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)

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)

Objective Bayesianism is a methodological theory that is currently applied in statistics, philosophy, artificial intelligence, physics and other sciences. This book develops the formal and philosophical foundations of the theory, at a level accessible to a graduate student with some familiarity with mathematical notation.

An examination of topics involved in statistical reasoning with imprecise probabilities. The book discusses assessment and elicitation, extensions, envelopes and decisions, the importance of imprecision, conditional previsions and coherent statistical models.

The principle of indifference is supposed to suffice for the rational assignation of probabilities to possibilities. Bertrand advances a probability problem, now known as his paradox, to which the principle is supposed to apply; yet, just because the problem is ill‐posed in a technical sense, applying it leads to a contradiction. Examining an ambiguity in the notion of an ill‐posed problem shows that there are precisely two strategies for resolving the paradox: the distinction strategy and the well‐posing strategy. The main (...) contenders for resolving the paradox, Marinoff and Jaynes, offer solutions which exemplify these two strategies. I show that Marinoff’s attempt at the distinction strategy fails, and I offer a general refutation of this strategy. The situation for the well‐posing strategy is more complex. Careful formulation of the paradox within measure theory shows that one of Bertrand’s original three options can be ruled out but also shows that piecemeal attempts at the well‐posing strategy will not succeed. What is required is an appeal to general principle. I show that Jaynes’s use of such a principle, the symmetry requirement, fails to resolve the paradox; that a notion of metaindifference also fails; and that, while the well‐posing strategy may not be conclusively refutable, there is no reason to think that it can succeed. So the current situation is this. The failure of Marinoff’s and Jaynes’s solutions means that the paradox remains unresolved, and of the only two strategies for resolution, one is refuted and we have no reason to think the other will succeed. Consequently, Bertrand’s paradox continues to stand in refutation of the principle of indifference. (shrink)

Many have claimed that unspecific evidence sometimes demands unsharp, indeterminate, imprecise, vague, or interval-valued probabilities. Against this, a variant of the diachronic Dutch Book argument shows that perfectly rational agents always have perfectly sharp probabilities.

This is the classic work upon which modern-day game theory is based. What began as a modest proposal that a mathematician and an economist write a short paper together blossomed, when Princeton University Press published Theory of Games and Economic Behavior. In it, John von Neumann and Oskar Morgenstern conceived a groundbreaking mathematical theory of economic and social organization, based on a theory of games of strategy. Not only would this revolutionize economics, but the entirely new field of scientific inquiry (...) it yielded--game theory--has since been widely used to analyze a host of real-world phenomena from arms races to optimal policy choices of presidential candidates, from vaccination policy to major league baseball salary negotiations. And it is today established throughout both the social sciences and a wide range of other sciences. (shrink)

Traditional philosophical discussions of knowledge have focused on the epistemic status of full beliefs. In this book, Moss argues that in addition to full beliefs, credences can constitute knowledge. For instance, your .4 credence that it is raining outside can constitute knowledge, in just the same way that your full beliefs can. In addition, you can know that it might be raining, and that if it is raining then it is probably cloudy, where this knowledge is not knowledge of propositions, (...) but of probabilistic contents. -/- The notion of probabilistic content introduced in this book plays a central role not only in epistemology, but in the philosophy of mind and language as well. Just as tradition holds that you believe and assert propositions, you can believe and assert probabilistic contents. Accepting that we can believe, assert, and know probabilistic contents has significant consequences for many philosophical debates, including debates about the relationship between full belief and credence, the semantics of epistemic modals and conditionals, the contents of perceptual experience, peer disagreement, pragmatic encroachment, perceptual dogmatism, and transformative experience. In addition, accepting probabilistic knowledge can help us discredit negative evaluations of female speech, explain why merely statistical evidence is insufficient for legal proof, and identify epistemic norms violated by acts of racial profiling. Hence the central theses of this book not only help us better understand the nature of our own mental states, but also help us better understand the nature of our responsibilities to each other. (shrink)

The representation theorems of expected utility theory show that having certain types of preferences is both necessary and sufficient for being representable as having subjective probabilities. However, unless the expected utility framework is simply assumed, such preferences are also consistent with being representable as having degrees of belief that do not obey the laws of probability. This fact shows that being representable as having subjective probabilities is not necessarily the same as having subjective probabilities. Probabilism can be defended on the (...) basis of the representation theorems only if attributions of degrees of belief are understood either antirealistically or purely qualitatively, or if the representation theorems are supplemented by arguments based on other considerations (simplicity, consilience, and so on) that single out the representation of a person as having subjective probabilities as the only true representation of the mental state of any person whose preferences conform to the axioms of expected utility theory. (shrink)

In his important book Knowledge and Practical Interests, Jason Stanley advances a proposal about knowledge and the semantics of knowledge ascriptions which he calls interest-relative invariantism. A theory of knowledge ascriptions of the form ‘A knows that S’ is invariantist.

