Advanced lesson on fallacies involving conditional probability, particularly in legal and forensic contexts. Students learn to distinguish between P(A|B) and P(B|A), understand the importance of independence in probability calculations, recognize when low probability doesn't mean impossibility, and identify when similarity to stereotypes substitutes for actual probability assessment.
Confusing the probability of evidence given innocence P(evidence|innocent) with the probability of innocence given evidence P(innocent|evidence). This error involves transposing conditional probabilities, typically by arguing that because the evidence would be unlikely if the defendant were innocent, the defendant is therefore unlikely to be innocent.
Dismissing statistical evidence by pointing to the large number of people who could potentially match the evidence, without considering that the defendant was not selected randomly from that large pool but through an investigation process. This argues that because many people could match the evidence, the match to the defendant is not significant.
Incorrectly multiplying probabilities of events that are not independent, treating dependent or correlated events as if they were independent. Named after the Sally Clark case where an expert incorrectly multiplied probabilities of SIDS deaths without accounting for genetic, environmental, or medical factors that could make multiple deaths in one family correlated.
Arguing that because something has a very low probability, it is effectively impossible or could not have occurred by natural processes, therefore requiring an alternative explanation (often design or intent). This confuses 'extremely unlikely in any specific instance' with 'impossible' or 'could never happen.'
Judging the probability of an event or category membership based on how similar it is to a typical example or stereotype, while ignoring relevant statistical information like base rates, sample size, or randomness. This involves substituting similarity assessment for proper probability calculation.
Treating morally distinct situations, actions, or agents as equivalent by focusing on superficial similarities while ignoring crucial moral differences in intent, context, magnitude, or consequences. This fallacy creates a false symmetry between unequal moral situations.
Arguing that because one is morally superior or has taken the ethical position on an issue, one is therefore exempt from obligations, criticism, or normal rules that apply to others. The fallacy assumes moral correctness grants special privileges or immunity from accountability.
Reasoning that past good behavior, virtuous identity, or progressive credentials grant permission for current questionable behavior. This fallacy treats moral worth as a currency that can be accumulated and spent, rather than as a standard that applies to each action independently.
Judging the morality of an action primarily or solely by its outcome rather than by the intent, care, and reasonableness of the decision at the time it was made. This fallacy makes moral assessment hostage to factors beyond the agent's control, treating lucky and unlucky versions of the same decision as morally different.
Inferring that because something ought (not) to be the case, it therefore is (not) the case in reality. This fallacy derives factual claims from moral preferences, assuming that what should be true must be true, or what shouldn't be true must be false. It's the inverse of the naturalistic fallacy.
Arguing that suffering, hardship, or pain is inherently valuable for character development or moral improvement, without evidence that the specific suffering produces the claimed benefits. This fallacy assumes all suffering is purifying or educational, regardless of its nature, severity, or context.
The claim that listening to classical music, particularly Mozart, enhances intelligence or cognitive abilities in lasting ways. This fallacy overgeneralizes limited research findings about temporary, task-specific effects into broad claims about permanent intelligence enhancement.
Conducting numerous statistical tests or comparisons and then highlighting the significant results without accounting for the increased probability of finding false positives by chance alone. The more comparisons you make, the more likely you are to find some significant results purely by random chance, even when no real effect exists.
Using the adage 'anything that can go wrong will go wrong' as if it were an actual predictive principle or law of nature, rather than a humorous observation about selective attention to negative outcomes. This involves treating a folk saying as if it provides explanatory power or justifies assuming the worst-case scenario will occur.
Rejecting a realistic solution to a problem because it doesn't achieve perfection, or comparing an imperfect real-world option unfavorably to an idealized, often unattainable alternative. This fallacy assumes that unless a solution solves the problem completely and without any downsides, it shouldn't be pursued.
Dismissing new ideas, discoveries, or developments by claiming that everything is merely a repetition of the past, that nothing is genuinely new, or that any apparent novelty is just superficial variation on eternal themes. This fallacy uses superficial similarities to past events or ideas to deny meaningful innovation or change.
A formal error in categorical syllogisms where the conclusion is negative (contains 'not' or 'no') but both premises are affirmative (contain 'all' or 'some' without negation). In valid syllogistic logic, at least one premise must be negative to validly derive a negative conclusion.
Rejecting ideas, solutions, or innovations primarily because they originate from outside one's own organization, team, or field, while assuming that internally developed solutions are superior regardless of objective merit. This fallacy prioritizes the source of an idea over its actual quality or applicability.