Extreme Permissivism is the view that a body of evidence could rationally permit both the attitude of belief and disbelief towards a proposition. This paper puts forward a new argument against Extreme Permissivism, which improves on a similar style of argument due to Roger White (2005, 2014). White’s argument is built around the principle that the support relation between evidence and a hypothesis is objective: so that if evidence E makes it rational for an agent to believe a hypothesis H, (...) then E makes it rational to believe H, for all agents. In this paper, I construct a new argument against Extreme Permissivism that appeals to a logically weaker, less demanding view about evidential support, Relational Objectivity: whether a body of evidence E is more likely if H is true than if H is false is an objective matter and does not depend on how any agent interprets the relationship between E and H. Relational Objectivity is solely concerned with the conditional probabilities called likelihoods and does not put substantive constraints on an agent’s prior and posterior credences. For this reason, the presented argument avoids the standard permissivist criticism levelled against White’s argument. (shrink)

Sections 1 through 3 present all of the main ideas behind the probabilistic logic of evidential support. For most readers these three sections will suffice to provide an adequate understanding of the subject. Those readers who want to know more about how the logic applies when the implications of hypotheses about evidence claims (called likelihoods) are vague or imprecise may, after reading sections 1-3, skip to section 6. Sections 4 and 5 are for the more advanced reader who wants a (...) detailed understanding of some telling results about how this logic may bring about convergence to the truth. (shrink)

Evidential support is often equated with confirmation, where evidence supports hypothesis H if and only if it increases the probability of H. This article argues against this received view. As the author shows, support is a comparative notion in the sense that increase-in-probability is not. A piece of evidence can confirm H, but it can confirm alternatives to H to the same or greater degree; and in such cases, it is at best misleading to conclude that the evidence supports H. (...) The author puts forward an alternative view that defines support in terms of measures of degree of confirmation. The proposed view is both sufficiently comparative and able to accommodate the increase-in-probability aspect of support. The author concludes that the proposed measure-theoretic approach to support provides a superior alternative to the standard confirmatory approach. (shrink)

One leading account of justification comes from the evidentialist tradition. According to evidentialists, whether a doxastic attitude is justified depends on whether that attitude is supported by the believer’s evidence. This chapter assesses the prospects for evidentialism, focusing on the question of whether evidentialists can provide a satisfactory account of their key notions – evidence possession and evidential support – without helping themselves to the notion of justification.

Peter Achinstein has argued at length and on many occasions that the view according to which evidential support is defined in terms of probability-raising faces serious counterexamples and, hence, should be abandoned. Proponents of the positive probabilistic relevance view have remained unconvinced. The debate seems to be in a deadlock. This paper is an attempt to move the debate forward and revisit some of the central claims within this debate. My conclusion here will be that while Achinstein may be right (...) that his counterexamples undermine probabilistic relevance views of what it is for e to be evidence that h, there is still room for a defence of a related probabilistic view about an increase in being supported, according to which, if p > p, then h is more supported given e than it is without e. My argument relies crucially on an insight from recent work on the linguistics of gradable adjectives. (shrink)

This article reveals one general scheme for creating counter examples to Bayesian confirmation theory. The reason of the problems is that: in daily life the degree of confirmation is affected not only by probability but also by some non-probabilistic factors, e.g., structural similarity, quantity of evidence, and marginal utility, while Bayesian confirmation theory considers only probabilities to measure the degree of confirmation. This article resolves these problems after some detail analyses, and proposes a new confirmation measure based on these factors.

It is argued that a subject's evidence consists of all and only the propositions that the subject knows.

