics
    - - Guarding (also Hedging Language, Qualifying Phrases) Weaken the premise in some respect. In effect, reducing the Sufficiency of the premise in order to increase its Acceptability.
        
        Introducing Probability Introducing the language of uncertainty, Example terms: Certainly, probably, possibly, ...
        
        Reducing Level of Commitment Reducing the level of personal commitment in the premise. Example terms: I know, I believe, I suspect, ...
        
        Weakening the Extent Weakening the quantification used in the premise. Example terms: All, most, many, some, few, ...
        
        Corrupt Guards Guarding can be misused in dishonest rhetorical strategies.
        
        Disappearing Guard Introduce a guarded premise in the argument. Later in the same argument refer or reintroduce the same premise with the guard removed (or at least in a stronger form), without acknowledging anything has changed.
        
        Hedging The opposite of Disappearing Guard. An unguarded premise is introduced in the argument. Later in the the same argument the premise is reintroduced with a guard, without acknowledging anything has changed. A subtype of the Motte and Bailey strategy.
      - Discounting Acknowledge a possible criticism of a premise in order preemptively counter it.
        Example: Jones is an aggressive play, but he is not dirty
        Discounting has the following pattern:
        \(P1\): The assertion of \(A\)
        \(P2\): The assertion of \(B\)
        \(P3\): There is opposition between \(A\) and \(B\)
        \(P4\): \(B\) is more important than \(A\)
        \(C1\): \(A\) can be disregarded as a criticism of \(B\)
        
        Attacking Straw Men One common misuse of discounting is to attack objections nobody would raise, but are similar to genuine objections people might raise, then claim the genuine objection has been discounted.
        Example: A public healthcare system is a might improve some life expectancy, but it won't be free
        This is a type of Straw Man argument.
      - Assuring (also Persuader Words) State that there are good reasons why the premise is true, but they are not being given now. Can be used to avoid tangents or justifying premises that people already agree on. However, can also be used to paper over weaknesses in an argument.
        
        Reflexive Emphasise how strongly a belief in the premise is held. Examples: I am certain that .., I can assure you ...
        
        Abusive Assurances Imply that there would be some intellectual or moral defect in any person who would challenge the premise. Examples: Only a fool would think .., It is common sense that ... Can be indicative of an Ad Hominem.
        
        Authoritative Appeal to expert opinion or research. Examples: Experts agree .., Studies have shown that ... Can be indicative of an Appeal to Authority.
- - - - Sufficient and Necessary Conditions Two concepts used to describe the relationship between factors or events in the context of causation or logical reasoning.
        
        Sufficient Conditions A factor or event (B) that, if present, guarantees the occurrence of another factor or event (A). In other words, if B happens, then A must also happen. However, the presence of A does not necessarily require the presence of B, as there may be other conditions that can also cause A. A sufficient condition is enough to cause an outcome, but it is not always required for the outcome to happen. For example, being struck by lightning is a sufficient condition for a fire to start, but it is not necessary, as there are other ways a fire can ignite.
        
        Necessary Conditions A a factor or event (B) that must be present for another factor or event (A) to occur. In other words, if A happens, then B must also be present. However, the presence of B alone does not guarantee that A will happen. It is important to note that a necessary condition is not always sufficient to cause an outcome, but it is required for the outcome to happen. For example, having oxygen is a necessary condition for a fire to occur, but having oxygen alone does not guarantee that a fire will start.
      - Inferring Causality Correlation in a necessary, but not sufficient condition for inferring that one phenomenon is the causal of another \(A \rightarrow B\). Fallacies concerning the nature of causation between two events are collectively known as Post Hoc fallacies.
        
        Errors
        
        Common Cause Arises when one assumes that A causes B, while ignoring the possibility that both A and B are caused by an underlying, third variable (C). The fallacy stems from overlooking a common cause, leading to false conclusions about the relationship between A and B. For instance, if there's a correlation between ice cream sales and drowning incidents, it would be wrong to conclude that ice cream consumption causes drowning; instead, both events are likely driven by warmer weather.
        