What is the normative role of knowledge? I argue that knowledge plays an important role as a norm of assertion and action, which is explained and unified by its more fundamental role as a norm of belief. Moreover, I propose a distinctive account of what this normative role consists in. I argue that knowledge is the aim of belief, which sets a normative standard of correctness and a corresponding normative standard of justification. According to my proposal, it is correct to (...) believe, assert and act on a proposition if and only if one is in a position to know it, but one has justification to believe, assert and act on a proposition if and only if one has justification to believe that one is in a position to know it. (shrink)

It has been claimed that, in response to certain kinds of evidence, agents ought to adopt imprecise credences: doxastic states that are represented by sets of credence functions rather than single ones. In this paper I argue that, given some plausible constraints on accuracy measures, accuracy-centered epistemologists must reject the requirement to adopt imprecise credences. I then show that even the claim that imprecise credences are permitted is problematic for accuracy-centered epistemology. It follows that if imprecise credal states are permitted (...) or required in the cases that their defenders appeal to, then the requirements of rationality can outstrip what would be warranted by an interest in accuracy. (shrink)

Sarah Moss’ thesis that we have probabilistic knowledge is from some perspectives unsurprising and from other perspectives hard to make sense of. The thesis is potentially transformative, but not yet elaborated in sufficient detail for epistemologists. This paper interprets Mossean probabilistic knowledge in a suitably-modified Kripke framework, thus filling in key details. It argues that probabilistic knowledge looks natural and plausible when so interpreted, and shows how the most pressing challenges to the thesis can be overcome. Most importantly, probabilistic knowledge (...) can satisfy factivity in the framework, though we are not forced to accept a specific account of probabilistic “facts”. The framework also reflects Moss’ claim that old-fashioned propositional knowledge is just a limiting case of probabilistic knowledge, and all knowledge is fundamentally probabilistic. Finally, Moss endorses a failure of contraposition: for example, p implies probably p, but not probably p does not imply not p. The framework makes clear the sense in which the valid inferences regarding probably p are as Moss claims. (shrink)

This paper argues that just as full beliefs can constitute knowledge, so can properties of your credence distribution. The resulting notion of probabilistic knowledge helps us give a natural account of knowledge ascriptions embedding language of subjective uncertainty, and a simple diagnosis of probabilistic analogs of Gettier cases. Just like propositional knowledge, probabilistic knowledge is factive, safe, and sensitive. And it helps us build knowledge-based norms of action without accepting implausible semantic assumptions or endorsing the claim that knowledge is interest-relative.

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)

"[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_.

This paper distinguishes two ways to ?put knowledge first?. One way affirms a knowledge norm. For example, Williamson [2000] argues that one must only assert that which one knows. Hawthorne and Stanley [2008] argue that one must only treat as a reason for action that which one knows. Another way to put knowledge first affirms a determination thesis. For example, Williamson [2000] argues that what one knows determines what one is justified in believing. Hawthorne and Stanley [2008] argue that what (...) one knows determines what it is rational for one to do. This paper argues that the defender of the knowledge norms can and should reject the determination theses. For example, the rationality of acting on a partial belief cannot be explained in terms of the subject's knowledge. That's no problem for the knowledge norm, which only governs acting on full belief. (Analogously, the knowledge norm of flat-out assertion does not govern hedged assertion.) One might worry that rejecting the determination theses undermines the importance of knowing. I reply that the knowledge norms set the standard for epistemic success. The importance of success is not undermined by loosening its ties to justification and rationality. (shrink)

We study decision under uncertainty in an Anscombe–Aumann framework. Two binary relations characterize a decision-maker: one incomplete relation, reflecting her objective rationality, and a second complete relation, reflecting her subjective rationality. We require the latter to be an extension of the former. Our key axiom is a dominance condition. Our main theorem provides a representation of the two relations. The objectively rational relation has a Bewley-style multiple prior representation. Using this set of priors, we fully characterize the subjectively rational relation (...) in terms of the most optimistic and most pessimistic expected utilities. (shrink)