A theory of evidential probability is developed from two assumptions:(1) the evidential probability of a proposition is its probability conditional on the total evidence;(2) one's total evidence is one's total knowledge. Evidential probability is distinguished from both subjective and objective probability. Loss as well as gain of evidence is permitted. Evidential probability is embedded within epistemic logic by means of possible worlds semantics for modal logic; this allows a natural theory of higher-order probability to be developed. In particular, it is (...) emphasized that it is sometimes uncertain which propositions are part of one's total evidence; some surprising implications of this fact are drawn out. (shrink)

Falsificationism has dominated 20th century philosophy of science. It seemed to have eclipsed all forms of inductivism. Yet recent debates have revived a specific form of eliminative inductivism, the basic ideas of which go back to F. Bacon and J.S. Mill. These modern endorsements of eliminative inductivism claim to show that progressive problem solving is possible using induction, rather than falsification as a method of justification. But this common ground between falsificationism and eliminative inductivism has not led to a detailed (...) investigation into the relationship, if any, which may exist between these two methodologies. This paper reviews several versions of eliminative inductivism, establishes a natural relation between eliminative inductivism and falsificationism, which derives from the distinction between models and theories, and carries out this investigation against a case study of the construction of atom models. The result of the investigation is that falsificationism is a form of eliminative inductivism in the limit of certain constraints. (shrink)

We have known for a long time that there is complex, intelligent life. More recently we have discovered that the physics of our universe is fine-tuned so as to allow for the existence of such life. Call these two observations the Old Datum and the New Datum, respectively. Our question here is: once we know the Old Datum, does the New Datum provide additional evidence for the design hypothesis? I argue that it does not. Thus, there is an important sense (...) in which the much-touted fine-tuning of physics is irrelevant to debates about design. (shrink)

The likelihood principle (LP) is a core issue in disagreements between Bayesian and frequentist statistical theories. Yet statements of the LP are often ambiguous, while arguments for why a Bayesian must accept it rely upon unexamined implicit premises. I distinguish two propositions associated with the LP, which I label LP1 and LP2. I maintain that there is a compelling Bayesian argument for LP1, based upon strict conditionalization, standard Bayesian decision theory, and a proposition I call the practical relevance principle. In (...) contrast, I argue that there is no similarly compelling argument for or against LP2. I suggest that these conclusions lead to a restrictedly pluralistic view of Bayesian confirmation measures. (shrink)

Disputes between advocates of Bayesians and more orthodox approaches to statistical inference presuppose that Bayesians must regard must regard stopping rules, which play an important role in orthodox statistical methods, as evidentially irrelevant.In this essay, I show that this is not the case and that the stopping rule is evidentially relevant given some Bayesian confirmation measures that have been seriously proposed. However, I show that accepting a confirmation measure of this sort comes at the cost of rejecting two useful ancillaryBayesian (...) principles. (shrink)

According to the probabilistic relevance account of confirmation, E confirms H relative to background knowledge K just in case P(H/K&E) > P(H/K). This requires an inequality between the rational degree of belief in H determined relative to two bodies of total knowledge which are such that one (K&E) includes the other (K) as a proper part. In this paper, I argue that it is quite plausible that there are no two possible bodies of total knowledge for ideally rational agents meeting (...) this requirement. Hence, the positive relevance account may have to be rejected. (shrink)

There are some candidates that have been thought to measure the degree to which evidence incrementally confirms a hypothesis. This paper provides an argument for one candidate—the log-likelihood ratio measure. For this purpose, I will suggest a plausible requirement that I call the Requirement of Collaboration. And then, it will be shown that, of various candidates, only the log-likelihood ratio measure \(l\) satisfies this requirement. Using this result, Jeffrey conditionalization will be reformulated so as to disclose explicitly what determines new (...) credences after experience. (shrink)

Epistemic justification has been widely accepted as both a gradational and relational notion. Given those properties, a natural thought is to take degrees of epistemic justification to be probabilities. In this paper, we present a simple Bayesian framework for justification. In the first part, after putting the model in an evidentialist form, we distinguish different senses of “being evidence for” and “confirming”. Next, we argue that this conception should accommodate the two relevant kinds of qualitative confirmation or evidential support. In (...) the second part of the paper, we discuss the claim that this view is unable to satisfy the modified version of the conjunction closure for beliefs in probabilistically independent propositions. We defend that the underlying assumption on which this objection depends leads to an improper reading of the concept of epistemic probability. After providing a better interpretation of it, we put forward a rationale, which is based on the notion of conditional uncertainty, in support of a more plausible and restricted version of the closure of justification under conjunction. (shrink)

