First published in 2000. Routledge is an imprint of Taylor & Francis, an informa company.

A wide-ranging study of the central concepts in epistemology - belief, truth and knowledge. Professor Armstrong offers a dispositional account of general beliefs and of knowledge of general propositions. Belief about particular matters of fact are described as structures in the mind of the believer which represent or 'map' reality, while general beliefs are dispositions to extend the 'map' or introduce casual relations between portions of the map according to general rules. 'Knowledge' denotes the reliability of such beliefs as representations (...) of reality. Within this framework Professor Armstrong offers a distinctive account of many of the main questions in general epistemology - the relations between beliefs and language, the notions of proposition, concept and idea, the analysis of truth, the varieties of knowledge, and the way in which beleifs and knowledge are supported by reasons. The book as a whole if offered as a contribution to a naturalistic account of man. (shrink)

Conditionalization and Jeffrey Conditionalization cannot simultaneously satisfy two widely held desiderata on rules for empirical learning. The first desideratum is confirmational holism, which says that the evidential import of an experience is always sensitive to our background assumptions. The second desideratum is commutativity, which says that the order in which one acquires evidence shouldn't affect what conclusions one draws, provided the same total evidence is gathered in the end. (Jeffrey) Conditionalization cannot satisfy either of these desiderata without violating the other. (...) This is a surprising problem, and I offer a diagnosis of its source. I argue that (Jeffrey) Conditionalization is inherently anti-holistic in a way that is just exacerbated by the requirement of commutativity. The dilemma is thus a superficial manifestation of (Jeffrey) Conditionalization's fundamentally anti-holistic nature. (shrink)

This is a collection of chapters by the leading proponent of process reliabilism, explaining its relation to rival and/or neighboring theories including evidentialism, other forms of reliabilism, and virtue epistemology. It addresses other prominent themes in contemporary epistemology, such as the internalism/externalism debate, the epistemological upshots of experimental challenges to intuitional methodology, the source of epistemic value, and social epistemology. The Introduction addresses late-breaking responses to ongoing exchanges with friends, rivals, and critics of reliabilism.

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)

The aim of this paper is to sketch a theory of justified belief. What I have in mind is an explanatory theory, one that explains in a general way why certain beliefs are counted as justified and others as unjustified. Unlike some traditional approaches, I do not try to prescribe standards for justification that differ from, or improve upon, our ordinary standards. I merely try to explicate the ordinary standards, which are, I believe, quite different from those of many classical, (...) e. g., ‘Cartesian’, accounts. (shrink)

The value problem -- Unpacking the value problem -- The swamping problem -- fundamental and non-fundamental epistemic goods -- The relevance of epistemic value monism -- Responding to the swamping problem I : the practical response -- Responding to the swamping problem II : the monistic response -- Responding to the swamping problem III : the pluralist response -- Robust virtue epistemology -- Knowledge and achievement -- Interlude : is robust virtue epistemology a reductive theory of knowledge? -- Achievement without (...) achievement -- Back to the value problem -- Contra virtue epistemology -- Two master intuitions about knowledge -- Anti-luck virtue epistemology -- Interlude : is anti-luck virtue epistemology a reductive theory of knowledge? -- Diagnosing the structure of knowledge -- Back to the value problem -- The final value of achievements -- Understanding -- Understanding and epistemic luck -- Understanding and cognitive achievement -- Back to the value problem -- Two potential implications of the distinctive value of understanding thesis -- The traditional analytical project and the central tension -- Knowledge, evidence, and reasons -- Concepts versus phenomena -- The way ahead -- Perceptual-recognitional abilities -- Broad and narrow competence -- Avoiding reduction -- Perpetual-recognitional abilities -- Broad and narrow competence -- Avoiding reduction -- Perceptual knowledge and justified belief -- Closure and doxastic responsibility -- Knowledge from indicators -- Recognitional abilities again -- Detached standing knowledge -- Back to knowledge from indicators -- Taking stock -- Why knowledge matters -- Approaching the epistemology of testimony -- Telling and informing -- Acquiring true beliefs and acquiring knowledge through being told -- Access to facts about knowledge -- The modest route -- Fool's knowledge -- The distinctive value of knowledge -- Fool's justification -- Arguing from illusion -- The regress of justifications -- Transparency and knowledge -- Transparency and entitlement -- On trying to do without transparency -- Transparency and luminosity -- Non-sensible knowledge -- Self-knowledge -- Non-sensible knowledge of action -- The two dimensions -- The distinctive value of knowledge of action -- Non-observational knowledge -- Practical knowledge and intention -- Practical knowledge and direction of fit. (shrink)

This paper discusses two versions of reliabilism: modal and probabilistic reliabilism. Modal reliabilism faces the problem of the missing closeness metric for possible worlds while probalistic reliabilism faces the problem of the relevant reference class. Despite the severity of these problems, reliabilism is still very plausible (also for independent reasons). I propose to stick with reliabilism, propose a contextualist (or, alternatively, harmlessly relativist) solution to the above problems and suggest that probabilistic reliabilism has the advantage over modal reliabilism.

