In days past, epistemologists expended a good deal of effort trying to analyze the basing relation—the relation between a belief and its basis. No satisfying account was offered, and the project was largely abandoned. Younger epistemologists, however, have begun to yearn for an adequate theory of basing. I aim to deliver one. After establishing some data and arguing that traditional accounts of basing are unsatisfying, I introduce a novel theory of the basing relation: the dispositional theory. It begins with the (...) pedestrian observation that beliefs stand or fall with their bases. The theory I offer is an elucidation and refinement of this thought. (shrink)
Introductions to the theory of knowledge are plentiful, but none introduce students to the most recent debates that exercise contemporary philosophers. Ian Evans and Nicholas D. Smith aim to change that. Their book guides the reader through the standard theories of knowledge while simultaneously using these as a springboard to introduce current debates. Each chapter concludes with a “Current Trends” section pointing the reader to the best literature dominating current philosophical discussion. These include: the puzzle of reasonable disagreement; the so-called (...) “problem of easy knowledge”; the intellectual virtues; and new theories in the philosophy of language relating to knowledge. Chapters include discussions of skepticism, the truth condition, belief and acceptance, justification, internalism versus externalism, epistemic evaluation, and epistemic contextualism. Evans and Smith do not merely offer a review of existing theories and debates; they also offer a novel theory that takes seriously the claim that knowledge is not unique to humans. Surveying current scientific literature in animal ethology, they discover surprising sophistication and diversity in non-human cognition. In their final analysis the authors provide a unified account of knowledge that manages to respect and explain this diversity. They argue that animals know when they make appropriate use of the cognitive processes available to animals of that kind, in environments within which those processes are veridically well-adapted. _Knowledge_ is a lively and accessible volume, ideal for undergraduate and post-graduate students. It is also set to spark debate among scholars for its novel approaches to traditional topics and its thoroughgoing commitment to naturalism. (shrink)
Jonathan Schaffer (2010) has summoned a new sort of demon – which he calls the debasing demon – that apparently threatens all of our purported knowledge. We show that any debasing skeptical argument must attack the justification condition and can do so only if a plausible thesis about justification is false.
Bayesians take “definite” or “single-case” probabilities to be basic. Definite probabilities attach to closed formulas or propositions. We write them here using small caps: PROB(P) and PROB(P/Q). Most objective probability theories begin instead with “indefinite” or “general” probabilities (sometimes called “statistical probabilities”). Indefinite probabilities attach to open formulas or propositions. We write indefinite probabilities using lower case “prob” and free variables: prob(Bx/Ax). The indefinite probability of an A being a B is not about any particular A, but rather about the (...) property of being an A. In this respect, its logical form is the same as that of relative frequencies. For instance, we might talk about the probability of a human baby being female. That probability is about human babies in general — not about individuals. If we examine a baby and determine conclusively that she is female, then the definite probability of her being female is 1, but that does not alter the indefinite probability of human babies in general being female. Most objective approaches to probability tie probabilities to relative frequencies in some way, and the resulting probabilities have the same logical form as the relative frequencies. That is, they are indefinite probabilities. The simplest theories identify indefinite probabilities with relative frequencies.3 It is often objected that such “finite frequency theories” are inadequate because our probability judgments often diverge from relative frequencies. For example, we can talk about a coin being fair (and so the indefinite probability of a flip landing heads is 0.5) even when it is flipped only once and then destroyed (in which case the relative frequency is either 1 or 0). For understanding such indefinite probabilities, it has been suggested that we need a notion of probability that talks about possible instances of properties as well as actual instances.. (shrink)