It is well known that the process of scientific inquiry, according to Peirce, is drivenby three types of inference, namely abduction, deduction, and induction. What isbehind these labels is, however, not so clear. In particular, the common identificationof abduction with Inference to the Best Explanation (IBE) begs the question,since IBE appears to be covered by Peirce's concept of induction, not that of abduction.Consequently, abduction ought to be distinguished from IBE, at least on Peirce's account. The main aim of the paper, (...) however, is to show that this distinction is most relevant with respect to current problems in philosophy of science and epistemology (like attempts to supply suitable notions of realism and truth as well as related concepts like coherence and unification). In particular, I also try to show that (and in what way) Peirce's inferential triad can function as a method that ensures both coherence and correspondence. It is in this respect that his careful distinction between abduction and induction (or IBE) ought to be heeded. (shrink)

The article is an attempt to better understand the objections to the doctrine of 'reliabilism' made by prominent epistemologists. The view argued for here is that while one extreme case of anti-reliabilism seems to be the paradigm case against the entire concept, this very case points out some additional, and implicit, problems with the standard account of epistemic justification. The most notable is that the standard view attacks reliabilism on the grounds that it lacks a means of giving adequate reasons (...) or evidence for its claims. We argue that the standard view, while correct on its paradigm case against reliabilism, is itself weakened by its lack of recognition of the central role theories of evidence must play in its basic account. Since theories of evidence are themselves divergent and problematic in terms of explaining how claims are justified, the standard account needs to address the issues of which account of evidence is 'adequate' and why it is. It is finally suggested that traditional epistemology might be more accurately described as a branch of confirmation theory. (shrink)

Hempel's paradox of the ravens arises from the inconsistency of three prima facie plausible principles of confirmation. This paper uses Carnapian inductive logic to (a) identify which of the principles is false, (b) give insight into why this principle is false, and (c) identify a true principle that is sufficiently similar to the false one that failure to distinguish the two might explain why the false principle is prima facie plausible. This solution to the paradox is compared with a variety (...) of other responses and is shown to differ from all of them. (shrink)

Inductive probability is the logical concept of probability in ordinary language. It is vague but it can be explicated by defining a clear and precise concept that can serve some of the same purposes. This paper presents a general method for doing such an explication and then a particular explication due to Carnap. Common criticisms of Carnap's inductive logic are examined; it is shown that most of them are spurious and the others are not fundamental.

Peter Achinstein has argued at length and on many occasions that the view according to which evidential support is defined in terms of probability-raising faces serious counterexamples and, hence, should be abandoned. Proponents of the positive probabilistic relevance view have remained unconvinced. The debate seems to be in a deadlock. This paper is an attempt to move the debate forward and revisit some of the central claims within this debate. My conclusion here will be that while Achinstein may be right (...) that his counterexamples undermine probabilistic relevance views of what it is for e to be evidence that h, there is still room for a defence of a related probabilistic view about an increase in being supported, according to which, if p > p, then h is more supported given e than it is without e. My argument relies crucially on an insight from recent work on the linguistics of gradable adjectives. (shrink)

In this paper, I shall discuss a problem that arises when you try to combine an attractive account of what constitutes evidence with an independently plausible account of the kind of access we have to our evidence. According to E = K, our evidence consists of what we know. According to the principle of armchair access, we can know from the armchair what our evidence is. Combined, these claims entail that we can have armchair knowledge of the external world. Because (...) it seems that the principle of armchair access is supported by widely shared intuitions about epistemic rationality, it seems we ought to embrace an internalist conception of evidence. I shall argue that this response is mistaken. Because externalism about evidence can accommodate the relevant intuitions about epistemic rationality, the principle of armchair access is unmotivated. We also have independent reasons for preferring externalism about evidence to the principle of armchair access. (shrink)

