Epistemology is the study of knowledge and justified belief. Belief is thus central to epistemology. It comes in a qualitative form, as when Sophia believes that Vienna is the capital of Austria, and a quantitative form, as when Sophia's degree of belief that Vienna is the capital of Austria is at least twice her degree of belief that tomorrow it will be sunny in Vienna. Formal epistemology, as opposed to mainstream epistemology (Hendricks 2006), is epistemology done in a formal way, (...) that is, by employing tools from logic and mathematics. The goal of this entry is to give the reader an overview of the formal tools available to epistemologists for the representation of belief. A particular focus will be the relation between formal representations of qualitative belief and formal representations of quantitative degrees of belief. (shrink)

How, if at all, is knowing how to do something defeasible? Some, the “intellectualists”, treat the defeasibility of knowledge-how as in some way derivative on the defeasibility of knowledge-that. According to a recent proposal by Carter and Navarro (Philos Phenomenol Res 3:662–685, 2017), knowledge-how defeat cannot be explained in terms of knowledge-that defeat; instead, knowledge-how defeat merits and entirely separate treatment. The thought behind “separatism” is easy to articulate. Assuming that knowledge of any kind is defeasible, since knowledge-that and knowledge-how (...) are fundamentally different beasts, the best accounts of their defeasibility must reflect the underlying differences between them. I reject a separatist treatment of the defeasibility of knowledge-that and knowledge-how. One can acknowledge certain important differences between knowledge-that and knowledge-how without thereby needing two theories of defeasibility. Ultimately, though, I’ll argue that the defeasibility of basic knowledge-how, unlike non-basic knowledge-how, is a much more difficult issue than has been acknowledged. (shrink)

In this paper I’ll suggest that a certain challenge facing defeatist views about higher-order evidence cannot be met, namely, motivating principles that recommend abandoning belief in cases of higher order defeat, but do not recommend global scepticism. I’ll propose that, ultimately, the question of whether to abandon belief in response to the realization that our belief can’t be recovered from what I’ll call ‘a perspective of doubt’ can’t be answered through rational deliberation aimed at truth or accuracy.

– We offer a new motivation for imprecise probabilities. We argue that there are propositions to which precise probability cannot be assigned, but to which imprecise probability can be assigned. In such cases the alternative to imprecise probability is not precise probability, but no probability at all. And an imprecise probability is substantially better than no probability at all. Our argument is based on the mathematical phenomenon of non-measurable sets. Non-measurable propositions cannot receive precise probabilities, but there is a natural (...) way for them to receive imprecise probabilities. The mathematics of non-measurable sets is arcane, but its epistemological import is far-reaching; even apparently mundane propositions are liable to be affected by non-measurability. The phenomenon of non-measurability dramatically reshapes the dialectic between critics and proponents of imprecise credence. Non-measurability offers natural rejoinders to prominent critics of imprecise credence. Non-measurability even reverses some of the critics’ arguments—by the very lights that have been used to argue against imprecise credences, imprecise credences are better than precise credences. (shrink)

The coherence of independent reports provides a strong reason to believe that the reports are true. This plausible claim has come under attack from recent work in Bayesian epistemology. This work shows that, under certain probabilistic conditions, coherence cannot increase the probability of the target claim. These theorems are taken to demonstrate that epistemic coherentism is untenable. To date no one has investigated how these results bear on different conceptions of coherence. I investigate this situation using Thagard’s ECHO model of (...) explanatory coherence. Thagard’s ECHO model provides a natural representation of the evidential significance of multiple independent reports. (shrink)

According to the recent Perceptual Confidence view, perceptual experiences possess not only a representational content, but also a degree of confidence in that content. The motivations for this view are partly phenomenological and partly epistemic. We discuss both the phenomenological and epistemic motivations for the view, and the resulting account of the interface between perceptual experiences and degrees of belief. We conclude that, in their present state of development, orthodox accounts of perceptual experience are still to be favoured over the (...) perceptual confidence view. (shrink)

This paper considers a problem for Bayesian epistemology and proposes a solution to it. On the traditional Bayesian framework, an agent updates her beliefs by Bayesian conditioning, a rule that tells her how to revise her beliefs whenever she gets evidence that she holds with certainty. In order to extend the framework to a wider range of cases, Jeffrey (1965) proposed a more liberal version of this rule that has Bayesian conditioning as a special case. Jeffrey conditioning is a rule (...) that tells the agent how to revise her beliefs whenever she gets evidence that she holds with any degree of confidence. The problem? While Bayesian conditioning has a foundationalist structure, this foundationalism disappears once we move to Jeffrey conditioning. If Bayesian conditioning is a special case of Jeffrey conditioning, then they should have the same normative structure. The solution? To reinterpret Bayesian updating as a form of diachronic coherentism. (shrink)

