We use a theorem from M. J. Schervish to explore the relationship between accuracy and practical success. If an agent is pragmatically rational, she will quantify the expected loss of her credence with a strictly proper scoring rule. Which scoring rule is right for her will depend on the sorts of decisions she expects to face. We relate this pragmatic conception of inaccuracy to the purely epistemic one popular among epistemic utility theorists.

Good’s theorem is the apparent platitude that it is always rational to ‘look before you leap’: to gather information before making a decision when doing so is free. We argue that Good’s theorem is not platitudinous and may be false. And we argue that the correct advice is rather to ‘make your act depend on the answer to a question’. Looking before you leap is rational when, but only when, it is a way to do this.

Data which constitute satisfactory evidence in other contexts are sometimes not treated as valid evidence in the context of scientic conrmation. I give a justicatory explanation of this fact, appealing to the incentives, biases, and social situatedness of scientists.

Recent years have seen a surge in online collaboration between experts and amateurs on scientific research. In this article, we analyse the epistemological implications of these crowdsourced projects, with a focus on Zooniverse, the world’s largest citizen science web portal. We use quantitative methods to evaluate the platform’s success in producing large volumes of observation statements and high impact scientific discoveries relative to more conventional means of data processing. Through empirical evidence, Bayesian reasoning, and conceptual analysis, we show how information (...) and communication technologies enhance the reliability, scalability, and connectivity of crowdsourced e-research, giving online citizen science projects powerful epistemic advantages over more traditional modes of scientific investigation. These results highlight the essential role played by technologically mediated social interaction in contemporary knowledge production. We conclude by calling for an explicitly sociotechnical turn in the philosophy of science that combines insights from statistics and logic to analyse the latest developments in scientific research. (shrink)

Sometimes it’s not certain which of several mutually exclusive moral views is correct. Like almost everyone, I think that there’s some sense in which what one should do depends on which of these theories is correct, plus the way the world is non-morally. But I also think there’s an important sense in which what one should do depends upon the probabilities of each of these views being correct. Call this second claim “moral uncertaintism”. In this paper, I want to address (...) an argument against moral uncertaintism offered in the pages of this journal by Brian Weatherson, and seconded elsewhere by Brian Hedden, the crucial premises of which are: that acting on moral uncertaintist norms necessarily involves motivation by reasons or rightness as such, and that such motivation is bad. I will argue that and are false, and that at any rate, the quality of an agent’s motivation is not pertinent to the truth or falsity of moral uncertaintism in the way that Weatherson’s and Hedden’s arguments require. (shrink)

I show that the social stratification of academic science can arise as a result of academics’ preference for reading work of high epistemic value. This is consistent with a view on which academic superstars are highly competent academics, but also with a view on which superstars arise primarily due to luck. I argue that stratification is beneficial if most superstars are competent, but not if most superstars are lucky. I also argue that it is impossible to tell whether most superstars (...) are in fact competent or lucky, or which group a given superstar belongs to, and hence whether stratification is overall beneficial. (shrink)

With the ascent of modern epidemiology in the Twentieth Century came a new standard model of prediction in public health and clinical medicine. In this article, we describe the structure of the model. The standard model uses epidemiological measures-most commonly, risk measures-to predict outcomes (prognosis) and effect sizes (treatment) in a patient population that can then be transformed into probabilities for individual patients. In the first step, a risk measure in a study population is generalized or extrapolated to a target (...) population. In the second step, the risk measure is particularized or transformed to yield probabilistic information relevant to a patient from the target population. Hence, we call the approach the Risk Generalization-Particularization (Risk GP) Model. There are serious problems at both stages, especially with the extent to which the required assumptions will hold and the extent to which we have evidence for the assumptions. Given that there are other models of prediction that use different assumptions, we should not inflexibly commit ourselves to one standard model. Instead, model pluralism should be standard in medical prediction. (shrink)