I develop an approach to action and practical deliberation according to which the degree of epistemic warrant required for practical rationality varies with practical context. In some contexts of practical deliberation, very strong warrant is called for. In others, less will do. I set forth a warrant account, (WA), that captures this idea. I develop and defend (WA) by arguing that it is more promising than a competing knowledge account of action due to John Hawthorne and Jason Stanley. I argue (...) that cases of warranted false belief speak in favor of (WA) and against the knowledge account. Moreover, I note some problems with an “excuse maneuver” that proponents of the knowledge account frequently invoke in response to cases of warranted false belief. Finally, I argue that (WA) may provide a strict invariantist account of cases that have been thought to motivate interest-relative or subject-sensitive theories of knowledge and warrant. (shrink)

Philosophy and Phenomenological Research, EarlyView.

It has become recently popular to suggest that knowledge is the epistemic norm of practical reasoning and that this provides an important constraint on the correct account of knowledge, one which favours subject-sensitive invariantism over contextualism and classic invariantism. I argue that there are putative counterexamples to both directions of the knowledge norm. Even if the knowledge norm can be defended against these counterexamples, I argue that it is a delicate issue whether it is true, one which relies on fine (...) distinctions among a variety of relevant notions of propriety which our intuitions may reflect. These notions variously apply to the agent herself, her character traits, her beliefs, her reasoning and any resultant action. Given the delicacy of these issues, I argue that the knowledge norm is not a fixed point from which to defend substantive and controversial views in epistemology. Rather, these views need to be defended on other grounds. (shrink)

In “Knowledge Under Threat” (Philosophy and Phenomenological Research 2012), Tomas Bogardus proposes a counterexample to the safety condition for knowledge. Bogardus argues that the case demonstrates that unsafe knowledge is possible. I argue that the case just corroborates the well-known requirement that modal conditions like safety must be relativized to methods of belief formation. I explore several ways of relativizing safety to belief-forming methods and I argue that none is adequate: if methods were individuated in those ways, safety would fail (...) to explain several much-discussed cases. I then propose a plausible externalist principle of method individuation. On the one hand, relativizing safety to belief-forming methods in the way suggested allows the defender of safety to account for the cases. On the other hand, it shows that the target known belief of Bogardus’s example is safe. Finally, I offer a diagnosis of a common error about the kind of cases that are typically considered potential counterexamples to the necessity of the epistemic condition: proponents of the alleged counterexamples mistake a strong condition that I call super-safety for safety. (shrink)

There has been much recent interest in imprecise probabilities, models of belief that allow unsharp or fuzzy credence. There have also been some influential criticisms of this position. Here we argue, chiefly against Elga (2010), that subjective probabilities need not be sharp. The key question is whether the imprecise probabilist can make reasonable sequences of decisions. We argue that she can. We outline Elga's argument and clarify the assumptions he makes and the principles of rationality he is implicitly committed to. (...) We argue that these assumptions are too strong and that rational imprecise choice is possible in the absence of these overly strong conditions. (shrink)

Many contemporary epistemologists hold that a subject S’s true belief that p counts as knowledge only if S’s belief that p is also, in some important sense, safe. I describe accounts of this safety condition from John Hawthorne, Duncan Pritchard, and Ernest Sosa. There have been three counterexamples to safety proposed in the recent literature, from Comesaña, Neta and Rohrbaugh, and Kelp. I explain why all three proposals fail: each moves fallaciously from the fact that S was at epistemic risk (...) just before forming her belief to the conclusion that S’s belief was formed unsafely. In light of lessons from their failure, I provide a new and successful counterexample to the safety condition on knowledge. It follows, then, that knowledge need not be safe. Safety at a time depends counterfactually on what would likely happen at that time or soon after in a way that knowledge does not. I close by considering one objection concerning higher-order safety. (shrink)

