Does rationality require imprecise credences? Many hold that it does: imprecise evidence requires correspondingly imprecise credences. I argue that this is false. The imprecise view faces the same arbitrariness worries that were meant to motivate it in the first place. It faces these worries because it incorporates a certain idealization. But doing away with this idealization effectively collapses the imprecise view into a particular kind of precise view. On this alternative, our attitudes should reflect a kind of normative uncertainty: uncertainty (...) about what to believe. This view refutes the claim that precise credences are inappropriately informative or committal. Some argue that indeterminate evidential support requires imprecise credences; but I argue that indeterminate evidential support instead places indeterminate requirements on credences, and is compatible with the claim that rational credences may always be precise. (shrink)

We introduce a distinction, unnoticed in the literature, between four varieties of objective Bayesianism. What we call ' strong objective Bayesianism' is characterized by two claims, that all scientific inference is 'logical' and that, given the same background information two agents will ascribe a unique probability to their priors. We think that neither of these claims can be sustained; in this sense, they are 'dogmatic'. The first fails to recognize that some scientific inference, in particular that concerning evidential relations, is (...) not (in the appropriate sense) logical, the second fails to provide a non-question-begging account of 'same background information'. We urge that a suitably objective Bayesian account of scientific inference does not require either of the claims. Finally, we argue that Bayesianism needs to be fine-grained in the same way that Bayesians fine-grain their beliefs. (shrink)

It is natural to think of precise probabilities as being special cases of imprecise probabilities, the special case being when one’s lower and upper probabilities are equal. I argue, however, that it is better to think of the two models as representing two different aspects of our credences, which are often vague to some degree. I show that by combining the two models into one model, and understanding that model as a model of vague credence, a natural interpretation arises that (...) suggests a hypothesis concerning how we can improve the accuracy of aggregate credences. I present empirical results in support of this hypothesis. I also discuss how this modeling interpretation of imprecise probabilities bears upon a philosophical objection that has been raised against them, the so-called inductive learning problem. (shrink)

I raise skeptical doubts about the prospects of Bayesian formal epistemology for providing an adequate general normative model of epistemic rationality. The notion of credence, I argue, embodies a very dubious psychological myth, viz., that for virtually any proposition p that one can entertain and understand, one has some quantitatively precise, 0-to-1 ratio-scale, doxastic attitude toward p. The concept of credence faces further serious problems as well—different ones depending on whether credence 1 is construed as full belief (the limit case (...) of so-called partial belief) or instead is construed as absolute certainty. I argue that the notion of an “ideal Bayesian reasoner” cannot serve as a normative ideal that actual human agents should seek to emulate as closely as they can, because different such reasoners who all have the same evidence as oneself—no single one them being uniquely psychologically most similar to oneself—will differ from one another in their credences (e.g., because they commence from different prior credences). I argue that epistemic probability, properly understood, is quantitative degree of evidential support relative to one’s evidence, and that principled epistemic probabilities arise only under quite special evidential circumstances—which means that epistemic probability is ill suited to figure centrally within general norms of human epistemic rationality. (shrink)

In spite of several attempts to explicate the relationship between a scientific hypothesis and evidence, the issue still cries for a satisfactory solution. Logical approaches to confirmation, such as the hypothetico-deductive method and the positive instance account of confirmation, are problematic because of their neglect of the semantic dimension of hypothesis confirmation. Probabilistic accounts of confirmation are no better than logical approaches in this regard. An outstanding probabilistic account of confirmation, the Bayesian approach, for instance, is found to be defective (...) in that it treats evidence as a formal entity and this creates the problem of relevance of evidence to the hypothesis at issue, in addition to the difficulties arising from the subjective interpretation of probabilities. This essay purports to satisfy the need for a successful account of hypothesis confirmation by offering an original formulation based on the notion of instantiation of the relation urged by an hypothesis. (shrink)

Traditional accounts of justification can be characterized as trying to analyze justification in such a way that having a justified belief brings with it assurance of truth. The internalist offers a demanding requirement on justification: one's having a justified belief requires that one see what the belief has going for it. Externalists worry that the internalist's narrow conception of justification will lead to unacceptably radical and implausible skepticism. According to the externalist, one need not know what a belief has going (...) for it in order for that belief to be justified. Externalism, though, comes with its own problems. Ernest Sosa has attempted to bridge the divide between internalism and externalism by pairing the strengths of internalism with the strengths of externalism. Sosa distinguishes two kinds of knowledge: animal knowledge that is essentially externalist in character and reflective knowledge that is intended to capture our best intellectual procedure in regards to knowledge. On Sosa's view, one gains reflective knowledge by building upon animal knowledge. As a result, Sosa's view seems to illustrate a bottom-up approach to the analysis of knowledge : reflective knowledge is the result of animal knowledge and some other epistemic factor. My project, in contrast to Sosa's, is to argue that one should start with an account of ideal justification and then proceed by loosening the standards on ideal justification in an effort to develop the possibility of non- ideal kinds of justification. The view that I will develop will adopt Sosa's strategy of distinguishing kinds of knowledge, but will result in a top-down approach to the analysis of justification. Instead of starting with an undemanding standard and layer levels on top, I will start with an ideal standard and strip layers away. I will also argue that my view has some important advantages over Sosa's. Not only does Sosa's view seem to run into many of the problems that threaten externalism, but his view is incapable of offering the kind of assurance that the internalist is after. The view I develop will maintain the internalist's interest in assurance while also providing a response to some of the skeptical problems that have plagued internalists. If my project is successful, then, even if the justification that results in many of the cases I will be exploring is not ideal, we can use these conceptions of justification to help explicate how one might have justified beliefs about a great number of things. The essentially internalist account that I have offered will not only illustrate a serious approach to dealing with skepticism, but it will also capture how many of our commonsensically justified beliefs are in fact justified. (shrink)