Both dilation and non-conglomerability have been alleged to conflict with a fundamental principle of Bayesian methodology that we call \textit{Good's Principle}: one should always delay making a terminal decision between alternative courses of action if given the opportunity to first learn, at zero cost, the outcome of an experiment relevant to the decision. In particular, both dilation and non-conglomerability have been alleged to permit or even mandate choosing to make a terminal decision in deliberate ignorance of relevant, cost-free information. Although (...) dilation and non-conglomerability share some similarities, some authors maintain that there are important differences between the two that warrant endorsing different normative positions regarding dilation and non-conglomerability. This article reassesses the grounds for treating dilation and non-conglomerability differently. Our analysis exploits a new and general characterization result for dilation to draw a closer connection between dilation and non-conglomerability. (shrink)

In this contribution, I comment on Raffaella Campaner’s defense of explanatory pluralism in psychiatry (in this volume). In her paper, Campaner focuses primarily on explanatory pluralism in contrast to explanatory reductionism. Furthermore, she distinguishes between pluralists who consider pluralism to be a temporary state on the one hand and pluralists who consider it to be a persisting state on the other hand. I suggest that it would be helpful to distinguish more than those two versions of pluralism – different understandings (...) of explanatory pluralism both within philosophy of science and psychiatry – namely moderate/temporary pluralism, anything goes pluralism, isolationist pluralism, integrative pluralism and interactive pluralism. Next, I discuss the pros and cons of these different understandings of explanatory pluralism. Finally, I raise the question of how to implement or operationalize explanatory pluralism in scientific practice; how to structure the “genuine dialogue” or shape “the pluralistic attitude” Campaner is referring to. As tentative answers, I explore a question-based framework for explanatory pluralism as well as social-epistemological procedures for interaction among competing approaches and explanations. (shrink)

Medical scientists employ ‘quality assessment tools’ (QATs) to measure the quality of evidence from clinical studies, especially randomized controlled trials (RCTs). These tools are designed to take into account various methodological details of clinical studies, including randomization, blinding, and other features of studies deemed relevant to minimizing bias and error. There are now dozens available. The various QATs on offer differ widely from each other, and second-order empirical studies show that QATs have low inter-rater reliability and low inter-tool reliability. This (...) is an instance of a more general problem I call the underdetermination of evidential significance. Disagreements about the strength of a particular piece of evidence can be due to different—but in principle equally good—weightings of the fine-grained methodological features which constitute QATs. (shrink)

Dilation occurs when an interval probability estimate of some event E is properly included in the interval probability estimate of E conditional on every event F of some partition, which means that one’s initial estimate of E becomes less precise no matter how an experiment turns out. Critics maintain that dilation is a pathological feature of imprecise probability models, while others have thought the problem is with Bayesian updating. However, two points are often overlooked: (1) knowing that E is stochastically (...) independent of F (for all F in a partition of the underlying state space) is sufficient to avoid dilation, but (2) stochastic independence is not the only independence concept at play within imprecise probability models. In this paper we give a simple characterization of dilation formulated in terms of deviation from stochastic independence, propose a measure of dilation, and distinguish between proper and improper dilation. Through this we revisit the most sensational examples of dilation, which play up independence between dilator and dilatee, and find the sensationalism undermined by either fallacious reasoning with imprecise probabilities or improperly constructed imprecise probability models. (shrink)

This paper provides an account of what it is to have faith in a proposition p, in both religious and mundane contexts. It is argued that faith in p doesn’t require adopting a degree of belief that isn’t supported by one’s evidence but rather it requires terminating one’s search for further evidence and acting on the supposition that p. It is then shown, by responding to a formal result due to I.J. Good, that doing so can be rational in a (...) number of circumstances. If expected utility theory is the correct account of practical rationality, then having faith can be both epistemically and practically rational if the costs associated with gathering further evidence or postponing the decision are high. If a more permissive framework is adopted, then having faith can be rational even when there are no costs associated with gathering further evidence. (shrink)

