In this article I have two primary goals. First, I present two recent views on the distinction between knowledge-that and knowledge-how (Stanley and Williamson, The Journal of Philosophy 98(8):411–444, 2001; Hetherington, Epistemology futures, 2006). I contend that neither of these provides conclusive arguments against the distinction. Second, I discuss studies from neuroscience and experimental psychology that relate to this distinction. Having examined these studies, I then defend a third view that explains certain relevant data from these studies by positing the (...) double dissociation of knowledge-that and knowledge-how and that is also able to do explanatory work elsewhere. (shrink)

Original and penetrating, this book investigates of the notion of inference from signs, which played a central role in ancient philosophical and scientific method. It examines an important chapter in ancient epistemology: the debates about the nature of evidence and of the inferences based on it--or signs and sign-inferences as they were called in antiquity. As the first comprehensive treatment of this topic, it fills an important gap in the histories of science and philosophy.

Legal scholarship exploring the nature of evidence and the process of juridical proof has had a complex relationship with formal modeling. As evident in so many fields of knowledge, algorithmic approaches to evidence have the theoretical potential to increase the accuracy of fact finding, a tremendously important goal of the legal system. The hope that knowledge could be formalized within the evidentiary realm generated a spate of articles attempting to put probability theory to this purpose. This literature was both insightful (...) and frustrating. Much light was shed on the legal system, but it also quickly became evident that the tools of probability theory were in many ways ill-constructed for the task. Fundamental incompatibilities between the structure of legal decision making and the extant formal tools were identified, and it became evident that many of the purported explanations of legal phenomena were internally inconsistent. As a consequence, interest in this type of formal modeling declined, and attention was directed toward different kinds of explanations of the phenomena. Perhaps under the influence of a recent trend toward various types of formal modeling in legal scholarship, a recent burst of articles, rather than attempting to explain the macro structure of trials, which was the previous object of interest, attempts to quantify the probative value of various items of evidence in ways consistent with the formal features of various probability theories, and then to study decision making from that perspective. For example, the value of evidence is often purported to be its likelihood ratio, that is, the probability of discovering or receiving the evidence given a hypothesis (e.g., the defendant did it) divided by the probability of discovering or receiving the evidence given the negation of the hypothesis (the defendant didn't do it). Alternatively, the value of evidence is purported (more contextually) to be the information gain it provides, defined as the increase in probability it provides for a hypothesis above the probability of the hypothesis based on the other available evidence. Both conceptions then assume that all of the various probability assessments conform or ought to conform to the dictates of Bayes' theorem (that maintains consistency among such assessments); empirical studies are then done testing the extent to which this is so and proposing how the law can increase the probability that it is so. The general criticisms of using Bayes' theorem as a formal model of juridical proof are well known and were integral to the last wave of interest in formal modeling of the evidentiary process. This paper thus for the most part puts aside that more general issue, and focuses specifically on mathematical modeling of the value of particular items of evidence. The paper demonstrates that formal modeling has only limited value in explaining the value of legal evidence, much more limited than those constructing and discussing the models assume, and thus that the conclusions they draw about the value of evidence are unwarranted. This is done through a discussion of four recent examples that attempt to quantify evidence relating to, respectively, carpet fibers, infidelity, DNA random-match evidence, and character evidence used to impeach a witness. This article thus makes two contributions. First, and most importantly, it is another demonstration of the complex relationship between algorithmic tools and legal decision making. Second, at a minimum it points out serious pitfalls for analytical or empirical studies of juridical proof. (shrink)

provides a sustained and ambitious development of the basic idea that knowledge is true belief that tracks the truth. In this essay, I provide a quick synopsis of Roush's book and offer a substantive discussion of her analysis of scientific evidence. Roush argues that, for e to serve as evidence for h, it should be easier to determine the truth value of e than it is to determine the truth value of h, an ideal she refers to as ‘leverage’. She (...) defends a detailed method by which the value of p(h/e) is computed without ‘direct’ information about p(h) but only using evidence about the value of p(e), from which the value of p(h) is derived. She presents an example of how to use her leverage method, which I argue involves a certain critical mistake. I show how the leveraging method can be used in a way that is sound—I conclude with a few remarks about the importance of distinguishing clearly between prior and posterior probabilities. CiteULike    Connotea    Del.icio.us    What's this? (shrink)