According to Williamson, your evidence consists of all and only what you know (E = K). According to his critics, it doesn’t. While E = K calls for revision, the revisions it calls for are minor. E = K gets this much right. Only true propositions can constitute evidence and anything you know non-inferentially is part of your evidence. In this paper, I defend these two theses about evidence and its possession from Williamson’s critics who think we should break more (...) radically from E = K. (shrink)

Lewis thought concessive knowledge attributions (e.g., ‘I know that Harry is a zebra, but it might be that he’s just a cleverly disguised mule’) caused serious trouble for fallibilists. As he saw it, CKAs are overt statements of the fallibilist view and they are contradictory. Dougherty and Rysiew have argued that CKAs are pragmatically defective rather than semantically defective. Stanley thinks that their pragmatic response to Lewis fails, but the fallibilist cause is not lost because Lewis was wrong about the (...) commitments of fallibilism. There are problems with Dougherty and Rysiew’s response to Stanley and there are problems with Stanley’s response to Lewis. I’ll offer a defense of fallibilism of my own and show that fallibilists needn’t worry about CKAs. (shrink)

This paper discusses an aspect of the problem of old evidence which I call here the general problem of old evidence. The probability of old evidence is one or close to one, because background information K entails the evidence E or K consists of propositions which make E probable. In the literature, K is considered as a proposition relevant to E. Based on examples, I argue that K does not support the truth of E; instead, K supports the evidential status (...) of E. I define background information as a set of propositions necessary and sufficient to consider E as the evidence of hypothesis H. Background information is relevant to the bearing of E on H, but not to the truth of E itself. My definition of background information implies that background information of E is probabilistically independent of E; that is, in the case of old evidence, neither P = 1, nor P ≈ 1. (shrink)

This paper places formal learning theory in a broader philosophical context and provides a glimpse of what the philosophy of induction looks like from a learning-theoretic point of view. Formal learning theory is compared with other standard approaches to the philosophy of induction. Thereafter, we present some results and examples indicating its unique character and philosophical interest, with special attention to its unified perspective on inductive uncertainty and uncomputability.

– 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)

This paper formally explores the common ground between mild versions of epistemological coherentism and infinitism; it proposes—and argues for—a hybrid, coherentist–infinitist account of epistemic justification. First, the epistemological regress argument and its relation to the classical taxonomy regarding epistemic justification—of foundationalism, infinitism and coherentism—is reviewed. We then recall recent results proving that an influential argument against infinite regresses of justification, which alleges their incoherence on account of probabilistic inconsistency, cannot be maintained. Furthermore, we prove that the Principle of Inferential Justification (...) has rather unwelcome consequences—formally resembling the Sorites paradox—as soon as it is iterated and combined with a natural Bayesian perspective on probabilistic inferences. We conclude that strong versions of foundationalism and infinitism should be abandoned. Positively, we provide a rough sketch for a graded formal coherence notion, according to which infinite regresses of epistemic justification will often have more than a minimal degree of coherence. (shrink)

The running debate between Peter Achinstein and his critics concerning the nature of scientific evidence is misguided as each side attempts to explicate a distinct notion of evidence. Achinstein's approach, however, is valuable in helping to point out a problem with Carnap's statistical relevance model. By claiming an increase in probability to be necessary for evidence, the received view is incapable of accounting for evidence which is statistically irrelevant but explanatorily relevant. A broader view of evidence which can account for (...) pragmatic concerns such as explanation is thereby required. (shrink)