In “Can it be rational to have faith?”, it was argued that to have faith in some proposition consists, roughly speaking, in stopping one’s search for evidence and committing to act on that proposition without further evidence. That paper also outlined when and why stopping the search for evidence and acting is rationally required. Because the framework of that paper was that of formal decision theory, it primarily considered the relationship between faith and degrees of belief, rather than between faith (...) and belief full stop. This paper explores the relationship between rational faith and justified belief, by considering four prominent proposals about the relationship between belief and degrees of belief, and by examining what follows about faith and belief according to each of these proposals. It is argued that we cannot reach consensus concerning the relationship between faith and belief at present because of the more general epistemological lack of consensus over how belief relates to rationality: in particular, over how belief relates to the degrees of belief it is rational to have given one’s evidence. (shrink)

This paper discusses the epistemic outcomes of following a belief-forming policy of inclusiveness under conditions in which one anticipates systematic disagreement with one’s interlocutors. These cases highlight the possibility of distinctly epistemic costs of inclusiveness, in the form of lost knowledge of or a diminishment in one’s rational confidence in a proposition. It is somewhat controversial whether following a policy of inclusiveness under such circumstances will have such costs; this will depend in part on the correct account of the epistemic (...) significance of disagreement (a topic over which there is some disagreement). After discussing this matter at some length, I conclude, tentatively, that inclusiveness under disagreement can have such epistemic costs. Still, I go on to argue, such costs by themselves would not rationalize substantial limitations on a broad policy of inclusiveness. Insofar as there are grounds for restricting how inclusive one should be in belief-formation, these grounds will not be epistemic, but instead will reflect the practical costs—the time, effort, and resource costs to the subject—of following such a policy. (shrink)

The paper shows why and how an empirical study of fast-and-frugal heuristics can provide norms of good reasoning, and thus how (and how far) rationality can be naturalized. We explain the heuristics that humans often rely on in solving problems, for example, choosing investment strategies or apartments, placing bets in sports, or making library searches. We then show that heuristics can lead to judgments that are as accurate as or even more accurate than strategies that use more information and computation, (...) including optimization methods. A standard way to defend the use of heuristics is by reference to accuracy-effort trade-offs. We take a different route, emphasizing ecological rationality (the relationship between cognitive heuristics and environment), and argue that in uncertain environments, more information and computation are not always better (the “less-can-be-more” doctrine). The resulting naturalism about rationality is thus normative because it not only describes what heuristics people use, but also in which specific environments one should rely on a heuristic in order to make better inferences. While we desist from claiming that the scope of ecological rationality is unlimited, we think it is of wide practical use. (shrink)

This paper addresses the question of whether gathering additional evidence is always rationally required, both from the point of view of instrumental rationality and of epistemic rationality. It is shown that in certain situations, it is not instrumentally rational to look for more evidence before making a decision. These are situations in which the risk of “misleading” evidence – a concept that has both instrumental and epistemic senses – is not offset by the gains from the possibility of non-misleading evidence. (...) These situations also undermine a particular argument for the claim that it is epistemically rational to look for more evidence, though it is argued that the relationship between instrumental and epistemic rationality makes such arguments flawed to begin with. Furthermore, these situations show us that our epistemic and our practical goals sometimes point us in different directions, not merely because of our limited resources or because our desires are sometimes best served by being in particular epistemic states, but because of the nature of rational action. (shrink)

Is there a duty to respond to objections in order to present a good argument? Ralph Johnson argues that there is such a duty, which he refers to as the ‘dialectical tier’ of an argument. I deny the (alleged) duty primarily on grounds that it would exert too great a demand on arguers, harming argumentation practices. The valuable aim of responding to objections, which Johnson’s dialectical tier is meant to satisfy, can be achieved in better ways, as argumentation is a (...) social-epistemic activity. (shrink)

Colin Howson (1995 ) offers a counter-example to the rule of conditionalization. I will argue that the counter-example doesn't hit its target. The problem is that Howson mis-describes the total evidence the agent has. In particular, Howson overlooks how the restriction that the agent learn 'E and nothing else' interacts with the de se evidence 'I have learnt E'.

To clarify and illuminate the place of probability in science Ellery Eells and James H. Fetzer have brought together some of the most distinguished philosophers ...

