Call the norms of inquiry zetetic norms. How are zetetic norms related to epistemic norms? At first glance, they seem quite closely connected. Aren't epistemic norms norms that bind inquirers qua inquirers? And isn't epistemology the place to look for a normative theory of inquiry? While much of this thought seems right, this paper argues that the relationship between the epistemic and the zetetic is not as harmonious as one might have thought and liked. In particular, this paper argues that (...) some familiar contemporary epistemic norms are in tension with, and even in conflict with, central zetetic norms. (shrink)

The overwhelming majority of those who theorize about implicit biases posit that these biases are caused by some sort of association. However, what exactly this claim amounts to is rarely specified. In this paper, I distinguish between different understandings of association, and I argue that the crucial senses of association for elucidating implicit bias are the cognitive structure and mental process senses. A hypothesis is subsequently derived: if associations really underpin implicit biases, then implicit biases should be modulated by counterconditioning (...) or extinction but should not be modulated by rational argumentation or logical interventions. This hypothesis is false; implicit biases are not predicated on any associative structures or associative processes but instead arise because of unconscious propositionally structured beliefs. I conclude by discussing how the case study of implicit bias illuminates problems with popular dual-process models of cognitive architecture. (shrink)

The pragmatic character of the Dutch book argument makes it unsuitable as an "epistemic" justification for the fundamental probabilist dogma that rational partial beliefs must conform to the axioms of probability. To secure an appropriately epistemic justification for this conclusion, one must explain what it means for a system of partial beliefs to accurately represent the state of the world, and then show that partial beliefs that violate the laws of probability are invariably less accurate than they could be otherwise. (...) The first task can be accomplished once we realize that the accuracy of systems of partial beliefs can be measured on a gradational scale that satisfies a small set of formal constraints, each of which has a sound epistemic motivation. When accuracy is measured in this way it can be shown that any system of degrees of belief that violates the axioms of probability can be replaced by an alternative system that obeys the axioms and yet is more accurate in every possible world. Since epistemically rational agents must strive to hold accurate beliefs, this establishes conformity with the axioms of probability as a norm of epistemic rationality whatever its prudential merits or defects might be. (shrink)

The object of this paper is to show why recent research in the psychology of deductive and probabilistic reasoning does not have.

A leading political theorist’s groundbreaking defense of ideal conceptions of justice in political philosophy Throughout the history of political philosophy and politics, there has been continual debate about the roles of idealism versus realism. For contemporary political philosophy, this debate manifests in notions of ideal theory versus nonideal theory. Nonideal thinkers shift their focus from theorizing about full social justice, asking instead which feasible institutional and political changes would make a society more just. Ideal thinkers, on the other hand, question (...) whether full justice is a standard that any society is likely ever to satisfy. And, if social justice is unrealistic, are attempts to understand it without value or importance, and merely utopian? Utopophobia argues against thinking that justice must be realistic, or that understanding justice is only valuable if it can be realized. David Estlund does not offer a particular theory of justice, nor does he assert that justice is indeed unrealizable—only that it could be, and this possibility upsets common ways of proceeding in political thought. Estlund engages critically with important strands in traditional and contemporary political philosophy that assume a sound theory of justice has the overriding, defining task of contributing practical guidance toward greater social justice. Along the way, he counters several tempting perspectives, including the view that inquiry in political philosophy could have significant value only as a guide to practical political action, and that understanding true justice would necessarily have practical value, at least as an ideal arrangement to be approximated. Demonstrating that unrealistic standards of justice can be both sound and valuable to understand, Utopophobia stands as a trenchant defense of ideal theory in political philosophy. (shrink)

The paper argues against a widely held synchronic view of emotional rationality. I begin by considering recent philosophical literature on various backward‐looking emotions, such as regret, grief, resentment, and anger. I articulate the general problem these accounts grapple with: a certain diminution in backward‐looking emotions seems fitting while the reasons for these emotions seem to persist. The problem, I argue, rests on the assumption that if the facts that give reason for an emotion remain unchanged, the emotion remains fitting. However, (...) I argue there are rationally self‐consuming attitudes: affective attitudes that become less fitting the longer they endure while the facts that give reason for them persist. A widely held synchronic view of fitting affective attitudes denies that fittingness at a time depends on the agent's attitudes at different times and therefore denies that the fittingness of an affective attitude can depend on its duration. Once we reject the synchronic view, we may see that affective attitudes are often fitting due to the fitting processes of which they are part. These fitting processes explain the fitting diminution of backward‐looking emotions as well as other diachronic aspects of the fittingness of emotions. -/- . (shrink)