The logical interpretation of probability, or "objective Bayesianism'' – the theory that (some) probabilities are strictly logical degrees of partial implication – is defended. The main argument against it is that it requires the assignment of prior probabilities, and that any attempt to determine them by symmetry via a "principle of insufficient reason" inevitably leads to paradox. Three replies are advanced: that priors are imprecise or of little weight, so that disagreement about them does not matter, within limits; that it (...) is possible to distinguish reasonable from unreasonable priors on logical grounds; and that in real cases disagreement about priors can usually be explained by differences in the background information. It is argued also that proponents of alternative conceptions of probability, such as frequentists, Bayesians and Popperians, are unable to avoid committing themselves to the basic principles of logical probability. (shrink)

Contemporary Bayesian confirmation theorists measure degree of (incremental) confirmation using a variety of non-equivalent relevance measures. As a result, a great many of the arguments surrounding quantitative Bayesian confirmation theory are implicitly sensitive to choice of measure of confirmation. Such arguments are enthymematic, since they tacitly presuppose that certain relevance measures should be used (for various purposes) rather than other relevance measures that have been proposed and defended in the philosophical literature. I present a survey of this pervasive class of (...) Bayesian confirmation-theoretic enthymemes, and a brief analysis of some recent attempts to resolve the problem of measure sensitivity. (shrink)

Perhaps personality traits substantially influence one’s philosophically relevant intuitions. This suggestion is not only possible, it is consistent with a growing body of empirical research: Personality traits have been shown to be systematically related to diverse intuitions concerning some fundamental philosophical debates. We argue that this fact, in conjunction with the plausible principle that almost all adequate philosophical views should take into account all available and relevant evidence, calls into question some prominent approaches to traditional philosophical projects. To this end, (...) we present the Philosophical Personality Argument (PPA). We explain how it supports the growing body of evidence challenging some of the uses of intuitions in philosophy, and we defend it from some criticisms of empirically based worries about intuitions in philosophy. We conclude that the current evidence indicates that the PPA is sound, and thus many traditional philosophical projects that use intuitions must become substantially more empirically oriented. (shrink)

We often evaluate belief-forming processes, agents, or entire belief states for reliability. This is normally done with the assumption that beliefs are all-or-nothing. How does such evaluation go when we’re considering beliefs that come in degrees? I consider a natural answer to this question that focuses on the degree of truth-possession had by a set of beliefs. I argue that this natural proposal is inadequate, but for an interesting reason. When we are dealing with all-or-nothing belief, high reliability leads to (...) high levels of truth-possession. However, when it comes to degrees of belief, reliability and truth-possession part ways. The natural answer thus fails to be a good way to evaluate degrees of belief for reliability. I propose and develop an alternative method based on the notion of calibration, suggested by Frank Ramsey, which does not have this problem and consider why we should care about such assessments of reliability even if they are not tied directly to truth-possession. (shrink)

Consider the Evidence Question: When and under what conditions is proposition P evidence for some agent S? Silins (Philos Perspect 19:375–404, 2005) has recently offered a partial answer to the Evidence Question. In particular, Silins argues for Evidential Internalism (EI), which holds that necessarily, if A and B are internal twins, then A and B have the same evidence. In this paper I consider Silins’s argument, and offer two response on behalf of Evidential Externalism (EE), which is the denial of (...) Evidential Internalism. The first response claims that the allegedly unattractive consequence for EE is not so unattractive. The second response takes the form of a tu quoque, demonstrating that a structurally similar argument can be constructed against EI. The two responses play off one another: objecting to the first puts pressure on one to accept the other. Taken together, the two responses have important ramifications for how we answer the Evidence Question, and how we think about evidence in general. (shrink)

I argue that when we use ‘probability’ language in epistemic contexts—e.g., when we ask how probable some hypothesis is, given the evidence available to us—we are talking about degrees of support, rather than degrees of belief. The epistemic probability of A given B is the mind-independent degree to which B supports A, not the degree to which someone with B as their evidence believes A, or the degree to which someone would or should believe A if they had B as (...) their evidence. My central argument is that the degree-of-support interpretation lets us better model good reasoning in certain cases involving old evidence. Degree-of-belief interpretations make the wrong predictions not only about whether old evidence confirms new hypotheses, but about the values of the probabilities that enter into Bayes’ Theorem when we calculate the probability of hypotheses conditional on old evidence and new background information. (shrink)