In addition to purely practical values, cognitive values also figure into scientific deliberations. One way of introducing cognitive values is to consider the cognitive value that accrues to the act of accepting a hypothesis. Although such values may have a role to play, such a role does not exhaust the significance of cognitive values in scientific decision-making. This paper makes a plea for consideration of epistemic value —that is, value attaching to a state of belief—and defends the notion of cognitive (...) epistemic value against some criticisms that have been raised. A stability requirement for epistemic value functions is argued for on the basis of considerations of diachronic coherence. This stability requirement is sufficient to obtain the Value of Learning Theorem, which says that the expected utility of cost-free learning cannot be negative. This holds also for cognitive epistemic values, provided that the stability requirement is met. (shrink)

Does the philosophy of Radical Probabilism have enough structure to enable it to address fundamental epistemological questions? The requirement of dynamic coherence provides the structure for radical probabilist epistemology. This structure is sufficient to establish (i) the value of knowledge and (ii) long run convergence of degrees of belief.

This paper discusses the Bayesian updating rules of ordinary and Jeffrey conditionalisation. Their justification has been a topic of interest for the last quarter century, and several strategies proposed. None has been accepted as conclusive, and it is argued here that this is for a good reason; for by extending the domain of the probability function to include propositions describing the agent's present and future degrees of belief one can systematically generate a class of counterexamples to the rules. Dynamic Dutch (...) Book and other arguments for them are examined critically. A concluding discussion attempts to put these results in perspective within the Bayesian approach. (shrink)

We show there is only one consistent way to update a probability assignment, that given by Bayes's rule. The price of inconsistent updating is a loss of efficiency. The implications of this for the problem of induction are discussed.

William K. Goosens claims to show that my account of epistemic utility runs into serious difficulties when confronted with certain attractive conditions of adequacy for the evaluation of experiments. I show that those conditions of adequacy which are, indeed, acceptable to both of us are satisfied by the procedures for evaluating experiments mandated by combining my theory of epistemic utilities with the approach to evaluating experiments on which Goosens' argument is based. In particular, I demonstrate that my theory does not (...) violate the requirement that an "ideal experiment" be no worse than any alternative experiment. (shrink)

A person required to risk money on a remote digit of π would, in order to comply fully with the theory [of personal probability] have to compute that digit, though this would really be wasteful if the cost of computation were more than the prize involved. For the postulates of the theory imply that you should behave in accordance with the logical implications of all that you know. Is it possible to improve the theory in this respect, making allowance within (...) it for the cost of thinking, or would that entail paradox? (shrink)

Can you rationally double-check what you already know? In this paper, I argue that you can. Agents can know that something is true and rationally double-check it at the very same time. I defend my position by considering a wide variety of cases where agents double-check their beliefs to gain epistemic improvements beyond knowledge. These include certainty, epistemic resilience, and sensitivity to error. Although this phenomenon is widespread, my proposal faces two types of challenges. First, some have defended ignorance norms, (...) on which agents are only allowed to inquire about things they don't already know. Second – motivated by strong conceptions of belief or pragmatic encroachment – some have argued that double-checking destroys knowledge. I argue that these competing views fail to capture both the epistemic value of double-checking and the many reasons why agents might double-check. Moreover, they rely on overly strong assumptions about what inquiry, knowledge, or belief requires. Finally, I marshal linguistic data in favor of the compatibility of knowledge and double-checking. (shrink)

The Value of Evidence thesis (VE) tells us to gather evidence before deciding in any decision problem, if the evidence is free. This appar- ently plausible principle faces two problems. First, it fails on evidence externalism or nonclassical decision theories. Second, it’s not general enough: it tells us to prefer gaining free evidence to gaining no evi- dence, but it doesn’t tell us to prefer gaining more informative evidence to gaining less informative evidence when both are free. This paper defends (...) an alternative value-of-evidence principle that solves the above two problems. We call it ‘the Comparative Value of Evidence for the Resolute (CVER).’ CVER not only generalizes VE to the comparative case but is also compatible with evidence externalism and nonclassical decision theories. Our argument, if successful, broadens the scope of the value-of-evidence principle and shows that it’s more robust than previously imagined. (shrink)

