I've been studying critical thinking and come across what looks like a paradox. Let's say we have the following argument:
P1) If a person is A, then it's likely that that person is also B.
P2) This person is A.
C) This person is likely to be B.
Here, "likely" is interpreted as having a probability greater than 0.5. Using conditional probability we can write P1 as
Pr(B|A) > 0.5
This argument is deductively valid. If our premises are true we can confidently say that the person is more likely to be B than not.
Now, let's consider another argument:
P1) If a person is C, then it's likely that that person is also B.
P2) This person is C.
C) This person is likely to be B.
Just like with the first argument we can write P1 as
Pr(B|C) > 0.5
And again, taking this argument in isolation and assuming the premises are true, we can say that the person in question is more likely to be B than not.
Finally, let's assume that we have both arguments and their second premises refer to the same person. Is it likely that that person is B? On the surface it seems to be likely - we have two arguments both of which confirm it. At the same time, what I now need to show is that
Pr(B|A,C) > 0.5
Using Bayes theorem we can write it as follows:
Pr(B|A,C) = Pr(B ∧ A ∧ C) / Pr(A ∧ C)
I believe, those values cannot be expressed using Pr(B|C) and Pr(B|A), so we can't be confident that Pr(B|A,C) > 0.5. I have found an article on Cross Validated which confirms my intuition.
This looks paradoxical because we have two arguments each of which confirms likelihood of the person being B, but still, when we combine them they do not reinforce each other. My only explanation of this paradox is that, as humans, we tend to put significance on value 0.5 which separates "likely" from "unlikely" while in mathematics it's just an ordinary number between 0 and 1.
So my questions are:
- Is my intuition about impossibility of estimating Pr(B|A,C) from Pr(B|A) and Pr(B|C) correct?
- If it's correct why does this situation look paradoxical?