Despite the recent backlash against epistemic consequentialism, an explicit systematic alternative has yet to emerge. This paper articulates and defends a novel alternative, Epistemic Kantianism, which rests on a requirement of respect for the truth. §1 tackles some preliminaries concerning the proper formulation of the epistemic consequentialism / non-consequentialism divide, explains where Epistemic Kantianism falls in the dialectical landscape, and shows how it can capture what seems attractive about epistemic consequentialism while yielding predictions that are harder for the latter to (...) secure in a principled way. §2 presents Epistemic Kantianism. §3 argues that it is uniquely poised to satisfy the desiderata set out in §1 on an ideal theory of epistemic justification. §4 gives three further arguments, suggesting that it (i) best explains the objective normative significance of the subject's perspective in epistemology, (ii) follows from the kind of axiology needed to solve the swamping problem together with modest assumptions about the relation between the evaluative and the deontic, and (iii) illuminates certain asymmetries in epistemic value and obligation. §5 takes stock and reassesses the score in the debate. (shrink)

Research programs in empirical psychology from the past two decades have revealed implicit biases. Although implicit processes are pervasive, unavoidable, and often useful aspects of our cognitions, they may also lead us into error. The most problematic forms of implicit cognition are those which target social groups, encoding stereotypes or reflecting prejudicial evaluative hierarchies. Despite intentions to the contrary, implicit biases can influence our behaviours and judgements, contributing to patterns of discriminatory behaviour. These patterns of discrimination are obviously wrong and (...) unjust. But in remedying such wrongs, one question to be addressed concerns responsibility for implicit bias. Unlike some paradigmatic forms of wrongdoing, such discrimination is often unintentional, unendorsed, and perpetrated without awareness; and the harms are particularly damaging because they are cumulative and collectively perpetrated. So, what are we to make of questions of responsibility? In this article, we outline some of the main lines of recent philosophical thought, which address questions of responsibility for implicit bias. We focus on (a) the kind of responsibility at issue; (b) revisionist versus nonrevisionist conceptions of responsibility as applied to implicit bias; and (c) individual, institutional, and collective responsibility for implicit bias. (shrink)

The zetetic turn in epistemology raises three questions about epistemic and zetetic norms. First, there is the relationship question: what is the relationship between epistemic and zetetic norms? Are some epistemic norms zetetic norms, or are epistemic and zetetic norms distinct? Second, there is the tension question: are traditional epistemic norms in tension with plausible zetetic norms? Third, there is the reaction question: how should theorists react to a tension between epistemic and zetetic norms? Drawing on an analogy to practical (...) philosophy, I develop a focal point view to resolve these motivating questions. On the focal point view, traditional epistemic norms and zetetic norms answer different types of normative questions. There is nevertheless a familiar type of evaluative tension between traditional epistemic norms and zetetic norms, but this tension is an unavoidable feature of the normative landscape and not a sign that traditional epistemic norms need revision. But if traditional epistemic norms are not zetetic norms, then in what sense is zetetic epistemology a project for epistemologists? I conclude by articulating a sense in which some nontraditional epistemic norms are zetetic norms, and in which zetetic epistemology is an important part of the study of theoretical rationality. (shrink)