Epistemology has taken a zetetic turn from the study of belief towards the study of inquiry. Several decades ago, theories of bounded rationality took a procedural turn from attitudes towards the processes of inquiry that produce them. What is the relationship between the zetetic and procedural turns? In this paper, I argue that we should treat the zetetic turn in epistemology as part of a broader procedural turn in the study of bounded rationality. I use this claim to motivate and (...) clarify the zetetic turn in epistemology, as well as to reveal the need for a second zetetic turn within practical philosophy. (shrink)

My dissertation is about Bayesian rationality for non-ideal agents. I show how to derive subjective probabilities from preferences using much weaker rationality assumptions than other standard representation theorems. I argue that non-ideal agents might be uncertain about how they will update on new information and consider two consequences of this uncertainty: such agents should sometimes reject free information and make choices which, taken together, yield sure loss. The upshot is that Bayesian rationality for non-ideal agents makes very different normative demands (...) than ideal Bayesian rationality. (shrink)

Why engage in inquiry? According to many philosophers, the goal of inquiring into some question is to come to know its answer. While this view holds considerable appeal, this paper argues that it stands in tension with another highly attractive thesis: knowledge does not require absolute certainty. Forced to choose between these two theses, I argue that we should reject the idea that inquiry aims at knowledge. I go on to develop an alternative view, according to which inquiry aims at (...) maximizing the epistemic value of our credences. This alternative view makes room for knowledge that falls shy of certainty, and it coheres nicely with a rich body of work in epistemic decision theory. I proceed to highlight the implications of this replacement for some important topics in epistemology, including the dogmatism paradox, the nature of interrogative attitudes, and the norm of practical reasoning. (shrink)

This thesis is about making decisions when we are uncertain about what will happen, how valuable it will be, and even how to make decisions. Even the most sure-footed amongst us are sometimes uncertain about all three, but surprisingly little attention has been given to the latter two. The three essays that constitute my thesis hope to do a small part in rectifying this problem. The first essay is about the value of finding out how to make decisions. Society spends (...) considerable resources funding people (like me) to research decision-making, so it is natural to wonder whether society is getting a good deal. This question is so shockingly underresearched that bedrock facts are readily discoverable, such as when this kind of information is valuable. My second essay concerns whether we can compare value when we are uncertain about value. Many people are in fact uncertain about value, and how we deal with this uncertainty hinges on these comparisons. I argue that value comparisons are only sometimes possible; I call this weak comparability. This essay is largely a synthesis of the literature, but I also present an argument which begins with a peculiar view of the self: it is as if each of us is a crowd of different people separated by time (but connected by continuity of experience). I’m not the first to endorse this peculiar view of the self, but I am the first to show how it supports the benign view that value is sometimes comparable. We may be uncertain of any decision rules, even those that would tell us how to act when we face uncertainty in decision rules. We may be uncertain of how to decide how to decide how to... And so on. If so, we might have to accept infinitely many decision rules just to make any mundane decision, such as whether to pick up a five-cent piece from the gutter. My third essay addresses this problem of regress. I think all of our decisions are forced: we must decide now or continue to deliberate. Surprisingly, this allows us to avoid the original problem. I call this solution “when forced, do your best”. (shrink)

Predictable polarization is everywhere: we can often predict how people’s opinions, including our own, will shift over time. Extant theories either neglect the fact that we can predict our own polarization, or explain it through irrational mechanisms. They needn’t. Empirical studies suggest that polarization is predictable when evidence is ambiguous, that is, when the rational response is not obvious. I show how Bayesians should model such ambiguity and then prove that—assuming rational updates are those which obey the value of evidence—ambiguity (...) is necessary and sufficient for the rationality of predictable polarization. The main theoretical result is that there can be a series of such updates, each of which is individually expected to make you more accurate, but which together will predictably polarize you. Polarization results from asymmetric increases in accuracy. This mechanism is not only theoretically possible, but empirically plausible. I argue that cognitive search—searching a cognitively accessible space for a particular item—often yields asymmetrically ambiguous evidence, I present an experiment supporting its polarizing effects, and I use simulations to show how it can explain two of the core causes of polarization: confirmation bias and the group polarization effect. (shrink)