        Coincidence (also Spurious Correlation) Occurs when two variables (A and B) are found to be correlated, but the correlation is purely coincidental or due to chance, rather than reflecting any causal relationship. A spurious correlation may arise when unrelated events or variables just happen to display a pattern that appears to suggest a connection. Believing that one variable is causing the other in these instances leads to erroneous conclusions. For example, there may be a correlation between the number of pirates in the world and global warming, but it would be fallacious to infer that a decline in piracy is causing global warming, as the correlation is purely coincidental and not indicative of a causal relationship.
        
        Causal Oversimplification (also Ceteris Paribus, All Other Things Being Equal) Occurs when one assumes that a single variable (A) causes another variable (B), while ignoring or downplaying the potential influence of other variables that may also contribute to the observed outcome. Causal oversimplification often arises from the desire to find a simple explanation for a complex phenomenon, leading to a reductionist and potentially misleading understanding of causality. For example, attributing the rise in obesity solely to increased fast-food consumption, while disregarding factors such as sedentary lifestyles, genetics, and socioeconomic conditions, would be an instance of causal oversimplification.
        
        Backwards Causality (also Reverse Causation) Occurs when one mistakenly infers that A causes B, when in reality, B is the cause of A. It's an error in understanding the temporal order of events, leading to the belief that the effect is causing the cause, rather than the other way around. For example, if people who take headache medicine have more headaches than those who don't, it would be incorrect to assume that the medicine is causing the headaches, rather than the headaches prompting the use of the medicine.
        
        Collider Bias (also Berkson's Paradox) Occurs when an observed correlation between two variables (A and B) is distorted due to conditioning on a third variable (C) that is a consequence of both A and B. By conditioning on C, the causal pathways between A and B are effectively blocked or altered, leading to a biased or spurious association between the two variables. This can result in misleading conclusions about the relationship between A and B, as the correlation may be entirely driven by the influence of C. For example, if we examine the relationship between exercise and heart disease among patients visiting a cardiologist, we may find a spurious correlation between exercise and heart disease, since visiting a cardiologist (C) is influenced by both exercise habits (A) and heart disease (B). Conditioning on C (visiting the cardiologist) may create the impression that exercise is causing heart disease when, in reality, exercise is generally protective against heart disease. Related to Sampling Bias.
        
        Bidirectional Causality A complex causal relationship between two variables (A and B), in which each variable influences the other. This means that A causes B, and at the same time, B also causes A. This bidirectional relationship can make it difficult to determine the primary cause of an observed outcome and can lead to circular reasoning if not properly accounted for. It is important to recognise bidirectional causality in order to avoid oversimplifying the relationship between the two variables and to develop a more accurate understanding of the underlying causal mechanisms. For example, in the relationship between stress and poor sleep quality, stress can lead to difficulty sleeping, while poor sleep quality can also exacerbate stress levels, creating a bidirectional causal loop.
        
        Proximate / Remote Cause A proximate cause refers to an immediate factor or event that directly leads to an observed outcome or consequence. It is often the most noticeable cause, as it is closely linked in time and space to the outcome. Proximate causes help explain the specific mechanisms through which a particular outcome occurs. In contrast, a remote cause is a factor or event that is more distant in time or indirectly connected to the observed outcome. Remote causes are often underlying factors that set the stage for the proximate cause to have an effect. They are generally less obvious than proximate causes, as they involve more complex and extended chains of causation.
        The distinction between proximate and remote causes is important for understanding the full spectrum of factors that contribute to an outcome. By considering both types of causes, we can develop a more comprehensive understanding of causality and potentially identify more effective interventions to address the root causes of a problem. For example, in a car accident, the proximate cause might be a driver's failure to stop at a red light, while a remote cause could be inadequate driver education or poor traffic signal visibility.
    - - Level of Abstraction Choosing the correct level of abstraction between two things is crucial for determining the strength of an argument from analogy. The level of abstraction refers to the degree of generality or specificity with which the shared properties or characteristics are described in the analogy. A well-chosen level of abstraction can highlight the relevant similarities and minimise the impact of irrelevant differences, leading to a more persuasive and compelling analogy. To strengthen an argument from analogy, it is important to choose a level of abstraction that captures the most relevant and meaningful similarities between the objects, situations, or events being compared. This involves carefully considering which shared properties are directly related to the property in question (P4) and are representative of the broader phenomenon under investigation. By doing so, the argument from analogy can provide a more accurate and persuasive
        
        Too General When the level of abstraction is too high or too general, the argument from analogy may become weak, as the shared properties might not be relevant or specific enough to support the conclusion.
        
