Fallacies: types and examples (chatGPT)


1. Fallacies of Relevance

  • Ad Hominem
    “You can’t trust Dave’s argument on climate change—he failed high school science.”
  • Tu Quoque
    “You say smoking is bad, but I’ve seen you smoke before!”
  • Appeal to Authority
    “A famous actor said this vitamin cures cancer, so it must be true.”
  • Appeal to Emotion
    “Think of the poor children—how can you not support this policy?”
  • Appeal to Fear
    “If we don’t increase surveillance, terrorists will destroy everything we love.”
  • Appeal to Ignorance
    “No one has proven aliens don’t exist, so they must be real.”
  • Appeal to Popularity (Bandwagon)
    “Everyone’s switching to this diet, so it must be the healthiest one.”
  • Appeal to Tradition
    “We’ve always done it this way, so it must be the best way.”
  • Red Herring
    “Why worry about pollution when there are people unemployed?”
  • Straw Man
    “You want to reduce military spending? So you think we should just disband the army?”
  • Genetic Fallacy
    “That idea came from a communist, so it must be wrong.”
  • Guilt by Association
    “You supported that idea, and so did that extremist group—are you one of them?”

2. Fallacies of Ambiguity

  • Equivocation
    “A feather is light. Light can’t be dark. So a feather can’t be dark.”
  • Amphiboly
    “The burglar threatened the student with a knife. So the student must have had the knife.”
  • Accent
    “I didn’t say she stole the money.” (Ambiguity depends on what word is emphasized)
  • Composition
    “Every part of the engine is light, so the engine must be light.”
  • Division
    “The team is the best in the league, so every player must be the best too.”

3. Fallacies of Presumption

  • Begging the Question
    “Reading is beneficial because it’s good for you.”
  • Complex Question (Loaded Question)
    “Have you stopped cheating on exams?”
  • False Dilemma / False Dichotomy
    “You’re either with us or against us.”
  • False Cause (Post Hoc)
    “I wore my lucky socks and we won the game, so they caused the win.”
  • Slippery Slope
    “If we allow one student to redo the test, next thing you know, no one will follow deadlines.”
  • Hasty Generalization
    “Two of my coworkers are rude. Everyone in this office must be awful.”
  • Suppressed Evidence / Cherry Picking
    “This study shows coffee is healthy.” (ignores 10 other studies showing negative effects)

4. Statistical & Probabilistic Fallacies

  • Gambler’s Fallacy
    “It’s been red five times in a row—black must be next.”
  • Base Rate Fallacy
    “This test says you have a rare disease, so you probably do.” (ignores the disease’s rarity)
  • Texas Sharpshooter Fallacy
    “This town has a lot of cancer—and look, there’s a cell tower nearby!”
  • Misleading Vividness
    “I saw a news story about a plane crash. Flying must be dangerous.”
  • Overgeneralization
    “My neighbor from Canada is rude. Canadians must be rude.”

5. Causal Fallacies

  • Post Hoc Ergo Propter Hoc
    “The rooster crowed, and then the sun rose. The rooster caused the sunrise.”
  • Non Causa Pro Causa
    “More people drown when ice cream sales go up—so ice cream causes drowning.”
  • Correlation vs. Causation
    “Kids who play violent games are more aggressive. Games must be making them violent.”
  • Oversimplified Cause
    “The car crashed because of bad tires.” (ignores speeding and foggy weather)

6. Fallacies of Logical Structure

  • Affirming the Consequent
    “If it rains, the ground gets wet. The ground is wet, so it must have rained.”
  • Denying the Antecedent
    “If it rains, the ground gets wet. It didn’t rain, so the ground isn’t wet.”
  • Undistributed Middle
    “All cats are mammals. All dogs are mammals. So all dogs are cats.”

7. Informal Strategy Fallacies

  • No True Scotsman
    “No Scotsman puts sugar in his porridge.”
    “I’m Scottish and I do.”
    “Then you’re not a true Scotsman.”
  • Moving the Goalposts
    “You need 10 years’ experience to qualify.”
    “I have that.”
    “Actually, you also need a PhD.”
  • Special Pleading
    “Yes, I said no exceptions—but my case is different.”
  • Moral Equivalence
    “Stealing a pen is just as bad as stealing a car.”
  • Whataboutism
    “You committed fraud.”
    “Well, what about that other guy who did worse?”
  • Appeal to Nature
    “It’s natural, so it must be good for you.”
  • Relative Privation (Not as Bad As)
    “You’re upset about the potholes? People in other countries don’t even have roads!”
  • Appeal to Consequences
    “If there’s no afterlife, life has no meaning. So there must be an afterlife.”
  • Argument from Silence
    “He didn’t deny the accusation, so he must be guilty.”

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