Bayesian conceptions of evidence have been invoked in recent arguments regarding the existence of God, the hypothesis of multiple physical universes, and the Doomsday Argument. Philosophers writing on these topics often claim that, given a Bayesian account of evidence, our existence or something entailed by our existence (perhaps in conjunction with some background knowledge or assumption) may serve as evidence for each of us. In this paper, I argue that this widespread view is mistaken. The mere fact of one's existence (...) qua conscious creature cannot serve as evidence on the standard Bayesian conception of evidence because knowledge of one's existence is a necessary part of the background knowledge relative to which all epistemic probabilities are defined. It follows that some formulations of the fine-tuning argument (for theism or a multiverse), the argument from consciousness (for theism) and a rejoinder to the Doomsday argument are mistaken. (shrink)

In this paper I outline my conception of the epistemology of science, by reference to my published papers, showing how the ideas presented there fit together. In particular I discuss the aim of science, scientific progress, the nature of scientific evidence, the failings of empiricism, inference to the best (or only) explanation, and Kuhnian psychology of discovery. Throughout, I emphasize the significance of the concept of scientific knowledge.

Evidence is often taken to be foundational, in that while other propositions may be inferred from our evidence, evidence propositions are themselves not inferred from anything. I argue that this conception is false, since the non-inferential propositions on which beliefs are ultimately founded may be forgotten or undermined in the course of enquiry.

This paper explores what happens if we construe evidentialism as a thesis about the metaphysical grounds of justification. According to grounding evidentialism, facts about what a subject is justified in believing are grounded in facts about that subject’s evidence. At first blush, grounding evidentialism appears to enjoy advantages over a more traditional construal of evidentialism as a piece of conceptual analysis. However, appearances are deceiving. I argue that grounding evidentialists are unable to provide a satisfactory story about what grounds the (...) evidential facts, and that this provides good reason to reject grounding evidentialism. (shrink)

The quantitative problem of old evidence is the problem of how to measure the degree to which e confirms h for agent A at time t when A regards e as justified at t. Existing attempts to solve this problem have applied the e-difference approach, which compares A's probability for h at t with what probability A would assign h if A did not regard e as justified at t. The quantitative problem has been widely regarded as unsolvable primarily on (...) the grounds that the e-difference approach suffers from intractable problems. Various philosophers have proposed that 'Bayesianism' should be rejected as a research strategy in confirmation theory in part because of the unsolvability of this problem. I develop a version of the e-difference approach which overcomes these problems and possesses various advantages (but also certain limitations). I develop an alternative 'theistic' approach which handles many cases that my development of the e-difference approach does not handle. I conclude with an assessment of the significance of the quantitative problem for Bayesianism and argue that this problem is misunderstood in so far as it is regarded as unsolvable, and in so far as it is regarded as a problem only for Bayesians. (shrink)