        Too Specific When the level of abstraction is too low or too specific, the analogy may also be weak because it focuses on details that may not be representative of the broader category or phenomenon in question. In this case, the argument might be vulnerable to counterexamples or exceptions that challenge the conclusion.
    - - Defeasible A conclusion or argument is considered defeasible if it can be invalidated, revised, or overridden by new evidence or stronger counterarguments. Defeasible reasoning is often associated with inductive and abductive reasoning, where conclusions are based on patterns or limited information and are thus subject to change as more data becomes available or new insights emerge.
      - Total Evidence Requirement A principle of inductive reasoning that states that in order to make a strong and reliable inference, all relevant evidence must be taken into account. This includes both positive evidence that supports the inference, as well as negative evidence that contradicts or undermines it. The Total Evidence Requirement holds that a conclusion based on incomplete or biased evidence is less reliable than one that takes into account all available evidence. This principle emphasises the importance of being thorough and systematic in gathering and evaluating evidence when making inferences or drawing conclusions.
        
        Cogency An argument which both has a high degree of strength and meets the Total Evidence Requirement. Broadly analogous to Soundness in deductive reasoning.
      - Strength (also Force) A continuous value representing the degree of belief in statements. In practice, probability values between \(0\)% and \(100\)% are commonly used.
        An example:
        \(P1\): There is a \(70\)% change that it will rain later today.
        \(P2\): If it will rain later today, you should take an umbrella.
        \(C1\): Therefore, you should take an umbrella.
        \(P1\) is NOT stating that it is \(70\)% true it will rain. It will either rain or not; the statement is not true in degrees. What \(P1\) IS claiming is that we can only be certain of rain to a \(70\)% degree. Whether you find \(P1\) acceptable or not would depend on the weather forecast or an assessment of the meteorological data. However, changing the percentage in \(P1\) would provide stronger (or weaker) support to the conclusion. Therefore the degree of strength given to the premise is associated with Adequacy rather then Acceptability (truth).
    - - Unrepresentative Sample (also Rash Generalisation, Hasty Generalisation, Faulty Generalisation, Converse Accident) It is rarely practical to observe every member of a given group, so an assumption always made (but not always explicitly stated) is that the observed members of the group are a representative sample of the whole population (\(P2\)). There are two major ways in which this assumption can be incorrect.
        
        Criticism of Insufficient Statistics (also Random Error) The number of observed members is too small to support any general conclusions about the whole group.
        There is often an element of chance deciding which members of the population are observed. With small samples sizes, chance plays a greater role in determining the outcome. If a two of more small groups of observations are taken from the same population, they are likely to be very different. As the sizes of the samples are increased, the different groups converge to be similar. Thus, large sample sizes will more precisely reflect the whole population.
        
        How Large Should a Sample Size Be? Statistics has a number of methods for determining adequate sample sizes for different situations. However, we make two general observations here. Firstly, the greater the variation in the population, the greater the sample size will need to be. Secondly, the amount of information added by each new observation diminishes as the sample size increases. Therefore, in practice we can justify basing conclusions on sample sizes which are much smaller than the whole population.
        
        Criticism of Biased Statistics (also Sampling Bias, Selection Bias, Systematic Error) The population may contain different sub-populations (strata) which have different characteristics. Therefore, if the observations have been taken disproportionately from a particular sub-group, they may not provide adequate support for general conclusions about the whole population. An example would be conducting an opinion poll in one region of a country which is demographically or economically different from other regions, but than claiming the results are reflective of the whole country's population.
        Sometimes this happens due to the bad faith of researchers, who cherry pick samples in order to support the particular conclusions they prefer. More often, this problem occurs when some part of population is less visible than others and thus is not sufficiently accounted for.
        