One of the fundamental problems of epistemology is to say when the evidence in an agent’s possession justifies the beliefs she holds. In this paper and its prequel, we defend the Bayesian solution to this problem by appealing to the following fundamental norm: Accuracy An epistemic agent ought to minimize the inaccuracy of her partial beliefs. In the prequel, we made this norm mathematically precise; in this paper, we derive its consequences. We show that the two core tenets of Bayesianism (...) follow from the norm, while the characteristic claim of the Objectivist Bayesian follows from the norm along with an extra assumption. Finally, we consider Richard Jeffrey’s proposed generalization of conditionalization. We show not only that his rule cannot be derived from the norm, unless the requirement of Rigidity is imposed from the start, but further that the norm reveals it to be illegitimate. We end by deriving an alternative updating rule for those cases in which Jeffrey’s is usually supposed to apply. (shrink)

One of the fundamental problems of epistemology is to say when the evidence in an agent’s possession justifies the beliefs she holds. In this paper and its sequel, we defend the Bayesian solution to this problem by appealing to the following fundamental norm: Accuracy An epistemic agent ought to minimize the inaccuracy of her partial beliefs. In this paper, we make this norm mathematically precise in various ways. We describe three epistemic dilemmas that an agent might face if she attempts (...) to follow Accuracy, and we show that the only inaccuracy measures that do not give rise to such dilemmas are the quadratic inaccuracy measures. In the sequel, we derive the main tenets of Bayesianism from the relevant mathematical versions of Accuracy to which this characterization of the legitimate inaccuracy measures gives rise, but we also show that Jeffrey conditionalization has to be replaced by a different method of update in order for Accuracy to be satisfied. (shrink)

"[This book] proposes new foundations for the Bayesian principle of rational action, and goes on to develop a new logic of desirability and probabtility."—Frederic Schick, _Journal of Philosophy_.

I begin with some familiar conceptions of epistemic relativism. One kind of epistemic relativism is descriptive pluralism. This is the simple, non-normative thesis that many different communities, cultures, social networks, etc. endorse different epistemic systems (E-systems), i.e., different sets of norms, standards, or principles for forming beliefs and other doxastic states. Communities try to guide or regulate their members’ credence-forming habits in a variety of different, i.e., incompatible, ways. Although there may be considerable overlap across cultures in certain types of (...) epistemic norms (e.g., norms for perceptual belief), there are sharp differences across groups in other types of epistemic norms. (shrink)

Knowledge and its Limits presents a systematic new conception of knowledge as a kind of mental stage sensitive to the knower's environment. It makes a major contribution to the debate between externalist and internalist philosophies of mind, and breaks radically with the epistemological tradition of analyzing knowledge in terms of true belief. The theory casts new light on such philosophical problems as scepticism, evidence, probability and assertion, realism and anti-realism, and the limits of what can be known. The arguments are (...) illustrated by rigorous models based on epistemic logic and probability theory. The result is a new way of doing epistemology and a notable contribution to the philosophy of mind. (shrink)

Knowledge in a Social World offers a philosophy for the information age. Alvin Goldman explores new frontiers by creating a thoroughgoing social epistemology, moving beyond the traditional focus on solitary knowers. Against the tides of postmodernism and social constructionism Goldman defends the integrity of truth and shows how to promote it by well-designed forms of social interaction. From science to education, from law to democracy, he shows why and how public institutions should seek knowledge-enhancing practices. The result is a bold, (...) timely, and systematic treatment of the philosophical foundations of an information society. (shrink)

Against the traditional view, Alvin Goldman argues that logic, probability theory, and linguistic analysis cannot by themselves delineate principles of rationality or justified belief. The mind's operations must be taken into account.

This paper reviews two skeptical arguments and argues that a reliabilist framework is necessary to avoid them. The paper also argues that agent reliabilism, which makes the knower the seat of reliability, is the most plausible version of reliabilism.

Your evidence constrains your rational degrees of confidence both locally and globally. On the one hand, particular bits of evidence can boost or diminish your rational degree of confidence in various hypotheses, relative to your background information. On the other hand, epistemic rationality requires that, for any hypothesis h, your confidence in h is proportional to the support that h receives from your total evidence. Why is it that your evidence has these two epistemic powers? I argue that various proposed (...) accounts of what it is for something to be an element of your evidence set cannot answer this question. I then propose an alternative account of what it is for something to be an element of your evidence set. 1 Introduction 2 The elements of one's evidence set are propositions 3 Which kinds of propositions are in one's evidence set? 3.1 Doxastic accounts of evidence 3.2 Non-doxastic accounts of evidence 4 Elaborating and defending the LIE CiteULike Connotea Del.icio.us What's this? (shrink)

Economic forms of analysis have penetrated to many disciplines in the last 30 years: political science, sociology, law, social and political philosophy, and so forth. We wish to extend the economic paradigm to certain problems in epistemology and the philosophy of science. Scientific agents, and scholarly inquirers generally, act in some ways like vendors, trying to "sell" their findings, theories, analyses, or arguments to an audience of prospective "buyers". The analogy with the marketplace is imperfect. The ideas or discoveries that (...) a scientist offers are not private goods in the economist's sense. Nonetheless, there are parallels with the marketplace that are worth exploring. (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.

