E is "we have seen no subversive activity".
I don't like the way you describe that. It is confusing. The evidence is subversive activity. You cannot go out and look for no subversive activity, that makes no sense. You have to look for subversive activity. I'm not sure why you're fighting so hard for this point, since not finding something suggests just as much as finding something does. The only reason I suggest a change is for clarity. I don't want to think about no subversive activity and not no subversive activity, I want to think about subversive activity or no subversive activity. There is no difference, the second is simply less confusing.
E is subversive activity, and Warren's position is p(Q|~E).
Do you agree that, under some priors, you could have p(Q|E) > p(Q) and p(R|E) > p(R), even though Q implies not-R?
Absolutely. I said so two posts up. The question is not about Q and R, though, it's about Q and ~Q.
Set aside the question of whether these are reasonable priors.
But the whole argument is about the priors. The reason Warren's position is nonsensical is not because he believes a lack of subversion suggests some fact, it's that he argues that a lack of subversion suggests a fact, and then behaves in a manner counter to his argument. I've been arguing the fact that Warren argues p(Q|~E), But the reason he is locking up the Japanese-Americans is because he expects p(E|Q). The only way p(E|Q) makes any sense is if p(Q|E) is also true.
Warren's fundamental fear is based on p(E|Q) - that is, the 5th Column is plotting and scheming, and this will lead to subversion. The argument he uses to support this, however, is that p(Q|~E). The two positions are inversely related. If p(E|Q) is strong, then p(Q|~E) must be weak.
In other words, if p(E|Q) is strong, and p(Q) is high, then p(E) should be very high (because Q implies E), and p(~E) should be very small. Yet a very high ~E is used as evidence of p(Q). That makes no sense. If p(E|Q) is high, then ~E can exist in spite of Q, but it cannot exist because of Q.
The only way this is at all tenable is if p(E|Q) and p(~E|Q) are both true. In which case, neither E nor ~E is evidence of Q.
That's the whole point.
probability calculus doesn't tell you how to pick your prior.
The whole point of this discussion is that his reasoning does not coincide with his actions. Thus one or the other is wrong.
E is "we have seen no subversive activity".
I don't like the way you describe that. It is confusing. The evidence is subversive activity. You cannot go out and look for no subversive activity, that makes no sense.
Our evidence is always only what we have observed. Maybe it is strange to say that you "looked for no subversive activity". But you certainly can look for subversive activity and fail to find it. Not seeing subversive activity when you looked for it is Bayesian evidence. But it would be an error to condition on ther...
From Robyn Dawes’s Rational Choice in an Uncertain World:
Consider Warren’s argument from a Bayesian perspective. When we see evidence, hypotheses that assigned a higher likelihood to that evidence gain probability, at the expense of hypotheses that assigned a lower likelihood to the evidence. This is a phenomenon of relative likelihoods and relative probabilities. You can assign a high likelihood to the evidence and still lose probability mass to some other hypothesis, if that other hypothesis assigns a likelihood that is even higher.
Warren seems to be arguing that, given that we see no sabotage, this confirms that a Fifth Column exists. You could argue that a Fifth Column might delay its sabotage. But the likelihood is still higher that the absence of a Fifth Column would perform an absence of sabotage.
Let E stand for the observation of sabotage, and ¬E for the observation of no sabotage. The symbol H1 stands for the hypothesis of a Japanese-American Fifth Column, and H2 for the hypothesis that no Fifth Column exists. The conditional probability P(E | H), or “E given H,” is how confidently we’d expect to see the evidence E if we assumed the hypothesis H were true.
Whatever the likelihood that a Fifth Column would do no sabotage, the probability P(¬E | H1), it won’t be as large as the likelihood that there’s no sabotage given that there’s no Fifth Column, the probability P(¬E | H2). So observing a lack of sabotage increases the probability that no Fifth Column exists.
A lack of sabotage doesn’t prove that no Fifth Column exists. Absence of proof is not proof of absence. In logic, (A ⇒ B), read “A implies B,” is not equivalent to (¬A ⇒ ¬B), read “not-A implies not-B .”
But in probability theory, absence of evidence is always evidence of absence. If E is a binary event and P(H | E) > P(H), i.e., seeing E increases the probability of H, then P(H | ¬ E) < P(H), i.e., failure to observe E decreases the probability of H . The probability P(H) is a weighted mix of P(H | E) and P(H | ¬ E), and necessarily lies between the two.1
Under the vast majority of real-life circumstances, a cause may not reliably produce signs of itself, but the absence of the cause is even less likely to produce the signs. The absence of an observation may be strong evidence of absence or very weak evidence of absence, depending on how likely the cause is to produce the observation. The absence of an observation that is only weakly permitted (even if the alternative hypothesis does not allow it at all) is very weak evidence of absence (though it is evidence nonetheless). This is the fallacy of “gaps in the fossil record”—fossils form only rarely; it is futile to trumpet the absence of a weakly permitted observation when many strong positive observations have already been recorded. But if there are no positive observations at all, it is time to worry; hence the Fermi Paradox.
Your strength as a rationalist is your ability to be more confused by fiction than by reality; if you are equally good at explaining any outcome you have zero knowledge. The strength of a model is not what it can explain, but what it can’t, for only prohibitions constrain anticipation. If you don’t notice when your model makes the evidence unlikely, you might as well have no model, and also you might as well have no evidence; no brain and no eyes.
1 If any of this sounds at all confusing, see my discussion of Bayesian updating toward the end of The Machine in the Ghost, the third volume of Rationality: From AI to Zombies.