Science is the study of our world, as it is in its messy reality. Nonetheless, science requires idealization to function—if we are to attempt to understand the world, we have to find ways to reduce its complexity. Idealization and the Aims of Science shows just how crucial idealization is to science and why it matters. Beginning with the acknowledgment of our status as limited human agents trying to make sense of an exceedingly complex world, Angela Potochnik moves on to explain (...) how science aims to depict and make use of causal patterns—a project that makes essential use of idealization. She offers case studies from a number of branches of science to demonstrate the ubiquity of idealization, shows how causal patterns are used to develop scientific explanations, and describes how the necessarily imperfect connection between science and truth leads to researchers’ values influencing their findings. The resulting book is a tour de force, a synthesis of the study of idealization that also offers countless new insights and avenues for future exploration. (shrink)

In my remarks, I discuss Sosa's attempt to deal with the sceptical threat posed by dreaming. Sosa explores two replies to the problem of dreaming scepticism. First, he argues that, on the imagination model of dreaming, dreaming does not threaten the safety of our beliefs. Second, he argues that knowledge does not require safety, but a weaker condition which is not threatened by dreaming skepticism. I raise questions about both elements of his reply.

Ernest Sosa's A Virtue Epistemology, Vol. I is arguably the single-most important monograph to be published in analytic epistemology in the last ten years. Sosa, the first in the field to employ the notion of intellectual virtue – in his ground-breaking ‘The Raft and the Pyramid’– is the leading proponent of reliabilist versions of virtue epistemology. In A Virtue Epistemology, he deftly defends an externalist account of animal knowledge as apt belief, argues for a distinction between animal and reflective knowledge, (...) contends that rational intuition is an intellectual virtue ; and offers responses to dream scepticism, the problem of the criterion and the value problem. Nearly all of these arguments are new, albeit consistent with Sosa's earlier work; that is, consistent with two notable exceptions. First, c ontra Sosa's ‘Replies’ in Ernest Sosa and His Critics, A Virtue Epistemology explicitly contends that safety is not required for animal knowledge. Second, unlike Sosa's Knowledge in Perspective, which arguably construes the intellectual virtues as merely instrumentally valuable, A Virtue Epistemology explicitly contends that the intellectual virtues are instrumentally and constitutively valuable. Best read in conjunction with the above monographs and Epistemic Justification, A Virtue Epistemology is mandatory reading for epistemologists and graduate students in the field. It will rightly set the standard for debates in analytic epistemology for years to come.I will summarize and raise objections to two key conclusions that are unique to A Virtue Epistemology: the ‘kaleidoscope-perceiver’ has animal knowledge but lacks reflective knowledge; unlike the k-perceiver, the ordinary perceiver has reflective knowledge. My objections …. (shrink)

I argue that understanding why p involves a kind of intellectual know how and differsfrom both knowledge that p and knowledge why p (as they are standardly understood).I argue that understanding, in this sense, is valuable.

What does it mean to understand something? What types of understanding can be distinguished? Is understanding always provided by explanations? And how is it related to knowledge? Such questions have attracted considerable interest in epistemology recently. These discussions, however, have not yet engaged insights about explanations and theories developed in philosophy of science. Conversely, philosophers of science have debated the nature of explanations and theories, while dismissing understanding as a psychological by-product. In this book, epistemologists and philosophers of science together (...) address basic questions about the nature of understanding, providing a new overview of the field. False theories, cognitive bias, transparency, coherency, and other important issues are discussed. Its 15 original chapters are essential reading for researchers and graduate students interested in the current debates about understanding. (shrink)

Achieving understanding of nature is one of the aims of science. In this paper we offer an analysis of the nature of scientific understanding that accords with actual scientific practice and accommodates the historical diversity of conceptions of understanding. Its core idea is a general criterion for the intelligibility of scientific theories that is essentially contextual: which theories conform to this criterion depends on contextual factors, and can change in the course of time. Our analysis provides a general account of (...) how understanding is provided by scientific explanations of diverse types. In this way, it reconciles conflicting views of explanatory understanding, such as the causal-mechanical and the unificationist conceptions. (shrink)

Epistemology has for a long time focused on the concept of knowledge and tried to answer questions such as whether knowledge is possible and how much of it there is. Often missing from this inquiry, however, is a discussion on the value of knowledge. In The Value of Knowledge and the Pursuit of Understanding Jonathan Kvanvig argues that epistemology properly conceived cannot ignore the question of the value of knowledge. He also questions one of the most fundamental assumptions in epistemology, (...) namely that knowledge is always more valuable than the value of its subparts. Taking Platos' Meno as a starting point of his discussion, Kvanvig tackles the different arguments about the value of knowledge and comes to the conclusion that knowledge is less valuable than generally assumed. Clearly written and well argued, this 2003 book will appeal to students and professionals in epistemology. (shrink)

Bas C. van Fraassen presents an original exploration of how we represent the world.

I explore the extent to which the epistemic state of understanding is transparent to the one who understands. Against several contemporary epistemologists, I argue that it is not transparent in the way that many have claimed, drawing on results from developmental psychology, animal cognition, and other fields.

