Brian Weatherson

There is a lot that we don't know. That means that there are a lot of possibilities that are, epistemically speaking, open. For instance, we don't know whether it rained in Seattle yesterday. So, for us at least, there is an epistemic possibility where it rained in Seattle yesterday, and one where it did not. What are these epistemic possibilities? They do not match up with metaphysical possibilities - there are various cases where something is epistemically possible but not metaphysically possible, and vice versa. How do we understand the semantics of statements of epistemic modality? The ten new essays in this volume explore various answers to these questions, including those offered by contextualism, relativism, and expressivism.

We have some of our properties purely in virtue of the way we are. (Our mass is an example.) We have other properties in virtue of the way we interact with the world. (Our weight is an example.) The former are the intrinsic properties, the latter are the extrinsic properties. This seems to be an intuitive enough distinction to grasp, and hence the intuitive distinction has made its way into many discussions in philosophy, including discussions in ethics, philosophy of mind, metaphysics, epistemology and philosophy of physics. Unfortunately, when we look more closely at the intuitive distinction, we find reason to suspect that it conflates a few related distinctions, and that each of these distinctions is somewhat resistant to analysis.

This paper has three aims. First, I’ll argue that there’s no good reason to accept any kind of ‘easy knowledge’ objection to externalist foundationalism. It might be a little surprising that we can come to know that our perception is accurate by using our perception, but any attempt to argue this is impossible seems to rest on either false premises or fallacious reasoning. Second, there is something defective about using our perception to test whether our perception is working. What this reveals is that there are things we aim for in testing other than knowing that the device being tested is working. I’ll suggest that testing aims for sensitive knowledge that the device is working. Testing a device, such as our perceptual system, by using its own outputs may deliver knowledge, but it can’t deliver sensitive knowledge. So it’s a bad way to test the system. The big conclusion here is that sensitivity is an important epistemic virtue, although it is not necessary for knowledge. Third, I’ll argue that the idea that sensitivity is an epistemic virtue can provide a solution to a tricky puzzle about inductive evidence. This provides another reason for thinking that the conclusion of section two is correct: not all epistemic virtues are to do with knowledge

Over the years I’ve written many papers defending an idiosyncratic version of interest-relative epistemology. This book collects and updates the views I’ve expressed over those papers. Interest-relative epistemologies all start in roughly the same way. A big part of what makes knowledge important is that it rationalises action. But for almost anything we purportedly know, there is some action that it wouldn’t rationalise. I know what I had for breakfast, but I wouldn’t take a bet at billion to one odds about it. Knowledge has practical limits. The first idiosyncratic feature of my version of interest-relative epistemology is how those limits are identified. Other interest-relative philosophers typically say that the limits have to do with stakes; in high stakes situations knowledge goes away. That’s no part of my view. I think knowledge goes away in long odds situations. High stakes situations are almost always are long odds situations, for reasons to do with the declining marginal utility of money. But the converse isn’t true. On my view, knowledge often goes away in cases where it is trivial to check before action. This idea, that interests matter in long odds cases, and not just in high stakes cases, is the main constant in what I’ve written on interest-relativity over the years. But there are three other respects in which the view I’m going to set out and defend in this book is very different from the view I set out in older papers. I used to identify the practical limits on knowledge with cases where relying on the purported knowledge would get the wrong answer. I focused, that is, on the outputs of inquiry. Knowledge goes away if relying on it would lead one to make a mistake. I now think I was looking at the wrong end of inquiry. Knowledge goes away if the thinker starts conducting an inquiry where the purported knowledge is an inappropriate starting point, and inappropriate for the special reason that it might be false. Now one way we can tell that something is a bad starting point is that starting there will mean we end up at the wrong place. But it’s not the only way. Sometimes a bad starting point will lead to the right conclusion for the wrong reasons. As the Nyāya philosophers argued, rational inquiry starts with knowledge. If it would be irrational to start this inquiry with a particular belief, that belief isn’t knowledge. Not all inquiries are practical inquiries, but many are. And practical inquiries are usually going to be at the center of attention in this book. But what is someone trying to figure out when they conduct a practical inquiry? I used to think that they were trying to figure out which option maximised expected utility, and to a first approximation identified knowledge with those things one could conditionalise on without changing the option that maximised expected utility. As noted in the previous paragraph, I no longer think that we can identify knowledge with what doesn’t change our verdicts. But more importantly, I no longer think that expected utility maximisation is as central to practical inquiry as I once did. There are some theoretical reasons from game theory that raise some doubts about expected utility maximisation. Weak dominance reasoning is part of our theory of rational choice, and can’t be modelled as expected utility maximisation. Perhaps some kinds of equilibrium seeking are parts of practical inquiry, and can’t be modelled as expected utility maximisation. But there are also very practical reasons to think that practical inquiry doesn’t aim at expected utility maximisation. When there are a lot of very similar options - think about selecting a can from a supermarket shelf - and it’s more trouble than it’s worth to figure out which of them maximises expected utility, it’s best to ignore the differences between them and just pick. As I’ll argue in Chapter 6, this makes a big difference to how interests and knowledge interact. In the version of interest-relativity that I’m defending here, everything in epistemology is interest-relative. Knowledge, rational belief, and evidence are all interest-relative. But they are all interest-relative in slightly different ways. The main aim here is to defend the interest-relativity of knowledge. A common objection to interest-relative theories of knowledge is that they can’t be extended into theories of all the things we care about in epistemology. Here I try to meet that challenge. The way I do so is a little messy. It would be nice if there was some part of epistemology that’s interest-invariant, as I used to think, or if all the interest-relative notions were interest-relative in the same way, as other interest-relative epistemologists argue. For better or worse, that’s not the view I’m defending. Interests matter throughout epistemology, and we just have to go case by case to figure out how and why they matter.