Seeing a red hat can (i) increase my credence in the hat is red, and (ii) introduce a negative dependence between that proposition and po- tential undermining defeaters such as the light is red. The rigidity of Jeffrey Conditionalization makes this awkward, as rigidity preserves inde- pendence. The picture is less awkward given ‘Holistic Conditionalization’, or so it is claimed. I defend Jeffrey Conditionalization’s consistency with underminable perceptual learning and its superiority to Holistic Conditionalization, arguing that the latter is merely (...) a special case of the former, is itself rigid, and is committed to implausible accounts of perceptual con- firmation and of undermining defeat. (shrink)

The externalist says that your evidence could fail to tell you what evidence you do or not do have. In that case, it could be rational for you to be uncertain about what your evidence is. This is a kind of uncertainty which orthodox Bayesian epistemology has difficulty modeling. For, if externalism is correct, then the orthodox Bayesian learning norms of conditionalization and reflection are inconsistent with each other. I recommend that an externalist Bayesian reject conditionalization. In its stead, I (...) provide a new theory of rational learning for the externalist. I defend this theory by arguing that its advice will be followed by anyone whose learning dispositions maximize expected accuracy. I then explore some of this theory’s consequences for the rationality of epistemic akrasia, peer disagreement, undercutting defeat, and uncertain evidence. (shrink)

It seems that epistemically rational agents should avoid incoherent combinations of beliefs and should respond correctly to their epistemic reasons. However, some situations seem to indicate that such requirements cannot be simultaneously satisfied. In such contexts, assuming that there is no unsolvable dilemma of epistemic rationality, either (i) it could be rational that one’s higher-order attitudes do not align with one’s first-order attitudes or (ii) requirements such as responding correctly to epistemic reasons that agents have are not genuine rationality requirements. (...) This result doesn’t square well with plausible theoretical assumptions concerning epistemic rationality. So, how do we solve this puzzle? In this paper, I will suggest that an agent can always reason from infallible higher-order reasons. This provides a partial solution to the above puzzle. (shrink)

Weisberg introduces a phenomenon he terms perceptual undermining. He argues that it poses a problem for Jeffrey conditionalization, and Bayesian epistemology in general. This is Weisberg’s paradox. Weisberg argues that perceptual undermining also poses a problem for ranking theory and for Dempster-Shafer theory. In this note I argue that perceptual undermining does not pose a problem for any of these theories: for true conditionalizers Weisberg’s paradox is a false alarm.

It has frequently been argued recently that Jeffrey Conditionalization (JC) does not permit undermining. For JC to be inapplicable in cases where the evidence could be undermined would severely compromise JC’s range. However, this paper contends that the argument fails to show that JC cannot accommodate undermining. This response turns on using the proper partition to capture the direct impact of our evidence in redistributing our credences.

There are three well-known models of how to account for perceptual belief within a probabilistic framework: (a) a Cartesian model; (b) a model advocated by Timothy Williamson; and (c) a model advocated by Richard Jeffrey. Each of these models faces a problem—in effect, the problem of accounting for the defeasibility of perceptual justification and perceptual knowledge. It is argued here that the best way of responding to this the best way of responding to this problem effectively vindicates the Cartesian model. (...) Finally, it is argued that, given the best interpretation of the probabilistic framework, that the Cartesian model is not vulnerable to the main criticisms that have been raised against it. (shrink)

As I head home from work, I’m not sure whether my daughter’s new bike is green, and I’m also not sure whether I’m on drugs that distort my color perception. One thing that I am sure about is that my attitudes towards those possibilities are evidentially independent of one another, in the sense that changing my confidence in one shouldn’t affect my confidence in the other. When I get home and see the bike it looks green, so I increase my (...) confidence that it is green. But something else has changed: now an increase in my confidence that I’m on color-drugs would undermine my confidence that the bike is green. Jonathan Weisberg and Jim Pryor argue that the preceding story is problematic for standard Bayesian accounts of perceptual learning. Due to the ‘rigidity’ of Conditionalization, a negative probabilistic correlation between two propositions cannot be introduced by updating on one of them. Hence if my beliefs about my own color-sobriety start out independent of my beliefs about the color of the bike, then they must remain independent after I have my perceptual experience and update accordingly. Weisberg takes this to be a reason to reject Conditionalization. I argue that this conclusion is too pessimistic: Conditionalization is only part of the Bayesian story of perceptual learning, and the other part needn’t preserve independence. Hence Bayesian accounts of perceptual learning are perfectly consistent with potential underminers for perceptual beliefs. (shrink)