Bayesianism is a collection of positions in several related fields, centered on the interpretation of probability as something like degree of belief, as contrasted with relative frequency, or objective chance. However, Bayesianism is far from a unified movement. Bayesians are divided about the nature of the probability functions they discuss; about the normative force of this probability function for ordinary and scientific reasoning and decision making; and about what relation (if any) holds between Bayesian and non-Bayesian concepts.

What is it to know more? By what metric should the quantity of one's knowledge be measured? I start by examining and arguing against a very natural approach to the measure of knowledge, one on which how much is a matter of how many. I then turn to the quasi-spatial notion of counterfactual distance and show how a model that appeals to distance avoids the problems that plague appeals to cardinality. But such a model faces fatal problems of its own. (...) Reflection on what the distance model gets right and where it goes wrong motivates a third approach, which appeals not to cardinality, nor to counterfactual distance, but to similarity. I close the paper by advocating this model and briefly discussing some of its significance for epistemic normativity. In particular, I argue that the 'trivial truths' objection to the view that truth is the goal of inquiry rests on an unstated, but false, assumption about the measure of knowledge, and suggest that a similarity model preserves truth as the aim of belief in an intuitively satisfying way. (shrink)

In this paper, I propose that the debate in epistemology concerning the nature and value of understanding can shed light on the role of scientific idealizations in producing scientific understanding. In philosophy of science, the received view seems to be that understanding is a species of knowledge. On this view, understanding is factive just as knowledge is, i.e., if S knows that p, then p is true. Epistemologists, however, distinguish between different kinds of understanding. Among epistemologists, there are those who (...) think that a certain kind of understanding—objectual understanding—is not factive, and those who think that objectual understanding is quasi-factive. Those who think that understanding is not factive argue that scientific idealizations constitute cognitive success, which we then consider as instances of understanding, and yet they are not true. This paper is an attempt to draw lessons from this debate as they pertain to the role of idealizations in producing scientific understanding. I argue that scientific understanding is quasi-factive. (shrink)

Approaches to explanation -- Causal and explanatory relevance -- The kairetic account of /D making -- The kairetic account of explanation -- Extending the kairetic account -- Event explanation and causal claims -- Regularity explanation -- Abstraction in regularity explanation -- Approaches to probabilistic explanation -- Kairetic explanation of frequencies -- Kairetic explanation of single outcomes -- Looking outward -- Looking inward.

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)

Among philosophers of science there seems to be a general consensus that understanding represents a species of knowledge, but virtually every major epistemologist who has thought seriously about understanding has come to deny this claim. Against this prevailing tide in epistemology, I argue that understanding is, in fact, a species of knowledge: just like knowledge, for example, understanding is not transparent and can be Gettiered. I then consider how the psychological act of "grasping" that seems to be characteristic of understanding (...) differs from the sort of psychological act that often characterizes knowledge. Zagzebski's account Kvanvig's account Two problems Comanche cases Unreliable sources of information The upper-right quadrant So is understanding a species of knowledge? A false choice. (shrink)

Thought experiments in science are merely picturesque argumentation. I support this view in various ways, including the claim that it follows from the fact that thought experiments can err but can still be used reliably. The view is defended against alternatives proposed by my cosymposiasts.

Truth is standardly considered a requirement on epistemic acceptability. But science and philosophy deploy models, idealizations and thought experiments that prescind from truth to achieve other cognitive ends. I argue that such felicitous falsehoods function as cognitively useful fictions. They are cognitively useful because they exemplify and afford epistemic access to features they share with the relevant facts. They are falsehoods in that they diverge from the facts. Nonetheless, they are true enough to serve their epistemic purposes. Theories that contain (...) them have testable consequences, hence are factually defeasible. (shrink)

If understanding is factive, the propositions that express an understanding are true. I argue that a factive conception of understanding is unduly restrictive. It neither reflects our practices in ascribing understanding nor does justice to contemporary science. For science uses idealizations and models that do not mirror the facts. Strictly speaking, they are false. By appeal to exemplification, I devise a more generous, flexible conception of understanding that accommodates science, reflects our practices, and shows a sufficient but not slavish sensitivity (...) to the facts. (shrink)

Scientific reasoning is—and ought to be—conducted in accordance with the axioms of probability. This Bayesian view—so called because of the central role it accords to a theorem first proved by Thomas Bayes in the late eighteenth ...

Science relies on models and idealizations that are known not to be true. Even so, science is epistemically reputable. To accommodate science, epistemology should focus on understanding rather than knowledge and should recognize that the understanding of a topic need not be factive. This requires reconfiguring the norms of epistemic acceptability. If epistemology has the resources to accommodate science, it will also have the resources to show that art too advances understanding.

Da Costa and French explore the consequences of adopting a 'pragmatic' notion of truth in the philosophy of science. Their framework sheds new light on issues to do with belief, theory acceptance, and the realism-antirealism debate, as well as the nature of scientific models and their heuristic development.

Inquiries into the nature of scientific modeling have tended to focus their attention on mathematical models and, relatedly, to think of nonconcrete models as mathematical structures. The arguments of this article are arguments for rethinking both tendencies. Nonmathematical models play an important role in the sciences, and our account of scientific modeling must accommodate that fact. One key to making such accommodations, moreover, is to recognize that one kind of thing we use the term ‘model’ to refer to is a (...) collection of propositions. (shrink)