Bayesianism — an unacceptable scientific reasoning

26 Feb, 2016 at 16:14 | Posted in Theory of Science & Methodology | 5 Comments

coming around to this point of view.









  1. Good for Chalmers, who is a proper Popperian. Bayesianism only works in closed worlds where one might imagine exhausting all possible hypotheses. Science is open and requires testing to find flaws in conjectures. Further, the only truly objective priors (not what goes by that name these days) need to be based on frequencies, and except in very special cases, frequencies of hypotheses being true are unknown.

  2. Isn’t the response to Chalmers’ technical point that in the case of infinitely many hypotheses, the prior is a probability density rather than a distribution? The probability mass of any single hypothesis may be zero, but the density could be non-zero. This criticism seems empty.

    • I agree, it seems like a modern day Zeno’s paradox. Integral calculus solves the technical aspect of the criticism.

      • Chalmers problem is not how you assign probabilities (or densities) to some given list (or space) of hypotheses, but where the set of hypotheses comes from in the first place.Given two definite hypotheses one can often determine a likelihood ratio, and this can be fairly non-controversial. As I understand it, in science one should only ever claim that a hypothesis is much more likely than all the others that have been thought of. The notion of probability seems redundant and potentially misleading.

        I assume that most ‘accepted’ empirical theories are more likely than the alternatives that have been studied. But in what sense does this make them ‘probable’? If they are, presumably we should stop trying to develop the science further.

      • I agree with the issue about where the set of hypothesis should come from (but I also believe this is not unique to Bayesianism, but also frequentism — the turkey’s frequentist assessment of its probability of being slaughtered on Christmas day is still pretty damn low). However, Chalmers explicitly writes “It might well be thought that the number of possible hypotheses in any domain is infinite, which would yield zero for the probability of each and the Bayesian game cannot get started. All theories have zero probability and Popper wins the day.”
        I don’t think that conclusion is valid.

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