Brian Weatherson

Recently, Timothy Williamson has argued that considerations about margins of errors can generate a new class of cases where agents have justified true beliefs without knowledge. I think this is a great argument, and it has a number of interesting philosophical conclusions. In this note I’m going to go over the assumptions of Williamson’s argument. I’m going to argue that the assumptions which generate the justification without knowledge are true. I’m then going to go over some of the recent arguments in epistemology that are refuted by Williamson’s work. And I’m going to end with an admittedly inconclusive discussion of what we can know when using an imperfect measuring device.

Many writers have held that in his later work, David Lewis adopted a theory of predicate meaning such that the meaning of a predicate is the most natural property that is (mostly) consistent with the way the predicate is used. That orthodox interpretation is shared by both supporters and critics of Lewis's theory of meaning, but it has recently been strongly criticised by Wolfgang Schwarz. In this paper, I accept many of Schwarze's criticisms of the orthodox interpretation, and add some more. But I also argue that the orthodox interpretation has a grain of truth in it, and seeing that helps us appreciate the strength of Lewis's late theory of meaning.

The arguments for Bayesianism in the literature fall into three broad categories. There are Dutch Book arguments, both of the traditional pragmatic variety and the modern ‘depragmatised’ form. And there are arguments from the so-called ‘representation theorems’. The arguments have many similarities, for example they have a common conclusion, and they all derive epistemic constraints from considerations about coherent preferences, but they have enough differences to produce hostilities between their proponents. In a recent paper, Maher (1997) has argued that the pragmatised Dutch Book arguments are unsound and the depragmatised Dutch Book arguments question begging. He urges we instead use the representation theorem argument as in his (1993). In this paper I argue that Maher’s own argument is question-begging, though in a more subtle and interesting way than his Dutch Book wielding opponents.

This paper is about three of the most prominent debates in modern epistemology. The conclusion is that three prima facie appealing positions in these debates cannot be held simultaneously. The first debate is scepticism vs anti-scepticism. My conclusions apply to most kinds of debates between sceptics and their opponents, but I will focus on the inductive sceptic, who claims we cannot come to know what will happen in the future by induction. This is a fairly weak kind of scepticism, and I suspect many philosophers who are generally anti-sceptical are attracted by this kind of scepticism. Still, even this kind of scepticism is quite unintuitive. I’m pretty sure I know (1) on the basis of induction. (1) It will snow in Ithaca next winter. Although I am taking a very strong version of anti-scepticism to be intuitively true here, the points I make will generalise to most other versions of scepticism. (Focussing on the inductive sceptic avoids some potential complications that I will note as they arise.) The second debate is a version of rationalism vs empiricism. The kind of rationalist I have in mind accepts that some deeply contingent propositions can be known a priori, and the empiricist I have in mind denies this. Kripke showed that there are contingent propositions that can be known a priori. One example is Water is the watery stuff of our acquaintance. (‘Watery’ is David Chalmers’s nice term for the properties of water by which folk identify it.) All the examples Kripke gave are of propositions that are, to use Gareth Evans’s term, deeply necessary (Evans, 1979). It is a matter of controversy presently just how to analyse Evans’s concepts of deep necessity and contingency, but most of the controversies are over details that are not important right here. I’ll simply adopt Stephen Yablo’s recent suggestion: a proposition is deeply contingent if it could have turned out to be true, and could have turned out to be false (Yablo, 2002)1. Kripke did not provide examples of any deeply contingent propositions knowable a priori, though nothing he showed rules out their existence..

Gordon Belot has recently developed a novel argument against Bayesianism. He shows that there is an interesting class of problems that, intuitively, no rational belief forming method is likely to get right. But a Bayesian agent’s credence, before the problem starts, that she will get the problem right has to be 1. This is an implausible kind of immodesty on the part of Bayesians. My aim is to show that while this is a good argument against traditional, precise Bayesians, the argument doesn’t neatly extend to imprecise Bayesians. As such, Belot’s argument is a reason to prefer imprecise Bayesianism to precise Bayesianism.

I defend normative externalism from the objection that it cannot account for the wrongfulness of moral recklessness. The defence is fairly simple—there is no wrong of moral recklessness. There is an intuitive argument by analogy that there should be a wrong of moral recklessness, and the bulk of the paper consists of a response to this analogy. A central part of my response is that if people were motivated to avoid moral recklessness, they would have to have an unpleasant sort of motivation, what Michael Smith calls “moral fetishism”.

Orthodox Bayesian decision theory requires an agent’s beliefs representable by a real-valued function, ideally a probability function. Many theorists have argued this is too restrictive; it can be perfectly reasonable to have indeterminate degrees of belief. So doxastic states are ideally representable by a set of probability functions. One consequence of this is that the expected value of a gamble will be imprecise. This paper looks at the attempts to extend Bayesian decision theory to deal with such cases, and concludes that all proposals advanced thus far have been incoherent. A more modest, but coherent, alternative is proposed. Keywords: Imprecise probabilities, Arrow’s theorem.