The particular observation of no sabotage was evidence against, and could not legitimately be worked into evidence for.
You are assuming that there are only two types of evidence, sabotage v. no sabotage, but there can be much more differentiation in the actual facts.
Given Frank's claim, there is a reasoning model for which your claim is inaccurate. Whether this is the model Earl Warren had in his head is an entirely different question, but here it is:
We have some weak independent evidence that some fifth column exists giving us a prior probability of >50%. We have good evidence that some japanese americans are disaffected with a prior of 90%+. We believe that a fifth column which is organized will attempt to make a significant coordinated sabotage event, possibly holding off on any/all sabotage until said event. We also believe that the disaffected who are here, if there is no fifth column would engage is small acts of sabotage on their own with a high probability.
Therefore, if there are small acts of sabotage that show no large scale organization, this is weak evidence of a lack of a fifth column. If there is a significant sabotage event, this is strong evidence of a fifth column. If there is no sabotage at all, this is weak evidence of a fifth column. Not all sabotage is alike, it's not a binary question.
Now, this is a nice rationalization after the fact. The question is, if there had been rare small acts of sabotage, what is the likelihood that this would have been taken by Warren and others in power as evidence that there was no fifth column. I submit that it is very unlikely, and your criticism of their actual logic would thus be correct. But we can't know for certain since they were never presented with that particular problem. And in fact, I wish that you, or someone like you, had been on hand at the hearing to ask the key question: "Precisely what would you consider to be evidence that the fifth column does not exist?"
Of course, whether widespread internment was a reasonable policy, even if the logic they were using were not flawed, is a completely separate question, on which I'd argue that very strong evidence should be required to adopt such a severe policy (if we are willing to consider it at all), not merely of a fifth column, but of widespread support for it. It is hard to come up with a plausible set of priors where "no sabotage" could possibly imply a high probability of that situation.
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.