        Correcting for Bias In practise, it can be quite difficult to collect samples which are completely free from any bias. A number of statistical methods have been developed in order to account for the sampling bias and obtain something close to the correct results for the whole population. Unfortunately, these different techniques can produce very different results when applied to the same data and there is no general consensus on which technique is better.
    - - Ignoring Qualifications (also Secundum Quid, Destroying the Exception, Fallacy of Accident, Fallacy of Hasty Generalisation) A fallacy that occurs when someone applies a statistical syllogism to a specific case without taking into account relevant qualifications or exceptions. In other words, the person overlooks important details or conditions that may affect the applicability of the generalisation to the specific case.
  - - - Powerful (also Scope) The explanation should be able to account for a wide range of observations, not just a narrow set of data. A good explanation should be able to predict further observations or phenomena. It should make testable predictions that can be confirmed or falsified by future evidence.
      - Simplicity The simplest explanation is often the best one. The explanation that involves the fewest assumptions or postulates is generally preferred.
        
        Occam's Razor The principle states that when there are multiple explanations for a phenomenon, the simplest one is usually the best. In other words, we should prefer the explanation that makes the fewest assumptions or postulates. Occam's razor relates to simplicity because it suggests that the simplest explanation is more likely to be true than a complex one. This is based on the idea that the more assumptions we make, the more opportunities there are for our explanation to be wrong. By choosing the simplest explanation, we reduce the risk of errors and increase the likelihood of a correct explanation.
      - Falsifiable An explanation is considered better if it can be disproved with empirical evidence. An explanation that is unfalsifiable cannot be tested and therefore has less explanatory power. Related to Self Sealers
        
        No True Scotsman Fallacy (also Ad Hoc Clauses) a logical fallacy in which a person attempts to retain a claim or belief in the face of evidence to the contrary by redefining the term or category in a way that excludes the contradictory case. For example, suppose someone says, "All Scotsmen love haggis." Person B responds, "But my Scottish friend doesn't like haggis." Person A then responds, "Well, no true Scotsman would dislike haggis." This fallacy relates to falsifiability because it is a way of avoiding falsification of a claim or belief. By redefining the terms or categories in a way that excludes contradictory cases, the claim or belief becomes unfalsifiable. In other words, it becomes immune to evidence that would otherwise contradict it.
      - Conservative (also Coherance, Plausibility) The explanation should be consistent with other beliefs and knowledge we have. It should not conflict with other well-established theories or facts. The explanation should be plausible given the available evidence, and not rely on ad hoc or improbable assumptions.
  - - - Validity The structure of the argument is correct such that if the premises are true the the conclusion also has to be true. Valid arguments can still have false conclusions if one or more of the premises are false. Valid arguments by definition are both Relevant and Sufficient.
        
        Soundness An argument which is both valid and has Acceptable premises.
      - Indefeasible A conclusion or argument is considered indefeasible if it is not subject to change or revision based on new evidence or counterarguments. Indefeasible reasoning is typically associated with deductive reasoning, where conclusions are logically certain given the truth of the premises and the validity of the argument.
    - - Formal Fallacies
        
        Affirming the Consequent
        \( \frac{ P \rightarrow Q, Q}{\therefore P} \)
        If there is an electrical fault on the car, then the car will fail to start (\(P \rightarrow Q\)). The car fails to start (\(Q\)). But it would be erroneous to conclude the car has an electrical fault (\(P\)).
        
        Affirming a Disjunct
        \( \frac{U \lor P , U}{\therefore \lnot P} \)
        Either car's petrol tank is empty or there is an electrical fault on the car (\(U \lor P\)). At least one of these things must be true. The car's petrol tank is empty (\(U\)). But it would be erroneous to conclude that the car did not also have an electrical fault (\(\lnot P\)). The reason for this is that is is possible for the car's petrol tank to be empty (\(U\)) and for there to be an electrical fault on the car (\(P\)) at the same time. The fact that we know one of these things to be true does not tell us anything about the truth of the other one.
        