This paper contains replies to comments on the author's paper "A Priori Knowledge and the Scope of Philosophy." Several points in the argument of that paper are given further clarification: the notion of our standard justificatory procedure, the notion of a basic source of evidence, and the doctrine of modal reliabilism. The reliability of intuition is then defended against Lycan's skepticism and a response is given to Lycan's claim that the scope of a priori knowledge does not include philosophically central (...) topics such as the nature of consciousness. Next a counterfactual account of intuitions proposed by Sosa is criticized. Finally, in response to certain questions raised by Sosa, the explanation of the evidential status of intuition offered in the original paper receives further elaboration. (shrink)

The topic of a priori knowledge is approached through the theory of evidence. A shortcoming in traditional formulations of moderate rationalism and moderate empiricism is that they fail to explain why rational intuition and phenomenal experience count as basic sources of evidence. This explanatory gap is filled by modal reliabilism -- the theory that there is a qualified modal tie between basic sources of evidence and the truth. This tie to the truth is then explained by the theory of concept (...) possession: this tie is a consequence of what, by definition, it is to possess (i.e., to understand) one’s concepts. A corollary of the overall account is that the a priori disciplines (logic, mathematics, philosophy) can be largely autonomous from the empirical sciences. (shrink)

It is no secret that scientists argue. They argue about theories. But even more, they argue about the evidence for theories. Is the evidence itself trustworthy? This is a bit surprising from the perspective of traditional empiricist accounts of scientific methodology according to which the evidence for scientific theories stems from observation, especially observation with the naked eye. These accounts portray the testing of scientific theories as a matter of comparing the predictions of the theory with the data generated by (...) these observations, which are taken to provide an objective link to reality. (shrink)

The first obstacle that confronts the student of induction is that of defining the subject matter. One initial point is to note that much of the relevant subject matter goes under the description ‘the theory of confirmation’. The distinction is primarily that the study of induction concerns inference, i.e. cases where one takes the conclusion to be established by the evidence, whereas confirmation concerns the weight of evidence, which one may take to be something like the credibility of a hypothesis (...) in the light of the evidence. Discussions of confirmation often concern incremental confirmation, i.e. cases where the evidence is taken to increase the credibility of some hypothesis, even if not sufficiently to warrant inferring the truth of that hypothesis. However, some uses of ‘confirmation’ clearly refer to absolute confirmation, cases where the credibility of the hypothesis in the light of the evidence exceeds some (high) threshold. One may ask whether inductive inference corresponds to the case of absolute confirmation for some suitable threshold. I shall discuss inference and confirmation together, though it should be noted that some approaches eschew inference altogether. For example, the Bayesian takes scientific reasoning to be a matter of adjusting credences in propositions in the light of evidence, and says nothing about unqualified belief in a proposition. However, if we are interested in inductive knowledge then we must consider inference, since only then do we have a detached proposition that is the possible content of a mental state of knowing. A more pressing question concerns which inferences (or allegedly confirmatory relations) should be classed as inductive. A natural and straightforward approach is to define induction as encompassing any form of reasoning that extrapolates from one population to another, usually from a sample of a population to the whole population. For example, one might note that all observations of the position of some planet fall on an ellipse that has the Sun at one of its foci; from this one concludes that all the positions that planet takes fall on this ellipse (i.e.. (shrink)

The usual, comparative, conception of Inference to the Best Explanation (IBE) takes it to be ampliative. In this paper I propose a conception of IBE (‘Holmesian inference’) that takes it to be a species of eliminative induction and hence not ampliative. This avoids several problems for comparative IBE (e.g. how could it be reliable enough to generate knowledge?). My account of Holmesian inference raises the suspicion that it could never be applied, on the grounds that scientific hypotheses are inevitably underdetermined (...) by the evidence (i.e. are inevitably ampliative). I argue that this concern may be resisted by acknowledging, as Timothy Williamson has shown, that all knowledge is evidence. This suggests an approach to resisting scepticism different from those (e.g. the reliabilist approach) that embrace fallibilism. (shrink)

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.