Over the years I’ve written many papers defending an idiosyncratic version of interest-relative epistemology. This book collects and updates the views I’ve expressed over those papers. -/- Interest-relative epistemologies all start in roughly the same way. A big part of what makes knowledge important is that it rationalises action. But for almost anything we purportedly know, there is some action that it wouldn’t rationalise. I know what I had for breakfast, but I wouldn’t take a bet at billion to one (...) odds about it. Knowledge has practical limits. The first idiosyncratic feature of my version of interest-relative epistemology is how those limits are identified. Other interest-relative philosophers typically say that the limits have to do with stakes; in high stakes situations knowledge goes away. That’s no part of my view. I think knowledge goes away in long odds situations. High stakes situations are almost always are long odds situations, for reasons to do with the declining marginal utility of money. But the converse isn’t true. On my view, knowledge often goes away in cases where it is trivial to check before action. This idea, that interests matter in long odds cases, and not just in high stakes cases, is the main constant in what I’ve written on interest-relativity over the years. -/- But there are three other respects in which the view I’m going to set out and defend in this book is very different from the view I set out in older papers. -/- I used to identify the practical limits on knowledge with cases where relying on the purported knowledge would get the wrong answer. I focused, that is, on the outputs of inquiry. Knowledge goes away if relying on it would lead one to make a mistake. I now think I was looking at the wrong end of inquiry. Knowledge goes away if the thinker starts conducting an inquiry where the purported knowledge is an inappropriate starting point, and inappropriate for the special reason that it might be false. Now one way we can tell that something is a bad starting point is that starting there will mean we end up at the wrong place. But it’s not the only way. Sometimes a bad starting point will lead to the right conclusion for the wrong reasons. As the Nyāya philosophers argued, rational inquiry starts with knowledge. If it would be irrational to start this inquiry with a particular belief, that belief isn’t knowledge. -/- Not all inquiries are practical inquiries, but many are. And practical inquiries are usually going to be at the center of attention in this book. But what is someone trying to figure out when they conduct a practical inquiry? I used to think that they were trying to figure out which option maximised expected utility, and to a first approximation identified knowledge with those things one could conditionalise on without changing the option that maximised expected utility. As noted in the previous paragraph, I no longer think that we can identify knowledge with what doesn’t change our verdicts. But more importantly, I no longer think that expected utility maximisation is as central to practical inquiry as I once did. There are some theoretical reasons from game theory that raise some doubts about expected utility maximisation. Weak dominance reasoning is part of our theory of rational choice, and can’t be modelled as expected utility maximisation. Perhaps some kinds of equilibrium seeking are parts of practical inquiry, and can’t be modelled as expected utility maximisation. But there are also very practical reasons to think that practical inquiry doesn’t aim at expected utility maximisation. When there are a lot of very similar options - think about selecting a can from a supermarket shelf - and it’s more trouble than it’s worth to figure out which of them maximises expected utility, it’s best to ignore the differences between them and just pick. As I’ll argue in Chapter 6, this makes a big difference to how interests and knowledge interact. -/- In the version of interest-relativity that I’m defending here, everything in epistemology is interest-relative. Knowledge, rational belief, and evidence are all interest-relative. But they are all interest-relative in slightly different ways. The main aim here is to defend the interest-relativity of knowledge. A common objection to interest-relative theories of knowledge is that they can’t be extended into theories of all the things we care about in epistemology. Here I try to meet that challenge. The way I do so is a little messy. It would be nice if there was some part of epistemology that’s interest-invariant, as I used to think, or if all the interest-relative notions were interest-relative in the same way, as other interest-relative epistemologists argue. For better or worse, that’s not the view I’m defending. Interests matter throughout epistemology, and we just have to go case by case to figure out how and why they matter. (shrink)

Bayes' Theorem is a simple mathematical formula used for calculating conditional probabilities. It figures prominently in subjectivist or Bayesian approaches to epistemology, statistics, and inductive logic. Subjectivists, who maintain that rational belief is governed by the laws of probability, lean heavily on conditional probabilities in their theories of evidence and their models of empirical learning. Bayes' Theorem is central to these enterprises both because it simplifies the calculation of conditional probabilities and because it clarifies significant features of subjectivist position. Indeed, (...) the Theorem's central insight — that a hypothesis is confirmed by any body of data that its truth renders probable — is the cornerstone of all subjectivist methodology. (shrink)

