tag:blogger.com,1999:blog-3891434218564545511.post1836356875725411845..comments2024-03-28T19:56:42.305-05:00Comments on Alexander Pruss's Blog: The Bayesian false belief pandemicAlexander R Prusshttp://www.blogger.com/profile/05989277655934827117noreply@blogger.comBlogger4125tag:blogger.com,1999:blog-3891434218564545511.post-74174698788267209932019-05-03T13:41:57.188-05:002019-05-03T13:41:57.188-05:00Semantics here. I think at least some Bayesians wo...Semantics here. I think at least some Bayesians would consider Bayesian belief to be the degree of personal confidence we have in a hypothesis, which IanS would call a credence, not a belief. <br /><br />I suppose that I would call a belief in a probability distribution a belief too. Sometimes that kind of belief is all we tend to have, until we know more.<br /><br /><br /><br />Williamhttps://www.blogger.com/profile/09292602256213936359noreply@blogger.comtag:blogger.com,1999:blog-3891434218564545511.post-20579258484204476682019-05-03T09:16:36.264-05:002019-05-03T09:16:36.264-05:00Here is a view I find congenial. I will not say I...Here is a view I find congenial. I will not say I believe it yet. :-)<br /><br />Mentally representing the world takes some effort and resources. We often economize on these resources and use only as much as seems like a good idea. We have different levels of precision for representing the world, which I will call (a) belief, (b) credence, and (c) probability distribution. (There might be more levels/types.) It is fallacious to think that any of these is equivalent to any of the others, or that we only use one type.<br /><br />A belief is a simple yes/no view about whether a proposition obtains. We might modify this to include some in-between values for vague predicates.<br /><br />A credence is a probability assignment. (Values could be of varying degrees of precision.) It is harder to hold, and process, a probability assignment than a simple belief, so we don’t do it as much. (Vagueness in belief is metaphysical; probability in a credence is epistemic.) Bayesianism is an epistemic ideal for creatures with unlimited cognitive resources, which we are not.<br /><br />A probability distribution is a range of credences about a range of values as applied to an open sentence. Probability distributions entail credences but not vice versa. It is even harder to hold and process probability distributions than individual credences and so we do this very rarely indeed. Or maybe credences are actually a philosopher’s fiction; what we have in real life is almost always either a belief or a probability distribution. (I can think of few instances where I know the probability that X is F(n) but not the probability that X is F(n-1) or F(n+1). )<br /><br />So I would reject the inference from credence-above-a-threshhold to belief. If what you know is that a bunch of coins are flipped, what you rightly have in mind is a certain credence (indeed, probability distribution) and you have made no errors. <br />Heath Whitehttps://www.blogger.com/profile/13535886546816778688noreply@blogger.comtag:blogger.com,1999:blog-3891434218564545511.post-12953410712026307342019-05-02T20:30:02.472-05:002019-05-02T20:30:02.472-05:00Thorough Bayesians would have no use for beliefs. ...Thorough Bayesians would have no use for beliefs. They would have credences for everything. Some propositions might have credences close to 1, but calling them beliefs would add nothing.<br /><br />If the coin flips are taken as objectively chancy, then their probabilities are the best representation of reality, and the best guide to action, possible to someone who does not know the outcomes. Beliefs can add nothing to this.<br /><br />In real life, we are not thorough Bayesians. We apply Bayesian reasoning when we can, i.e. rarely. More often we act on the basis of beliefs. And yes, it’s true: we see true belief as intrinsically good, but sometimes reasonable false beliefs work just as well in guiding action.IanShttps://www.blogger.com/profile/00111583711680190175noreply@blogger.comtag:blogger.com,1999:blog-3891434218564545511.post-76697859958141850972019-05-01T22:23:03.758-05:002019-05-01T22:23:03.758-05:00Perhaps some beliefs are correct when they specify...Perhaps some beliefs are correct when they specify a range of possibilities, and become incorrect if they over-specify. This also is why overspecification (using too many variables, over-fitting the data) in a regression equation (in statistics) can be wrong.<br /><br />Williamhttps://www.blogger.com/profile/09292602256213936359noreply@blogger.com