        Denying the Antecedent
        \( \frac{ P \rightarrow Q, \lnot P}{\therefore \lnot Q} \)
        If there is an electrical fault on the car, then the car will fail to start (\(P \rightarrow Q\)). There is no electrical fault on the car (\(\lnot P\)). But it would be erroneous to conclude the car will start (\(\lnot Q\)), as there may be another problem.
        
        Denying a Conjunct
        \( \frac{\lnot (P \wedge W), \lnot W}{\therefore P} \)
        It is not true that the car can have an electrical fault and only be in good condition (\(\lnot (P \wedge W)\)). One of these things may be true or neither, but not both at the same time. The car is not is good condition (\(\lnot W\)). But it would be erroneous to conclude that the car has an electrical fault (\(P\))
      - Valid Argument Forms
        
        Denying the Consequent (also Modus Tollens)
        \( \frac{ P \rightarrow Q, \lnot Q}{\therefore \lnot P} \)
        If there is an electrical fault on the car, then the car will fail to start (\(P \rightarrow Q\)). The car has not failed to start (\(\lnot Q\)). Therefore there is no electrical fault on the car (\(\lnot P\)).
        
        Hypothetical Syllogism
        \( \frac{ P \rightarrow Q, Q \rightarrow R}{\therefore P \rightarrow R} \)
        If there is an electrical fault on the car, then the car will fail to start (\(P \rightarrow Q\)). If the car fails to start, the car is immobile (\(Q \rightarrow R\)). Therefore if there is an electrical fault on the car, the car is immobile (\(P \rightarrow R\)).
        
        Affirming the Antecedent (also Modus Ponens)
        \( \frac{ P \rightarrow Q, P}{\therefore Q} \)
        If there is an electrical fault on the car, then the car will fail to start (\(P \rightarrow Q\)). There is an electrical fault on the car (\(P\)). Therefore the car will fail to start (\(Q\)).
        
        Disjunctive Syllogism (also Modus Tollendo Ponens)
        \( \frac{ U \lor P , \lnot U}{\therefore P} \)
        Either car's petrol tank is empty or there is an electrical fault on the car (\(U \lor P\)). At least one of these things must be true. We can rule out the car's petrol tank is not empty (\(\lnot U\)). Therefore there is an electrical fault on the car (\(P\)).
- - - - Language The phrasing of questions in an opinion poll can significantly impact the responses people provide. Slight changes in the wording or the order of questions can lead to different interpretations or emphasis, which can in turn affect the results. Additionally, leading questions or questions that assume a particular stance can also influence responses. It is crucial for opinion polls to use clear, neutral, and unbiased language to avoid misrepresenting popular opinion due to language-related issues.
      - Sampling Issues Obtaining a representative sample of the population is crucial for accurately reflecting popular opinion. Sampling problems and biases can occur when the selected sample is not representative of the larger population, leading to skewed results. This can lead to an inaccurate representation of the true popular opinion, and the results of the poll may not accurately reflect the views of the wider population.
      - Preference Falsification Occurs when individuals do not express their true beliefs or preferences in an opinion poll, often due to social pressure or fear of repercussions. People may choose to provide answers they believe are socially acceptable, politically correct, or in line with the perceived majority opinion, rather than expressing their genuine views. This can lead to a significant discrepancy between the results of an opinion poll and the actual popular opinion. Factors that contribute to preference falsification include the desire to conform to social norms, the fear of being ostracised or discriminated against for holding unpopular views, and the tendency to avoid controversy or conflict.
  - - - Halo Effect (also Appeal to Celebrity) Someone who is a revered expert in one field gives an opinion on an issue in another (sometimes completely unrelated) field but the reverence is carried over.
    - - Technical Jargon Certain domains use specialised terminology. Misinterpreting the meaning of terms can lead to the expert's argument being misrepresented.
      - Missing Caveats Experts in a domain will often understand the uncertainties and limits of the current knowledge in that domain. As such they will often give opinions containing caveats or conditions. One particular trick is for a third party to quote (or paraphrase) the expert leaving out these caveats in order to make an argument appear stronger then it actually is.
    - - Failure to Cite One particular problem is when we do not know who the experts are if referred to by a another party. For example, we could state: experts agree that .... This is always a fallacy since we have no way of validating the claims.
      - Confusion with Authority / Popularity The fact that a person holds a senior position or is often quoted by the media does not itself denote that person is an expert. The position might be an administrative role or the media might quote a person because they are well known.
- - - - False statements, whether intentional or not, perform a significant function in a system of freedom of expression by forcing citizens to defend, justify and rethink their positions. - Thomas Irwin Emerson
      - If you don’t understand how someone could possibly believe something as stupid as they do, then you should consider the possibility that that’s because you don’t understand, rather than because they’re stupid - Tom Chivers
  - - - Epistemic Humility refers to an intellectual virtue characterised by recognising the limitations of one's own knowledge and being open to the possibility that one's beliefs might be incorrect or incomplete. It involves a willingness to question one's assumptions, consider alternative perspectives, and revise beliefs in light of new evidence or logical arguments. Epistemic humility also encourages acknowledging the complexity and uncertainty inherent in many aspects of human knowledge and understanding.
      - What evidence would it take to change your mind? The way to test if a belief is held in the narrative or rational mindset is to ask: "What evidence would it take to change your mind?". The rational mindset is always open to revision of beliefs based on new evidence or information. No belief is ever final or beyond the possibility of change. The narrative mindset will either discard new information or interpret it in a way consistent with existing beliefs.
    - - Motivated Reasoning A cognitive phenomenon where people process information and form judgements in a way that aligns with their pre-existing beliefs, values, or desires. Instead of evaluating evidence and arguments objectively, individuals engaging in motivated reasoning tend to be biased towards information that confirms their existing views, while downplaying or ignoring evidence that contradicts them. This often results in selective exposure to information, confirmation bias, and cognitive dissonance.
        