Lewis Carroll’s 1895 paper “Achilles and the Tortoise” showed that we need a distinction between rules of inference and premises. We cannot, on pain of regress, treat all rules simply as further premises in an argument. But Carroll’s paper doesn’t say very much about what rules there must be. Indeed, it is consistent with what Carroll says there to think that the only rule is -elimination. You might think that modern Bayesians, who seem to think that the only rule of inference they need is conditionalisation, have taken just this lesson from Carroll. But obviously nothing in Carroll’s argument rules out there being other rules as well.

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.

This collection arose out of a conference on intuitions at the University of Notre Dame in April 1996. The papers in it mainly address two related questions: (a) How much evidential weight should be assigned to intuitions? and (b) Are concepts governed by necessary and sufficient conditions, or are they governed by ‘family resemblance’ conditions, as Wittgenstein suggested? The book includes four papers by psychologists relating and analyzing some empirical findings concerning intuitions and eleven papers by philosophers endorsing various answers to these questions.

The only part of the Patient Protection and Affordable Care Act (hereafter, ‘the ACA’) struck down in National Federation of Independent Business (NFIB) et al. v. Sebelius, Secretary of Health and Human Services, et al. was a provision expanding Medicaid. We will argue that this was a mistake; the provision should not have been struck down. We’ll do this by identifying a test that C.J. Roberts used to justify his view that this provision was unconstitutional. We’ll defend that test against some objections raised by J. Ginsburg. We’ll then go on to argue that, properly applied, that test establishes the constitutionality of the Medicaid provision

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.

One of the benefits of the 2D framework we looked at last week was that it explained how we could understand a sentence without knowing which proposition it expressed. And we could do this even if we give an account of understanding which is closely tied to the possible worlds semantics we use to analyse propositions. Really this can be done very easily, without appeal to any high-flying Kripkean cases. In “Analytic Metaphysics” Jackson discusses a very simple case of it. I can understand an utterance of “I have a beard” without knowing which proposition it expresses. I know how the proposition is generated from context plus meaning, if X is the speaker then the sentence expresses the proposition X has a beard. And that is enough for understanding. But if I don’t know who said the sentence, so I don’t know who X is, I don’t know which proposition is expressed by that utterance

This dissertation looks at a set of interconnected questions concerning the foundations of probability, and gives a series of interconnected answers. At its core is a piece of old-fashioned philosophical analysis, working out what probability is. Or equivalently, investigating the semantic question of what is the meaning of ‘probability’? Like Keynes and Carnap, I say that probability is degree of reasonable belief. This immediately raises an epistemological question, which degrees count as reasonable? To solve that in its full generality would mean the end of human inquiry, so that won’t be attempted here. Rather I will follow tradition and merely investigate which sets of partial beliefs are coherent. The standard answer to this question, what is commonly called the Bayesian answer, says that degrees of belief are coherent iff they form a probability function. I disagree with the way this is usually justified, but subject to an important qualification I accept the answer. The important qualification is that degrees of belief may be imprecise, or vague. Part one of the dissertation, chapters 1 to 6, looks largely at the consequences of this qualification for the semantic and epistemological questions already mentioned. It turns out that when we allow degrees of belief to be imprecise, we can discharge potentially fatal objections to some philosophically attractive theses. Two of these, that probability is degree of reasonable belief and that the probability calculus provides coherence constraints on partial beliefs, have been mentioned. Others include the claim, defended in chapter 4, that chance is probability given total history. As well as these semantic and epistemological questions, studies of the foundations of probability usually include a detailed discussion of decision theory. For reasons set out in chapter 2, I deny we can gain epistemological insights from decision theory. Nevertheless, it is an interesting field to study on its own, and it might be expected that there would be decision theoretic consequences of allowing imprecise degrees of belief. As I show in part two, this expectation seems to be mistaken. Chapter 9 shows that there aren’t interesting consequences of this theory for decision theory proper, and chapters 10 and 11 show that Keynes’s attempt to use imprecision in degrees of belief to derive a distinctive theory of interest rates is unsound. Chapters 7 and 8 provide a link between these two parts. In chapter 7 I look at some previous philosophical investigations into the effects of imprecision. In chapter 8 I develop what I take to be the best competitor to the theory defended here – a constructivist theory of probability. On this view degrees of belief are precise, but the relevant coherence constraint is a constructivist probability calculus. This view is, I think, mistaken, but the calculus has some intrinsic interest, and there are at least enough arguments for it to warrant a chapter-length examination.

