By the way, there is also an alternative to causal graphs, namely "finite factored sets" by Scott Garrabrant. Probably more alternatives exist. Though I don't know more about (dis)advantages.
Lesswrong promulgated a seriously misleading view of Aristole as some fussy logician who never observed reality and was unaware of probability, chance, the unknown, and so on. It is entirely false. Aristotle repeats, again and again and again, that we can only seek the degree of certainty that is appropriate for a given subject matter. In the Ethics, perhaps his most-read work, he says this, or something like it, at least five times.
I mention this because your association of the words "absolutist" and "Aristotelian" suggests your comment may have been influenced by this.
ISTM that there are two entirely different discussions taking place here, not opposed to each other. "Aristotelian" logic tends to be more concerned with ontology -- measles causes spots, therefore if he has measles, then he will have spots. Whereas the question of probability is entirely epistemological -- we know he has spots, which may indicate he has measles, but given everything else we know about his history and situation this seems unlikely; let's investigate further. Both describe reality, and both are useful.
So the fallacies are entirely fallacious: I don't think your point gainsays this. But I agree that, to us, B may suggest A, and it is then that the question of probability comes into play.
Aquinas, who was obviously greatly influenced by Aristotle, makes a similar point somewhere IIRC (I think in SCG when he's explaining why the ontological argument for God's existence fails), so it's not as if this is a new discovery.
See also Euclid; the fact that his geometry turns out not to be The Geometry does not diminish what it means to have blazed that trail. And it took centuries for anyone to find an alternative; that's quite an accomplishment.
If I have a backhanded criticism hiding in my comment, it actually isn't pointed at Aristotle, but at the school system that may teach some super basic logic at some point and accidentally teaches people that's all logic is, in much the same way stats class accidentally teaches people that everything is uniformly randomly distributed (because it makes the homework problems easier, which is legitimately true, but does reduce the education's value in the real world), leaving people fairly vulnerable to the lists of fallacies they may find on the internet and unequipped to realize that they only apply in certain ways, in certain cases. I don't know that I've ever seen such a list where they point out that they have some validity in a probabilistic sense. There's also the fallacies that are just plain fallacious even so, but I don't generally see them segmented off or anything.
Pedantry: s/centuries/millennia/ (roughly 21 of the former, 2 of the latter?)
EDIT: does anyone remember the quote about problems patiently waiting for our understanding to improve?
That's a specific instance of a more general problem in the "logical fallacies", which is that most of them are written to be true in an absolutist, Aristotelian frame. It is true that if two things are correlated you can not therefore infer a rigidly 100% chance that there is a causative relationship there. And that's how Aristotelian logic works; everything is either True or False and if there is anything else it is as most "Indeterminate" and there is absolutely, positively, no in betweens or probabilities or anything else.
However, consider the canonical "logical fallacy":
It is absolutely a logical fallacy in the Aristotelian sense. Just because B is there does not mean A is. However, probabilistically, if you are uncertain about A, the presence of B can be used to update your expected probability of A. After all, this is exactly what Bayes' rule is for!Many of the "fallacies" can be rewritten to be useful probabilistically, and aren't quite as fallacious as their many internet devotees fancy.
It is certainly reasonable to be "suspicious" about correlations. There often is a "there" there. Of course, whether you can ever figure out what the "there" is is quite a different question; https://gwern.net/everything really gets in your way. (I also recommend https://gwern.net/causality ).
The upshot is basically 1. the glib dismissal that correlation != causation is, well, too glib and throws away too many things but 2. it is still true you still generally can't assume it either. The reality of the situation is exceedingly complicated.