        Ignorance more frequently begets confidence than does knowledge - Charles Darwin
        
        Virtually no idea is too ridiculous to be accepted, even by very intelligent and highly educated people, if it provides a way for them to feel special and important. Some confuse that feeling with idealism. - Thomas Sowell
        
        Fundamentalism, properly understood, is not about religion. It is about the inability to seriously entertain the possibility that one might be wrong - Jonathan Rauch
        
        There are few people who are more often wrong than those who cannot suffer being wrong. - François de La Rochefoucauld
        
        So convenient a thing is it to be a reasonable creature, since it enables one to find or make a reason for everything one has a mind to do - Benjamin Franklin
        
        The Curse of Knowledge Experience or knowledge does not necessarily protect people from Cognitive Biases. In some cases, as individuals become more confident in their knowledge or experience, they may become more susceptible to certain cognitive biases.
        
        Intelligence vs Rationality It is possible for an intelligent person to be irrational or engage in biased thinking. In some cases, intelligent individuals may even use their cognitive abilities to construct elaborate arguments that support their pre-existing beliefs, regardless of the evidence or logic that may contradict those beliefs. This can be a manifestation of motivated reasoning, where people process information and form judgements in a way that aligns with their pre-existing beliefs, values, or desires.
        Conversely, a person may not have exceptional cognitive abilities but still be capable of engaging in rational thinking and making sound decisions by prioritising evidence, logic, and critical thinking in their decision-making process.
        
        Most scholarship involves judicious selection from a vast and usually incomplete body of material. It is possible to create an entirely false narrative without actually lying, by exaggeration and tendentious selection. The major threat to integrity comes when the criteria of selection are derived from a ideological agenda. - Jonathan Sumption
- - - - Data information collected from various sources. High-quality, relevant, and accurate data is essential for generating reliable predictions,
      - Assumptions The underlying beliefs or premises that are taken for granted in a given context. In the context of making a prediction, assumptions are necessary to simplify complex relationships, fill gaps in data, or establish a baseline for analysis. However, assumptions can also introduce errors or biases if they do not accurately reflect the real-world conditions or relationships being modelled.
      - Knowledge The understanding or expertise gained from experience, education, or research. In the context of making a prediction, knowledge helps in interpreting data, identifying relevant factors, and making sense of the patterns observed.
    - - Trade-Offs The process of balancing competing priorities or factors. It involves making a choice between two or more desirable but mutually exclusive options, with the understanding that selecting one option may result in the loss or reduction of the benefits associated with the other option(s). Trade-offs often arise when resources are limited, such as time, money, or effort, and decision-makers must allocate them in a way that optimises the overall outcome. In this process, decision-makers must consider the advantages and disadvantages of each option, and assess the relative importance of the factors involved to make the best possible decision.
        