Can there be good reasons for judging one set of probabilistic assertions more reliable than a second? There are many candidates for measuring "goodness" of probabilistic forecasts. Here, I focus on one such aspirant: calibration. Calibration requires an alignment of announced probabilities and observed relative frequency, e.g., 50 percent of forecasts made with the announced probability of.5 occur, 70 percent of forecasts made with probability.7 occur, etc. To summarize the conclusions: (i) Surveys designed to display calibration curves, from which a (...) recalibration is to be calculated, are useless without due consideration for the interconnections between questions (forecasts) in the survey. (ii) Subject to feedback, calibration in the long run is otiose. It gives no ground for validating one coherent opinion over another as each coherent forecaster is (almost) sure of his own long-run calibration. (iii) Calibration in the short run is an inducement to hedge forecasts. A calibration score, in the short run, is improper. It gives the forecaster reason to feign violation of total evidence by enticing him to use the more predictable frequencies in a larger finite reference class than that directly relevant. (shrink)

Confirmation is commonly identified with positive relevance, E being said to confirm H if and only if E increases the probability of H. Today, analyses of this general kind are usually Bayesian ones that take the relevant probabilities to be subjective. I argue that these subjective Bayesian analyses are irremediably flawed. In their place I propose a relevance analysis that makes confirmation objective and which, I show, avoids the flaws of the subjective analyses. What I am proposing is in some (...) ways a return to Carnap's conception of confirmation, though there are also important differences between my analysis and his. My analysis includes new accounts of what evidence is and of the indexicality of confirmation claims. Finally, I defend my analysis against Achinstein's criticisms of the relevance concept of confirmation. (shrink)

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

The pragmatic character of the Dutch book argument makes it unsuitable as an "epistemic" justification for the fundamental probabilist dogma that rational partial beliefs must conform to the axioms of probability. To secure an appropriately epistemic justification for this conclusion, one must explain what it means for a system of partial beliefs to accurately represent the state of the world, and then show that partial beliefs that violate the laws of probability are invariably less accurate than they could be otherwise. (...) The first task can be accomplished once we realize that the accuracy of systems of partial beliefs can be measured on a gradational scale that satisfies a small set of formal constraints, each of which has a sound epistemic motivation. When accuracy is measured in this way it can be shown that any system of degrees of belief that violates the axioms of probability can be replaced by an alternative system that obeys the axioms and yet is more accurate in every possible world. Since epistemically rational agents must strive to hold accurate beliefs, this establishes conformity with the axioms of probability as a norm of epistemic rationality whatever its prudential merits or defects might be. (shrink)

According to Bayesian epistemology, the epistemically rational agent updates her beliefs by conditionalization: that is, her posterior subjective probability after taking account of evidence X, pnew, is to be set equal to her prior conditional probability pold(·|X). Bayesians can be challenged to provide a justification for their claim that conditionalization is recommended by rationality—whence the normative force of the injunction to conditionalize? There are several existing justifications for conditionalization, but none directly addresses the idea that conditionalization will be epistemically rational (...) if and only if it can reasonably be expected to lead to epistemically good outcomes. We apply the approach of cognitive decision theory to provide a justification for conditionalization using precisely that idea. We assign epistemic utility functions to epistemically rational agents; an agent’s epistemic utility is to depend both upon the actual state of the world and on the agent’s credence distribution over possible states. We prove that, under independently motivated conditions, conditionalization is the unique updating rule that maximizes expected epistemic utility. (shrink)

It is common in recent epistemology to distinguish different senses, or conceptions, of epistemic justification. The proposed oppositions include the objective/subjective, internalist/externalist, regulative/nonregulative, resource-relative/resource-independent, personal/verific, and deontological/evaluative conceptions of justification. In some of these cases, writers regard both members of the contrasting pair as legitimate; in other cases only one member. In this paper I want to propose another contrasting pair of conceptions of justification, and hold that both are defensible and legitimate. The contrast will then be used to construct (...) a modified version of reliabilism, one which handles certain problem cases more naturally than my previous versions of reliabilism. (shrink)

Your evidence constrains your rational degrees of confidence both locally and globally. On the one hand, particular bits of evidence can boost or diminish your rational degree of confidence in various hypotheses, relative to your background information. On the other hand, epistemic rationality requires that, for any hypothesis h, your confidence in h is proportional to the support that h receives from your total evidence. Why is it that your evidence has these two epistemic powers? I argue that various proposed (...) accounts of what it is for something to be an element of your evidence set cannot answer this question. I then propose an alternative account of what it is for something to be an element of your evidence set. 1. Introduction2. The elements of one's evidence set are propositions3. Which kinds of propositions are in one's evidence set?3.1. Doxastic accounts of evidence3.2. Non-doxastic accounts of evidence4. Elaborating and defending the LIE. (shrink)