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Res Philosophica

Volume 94, Issue 2, April 2017
Special Conference Issue: Bridging Formal and Traditional Epistemology

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Displaying: 1-6 of 6 documents

1. Res Philosophica: Volume > 94 > Issue: 2
Kenny Easwaran

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Belief and credence are often characterized in three different ways—they ought to govern our actions, they ought to be governed by our evidence, and they ought to aim at the truth. If one of these roles is to be central, we need to explain why the others should be features of the same mental state rather than separate ones. If multiple roles are equally central, then this may cause problems for some traditional arguments about what belief and credence must be like. I read the history of formal and traditional epistemology through the lens of these functional roles, and suggest that considerations from one literature might have a role in the other. The similarities and differences between these literatures may suggest some more general ideas about the nature of epistemology in abstraction from the details of credence and belief in particular.

2. Res Philosophica: Volume > 94 > Issue: 2
Alan Hájek, Hanti Lin

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So-called “traditional epistemology” and “Bayesian epistemology” share a word, but it may often seem that the enterprises hardly share a subject matter. They differ in their central concepts. They differ in their main concerns. They differ in their main theoretical moves. And they often differ in their methodology.However, in the last decade or so, there have been a number of attempts to build bridges between the two epistemologies. Indeed, many would say that there is just one branch of philosophy here—epistemology. There is a common subject matter after all.In this paper, we begin by playing the role of a “bad cop,” emphasizing many apparent points of disconnection, and even conflict, between the approaches to epistemology. We then switch role, playing a “good cop” who insists that the approaches are engaged in common projects after all. We look at various ways in which the gaps between them have been bridged, and we consider the prospects for bridging them further. We conclude that this is an exciting time for epistemology, as the two traditions can learn, and have started learning, from each other.

3. Res Philosophica: Volume > 94 > Issue: 2
Terry Horgan

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I raise skeptical doubts about the prospects of Bayesian formal epistemology for providing an adequate general normative model of epistemic rationality. The notion of credence, I argue, embodies a very dubious psychological myth, viz., that for virtually any proposition p that one can entertain and understand, one has some quantitatively precise, 0-to-1 ratio-scale, doxastic attitude toward p. The concept of credence faces further serious problems as well—different ones depending on whether credence 1 is construed as full belief (the limit case of so-called partial belief) or instead is construed as absolute certainty. I argue that the notion of an “ideal Bayesian reasoner” cannot serve as a normative ideal that actual human agents should seek to emulate as closely as they can, because different such reasoners who all have the same evidence as oneself—no single one them being uniquely psychologically most similar to oneself—will differ from one another in their credences (e.g., because they commence from different prior credences). I argue that epistemic probability, properly understood, is quantitative degree of evidential support relative to one’s evidence, and that principled epistemic probabilities arise only under quite special evidential circumstances—which means that epistemic probability is ill suited to figure centrally within general norms of human epistemic rationality.

4. Res Philosophica: Volume > 94 > Issue: 2
Susanna Rinard

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There is a trade-off between specificity and accuracy in accounts of belief. Descriptions of agents in the tripartite account, which recognizes three doxastic attitudes—belief, disbelief, and suspension—are accurate, but not specific. The orthodox Bayesian account, which requires real-valued credences, is specific, but often inaccurate. I argue that a popular attempt to fix the Bayesian account by using sets of functions is also inaccurate; it suffers from a problem analogous to higher order vagueness. Ultimately, I argue, the only way to avoid these problems is to endorse a principle with the surprising consequence that the trade-off between accuracy and specificity is in-principle unavoidable. However, we can nonetheless improve on both the tripartite and existing Bayesian accounts. I construct a new framework that allows descriptions that are much more specific than those of the tripartite account and yet remain, unlike existing Bayesian accounts, perfectly accurate.

5. Res Philosophica: Volume > 94 > Issue: 2
Sherri Roush Orcid-ID

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Deduction is important to scientific inquiry because it can extend knowledge efficiently, bypassing the need to investigate everything directly. The existence of closure failure—where one knows the premises and that the premises imply the conclusion but nevertheless does not know the conclusion—is a problem because it threatens this usage. It means that we cannot trust deduction for gaining new knowledge unless we can identify such cases ahead of time so as to avoid them. For philosophically engineered examples we have “inner alarm bells” to detect closure failure, but in scientific investigation we would want to use deduction for extension of our knowledge to matters we don’t already know that we couldn’t know. Through a quantitative treatment of how fast probabilistic sensitivity is lost over steps of deduction, I identify a condition that guarantees that the growth of potential error will be gradual; thus, dramatic closure failure is avoided. Whether the condition is fulfilled is often obvious, but sometimes it requires substantive investigation. I illustrate that not only safe deduction but the discovery of dramatic closure failures can lead to scientific advances.

6. Res Philosophica: Volume > 94 > Issue: 2
Julia Staffel

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Ideal agents are role models whose perfection in some normative domain we try to approximate. But which form should this striving take? It is well known that following ideal rules of practical reasoning can have disastrous results for non-ideal agents. Yet, this issue has not been explored with respect to rules of theoretical reasoning. I show how we can extend Bayesian models of ideally rational agents in order to pose and answer the question of whether non-ideal agents should form new degrees of belief in the same way as their ideal counterparts. I demonstrate that the epistemic and the practical case are parallel: following ideal rules does not always lead to optimal outcomes for non-ideal agents.