In October 2009 I decided to stop doing philosophy. This meant, in particular, stopping work on the book that I was writing on the nature of probability. At that time, I had no intention of making my unfinished draft available to others. However, I recently noticed how many people are reading the lecture notes and articles on my web site. Since this draft book contains some important improvements on those materials, I decided to make it available to anyone who wants (...) to read it. That is what you have in front of you. The account of Laplace’s theory of probability in Chapter 4 is very different to what I said in my seminar lectures, and also very different to any other account I have seen; it is based on a reading of important texts by Laplace that appear not to have been read by other commentators. The discussion of von Mises’ theory in Chapter 7 is also new, though perhaps less revolutionary. And the final chapter is a new attempt to come to grips with the popular, but amorphous, subjective theory of probability. The material in the other chapters has mostly appeared in previous articles of mine but things are sometimes expressed differently here. I would like to say again that this is an incomplete draft of a book, not the book I would have written if I had decided to finish it. It no doubt contains poor expressions, it may contain some errors or inconsistencies, and it doesn’t cover all the theories that I originally intended to discuss. Apart from this preface, I have done no work on the book since October 2009. (shrink)

Bayesian Epistemology is a general framework for thinking about agents who have beliefs that come in degrees. Theories in this framework give accounts of rational belief and rational belief change, which share two key features: (i) rational belief states are represented with probability functions, and (ii) rational belief change results from the acquisition of evidence. This dissertation focuses specifically on the second feature. I pose the Evidence Question: What is it to have evidence? Before addressing this question we must have (...) an understanding of Bayesian Epistemology. The first chapter argues that we should understand Bayesian Epistemology as giving us theories that are evaluative and not action-guiding. I reach this verdict after considering the popular ‘ought’-implies-‘can’ objection to Bayesian Epistemology. The second chapter argues that it is important for theories in Bayesian Epistemology to answer the Evidence Question, and distinguishes between internalist and externalist answers. The third and fourth chapters present and defend a specific answer to the Evidence Question. The account is inspired by reliabilist accounts of justification, and attempts to understand what it is to have evidence by appealing solely to considerations of reliability. Chapter 3 explains how to understand reliability, and how the account fits with Bayesian Epistemology, in particular, the requirement that an agent’s evidence receive probability 1. Chapter 4 responds to objections, which maintain that the account gives the wrong verdict in a variety of situations including skeptical scenarios, lottery cases, scientific cases, and cases involving inference. After slight modifications, I argue that my account has the resources to answer the objections. The fifth chapter considers the possibility of losing evidence. I show how my account can model these cases. To do so, however, we require a modification to Conditionalization, the orthodox principle governing belief change. I present such a modification. The sixth and seventh chapters propose a new understanding of Dutch Book Arguments, historically important arguments for Bayesian principles. The proposal shows that the Dutch Book Arguments for implausible principles are defective, while the ones for plausible principles are not. The final chapter is a conclusion. (shrink)

According to all traditional theories of confirmation, statements such as “E confirms H” (where H is a hypothesis and E is the evidence that supports H) are a priori. Peter Achinstein has recently challenged this orthodox position. He claims that at least some confirmation statements are empirical. In this paper I criticize this thesis. I first show that Achinstein´s arguments are either flawed or inconclusive. I then argue that there are strong reasons to conceive of all confirmation statements as a (...) priori. I conclude that inductive logic, if possible, must be a priori knowledge. (shrink)

Handbook of the History of Logic, vol. 10, eds. Dov Gabbay, Stephan Hartmann, and John Woods, forthcoming.

If political decision-making aims at getting a particular result, like identifying just laws or policies that truly promote the common good, then political institutions can also be evaluated in terms of how often they achieve these results. Epistemic defenses of democracy argue that democracies have the upper hand when it comes to truth, identifying the laws and policies that are truly just or conducive to the common good. A number of epistemic democrats claim that democracies have this beneficial connection to (...) truth because of the type of deliberative environment created by democratic political institutions. Democratic political cultures make it easier to exchange and give reasons, ultimately improving the justification that citizens have for their political beliefs. With this improved justification comes a better chance at truth, or so the story goes. In this paper, I show that attempts to forge a connection between justification and truth in epistemology have encountered numerous difficulties, making the case that this causes trouble for deliberative epistemic defenses of democracy as well. If there is no well-defined connection between truth and justification, then increasing the justification that citizens have for their beliefs may not also increase the likelihood that those beliefs are true, revealing a serious flaw in charting a connection between political justification and political truth. (shrink)