It is often claimed that the greatest value of the Bayesian framework in cognitive science consists in its unifying power. Several Bayesian cognitive scientists assume that unification is obviously linked to explanatory power. But this link is not obvious, as unification in science is a heterogeneous notion, which may have little to do with explanation. While a crucial feature of most adequate explanations in cognitive science is that they reveal aspects of the causal mechanism that produces the phenomenon to be (...) explained, the kind of unification afforded by the Bayesian framework to cognitive science does not necessarily reveal aspects of a mechanism. Bayesian unification, nonetheless, can place fruitful constraints on causal–mechanical explanation. 1 Introduction2 What a Great Many Phenomena Bayesian Decision Theory Can Model3 The Case of Information Integration4 How Do Bayesian Models Unify?5 Bayesian Unification: What Constraints Are There on Mechanistic Explanation?5.1 Unification constrains mechanism discovery5.2 Unification constrains the identification of relevant mechanistic factors5.3 Unification constrains confirmation of competitive mechanistic models6 ConclusionAppendix. (shrink)

Some naturalistic philosophers of mind subscribing to the predictive processing theory of mind have adopted a realist attitude towards the results of Bayesian cognitive science. In this paper, we argue that this realist attitude is unwarranted. The Bayesian research program in cognitive science does not possess special epistemic virtues over alternative approaches for explaining mental phenomena involving uncertainty. In particular, the Bayesian approach is not simpler, more unifying, or more rational than alternatives. It is also contentious that the Bayesian approach (...) is overall better supported by the empirical evidence. So, to develop philosophical theories of mind on the basis of a realist interpretation of results from Bayesian cognitive science is unwarranted. Naturalistic philosophers of mind should instead adopt an anti-realist attitude towards these results and remain agnostic as to whether Bayesian models are true. For continuing on with an exclusive focus and praise of Bayes within debates about the predictive processing theory will impede progress in philosophical understanding of scientific practice in computational cognitive science as well as of the architecture of the mind. (shrink)

Does rationality require logical omniscience? Our best formal theories of rationality imply that it does, but our ordinary evaluations of rationality seem to suggest otherwise. This paper aims to resolve the tension by arguing that our ordinary evaluations of rationality are not only consistent with the thesis that rationality requires logical omniscience, but also provide a compelling rationale for accepting this thesis in the first place. This paper also defends an account of apriori justification for logical beliefs that is designed (...) to explain the rational requirement of logical omniscience. On this account, apriori justification for beliefs about logic has its source in logical facts, rather than psychological facts about experience, reasoning, or understanding. This account has important consequences for the epistemic role of experience in the logical domain. In a slogan, the epistemic role of experience in the apriori domain is not a justifying role, but rather an enabling and disabling role. (shrink)

Heuristics are efficient cognitive processes that ignore information. In contrast to the widely held view that less processing reduces accuracy, the study of heuristics shows that less information, computation, and time can in fact improve accuracy. We review the major progress made so far: the discovery of less-is-more effects; the study of the ecological rationality of heuristics, which examines in which environments a given strategy succeeds or fails, and why; an advancement from vague labels to computational models of heuristics; the (...) development of a systematic theory of heuristics that identifies their building blocks and the evolved capacities they exploit, and views the cognitive system as relying on an “adaptive toolbox;” and the development of an empirical methodology that accounts for individual differences, conducts competitive tests, and has provided evidence for people’s adaptive use of heuristics. Homo heuristicus has a biased mind and ignores part of the available information, yet a biased mind can handle uncertainty more efficiently and robustly than an unbiased mind relying on more resource-intensive and general-purpose processing strategies. (shrink)

The prominence of Bayesian modeling of cognition has increased recently largely because of mathematical advances in specifying and deriving predictions from complex probabilistic models. Much of this research aims to demonstrate that cognitive behavior can be explained from rational principles alone, without recourse to psychological or neurological processes and representations. We note commonalities between this rational approach and other movements in psychology – namely, Behaviorism and evolutionary psychology – that set aside mechanistic explanations or make use of optimality assumptions. Through (...) these comparisons, we identify a number of challenges that limit the rational program's potential contribution to psychological theory. Specifically, rational Bayesian models are significantly unconstrained, both because they are uninformed by a wide range of process-level data and because their assumptions about the environment are generally not grounded in empirical measurement. The psychological implications of most Bayesian models are also unclear. Bayesian inference itself is conceptually trivial, but strong assumptions are often embedded in the hypothesis sets and the approximation algorithms used to derive model predictions, without a clear delineation between psychological commitments and implementational details. Comparing multiple Bayesian models of the same task is rare, as is the realization that many Bayesian models recapitulate existing (mechanistic level) theories. Despite the expressive power of current Bayesian models, we argue they must be developed in conjunction with mechanistic considerations to offer substantive explanations of cognition. We lay out several means for such an integration, which take into account the representations on which Bayesian inference operates, as well as the algorithms and heuristics that carry it out. We argue this unification will better facilitate lasting contributions to psychological theory, avoiding the pitfalls that have plagued previous theoretical movements. (shrink)

