── ── Cognitive bias
Logical Fallacies
A fallacy is an argument that looks like it works but doesn't. The test is not whether the conclusion is true — it's whether the inference from premises to conclusion is valid. This skill covers two layers: the classical taxonomy (Aristotle's 13, c. 350 BCE — verbal and structural errors) and the modern cognitive map (Tversky-Kahneman 1983 — errors competent…
How it works
Run the Fallacy Audit in four passes — structure, language, cognition, rhetoric — then judge.
1. State the argument cleanly. Rewrite as premises → conclusion. If you cannot, first finding: it's an assertion dressed as an argument. 2. Structural pass. Begging the question, affirming the consequent, denying the antecedent, false cause (post hoc), hasty generalization, accident, complex question, ignoratio elenchi. 3. Linguistic pass. Equivocation (key term shifts meaning), amphiboly, composition/division (part↔whole), accent/figure of speech. 4. Cognitive pass. Conjunction fallacy (P(A∧B) > P(A) from representativeness), base-rate neglect, availability, anchoring — see anchoring. 5. Rhetorical-trap pass. Ad hominem, appeal to authority (exception: expert in own domain), appeal to popularity (weak prior only), appeal to emotion (evidence vs. substitute), false dichotomy, straw man, slippery slope, tu quoque. 6. Judge the argument, not the moves. A fallacy means the inference fails — not that the conclusion is false. 7. Fallacy-fallacy check. If you can't articulate why this instance fails, you have a dismissal, not a finding. 8. Output: for each fallacy — (a) which and where, (b) what the inference fails to establish, (c) what would actually support the conclusion.
When to use it
- someone says 'this argument feels off but I can't explain why', 'is this a real argument or just rhetoric?', 'what's wrong with this reasoning?', an argument relies entirely on authority/emotion/popularity, or you're about to decide based on a single analogy
When not to use it
the conclusion is already verifiable empirically (just check the data); casual conversation where rigor is socially expensive and stakes are low.
Worked example
Tversky & Kahneman's Linda Problem (1983)
To see logical-fallacy detection at full empirical force — not as debate-club gotcha but as an X-ray of how competent minds reason — the cleanest case in the modern literature is Amos Tversky and Daniel Kahneman's 1983 paper "Extensional versus Intuitive Reasoning: The Conjunction Fallacy in Probability Judgment" (Psychological Review, Vol. 90, No. 4, pp. 293–315).
Install this skill (free, MIT)
npx skills add deciqAI/knowledge-skills