        Optimisation Overemphasis refers to situations where decision-makers focus excessively on optimising one aspect or metric without adequately considering the trade-offs and consequences for other aspects or metrics. This can lead to sub-optimal solutions, as the overemphasis on a single criterion may result in unintended consequences, inefficiencies, or poor performance in other areas.
    - - Sunk Cost Fallacy (also Concorde Fallacy, Escalation of Commitment) Occurs when individuals continue to invest time, money, or resources into a project or decision based on the amount they have already invested, rather than evaluating the current and future value of the investment. The fallacy lies in the fact that the resources already spent, known as "sunk costs," cannot be recovered, and therefore should not influence the decision-making process.
      - Anchoring Bias Individuals often rely too heavily on the first piece of information they encounter (the "anchor") when making decisions. This can result in insufficient adjustments being made as new information becomes available.
      - Confirmation Bias People tend to seek, interpret, and remember information that confirms their pre-existing beliefs while dismissing or ignoring contradicting evidence. This can lead to a skewed perception of reality and hinder objective decision-making.
      - Overconfidence Bias (also Dunning-Kruger Effect) refers to the phenomenon where individuals with low levels of competence in a particular area tend to overestimate their abilities, while those with high levels of competence may underestimate their abilities. This occurs because individuals with low competence often lack the self-awareness and knowledge to accurately assess their own performance, leading to an inflated sense of confidence. On the other hand, highly competent individuals may assume that tasks are equally easy for others, causing them to underestimate their own abilities relative to their peers.
  - - - Advantages
        
        Efficiency Precedents can help streamline the decision-making process by providing a reference point or framework to follow, reducing the time and effort required to evaluate each individual case from scratch.
        
        Reduced Uncertainty Precedents can help reduce uncertainty in decision making by providing examples of how similar situations have been handled in the past, offering insights into potential outcomes and consequences.
        
        Consistency By referring to established precedents, decision-makers can maintain a level of consistency across similar cases, promoting fairness and predictability in their decision-making processes.
      - Disadvantages
        
        Resistance to Change Following precedents can perpetuate outdated practices, as decision-makers may be hesitant to adopt new approaches or challenge the status quo. This can result in missed opportunities for innovation and improvement.
        
        Unintended Consequences In some cases, decision-makers may achieve a particular outcome in the short term by following a precedent, but doing so could establish a new precedent or reinforce an existing one that leads to unwanted outcomes in future decisions.
  - - - Independence Refers to the ability of group members to form and express their own opinions, judgements, or perspectives without being unduly influenced by the opinions of others in the group. Independence is crucial for ensuring that a variety of perspectives are considered during the decision-making process, rather than just conforming to the majority or the views of a dominant individual.
      - Cognitive Diversity Refers to the differences in how individuals think, process information, perceive problems, and approach decision making. Cognitive diversity can result from variations in expertise, experiences, education, cultural backgrounds, or cognitive styles. In group decision making, cognitive diversity is essential for generating a wide range of ideas and solutions, promoting creativity, and enhancing problem-solving capabilities.
        
        Identity Diversity Refers to differences in personal characteristics or social identities, such as race, gender, ethnicity, age, religion, sexual orientation, or socioeconomic background.
        The relationship between cognitive diversity and identity diversity can be complex
        
        Identity diversity can contribute to cognitive diversity, as individuals from different backgrounds or with different personal characteristics may bring unique perspectives, experiences, and problem-solving approaches. For example, people from different cultures may have distinct ways of viewing and tackling challenges, which can enhance the cognitive diversity within a group.
        
