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shokwave comments on How to Fix Science - Less Wrong
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This seems the key step for incorporating falsification as a limiting case; I contest it. The rules of Bayesian rationality preclude assigning an a priori probability of 1 to a synthetic proposition: nothing empirical is so certain that refuting evidence is impossible. (Isthat assertion self-undermining? I hope that worry can be bracketed.) As long as you avoid assigning probabilities of 1 or 0 to priors, you will never get an outcome at those extremes.
But since P(X/A) is always "intermediate," observing X will never strictly falsify A—which is a good thing because the falsification prong of Popperianism has proven at least as scientifically problematic as the nonverification prong.
I don't think falsification can be squared with Bayes, even as a limiting case. In Basesian theory, verification and falsification are symmetric (as the slider metaphor really indicates). In principle, you can't strictly falsify a theory empirically any more (or less) than you can verify one. Verification, as the quoted essay confirms, is blocked by the > 0 probability mandatorily assigned to unpredicted outcomes; falsification is blocked by the < 1 probability mandatorily assigned to the expected results. It is no less irrational to be certain that X holds given A than to be certain that X fails given not-A. You are no more justified in assuming absolutely that your abstractions don't leak than in assuming you can range over all explanations.
This throws the baby out with the bathwater; we can falsify and verify to degrees. Refusing the terms verify and falsify because we are not able to assign infinite credence seems like a mistake.
I agree; that's why "strictly." But you seem to miss the point, which is that falsification and verification are perfectly symmetric: whether you call the glass half empty or half full on either side of the equation wasn't my concern.
Two basic criticisms apply to Popperian falsificationism: 1) it ignores verification (although the "verisimilitude" doctrine tries to overcome this limitation); and 2) it does assign infinite credence to falsification.
No. 2 doesn't comport with the principles of Bayesian inference, but seems part of LW Bayesianism (your term):
This allowance of a unitary probability assignment to evidence conditional on a theory is a distortion of Bayesian inference. The distortion introduces an artificial asymmetry into the Bayesian handling of verification versus falsification. It is irrational to pretend—even conditionally—to absolute certainty about an empirical prediction.