Ideal epistemologists investigate the nature of pure epistemic rationality, abstracting away from human cognitive limitations. Non-ideal epistemologists investigate epistemic norms that are satisfiable by most humans, most of the time. Ideal epistemology faces a number of challenges, aimed at both its substantive commitments and its philosophical worth. This paper explains the relation between ideal and non-ideal epistemology, with the aim of justifying ideal epistemology. Its approach is meta-epistemological, focusing on the meaning and purpose of epistemic evaluations. I provide an account (...) on which the fundamental difference between ideal and non-ideal epistemic evaluations is that only the non-ideal epistemic ‘ought’ implies any substantive ‘can’. I argue that only ideal epistemic evaluations are ‘normatively robust’: they are neither conventional nor seriously context-sensitive. Non-ideal epistemic evaluations are normatively non-robust, exhibiting both conventionality and serious context-sensitivity from an interesting variety of distinct sources. For this reason, non-ideal epistemic evaluations won’t characterize the fundamental nature of epistemic rationality. Non-ideal epistemic rationality depends, not merely on what’s epistemically valuable, but also on modally contingent epistemic conventions and contextually contingent constraints on epistemic options. If we want a normatively robust theory of epistemic rationality, ideal epistemology is the only game in town. (shrink)

Lipsey and Lancaster's "general theory of second best" is widely thought to have significant implications for applied theorizing about the institutions and policies that most effectively implement abstract normative principles. It is also widely thought to have little significance for theorizing about which abstract normative principles we ought to implement. Contrary to this conventional wisdom, I show how the second-best theorem can be extended to myriad domains beyond applied normative theorizing, and in particular to more abstract theorizing about the normative (...) principles we should aim to implement. I start by separating the mathematical model used to prove the second-best theorem from its familiar economic interpretation. I then develop an alternative normative-theoretic interpretation of the model, which yields a novel second best theorem for idealistic normative theory. My method for developing this interpretation provides a template for developing additional interpretations that can extend the reach of the second-best theorem beyond normative theoretical domains. I also show how, within any domain, the implications of the second-best theorem are more specific than is typically thought. I conclude with some brief remarks on the value of mathematical models for conceptual exploration. (shrink)

This paper begins by raising a puzzle about what function our use of the word ‘rational’ could serve. To solve the puzzle, I introduce a view I call Epistemic Communism: we use epistemic evaluations to promote coordination among our basic belief-forming rules, and the function of this is to make the acquisition of knowledge by testimony more efficient.

Bayesian epistemology addresses epistemological problems with the help of the mathematical theory of probability. It turns out that the probability calculus is especially suited to represent degrees of belief (credences) and to deal with questions of belief change, confirmation, evidence, justification, and coherence. Compared to the informal discussions in traditional epistemology, Bayesian epis- temology allows for a more precise and fine-grained analysis which takes the gradual aspects of these central epistemological notions into account. Bayesian epistemology therefore complements traditional epistemology; it (...) does not re- place it or aim at replacing it. (shrink)

A widely shared view in the cognitive sciences is that discovering and assessing explanations of cognitive phenomena whose production involves uncertainty should be done in a Bayesian framework. One assumption supporting this modelling choice is that Bayes provides the best approach for representing uncertainty. However, it is unclear that Bayes possesses special epistemic virtues over alternative modelling frameworks, since a systematic comparison has yet to be attempted. Currently, it is then premature to assert that cognitive phenomena involving uncertainty are best (...) explained within the Bayesian framework. As a forewarning, progress in cognitive science may be hindered if too many scientists continue to focus their efforts on Bayesian modelling, which risks to monopolize scientific resources that may be better allocated to alternative approaches. (shrink)

Saul_Jennifer, Scepticism and Implicit Bias.

