Brian Weatherson

The traditional generality problem for process reliabilism concerns the difficulty in identifying each belief forming process with a particular kind of process. Thatidentification is necessary since individual belief forming processes are typically of many kinds, and those kinds may vary in reliability. I raise a new kind of generality problem, one which turns on the difficulty of identifying beliefs with processes by which they were formed. This problem arises because individual beliefs may be the culmination of overlapping processes of distinct lengths, and these processes may differ in reliability. I illustrate the force of this problem with a discussion of recent work on the bootstrapping problem.

In a recent article, Adam Elga outlines a strategy for “Defeating Dr Evil with Self-Locating Belief”. The strategy relies on an indifference principle that is not up to the task. In general, there are two things to dislike about indifference principles: adopting one normally means confusing risk for uncertainty, and they tend to lead to incoherent views in some ‘paradoxical’ situations. I argue that both kinds of objection can be levelled against Elga’s indifference principle. There are also some difficulties with the concept of evidence that Elga uses, and these create further difficulties for the principle.

Many epistemologists hold that an agent can come to justifiably believe that p is true by seeing that it appears that p is true, without having any antecedent reason to believe that visual impressions are generally reliable. Certain reliabilists think this, at least if the agent’s vision is generally reliable. And it is a central tenet of dogmatism (as described by Pryor (2000) and Pryor (2004)) that this is possible. Against these positions it has been argued (e.g. by Cohen (2005) and White (2006)) that this violates some principles from probabilistic learning theory. To see the problem, let’s note what the dogmatist thinks we can learn by paying attention to how things appear. (The reliabilist says the same things, but we’ll focus on the dogmatist.) Suppose an agent receives an appearance that p, and comes to believe that p. Letting Ap be the proposition that it appears to the agent that p, and → be the material implication, we can say that the agent learns that p, and hence is in a position to infer Ap → p, once they receive the evidence Ap.1 This is surprising, because we can prove the following.

Thomas Blackson argues that interest-relative epistemologies cannot explain the irrationality of certain choices when the agent has three possible options. I argue that his examples only refute a subclass of interest-relative theories. In particular, they are good objections to theories that say that what an agent knows depends on the stakes involved in the gambles that she faces. But they are not good objections to theories that say that what an agent knows depends on the odds involved in the gambles that she faces. Indeed, the latter class of theories does a better job than interest-invariant epistemologies of explaining the phenomena he describes.

Over the last two decades, William Lycan’s work on the semantics of conditionals has been distinguished by his careful attention to the connection between syntax and semantics, and more generally by his impeccable methodology. Lycan takes compositionality seriously, so he requires that the meaning of compound expressions like ‘even if’ be a combination of the constituent expressions, here ‘even’ and ‘if’. After reading his work, it’s hard to take seriously work that does not share this methodology.

I argue with my friends a lot. That is, I offer them reasons to believe all sorts of philosophical conclusions. Sadly, despite the quality of my arguments, and despite their apparent intelligence, they don’t always agree. They keep insisting on principles in the face of my wittier and wittier counterexamples, and they keep offering their own dull alleged counterexamples to my clever principles. What is a philosopher to do in these circumstances? (And I don’t mean get better friends.) One popular answer these days is that I should, to some extent, defer to my friends. If I look at a batch of reasons and conclude p, and my equally talented friend reaches an incompatible conclusion q, I should revise my opinion so I’m now undecided between p and q. I should, in the preferred lingo, assign equal weight to my view as to theirs. This is despite the fact that I’ve looked at their reasons for concluding q and found them wanting. If I hadn’t, I would have already concluded q. The mere fact that a friend (from now on I’ll leave off the qualifier ‘equally talented and informed’, since all my friends satisfy that) reaches a contrary opinion should be reason to move me. Such a position is defended by Richard Feldman (2006a, 2006b), David Christensen (2007) and Adam Elga (forthcoming). This equal weight view, hereafter EW, is itself a philosophical position. And while some of my friends believe it, some of my friends do not. (Nor, I should add for your benefit, do I.) This raises an odd little dilemma. If EW is correct, then the fact that my friends disagree about it means that I shouldn’t be particularly confident that it is true, since EW says that I shouldn’t be too confident about any position on which my friends disagree. But, as I’ll argue below, to consistently implement EW, I have to be maximally confident that it is true. So to accept EW, I have to inconsistently both be very confident that it is true and not very confident that it is true. This seems like a problem, and a reason to not accept EW..

