Just a note about terminology: “expected bits of evidence” also goes by the name of entropy, and is a good thing to maximize in designing an experiment. (My previous comment on the issue.)
And if I understand you correctly, you’re saying that the problem with entropy as a measure of falsifiability, is that someone can come up with a crank theory that gives the same predictions in every single case, except one that is near impossible to observe, but which, if it happened, would completely vindicate them?
If so, the problem with such theories is that they have to provide a lot of bits to specify that improbable event, which would be penalized under the MML formalism because it lengthens the hypothesis significantly. That may be want you want to work into a measure of falsifiability.
But then, at that point, I’m not sure if you’re measuring falsifiability per se, or just general “epistemic goodness”. It’s okay to have those characteristics you want as a separate desideratum from falsifiability.
Just a note about terminology: “expected bits of evidence” also goes by the name of entropy, and is a good thing to maximize in designing an experiment. (My previous comment on the issue.)
And if I understand you correctly, you’re saying that the problem with entropy as a measure of falsifiability, is that someone can come up with a crank theory that gives the same predictions in every single case, except one that is near impossible to observe, but which, if it happened, would completely vindicate them?
If so, the problem with such theories is that they have to provide a lot of bits to specify that improbable event, which would be penalized under the MML formalism because it lengthens the hypothesis significantly. That may be want you want to work into a measure of falsifiability.
But then, at that point, I’m not sure if you’re measuring falsifiability per se, or just general “epistemic goodness”. It’s okay to have those characteristics you want as a separate desideratum from falsifiability.