Which rules should guide our reasoning? Human reasoners often use reasoning shortcuts, called heuristics, which function well in some contexts but lack the universality of reasoning rules like deductive implication or inference to the best explanation. Does it follow that human reasoning is hopelessly irrational? I argue: no. Heuristic reasoning often represents human reasoners reaching a local rational maximum, reasoning more accurately than if they try to implement more “ideal” rules of reasoning. I argue this is a genuine rational achievement. (...) Our ideal rational advisors would advise us to reason with heuristic rules, not more complicated ideal rules. I argue we do not need a radical new account of epistemic norms to make sense of the success of heuristic reasoning. (shrink)

In section 1, I develop epistemic communism, my view of the function of epistemically evaluative terms such as ‘rational’. The function is to support the coordination of our belief-forming rules, which in turn supports the reliable acquisition of beliefs through testimony. This view is motivated by the existence of valid inferences that we hesitate to call rational. I defend the view against the worry that it fails to account for a function of evaluations within first-personal deliberation. In the rest of (...) the paper, I then argue, on the basis of epistemic communism, for a view about rationality itself. I set up the argument in section 2 by saying what a theory of rational deduction is supposed to do. I claim that such a theory would provide a necessary, sufficient, and explanatorily unifying condition for being a rational rule for inferring deductive consequences. I argue in section 3 that, given epistemic communism and the conventionality that it entails, there is no such theory. Nothing explains why certain rules for deductive reasoning are rational. (shrink)

ABSTRACT Some epistemologists hold that all rational norms are fundamentally concerned with the agent’s states or attitudes at an individual time [Hedden 2015, 2016; Moss 2015]; others argue that all rational norms are fundamentally concerned with processes [Podgorski 2017]. This distinction is not drawn in discussions of emotional rationality. As a result, a widely held assumption in the literature on emotional rationality has gone unexamined. I employ Abelard Podgorski’s argument from rational delay to argue that many emotional norms are fundamentally (...) concerned with emotional processes. I also claim that the main response available to the synchronist about belief is not available to the synchronist about emotions and, therefore, fundamental process norms are more plausible than epistemologists tend to believe. (shrink)

In many learning or inference tasks human behavior approximates that of a Bayesian ideal observer, suggesting that, at some level, cognition can be described as Bayesian inference. However, a number of findings have highlighted an intriguing mismatch between human behavior and standard assumptions about optimality: People often appear to make decisions based on just one or a few samples from the appropriate posterior probability distribution, rather than using the full distribution. Although sampling-based approximations are a common way to implement Bayesian (...) inference, the very limited numbers of samples often used by humans seem insufficient to approximate the required probability distributions very accurately. Here, we consider this discrepancy in the broader framework of statistical decision theory, and ask: If people are making decisions based on samples—but as samples are costly—how many samples should people use to optimize their total expected or worst-case reward over a large number of decisions? We find that under reasonable assumptions about the time costs of sampling, making many quick but locally suboptimal decisions based on very few samples may be the globally optimal strategy over long periods. These results help to reconcile a large body of work showing sampling-based or probability matching behavior with the hypothesis that human cognition can be understood in Bayesian terms, and they suggest promising future directions for studies of resource-constrained cognition. (shrink)

I argue that bounded agents face a systematic accuracy-coherence tradeoff in cognition. Agents must choose whether to structure their cognition in ways likely to promote coherence or accuracy. I illustrate the accuracy-coherence tradeoff by showing how it arises out of at least two component tradeoffs: a coherence-complexity tradeoff between coherence and cognitive complexity, and a coherence-variety tradeoff between coherence and strategic variety. These tradeoffs give rise to an accuracy-coherence tradeoff because privileging coherence over complexity or strategic variety often leads to (...) a corresponding reduction in accuracy. I conclude with a discussion of two normative consequences for the study of bounded rationality: the importance of procedural rationality and the role of coherence in theories of bounded rationality. (shrink)

Options and the subjective ought Content Type Journal Article Pages 1-18 DOI 10.1007/s11098-012-9880-0 Authors Brian Hedden, Department of Linguistics and Philosophy, Massachusetts Institute of Technology, Cambridge, MA, USA Journal Philosophical Studies Online ISSN 1573-0883 Print ISSN 0031-8116.