Recently four different papers have suggested that the supervaluational solution to the Problem of the Many is flawed. Stephen Schiffer (1998, 2000a, 2000b) has argued that the theory cannot account for reports of speech involving vague singular terms. Vann McGee and Brian McLaughlin (2000) say that theory cannot, yet, account for vague singular beliefs. Neil McKinnon (2002) has argued that we cannot provide a plausible theory of when precisifications are acceptable, which the supervaluational theory needs. And Roy Sorensen (2000) argues that supervaluationism is inconsistent with a directly referential theory of names. McGee and McLaughlin see the problem they raise as a cause for further research, but the other authors all take the problems they raise to provide sufficient reasons to jettison supervaluationism. I will argue that none of these problems provide such a reason, though the arguments are valuable critiques. In many cases, we must make some adjustments to the supervaluational theory to meet the posed challenges. The goal of this paper is to make those adjustments, and meet the challenges.

In “A Reliabilist Solution to the Problem of Promiscuous Bootstrapping”, Hilary Kornblith (2009) proposes a reliabilist solution to the bootstrapping problem. I’m going to argue that Kornblith’s proposal, far from solving the bootstrapping problem, in fact makes the problem much harder for the reliabilist to solve. Indeed, I’m going to argue that Kornblith’s considerations give us a way to develop a quick reductio of a certain kind of reliabilism. Let’s start with a crude statement of the problem. The bootstrapper, call them S, looks at a device D1 that happens to be reliable, though at this stage S doesn’t know this. We assume that S is a reliable reader of devices. S then draws the following conclusions.

Uncertainty plays an important role in The General Theory, particularly in the theory of interest rates. Keynes did not provide a theory of uncertainty, but he did make some enlightening remarks about the direction he thought such a theory should take. I argue that some modern innovations in the theory of probability allow us to build a theory which captures these Keynesian insights. If this is the right theory, however, uncertainty cannot carry its weight in Keynes’s arguments. This does not mean that the conclusions of these arguments are necessarily mistaken; in their best formulation they may succeed with merely an appeal to risk.

An important tradition in metaphysics takes its job to be finding a limited number of ingredients with which we can tell the complete story of the world (or some subject matter). Physicalism, for example, claims that the list of ingredients sufficient to tell the complete story about the very small, or about the non-sentient, is sufficient to tell the complete story about all of the world. Some people take the moral of this kind of metaphysics to be eliminativist; that we can tell the complete story of the world without meanings, or inflations, shows that meaning and inflation do not exist. Most people are not so blasé about rejecting commonsense opinions. Inflations, wars, rivers and beliefs all exist, but there is nothing but atoms in the void, so we must find a way of showing that the arrangement of atoms in the void makes true the stories about inflations and so on

Call Justificatory Probabilism (hereafter, JP) the thesis that there is some (classical) probability function Pr such that for an agent S with evidence E, the degree to which they are justified in believing a hypothesis H is given by Pr(H|E). As stated, the thesis is fairly ambiguous, though none of the disambiguations are obviously true. Indeed, several of them are obviously false. If JP is a thesis about how justified agents are in fully believing propositions, it is trivially false. I’m about to flip a penny. Call H the proposition that it will land heads. Right now I’m completely unjustified in believing either H or ¬H . Yet according to JP, at least one of them must be half-justified

We generalize the Kolmogorov axioms for probability calculus to obtain conditions defining, for any given logic, a class of probability functions relative to that logic, coinciding with the standard probability functions in the special case of classical logic but allowing consideration of other classes of "essentially Kolmogorovian" probability functions relative to other logics. We take a broad view of the Bayesian approach as dictating inter alia that from the perspective of a given logic, rational degrees of belief are those representable by probability functions from the class appropriate to that logic. Classical Bayesianism, which fixes the logic as classical logic, is only one version of this general approach. Another, which we call Intuitionistic Bayesianism, selects intuitionistic logic as the preferred logic and the associated class of probability functions as the right class of candidate representions of epistemic states (rational allocations of degrees of belief). Various objections to classical Bayesianism are, we argue, best met by passing to intuitionistic Bayesianism—in which the probability functions are taken relative to intuitionistic logic—rather than by adopting a radically non-Kolmogorovian, for example, nonadditive, conception of (or substitute for) probability functions, in spite of the popularity of the latter response among those who have raised these objections. The interest of intuitionistic Bayesianism is further enhanced by the availability of a Dutch Book argument justifying the selection of intuitionistic probability functions as guides to rational betting behavior when due consideration is paid to the fact that bets are settled only when/if the outcome bet on becomes known