- truth and Validity
- statement vs argument
- argument mapping
- raisonnement contre-factuel
- Notes pointant ici
truth and Validity
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To me, this kind of argument is what is used when applying the Occam’s razor. We cannot ensure the conclusion is true, but we can decided to believe it because we think it is the best we can do, considering our belief system.
This process, unlike deductive reasoning, yields a plausible conclusion but does not positively verify it. Abductive conclusions are thus qualified as having a remnant of uncertainty or doubt, which is expressed in retreat terms such as “best available” or “most likely”.
abductive reasoning as inference to the best explanation
time text https://youtu.be/vflZuk-_Hz4&t=69.05s If you let your imagination rip, https://youtu.be/vflZuk-_Hz4&t=71.72s you’ll be able to think of other possible https://youtu.be/vflZuk-_Hz4&t=73.01s answers to the question […] https://youtu.be/vflZuk-_Hz4&t=76.5s Nonetheless, given your background knowledge, https://youtu.be/vflZuk-_Hz4&t=79.549s C seems like it’s the best explanation for P, or at least it’s a contender. https://youtu.be/vflZuk-_Hz4&t=83.92s If it is, then P gives you good reason to believe C. https://youtu.be/vflZuk-_Hz4&t=87.479s That’s how abductive arguments work.
time text https://youtu.be/vflZuk-_Hz4&t=52.539s Notice that the promise doesn’t guarantee that the conclusion is true. https://youtu.be/vflZuk-_Hz4&t=56.989s Something else might explain it instead.
time text https://youtu.be/vflZuk-_Hz4&t=108.74s Abductive arguments are nonetheless extremely common in all walks of life. https://youtu.be/vflZuk-_Hz4&t=113.24s It’s a very important critical thinking skill to be able to make, https://youtu.be/vflZuk-_Hz4&t=117.32s spot, and evaluate abductive arguments.
time text https://youtu.be/vflZuk-_Hz4&t=186.61s So what makes something a good explanation? https://youtu.be/vflZuk-_Hz4&t=190.34s Well, there’s a lot of debate about this amongst philosophers, https://youtu.be/vflZuk-_Hz4&t=194.15s but here are two characteristics of good explanations https://youtu.be/vflZuk-_Hz4&t=196.34s that most generally agree about. https://youtu.be/vflZuk-_Hz4&t=198.019s First, the more an explanation fits in with everything we already know, https://youtu.be/vflZuk-_Hz4&t=203.04s the better it tends to be.
time text https://youtu.be/vflZuk-_Hz4&t=233.799s Second, other things being equal, https://youtu.be/vflZuk-_Hz4&t=237.31s a simpler explanation is better than a complicated one. […] https://youtu.be/vflZuk-_Hz4&t=257.63s Since the original explanation is simpler, it’s preferable to this more complex one.
time text https://youtu.be/vflZuk-_Hz4&t=264.7s Both fit and simplicity come in degrees, https://youtu.be/vflZuk-_Hz4&t=267.34s and other factors are also relevant to how good an explanation is. https://youtu.be/vflZuk-_Hz4&t=271.29s There’s no sure-fire recipe for saying when an explanation is the best one. https://youtu.be/vflZuk-_Hz4&t=275.93s One way to challenge an abductive argument https://youtu.be/vflZuk-_Hz4&t=279.26s is to try to come up with a better https://youtu.be/vflZuk-_Hz4&t=280.7s explanation of the data than what the argument provides.
time text https://youtu.be/vflZuk-_Hz4&t=283.78s Another way to challenge an abductive argument https://youtu.be/vflZuk-_Hz4&t=287.16s is to look for more evidence to add to the promises. […] https://youtu.be/vflZuk-_Hz4&t=312.79s It’s important when relying on an abductive argument https://youtu.be/vflZuk-_Hz4&t=315.96s to make sure that you get all of the evidence that you can https://youtu.be/vflZuk-_Hz4&t=318.73s and then consider all of the evidence before drawing your conclusion. https://youtu.be/vflZuk-_Hz4&t=322.48s That’s because the fact that a conclusion is a good explanation for some https://youtu.be/vflZuk-_Hz4&t=326.59s evidence doesn’t mean that it’s a good explanation for all of your evidence. https://youtu.be/vflZuk-_Hz4&t=331.1s So, summing up.
time text https://youtu.be/vflZuk-_Hz4&t=333.66s Abductive arguments are a kind of ampliative argument: https://youtu.be/vflZuk-_Hz4&t=337.1s their premises don’t guarantee their conclusions. https://youtu.be/vflZuk-_Hz4&t=339.72s Abductive arguments involve an inference to the best explanation: https://youtu.be/vflZuk-_Hz4&t=344.21s their conclusions are supposed to be the best explanations for their premises. https://youtu.be/vflZuk-_Hz4&t=348.37s Abductive arguments play a central role in everyday life and scientific inquiry. https://youtu.be/vflZuk-_Hz4&t=353.69s Good explanations tend to fit with our background knowledge https://youtu.be/vflZuk-_Hz4&t=358.17s and to be simpler than the alternatives. https://youtu.be/vflZuk-_Hz4&t=360.19s And finally, you can challenge an abductive argument by coming up https://youtu.be/vflZuk-_Hz4&t=363.92s with a better explanation for the premises, or by finding https://youtu.be/vflZuk-_Hz4&t=367.09s additional relevant evidence that isn’t well-explained by the conclusion.
Référence externe : https://www.butte.edu/departments/cas/tipsheets/thinking/reasoning.html Deductive reasoning, or deduction, is making an inference based on widely accepted facts or premises
Inductive reasoning, or induction, is making an inference based on an observation, often of a sample
Abductive reasoning, or abduction, is making a probable conclusion from what you know.
