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gjm comments on Open thread, Dec. 21 - Dec. 27, 2015 - Less Wrong Discussion
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I'm arguing that Bayesian confirmation theory as a philosophy was originally conceived as a model using only two possibilities (A and ~A), and then this model was extrapolated into problems with more than two possibilities. If it had been originally conceived using more than two possibilities, it wouldn't have made any sense to use the word confirmation. So explanations of Bayesian confirmation theory will often entail considering theories or decisions in isolation rather than as part of a group of decisions or theories.
So if there are 20 possible explanations for a problem, and there is no strong evidence suggesting any one explanation, then I will have 5% certainty of the average explanation. Unless I am extremely good at calibration, then I can't confirm any of them, and if I consider each explanation in isolation from the other explanations, then all of them are wrong.
It doesn't matter whether we're talking about hypotheses or decision-making.
I'm not sure whether this is true, but it's irrelevant. Bayesian confirmation theory works just fine with any number of hypotheses.
If by "confirm" you mean "assign high probability to, without further evidence", yes. That seems to me to be exactly what you'd want. What is the problem you see here?