It is widely held that Bayesian decision theory is the final word on how a rational person should make decisions. However, Leonard Savage--the inventor of Bayesian decision theory--argued that it would be ridiculous to use his theory outside the kind of small world in which it is always possible to "look before you leap." If taken seriously, this view makes Bayesian decision theory inappropriate for the large worlds of scientific discovery and macroeconomic enterprise. When is it correct to use Bayesian (...) decision theory--and when does it need to be modified? Using a minimum of mathematics, Rational Decisions clearly explains the foundations of Bayesian decision theory and shows why Savage restricted the theory's application to small worlds. The book is a wide-ranging exploration of standard theories of choice and belief under risk and uncertainty. Ken Binmore discusses the various philosophical attitudes related to the nature of probability and offers resolutions to paradoxes believed to hinder further progress. In arguing that the Bayesian approach to knowledge is inadequate in a large world, Binmore proposes an extension to Bayesian decision theory--allowing the idea of a mixed strategy in game theory to be expanded to a larger set of what Binmore refers to as "muddled" strategies. Written by one of the world's leading game theorists, Rational Decisions is the touchstone for anyone needing a concise, accessible, and expert view on Bayesian decision making. (shrink)

Lara Buchak sets out a new account of rational decision-making in the face of risk. She argues that the orthodox view is too narrow, and suggests an alternative, more permissive theory: one that allows individuals to pay attention to the worst-case or best-case scenario, and vindicates the ordinary decision-maker.

According to a tradition reaching back to Plato, questions about the nature of knowledge are to be answered by offering an analysis in terms of truth, belief, justification, and other factors presumed to be in some sense more basic than knowledge itself. In light of the apparent failure of this approach, knowledge first philosophy instead takes knowledge as the starting point in epistemology and related areas of the philosophies of language and mind. Knowledge cannot be analyzed in the traditional sense, (...) but this does not make it mysterious or unimportant. On the contrary, we are freed to use our grasp of what knowledge is to elucidate the nature of belief, justification, evidence, the speech act of assertion, and the demands on action and practical reasoning, and to treat knowledge as a purely mental state in its own right. Knowledge First? offers the first overview and critical evaluation of knowledge first philosophy as a whole. (shrink)

It is widely held that Bayesian decision theory is the final word on how a rational person should make decisions. However, Leonard Savage--the inventor of Bayesian decision theory--argued that it would be ridiculous to use his theory outside the kind of small world in which it is always possible to "look before you leap." If taken seriously, this view makes Bayesian decision theory inappropriate for the large worlds of scientific discovery and macroeconomic enterprise. When is it correct to use Bayesian (...) decision theory--and when does it need to be modified? Using a minimum of mathematics, Rational Decisions clearly explains the foundations of Bayesian decision theory and shows why Savage restricted the theory's application to small worlds. The book is a wide-ranging exploration of standard theories of choice and belief under risk and uncertainty. Ken Binmore discusses the various philosophical attitudes related to the nature of probability and offers resolutions to paradoxes believed to hinder further progress. In arguing that the Bayesian approach to knowledge is inadequate in a large world, Binmore proposes an extension to Bayesian decision theory--allowing the idea of a mixed strategy in game theory to be expanded to a larger set of what Binmore refers to as "muddled" strategies. Written by one of the world's leading game theorists, Rational Decisions is the touchstone for anyone needing a concise, accessible, and expert view on Bayesian decision making. (shrink)

Classic analysis of the subject and the development of personal probability; one of the greatest controversies in modern statistcal thought.

Eighteen leading philosophers offer critical assessments of Timothy Williamson's ground-breaking work on knowledge and its impact on philosophy today. They discuss epistemological issues concerning evidence, defeasibility, scepticism, testimony, assertion, and perception, and debate Williamson's central claim that knowledge is a mental state.

Degrees of belief; Dempster's rule of combination; Simple and separable support functions; The weights of evidence; Compatible frames of discernment; Support functions; The discernment of evidence; Quasi support functions; Consonance; Statistical evidence; The dual nature of probable reasoning.

Sherrilyn Roush defends a new theory of knowledge and evidence, based on the idea of "tracking" the truth, as the best approach to a wide range of questions about knowledge-related phenomena. The theory explains, for example, why scepticism is frustrating, why knowledge is power, and why better evidence makes you more likely to have knowledge. Tracking Truth provides a unification of the concepts of knowledge and evidence, and argues against traditional epistemological realist and anti-realist positions about scientific theories and for (...) a piecemeal approach based on a criterion of evidence, a position Roush calls "real anti-realism." Epistemologists and philosophers of science will recognize this as a significant original contribution. (shrink)

'Knowledge and its Limits' starts its exposition of the knowledge-first approach to epistemology with a structural analogy between knowledge and action as the two key relations between mind and world (Williamson 2000: 1, 6-8). This chapter aims to reconsider the relation between knowledge and action, and refine the analogy.