How can philosophy of science be of more practical use? One thing we can do is provide practicable advice about how to determine when one empirical claim is relevant to the truth of another; i.e., about evidential relevance . This matters especially for evidence-based policy, where advice is thin—and misleading—about how to tell what counts as evidence for policy effectiveness. This paper argues that good efficacy results (as in randomized controlled trials), which are all the rage now, are only a (...) very small part of the story. To tell what facts are relevant for judging policy effectiveness, we need to construct causal scenarios about will happen when the policy is implemented. (shrink)

Joshua Thurow offers a defence of the claim that if a belief is defeasible by non-experiential evidence then it is defeasible by experiential evidence. He responds to an objection which I make against this claim, and offers two arguments in support of his own position. I show that Thurow's response misconstrues my objection, and that his supporting arguments fall short of their goal.

How much should your confidence in your beliefs be shaken when you learn that others – perhaps 'epistemic peers' who seem as well-qualified as you are – hold beliefs contrary to yours? This article describes motivations that push different philosophers towards opposite answers to this question. It identifies a key theoretical principle that divides current writers on the epistemology of disagreement. It then examines arguments bearing on that principle, and on the wider issue. It ends by describing some outstanding questions (...) that thinking about this issue raises. (shrink)

In some of the most important recent work in religious epistemology, Paul Moser (2002, 2004, 2008) develops a multifaceted reply to a prominent attack on belief in God—what we’ll call the Hiddenness Argument. This paper raises a number of worries about Moser’s novel treatment of the Hiddenness Argument. After laying out the version of that argument Moser most explicitly engages, we explain the four main elements of Moser’s reply and argue that it stands or falls with two pieces in particular—what (...) we call the Purposively Available Evidence Argument and the Cognitive Idolatry Argument. We then show that the Cognitive Idolatry Argument fails, leaving the Purposively Available Evidence Argument as Moser’s only potentially viable objection to the Hiddenness Argument. We conclude that Moser’s treatment of the Hiddenness Argument depends crucially on some controversial epistemological claims about certain of our moral beliefs, and is thus considerably more vulnerable than many have recognized. (shrink)

This paper assesses several prominent recent attacks on the view that epistemic justification is conceptually prior to knowledge. I argue that this view—call it the Received View (RV)—emerges from these attacks unscathed. I start with Timothy Williamson’s two strongest arguments for the claim that all evidence is knowledge (E>K), which impugns RV when combined with the claim that justification depends on evidence. One of Williamson’s arguments assumes a false epistemic closure principle; the other misses some alternative (to E>K) explanations of (...) a putative fact about the evidence a particular subject has. Next, I neutralize each of Jonathan Sutton’s three recent arguments to the conclusion that any justified belief constitutes knowledge. Finally, I consider a recent analysis of justification due to Alexander Bird, according to which justified belief is possible knowledge. I argue that Bird’s analysis delivers neither a sufficient nor (more importantly) a necessary condition for justification. [Word count: 149]. (shrink)

We argue that if evidence were knowledge, then there wouldn’t be any Gettier cases, and justification would fail to be closed in egregious ways. But there are Gettier cases, and justification does not fail to be close in egregious ways. Therefore, evidence isn’t knowledge.

The coherence of the whole truth is a presupposition of any holistic coherence theory of justification that postulates a positive connection between justification and truth, for unless the whole truth is itself systemically coherent there is no reason to look for systemic coherence when deciding whether one is justified in accepting a given body of beliefs as true. This paper develops a formal model of holistic evidential coherence and uses this model to formalize and defend the claim that the whole (...) truth must be coherent in an evidential sense. (shrink)