While recent discussions of contextualism have mostly focused on other issues, some influential early statements of the view emphasized the possibility of its providing an alternative to both coherentism and traditional versions of foundationalism. In this essay, I will pick up on this strand of contextualist thought, and argue that contextualist versions of foundationalism promise to solve some problems that their non-contextualist cousins cannot. In particular, I will argue that adopting contextualist versions of foundationalism can let us reconcile Bayesian accounts (...) of belief updating with a version of the holist claim that all beliefs are defeasible. (shrink)

Forty years ago, Bayesian philosophers were just catching a new wave of technical innovation, ushering in an era of scoring rules, imprecise credences, and infinitesimal probabilities. Meanwhile, down the hall, Gettier’s 1963 paper [28] was shaping a literature with little obvious interest in the formal programs of Reichenbach, Hempel, and Carnap, or their successors like Jeffrey, Levi, Skyrms, van Fraassen, and Lewis. And how Bayesians might accommodate the discourses of full belief and knowledge was but a glimmer in the eye (...) of Isaac Levi. Forty years later, scoring rules, imprecise credences, and infinitesimal probabilities are all the rage. And the formal and “informal” traditions are increasingly coming together as Bayesian arguments spill over into debates about the foundations of empirical knowledge, skepticism, and more. Relatedly, Bayesian interest in full belief and knowledge has never been greater. Much more besides has happened in the last forty years of Bayesian philosophy, .. (shrink)

The paper presents a new argument for epistemic permissivism. The version of permissivism that we defend is a moderate version that applies only to explicit doxastic attitudes. Drawing on Yalcin’s framework for modeling such attitudes, we argue that two fully rational subjects who share all their evidence, prior beliefs, and epistemic standards may still differ in the explicit doxastic attitudes that they adopt. This can happen because two such subjects may be sensitive to different questions. Thus, differing intellectual interests can (...) yield failures of uniqueness. This is not a merely pragmatic phenomenon. (shrink)

Jonathan Weisberg has argued that Bayesianism’s rigid updating rules make Bayesian updating incompatible with undermining defeat. In this paper, I argue that when we attend to the higher-order beliefs we must ascribe to agents in the kinds of cases Weisberg considers, the problem he raises disappears. Once we acknowledge the importance of higher-order beliefs to the undermining story, we are led to a different understanding of how these cases arise. And on this different understanding of things, the rigid nature of (...) Bayesianism’s updating rules is no obstacle to its accommodating undermining defeat. (shrink)

In previous work, I have suggested a doxastic account of perceptual experience according to which experiences form a kind of belief: Beliefs with what I have called “phenomenal” or “looks-content”. I have argued that this account can not only accommodate the intuitive reason providing role of experience, but also its justificatory role. I have also argued that, in general, construing experience and perceptual beliefs, i.e. the beliefs most directly based on experience, as having different contents best accounts for the defeasibility (...) of experiential reasons. In this paper, I shall have a closer look at the evidential or inferential relation between looks-propositions and the contents of perceptual beliefs and argue for a form of what I shall call “Pollockianism” about experiential reasons: such reasons are good unless defeated. Questions to be investigated include: Does the resulting picture of perceptual justification contain an externalist element? Is it compatible with Bayesianism? And how does it do with respect to problems that have been raised for other forms of Pollockianism such as dogmatism or phenomenal conservatism? (shrink)

We have several intuitive paradigms of defeating evidence. For example, let E be the fact that Ernie tells me that the notorious pet Precious is a bird. This supports the premise F, that Precious can fly. However, Orna gives me *opposing* evidence. She says that Precious is a dog. Alternatively, defeating evidence might not oppose Ernie's testimony in that direct way. There might be other ways for it to weaken the support that Ernie's testimony gives me for believing F, without (...) the new evidence itself intuitively constituting reasons to believe one way or the other about Precious's flight ability. An example: Ursula tells me that Ernie has no idea what Precious's species is; he's just guessing. She may not herself want to or be in a position to weigh in about Precious's real species or flight ability. I call defeating evidence of this sort *undermining evidence. (shrink)

Various real and imagined criminal law cases rest on “naked statistical evidence”. That is, they rest more or less entirely on a probability for guilt/liability derived from a single statistical model. The intuition is that there is something missing in these cases, high as the probability for guilt/liability may be, such that the relevant standard for legal proof is not met. Here we contribute to the considerable debate about how this intuition is best explained and what it teaches us about (...) evidential reasoning in the legal setting. We part ways with the recent scholarship, however. Unlike most others, our diagnosis is not that there is an important qualitative property that some evidence or bodies of evidence have, and that naked statistical evidence, most strikingly, lacks. Rather, we see cases resting on naked statistical evidence as lying at the extreme of a continuum of cases that are vulnerable to challenge due to “meta-uncertainty” about the underlying model. (shrink)

Philosophical Issues, Volume 30, Issue 1, Page 54-70, October 2020.