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.

As anyone who has flown out of a cloud knows, the boundaries of a cloud are a lot less sharp up close than they can appear on the ground. Even when it seems clearly true that there is one, sharply bounded, cloud up there, really there are thousands of water droplets that are neither determinately part of the cloud, nor determinately outside it. Consider any object that consists of the core of the cloud, plus an arbitrary selection of these droplets. It will look like a cloud, and circumstances permitting rain like a cloud, and generally has as good a claim to be a cloud as any other object in that part of the sky. But we cannot say every such object is a cloud, else there would be millions of clouds where it seemed like there was one. And what holds for clouds holds for anything whose boundaries look less clear the closer you look at it. And that includes just about every kind of object we normally think about, including humans. Although this seems to be a merely technical puzzle, even a triviality, a surprising range of proposed solutions has emerged, many of them mutually inconsistent. It is not even settled whether a solution should come from metaphysics, or from philosophy of language, or from logic. Here we survey the options, and provide several links to the many topics related to the Problem.

This paper contributes to the project of articulating and defending the supra-Bayesian approach to judgment aggregation. I discuss three cases where a person is disposed to defer to two different experts, and ask how they should respond when they learn about the opinion of each. The guiding principles are that this learning should go by conditionalisation, and that they should aim to update on the evidence that the expert had updated on. But this doesn’t settle how the update on pairs of experts should go, because we also need to know how the experts are related. I work through three examples showing how the results change given different prior beliefs about this relationship.

Most people who believe in temporal parts believe that the referents of our ordinary referring terms, like Bill Clinton, or that table, are fusions of temporal parts from past, present and future times. Call these fusions worms, and the theory that the referents of ordinary referring terms (ordinary objects) the worm theory. Buying the metaphysical theory of temporal parts does not immediately imply that we must buy the worm theory. Theodore Sider (1996, 2000), for example, has suggested that these ordinary referring terms just pick out a single, instantaneous, temporal part. Sider’s theory, called the stage theory, solves some pressing philosophical problems, including the problem of temporary intrinsics. But the stage theory has several difficulties of its own, especially what I will call the problem of long-term intrinsics. I argue for a rival theory, the growing individuals theory. On this theory, the referents of our ordinary referring terms have past and present temporal parts, but not future temporal parts. This theory best accounts for our intuitions about which intrinsic properties ordinary objects have.

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

Normative Externalism argues that it is not important that people live up to their own principles. What matters, in both ethics and epistemology, is that they live up to the correct principles: that they do the right thing, and that they believe rationally. This stance, that what matters are the correct principles, not one's own principles, has implications across ethics and epistemology. In ethics, it undermines the ideas that moral uncertainty should be treated just like factual uncertainty, that moral ignorance frequently excuses moral wrongdoing, and that hypocrisy is a vice. In epistemology, it suggests we need new treatments of higher-order evidence, and of peer disagreement, and of circular reasoning, and the book suggests new approaches to each of these problems. Although the debates in ethics and in epistemology are often conducted separately, putting them in one place helps bring out their common themes. One common theme is that the view that one should live up to one's own principles looks less attractive when people have terrible principles, or when following their own principles would lead to riskier or more aggressive action than the correct principles. Another common theme is that asking people to live up to their principles leads to regresses. It can be hard to know what action or belief complies with one's principles. And now we can ask, in such a case should a person do what they think their principles require, or what their principles actually require? Both answers lead to problems, and the best way to avoid these problems is to simply say people should follow the correct principles.

Recently several authors have argued that accuracy-first epistemology ends up licensing problematic epistemic bribes. They charge that it is better, given the accuracy-first approach, to deliberately form one false belief if this will lead to forming many other true beliefs. We argue that this is not a consequence of the accuracy-first view. If one forms one false belief and a number of other true beliefs, then one is committed to many other false propositions, e.g., the conjunction of that false belief with any of the true beliefs. Once we properly account for all the falsehoods that are adopted by the person who takes the bribe, it turns out that the bribe does not increase accuracy.

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

Our primary interest this week will be in two objections Jackson mentions which seem to threaten his program. Each of them is avoided by appeal to the two-dimensional framework we sketched last week. Before we go over that framework again, we will start by looking at the objections. For reasons that may become apparent shortly, we will look at them in reverse order. So first we’ll look at this objection from Chapter 3, an objection which turns on the discovery of a posteriori necessities by Kripke and Putnam.