Bayesian epistemology postulates a probabilistic analysis of many sorts of ordinary and scientific reasoning. Huber ([2005]) has provided a novel criticism of Bayesianism, whose core argument involves a challenging issue: confirmation by uncertain evidence. In this paper, we argue that under a properly defined Bayesian account of confirmation by uncertain evidence, Huber's criticism fails. By contrast, our discussion will highlight what we take as some new and appealing features of Bayesian confirmation theory. Introduction Uncertain Evidence and Bayesian Confirmation Bayesian Confirmation (...) by Uncertain Evidence: Test Cases and Basic Principles CiteULike Connotea Del.icio.us What's this? (shrink)

fits our evidence.[1] I will propose some potential counter-examples to test this evidentialist thesis. My main intention in presenting the “counter-examples” is to better understand Feldman’s evidentialism, and evidentialism in general. How are we to understand what our evidence is, how it works, and how are we to understand the phrase “epistemically ought to believe” such that evidentialism might make sense as a plausible thesis in light of the examples? Of course, we may decide that there’s no such way to (...) understand evidentialism -- that it just isn’t a plausible thesis. I must admit that my suspicions lean in that direction. But the potential counter-examples are put forward, not in a refutational spirit (though I have nothing against good refutations in philosophy), but as an invitation to evidentialists and potential evidentialists to refine and/or explain their thesis in light of the at least apparent problems that the examples highlight. (shrink)

J. David Velleman casts foreknowledge of one's own next move as psychologically active. As agents, we form prior intentions about what we will do next. Such prior intentions are licensed self-fulfilling beliefs or directive cognitions. These cognitions differ from ordinary predictions in their psychological relation to the evidence, in that they precede that crucial part of the evidence which consists in the fact that they have been formed. However, once formed, these cognitions are epistemologically unremarkable: they are directly justified by (...) evidence, which saliently includes the fact of their own existence. I argue that Velleman distorts both the epistemology and the etiology of self-knowing agency. Self-knowing agents typically know what they will do next non-evidentially, and yet their knowledge of their own next move is formed in response to their (perspective-relative) epistemic grounds. Velleman's account of self-knowing agency is doubly distortive because it ignores the role of the purely first-person point of view which typically characterizes such agency. In developing an alternative account of self-knowing agency, I argue that the kind of knowledge that we typically have of what we are about to do is like the kind of knowledge we have when we non-evidentially know what our own current, conscious propositional thoughts are. We can non-evidentially know what we think in virtue of having made up our minds what to think. Likewise, we can non-evidentially know what we are about to do in virtue of having settled on what to do next. (shrink)

We must allow that knowledge can be transmitted. But to allow this is to allow that an individual can know a proposition despite lacking any evidence for it and reaching belief by an unreliable means. So some explanation is required as to how knowledge rather than belief is transmitted. This paper considers two non-individualistic explanations: one in terms of knowledge existing autonomously, the other in terms of it existing as a property of communities. And it attempts to decide what is (...) at issue between these explanations. (shrink)

George Bealer argues that intuitions are not only reliable indicators of truth, they are necessary to the philosophical endeavor. Specifically, he thinks that intuitions are essential sources of evidence for epistemic justification. I argue that Bealer's defense of intuitions either (1) is insufficient to show that actual human beings are in a position to use intuitions for epistemic justification, or (2) begs the question. The growing empirical data about our intuitions support the view that humans are not creatures appropriately positioned (...) to use intuitions for epistemic justification in the way Bealer suggests. Without the appropriate empirical evidence that humans are beings so positioned, his view begs the question against those who think that intuitions are not reliable guides to truth. (shrink)

This paper critically analyzes Sherrilyn Roush’s (Tracking truth: knowledge, evidence and science, 2005) definition of evidence and especially her powerful defence that in the ideal, a claim should be probable to be evidence for anything. We suggest that Roush treats not one sense of ‘evidence’ but three: relevance, leveraging and grounds for knowledge; and that different parts of her argument fare differently with respect to different senses. For relevance, we argue that probable evidence is sufficient but not necessary for Roush’s (...) own two criteria of evidence to be met. With respect to grounds for knowledge, we agree that high probability evidence is indeed ideal for the central reason Roush gives: When believing a hypothesis on the basis of e it is desirable that e be probable. But we maintain that her further argument that Bayesians need probable evidence to warrant the method they recommend for belief revision rests on a mistaken interpretation of Bayesian conditionalization. Moreover, we argue that attempts to reconcile Roush’s arguments with Bayesianism fail. For leveraging, which we agree is a matter of great importance, the requirement that evidence be probable suffices for leveraging to the probability of the hypothesis if either one of Roush’s two criteria for evidence are met. Insisting on both then seems excessive. To finish, we show how evidence, as Roush defines it, can fail to track the hypothesis. This can remedied by adding a requirement that evidence be probable, suggesting another rationale for taking probable evidence as ideal—but only for a grounds-for-knowledge sense of evidence. (shrink)