Deduction is generally defined as “the deriving of a conclusion by reasoning.”
inference of a generalized conclusion from particular instances
a syllogism in which the major premise is evident but the minor premise and therefore the conclusion only probable
Reasoning is the process of using existing knowledge to draw conclusions, make predictions, or construct explanations
Three methods of reasoning are the deductive, inductive, and abductive approaches.
Deductive reasoning: conclusion guaranteed
propositions or premises, lead logically to the third statement, the conclusion
deductive reasoning cannot really increase human knowledge (it is nonampliative) because the conclusions yielded by deductive reasoning are tautologies-statements that are contained within the premises and virtually self-evident.
cannot make predictions about future or otherwise non-observed phenomena
Inductive reasoning: conclusion merely likely
observations that are specific and limited in scope, and proceeds to a generalized conclusion that is likely, but not certain, in light of accumulated evidence.
inductive reasoning moves from the specific to the general.
there is no way to know that all the possible evidence has been gathered, and that there exists no further bit of unobserved evidence that might invalidate my hypothesis
while the newspapers might report the conclusions of scientific research as absolutes, scientific literature itself uses more cautious language, the language of inductively reached, probable conclusions:
the conclusion is therefore probably true
while inductive reasoning cannot yield an absolutely certain conclusion, it can actually increase human knowledge (it is ampliative). It can make predictions about future events or as-yet unobserved phenomena
Abductive reasoning: taking your best shot
Abductive reasoning typically begins with an incomplete set of observations and proceeds to the likeliest possible explanation for the set.
medical diagnosis is an application of abductive reasoning: given this set of symptoms, what is the diagnosis that would best explain most of them?
- Référence externe : https://www.oxfordreference.com/view/10.1093/oi/authority.20110803095409681
Term used by Peirce to denote arguments whose conclusions go beyond their premises (and hence amplify the scope of our beliefs). Inductive arguments and arguments to the best explanation are not deductively valid, but may yield credible conclusions. Most reasoning takes us to conclusions that go beyond our data, in ways that interest us.
deductive vs. ampliative; also, repletive vs. attenuative
Référence externe : http://tetrast.blogspot.com/2015/08/idara.html
Deductive vs. ampliative; also, repletive vs. attenuative
Summary of entailment-related properties (‘entail’ ≡ ‘deductively imply’) INFERENCES ↓PROOF-THEORETICALLY:MODEL-THEORETICALLY: Deductive:The premisses entail the conclusion.Automatically preserves truth. Ampliative (i.e., non-deductive):The premisses do not entail the conclusion.Does not automatically preserve truth. Repletive:The premisses are entailed by the conclusion.Automatically preserves falsity. Attenuative (i.e., non-repletive):The premisses are not entailed by the conclusion.Does not automatically preserve falsity
Intersections of kinds of inference: Inferences Deductive: Ampliative (i.e., non-deductive):
Repletive: Reversible (i.e., equivalential) deduction. Induction, as one often thinks of it (but often not as it is actually framed*).
Attenuative (i.e., non-repletive): ‘Forward-only’ deduction.
Surmise, conjecture, abductive inference (and often induction as actually framed*).
validité d’un argument: comment démontrer n’importe quoi
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Somebody who makes a statement claims that something is true. If you do not know anything about it, this claim alone will not help you much in deciding if you should accept it or not. Somebody who makes an argument for a claim tries to show (by logical inference) that if you already accept some other statements (the premises) you should also accept (and believe) the statement in question (the conclusion).
Visualiser les arguments dans un graphe
Référence externe : https://argdown.org/syntax/
Référence externe : https://argdown.org/
Un outil d’argument mapping qui a l’air prometteur
sketching the argumentation
Sketching the argumentation It’s straight-forward to copy & paste the pros and cons into an Argdown document
Some of the above argument descriptions actually seem to contain different lines of thought, and it’s recommendable to split those descriptions up so that each argument is represented in Argdown by its own element.
questionable whether all pros and cons are directly supporting or attacking the central claim. Granted, <P1a>, for example, is doing so. But <C2> seems to be attacking the argument <P2>rather than attacking central thesis directly. Likewise, <C1b>is best interpreted as an attack on <P1b>. To effect these changes in Argdown, we simply have to shift and indent the corresponding list items
debate involves a further central claim
reconstructing the argumentation
How exactly do the different arguments work? We answer this question by reconstructing the individual arguments as premise-conclusion-structures. In doing so, one will typically revise the sketched dialectical relations between arguments and statements
advisable to start to reconstruct the most central arguments first and to move, gradually, to less central arguments
If all arguments are fully reconstructed, the Argdown document may simply consist in a list of statements, and arguments with attached premise-conclusion-structures.
- Référence externe : https://argdown.org/guide/a-first-example.html
Référence externe : https://fr.wikipedia.org/wiki/Raisonnement_contre-factuel
Le raisonnement contre-factuel est un type particulier de raisonnement qui consiste à modifier en imagination l’issue d’un évènement en modifiant l’une de ses causes
Notes pointant ici
- ad hominem
- argument qui pourrait être utilisé pour défendre un truc faux est un mauvais argument
- arguments vs metaphors
- biais du monde statique
- can programming be easier? (blog)
- ce qui est énoncé sans preuve peut être rejeté sans preuve
- difficulté d’utiliser l’induction sans modèle causal
- est-ce que je veux faire vacciner mon fils de 6 ans contre le COVID ?
- induction problem
- making an API is making a promise (blog)
- mediating assessment protocol
- méthode scientifique vs lecture de documentation
- people need explanations
- plausibility vs validity
- principe de parcimonie
- règle des règles
- scrum is not agile because formally defined?
- stable environment, repeated experiences, fast and clear feedback
- testing argdown