In sequential decision problems, an act of learning cost-free evidence might be symptomatic, in the sense that performing this act itself provides evidence about states of the world it does nothing to causally promote. It is well known that orthodox causal decision theory, like its main rival evidential decision theory, may sanction such acts as rationally impermissible. This paper shows that, under plausible assumptions, a minimal version of ratificationist causal decision theory, known as principled ratificationism, fares better in this respect, (...) for it never labels symptomatic acts of learning cost-free evidence as rationally impermissible. (shrink)

Is more information always better? Or are there some situations in which more information can make us worse off? Good (1967) argues that expected utility maximizers should always accept more information if the information is cost-free and relevant. But Good's argument presupposes that you are certain you will update by conditionalization. If we relax this assumption and allow agents to be uncertain about updating, these agents can be rationally required to reject free and relevant information. Since there are good reasons (...) to be uncertain about updating, rationality can require you to prefer ignorance. (shrink)

In the recent philosophical literature on inquiry, epistemologists point out that their subject has often begun at the point at which you already have your evidence and then focussed on identifying the beliefs for which that evidence provides justification. But we are not mere passive recipients of evidence. While some comes to us unbidden, we often actively collect it. This has long been recognised, but typically epistemologists have taken the norms that govern inquiry to be practical, not epistemic. The recent (...) literature challenges this assumption and uncovers a rich range of questions about the epistemic normativity of inquiry. In this paper, I approach these questions from the formal side of epistemology. Developing out of the philosophy of science, as it did, this branch of epistemology has long discussed inquiry. And, building on the insights of Janina Hosiasson (1931), David Blackwell (1951), and I. J. Good (1967), it has produced a reasonably well-developed framework in which to understand norms of inquiry, both epistemic and practical. In the first half of the paper, I will present the pragmatic versions of this framework due to Hosiasson, Blackwell, and Good, and the epistemic version due to Graham Oddie (1997); in the second half of the paper, I put this framework to work, turning to some of the questions from the recent debate about inquiry and asking how the framework can help us answer them. Questions include: When should we initiate an inquiry, when should we continue it, when should we conclude it, and when should we reopen it? How do epistemic norms of inquiry relate to epistemic norms of belief or credence, and can they conflict, as Jane Friedman (2020) contends? How should we resolve the apparent puzzle raised by Friedman's example of counting the windows in the Chrysler Building? How should we direct our attention, as Georgi Gardiner (2022) asks? How should we choose and reason after receiving evidence we'd rather not have received? And how should we understand the epistemic error that occurs when someone is resistant to evidence in the way Mona Simion (2023) describes? (shrink)

This chapter presents the reception of Leo Strauss by analytic philosophers after Strauss’s emigration to the United States. It gives a brief survey of the polemics against Strauss and his school by analytic philosophers, which aided in the self-constitution of analytic philosophy as a rival school of thought in philosophy. But most of the chapter is devoted to recovering the significance and influence of a criticism of Strauss by Ernest Nagel. The chapter argues that this response is of intrinsic interest (...) because it involves the relationship between science and values. Nagel’s response was foundational to Felix Oppenheim’s political philosophy or what Oppenheim called his project of ‘conceptual reconstruction.’ Lurking in Oppenheim’s response to Strauss are questions about the role of the principle of sufficient reason in philosophy. Rge chapter argues that an opportunity was missed to clarify questions pertaining to the inductive risk of philosophy more than a half century before these issues became fashionable again. (shrink)

Can scientific evidence outstretch what scientists have mentally entertained, or could ever entertain? This article focuses on the plausibility and consequences of an affirmative answer in a special case. Specifically, it discusses how we may treat automated scientific data-gathering systems—especially AI systems used to make predictions or to generate novel theories—from the point of view of confirmation theory. It uses AlphaFold2 as a case study.