Bayesian epistemology suggests various ways of measuring the support that a piece of evidence provides a hypothesis. Such measures are defined in terms of a subjective probability assignment, pr, over propositions entertained by an agent. The most standard measure (where “H” stands for “hypothesis” and “E” stands for “evidence”) is.

The question of whether or not to partition data for the purposes of inferring phylogenetic hypotheses remains controversial. Opinions have been especially divided since Kluge's (1989, Systematic Zoology 38, 7–25) claim that data partitioning violates the requirement of total evidence (RTE). Unfortunately, advocacy for or against the RTE has not been based on accurate portrayals of the requirement. The RTE is a basic maxim for non-deductive inference, stipulating that evidence must be considered if it has relevance to an inference. Evidence (...) is relevant if it has a positive or negative effect on a given conclusion. In the case of ℈partitioned’ phylogenetic inferences, the RTE is violated, and the basis for rational belief in any conclusion is compromised, unless it is shown that the partitions are evidentially irrelevant to one another. The goal of phylogenetic systematics is to hypothesize past causal conditions to account for observed shared similarities among two or more species. Such inferences are non-deductive, necessitating consideration of the RTE. Some phylogeneticists claim the parsimony criterion as justification for the RTE. There is no relation between the two – parsimony is a relation between a hypothesis and causal question(s). Parsimony does not dictate the content of premises prior to an inference. ℈Taxonomic congruence,’ ℈supertrees,’ and ℈conditional combination’ methods violate the RTE. Taxonomic congruence and supertree methods also fail to achieve the intended goal of phylogenetic inference, such that ℈consensus trees’ and ℈supertrees’ lack an empirical basis. ℈Conditional combination’ is problematic because hypotheses derived from partitioned data cannot be compared – a causal hypothesis inferred to account for a set of effects only has relevance to those effects, not any comparative relevance to other causal hypotheses. A similar problem arises in the comparisons of hypotheses derived from different causal theories. (shrink)

Because “evidence” is at issue in evidence-based medicine (EBM), the critical responses to the movement have taken up themes from post-positivist philosophy of science to demonstrate the untenability of the objectivist account of evidence. While these post-positivist critiques seem largely correct, I propose that when they focus their analyses on what counts as evidence, the critics miss important and desirable pragmatic features of the evidence-based approach. This article redirects critical attention toward EBM’s rigid hierarchy of evidence as the culprit of (...) its objectionable epistemic practices. It reframes the EBM discourse in light of a distinction between objectivist and pragmatic epistemology, which allows for a more nuanced analysis of EBM than previously offered: one that is not either/or in its evaluation of the decision-making technology as either iconoclastic or creedal. (shrink)

Timothy Williamson’s project in Knowledge and Its Limits (Williamson, 2000)1 includes proposals for substantial revisions in the received approach to epistemology. One received view is that knowledge is conceptualized in terms of a conjunction of factors that are individually necessary and jointly sufficient for knowing. A central aim of epistemology is to state such necessary and sufficient conditions. Against this received view, Williamson argues that a necessary but insufficient condition need not be a conjunct of a non-circular necessary and sufficient (...) condition. Although being coloured is a necessary but insufficient condition for being red, we cannot state a necessary and sufficient condition for being red by conjoining being coloured with other properties specified without reference to red. Neither the equation ‘Red = coloured + X’ nor the equation ‘Knowledge = true belief + X’ need have a non-circular solution. (3) Williamson further argues that we have inductive reasons for thinking that no analysis of the concept knows of the standard kind is correct. The inductive reasons are simply the history of failed attempts at such “factorizing” or “decompositional” analyses. Williamson not only rejects the prospect of explaining knowledge in terms of belief, justification, and evidence, but he proposes to reverse the order of explanation. That order of explanation has been reversed in this book. The concept knows is fundamental, the primary implement of epistemological inquiry. (185) It is not altogether easy, however, to reconcile this radical program with other things Williamson says in the book. In particular, the book contains two rather unrelated accounts of knowing, and one of these accounts appeals to some of the same ingredients that traditional (or semi-traditional) analysts have used in the past. The first account, which appears in Chapter 1, says that knowing is the most general factive stative propositional attitude. The account is presented in terms of three conditions: (1) If Φ is an FMSO [factive mental state operator], from ‘S Φs that A’ one may infer ‘A’.. (shrink)