        However, identity diversity does not guarantee cognitive diversity. It is possible for a group to have diverse personal characteristics yet still exhibit similar cognitive styles, problem-solving approaches, or areas of expertise. Similarly, cognitive diversity can exist within a group that appears homogeneous in terms of personal characteristics, as individuals may possess different skills, experiences, or cognitive styles despite sharing similar demographic backgrounds.
    - - It is hard to imagine a more stupid or more dangerous way of making decisions than by putting those decisions in the hands of people who pay no price for being wrong. - Thomas Sowell
- - - - Vacuity An argument is vacuous when it assumes as a Premise what it seeks to establish as a Conclusion. Such arguments are self-referential and do not lead anywhere.
        
        Kafka Trap A rhetorical fallacy in which an accusation is made in such a way that any denial or response by the accused is taken as further evidence of guilt. Named after the writer Franz Kafka, this fallacy is often employed in situations where the accused is placed in a no-win situation, as any attempt to defend themselves only reinforces the accusation.
        
        Begging the Question (also Petitio Principii) A logical fallacy where the conclusion of an argument is assumed in one or more of its premises. In other words, the argument relies on the very point it is trying to prove, making it circular and invalid.
        
        Self-Sealers An argument that is structured in such a way that any attempt to counter it or provide contrary evidence is interpreted as further proof of the argument's validity. These arguments can be difficult to refute because they are immune to criticism by design.
      - False Dichotomy (also False Dilemma) A premise which give a choice between two (or more) alternatives and falsely assumes these choices are exhaustive or exclusive.
      - Inconsistency
        
        Contrariety Two Premises in the argument cannot both be true. However, unlike Contradiction, both premises can be false.
        
        Contradiction Two Premises in the argument must have opposite truth values. That is, the truth of one implies falsity of the another while the falsity of one implies the truth of the other.
  - - - Genetic Fallacy A logical fallacy that occurs when an argument's validity or truth is assessed based on its origin or source, rather than on the merit of the argument itself. This fallacy involves the belief that if the origin of an idea, claim, or argument is questionable or disreputable, then the idea or argument must be inherently false, invalid, or untrustworthy.
      - Appeal to Novelty (also Argumentum ad Novitatem) A logical fallacy that occurs when someone claims that something is superior, better, or more valid simply because it is new or recent. This fallacy is based on the assumption that novelty, in and of itself, is an indicator of value, quality, or truth.
      - Appeal to Nature (also Naturalistic Fallacy, Argument from Nature) A logical fallacy that occurs when someone claims that something is inherently good, right, or beneficial simply because it is natural, or that something is inherently bad, wrong, or harmful because it is unnatural. This fallacy is based on the assumption that what is found in nature is always preferable or morally superior to what is created or modified by humans.
      - Fallacy of Composition Occurs when someone assumes that a property or characteristic of the individual parts or members of a whole must necessarily apply to the whole itself. This fallacy involves mistakenly believing that what is true for individual components must also be true for the collective entity they form.
      - Fallacy of Division Occurs when someone assumes that a property or characteristic of a whole must necessarily apply to its individual parts or members. This fallacy involves mistakenly believing that what is true for a collective entity must also be true for the individual components within that entity.
    - - Motte and Bailey Occurs when someone advances a controversial, bold, or easily criticised claim (the "bailey") and, when challenged, retreats to a less controversial or more easily defended position (the "motte"), while still claiming to hold the original stance. The fallacy lies in the switching between the two positions in an attempt to defend the weaker claim by conflating it with the stronger one. This can create confusion or make it difficult for opponents to argue effectively, as the person using the Motte and Bailey fallacy can shift between the two positions as needed to avoid criticism.
      - Red Herring Involves introducing an irrelevant or unrelated topic into a discussion to distract from the original argument or issue. By diverting attention away from the actual argument, the person using the red herring hopes to avoid addressing the issue at hand or make it seem less important.
      - Straw Man In an argument to refute a given statement, a straw man is a misrepresentation of the proposition under consideration. Often the misrepresentation will be a modification of the correct proposition which is easier to refute. Thus, allowing the arguer to falsely claim they have refuted the correct proposition. The misrepresentation may be deliberate or due to Unclarity in the correct proposition.