There has been a movement aiming to teach agents about their privilege by making the information about their privilege as costless as possible. However, some argue that in risk-sensitive frameworks, such as Lara Buchak’s (2013), it can be rational for privileged agents to shield themselves from learning about their privilege, even if the information is costless and relevant. This threatens the efficacy of these information-access efforts in alleviating the problem of elite-group ignorance. In response, I show that even within the (...) same framework, in this case David Kinney and Liam Kofi Bright’s (2021), the rationality of this information avoidance rests on shaky ground in practice. In this framework, whether an agent should avoid information depends on the precise details of (1) how relevant they expect the information to be, (2) their priors about the value of various options, and (3) their risk attitudes. The model suggests that the rationality of elite-group ignorance is a function of structural factors that are pervasive but nonetheless not insurmountable, thus offering a way out of pessimism about elite group education. (shrink)

In this paper, we argue that there are epistemic norms on evidence-gathering and consider consequences for how to understand epistemic normativity. Though the view that there are such norms seems intuitive, it has found surprisingly little defense. Rather, many philosophers have argued that norms on evidence-gathering can only be practical or moral. On a prominent evidentialist version of this position, epistemic norms only apply to responding to the evidence one already has. Here we challenge the orthodoxy. First, we argue that (...) there is no significant normative difference between responding to evidence you have and gathering more evidence. Second, we argue that our practices of epistemically criticizing agents for their poor evidence-gathering indicate the existence of epistemic norms on evidence-gathering. Finally, we show that our thesis has important implications for recent debates about the relationship between epistemic norms and inquiry. (shrink)

A decision theory is self-recommending if, when you ask it which decision theory you should use, it considers itself to be among the permissible options. I show that many alternatives to expected utility theory are not self-recommending, and I argue that this tells against them.

Ex-ante deontology is an attempt to combine deontological constraints on doing or intending harm with the idea that one should act in everyone’s interest if possible. I argue that ex-ante deontology has serious problems in cases where multiple decisions are to be made over time. I then argue that these problems force us to choose between commonsense deontological morality and a more consequentialist morality. I suggest that we should choose the latter.

Can you rationally double-check what you already know? In this paper, I argue that you can. Agents can know that something is true and rationally double-check it at the very same time. I defend my position by considering a wide variety of cases where agents double-check their beliefs to gain epistemic improvements beyond knowledge. These include certainty, epistemic resilience, and sensitivity to error. Although this phenomenon is widespread, my proposal faces two types of challenges. First, some have defended ignorance norms, (...) on which agents are only allowed to inquire about things they don't already know. Second – motivated by strong conceptions of belief or pragmatic encroachment – some have argued that double-checking destroys knowledge. I argue that these competing views fail to capture both the epistemic value of double-checking and the many reasons why agents might double-check. Moreover, they rely on overly strong assumptions about what inquiry, knowledge, or belief requires. Finally, I marshal linguistic data in favor of the compatibility of knowledge and double-checking. (shrink)

How ought you to evaluate your options if you're uncertain about what's fundamentally valuable? A prominent response is Expected Value Maximisation (EVM)—the view that under axiological uncertainty, an option is better than another if and only if it has the greater expected value across axiologies. But the expected value of an option depends on quantitative probability and value facts, and in particular on value comparisons across axiologies. We need to explain what it is for such facts to hold. Also, EVM (...) is by no means self-evident. We need an argument to defend that it’s true. This book introduces an axiomatic approach to answer these worries. It provides an explication of what EVM means by use of representation theorems: intertheoretic comparisons can be understood in terms of facts about which options are better than which, and mutatis mutandis for intratheoretic comparisons and axiological probabilities. And it provides a systematic argument to the effect that EVM is true: the theory can be vindicated through simple axioms. The result is a formally cogent and philosophically compelling extension of standard decision theory, and original take on the problem of axiological or normative uncertainty. (shrink)

Higher-order evidence is evidence about what is rational to think in light of your evidence. Many have argued that it is special – falling into its own evidential category, or leading to deviations from standard rational norms. But it is not. Given standard assumptions, almost all evidence is higher-order evidence.