Bayesian epistemology addresses epistemological problems with the help of the mathematical theory of probability. It turns out that the probability calculus is especially suited to represent degrees of belief (credences) and to deal with questions of belief change, confirmation, evidence, justification, and coherence. Compared to the informal discussions in traditional epistemology, Bayesian epis- temology allows for a more precise and fine-grained analysis which takes the gradual aspects of these central epistemological notions into account. Bayesian epistemology therefore complements traditional epistemology; it (...) does not re- place it or aim at replacing it. (shrink)

The paper attempts to give an account of the introspective self-knowledge of our own experiences which is in line with representationalism about phenomenal consciousness and the transparency of experience. A two-step model is presented. First, a demonstrative thought of the form ‚I am experiencing this’ is formed which refers to what one experiences, by means of attention. Plausibly, this thought is knowledge, since safe. Second, a non-demonstrative thought of the form ‚I am experiencing a pain’ occurs. This second self-ascription is (...) justified inferentially, on the basis of the first, demonstrative thought. Thus, an account of introspective experiential self-knowledge can be developed which is richer and more adequate to the phenomena than pure reliabilism and Dretske’s displaced perception model. There is really such a thing as introspection, but no inner sense. (shrink)

theory of knowledge defended in Timothy Williamson's book Knowledge and its Limits is compared here with the theory defended in the author's articles ‘How Knowledge Works’ and ‘Knowledge and Self-Knowledge’. It is argued that there are affinities between these theories, but that the latter has considerably more explanatory power.

The concept of evidence is central to both epistemology and the philosophy of science. Of course, ‘evidence’ is hardly a philosopher's term of art: it is not only, or even primarily, philosophers who routinely speak of evidence, but also lawyers and judges, historians and scientists, investigative journalists and reporters, as well as the members of numerous other professions and ordinary folk in the course of everyday life. The concept of evidence would thus seem to be on firmer pre-theoretical ground than (...) various other concepts which enjoy similarly central standing within philosophy. (Contrast, for example, the epistemologist's quasi-technical term ‘epistemic justification’.). (shrink)

The concept of evidence is among the central concerns of epistemology broadly construed. As such, it has long engaged the intellectual energies of both philosophers of science and epistemologists of a more traditional variety. Here I briefly survey some of the more important ideas to have emerged from this tradition of reflection. I then look somewhat more closely at an issue that has recently come to the fore, largely as a result of Williamson's Knowledge and Its Limits: that of whether (...) one's evidence supervenes on one's non-factive mental states. (shrink)

The aim of this paper is to examine the kind of evidence that might be adduced in support of relativist semantics of a kind that have recently been proposed for predicates of personal taste, for epistemic modals, for knowledge attributions and for other cases. I shall concentrate on the case of taste predicates, but what I have to say is easily transposed to the other cases just mentioned. I shall begin by considering in general the question of what kind of (...) evidence can be offered in favour of some semantic theory or framework of semantic theorizing. In other words, I shall begin with the difficult question of the empirical significance of semantic theorizing. In Sect. 2, I outline a relativist semantic theory, and in Sect. 3, I review four types of evidence that might be offered in favour of a relativistic framework. I show that the evidence is not conclusive because a sophisticated form of contextualism (or indexical relativism) can stand up to the evidence. However, the evidence can be taken to support the view that either relativism or the sophisticated form of contextualism is correct. (shrink)