Practical deliberation consists in thinking about what to do. Such deliberation is deemed rational when it conforms to certain normative requirements. What is often ignored is the role that an agent's context can play in so-called ‘failures’ of rationality. In this paper, I use recent cognitive science research investigating the effects of resource-scarcity on decision-making and cognitive function to argue that context plays an important role in determining which norms should structure an agent's deliberation. This evidence undermines the view that (...) the norms of ‘ideal’ rationality are necessary and universal requirements on deliberation. They are a solution to the problems faced by cognitively limited agents in a context of moderate scarcity. In a context of severe scarcity, the problems faced by cognitively limited agents are different and require deliberation structured by different norms. Agents reason rationally when they use the norms best suited to their context and cognitive capacities. (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)

While Bayesian models have been applied to an impressive range of cognitive phenomena, methodological challenges have been leveled concerning their role in the program of rational analysis. The focus of the current article is on computational impediments to probabilistic inference and related puzzles about empirical confirmation of these models. The proposal is to rethink the role of Bayesian methods in rational analysis, to adopt an independently motivated notion of rationality appropriate for computationally bounded agents, and to explore broad conditions under (...) which Bayesian agents would be rational. The proposal is illustrated with a characterization of costs inspired by thermodynamics. (shrink)

Bayesians defend norms of ideal rationality such as probabilism, which they claim should be approximated by non-ideal thinkers. Yet, it is not often discussed exactly in what sense it is beneficial for an agent’s credence function to approximate probabilistic coherence. Some existing research indicates that approximating coherence leads to improvements in accuracy, whereas other research suggests that it decreases Dutch book vulnerability. Yet, the existing results don’t settle whether there is a way of approximating coherence that delivers both benefits at (...) once. We show that there is. (shrink)

Finite agents such as human beings have reasoning and updating processes that are extended in time; consequently, there is always some lag between the point at which we gain new reasons and the point at which our attitudes have fully responded to those reasons. This phenomenon, which I call rational delay, poses a threat to the most common ways of formulating rational requirements on our attitudes, which do not allow rational beings to exhibit such delay. In this paper, I show (...) first how this problem undermines synchronic formulations of rational norms. Then I show how it likewise undermines the most natural diachronic modifications of these norms. Ultimately, I argue that a successful account of rational delay will reject norms that directly govern attitudes or states of mind like belief and intention altogether, in favor of norms that fundamentally concern temporally extended rational processes like deliberation. (shrink)

In this paper, I set out some desiderata for a model of implicit cognition. I present test cases and suggest that, when considered in light of them, some recent models of implicit cognition fail to satisfy these desiderata. The test cases also bring to light an important class of cases that have been almost completely ignored in philosophical discussions of implicit cognition and implicit bias. These cases have important work to do in helping us understand both the role of implicit (...) cognition in action and our attempts to combat implicit biases. (shrink)

Epistemology today centrally concerns the conceptual analysis of knowledge. Historically, however, this is a concept that philosophers have seldom been interested in analysing, particularly when it is construed as broadly as the English language would have it. Instead, the overriding focus of epistemologists over the centuries has been, first, to describe the epistemic ideal that human beings might hope to achieve, and then go on to chart the various ways in which we ordinarily fall off from that ideal. I discuss (...) in detail two historical manifestations of idealized epistemology — Aristotle and Descartes — and then consider how this perspective might make a difference to the discipline today. In the end, an idealized epistemology points toward a normative, prescriptive rather than descriptive enterprise. (shrink)

Some theorists, ranging from W. James to contemporary psychologists, have argued that forgetting is the key to proper functioning of memory. The authors elaborate on the notion of beneficial forgetting by proposing that loss of information aids inference heuristics that exploit mnemonic information. To this end, the authors bring together 2 research programs that take an ecological approach to studying cognition. Specifically, they implement fast and frugal heuristics within the ACT-R cognitive architecture. Simulations of the recognition heuristic, which relies on (...) systematic failures of recognition to infer which of 2 objects scores higher on a criterion value, demonstrate that forgetting can boost accuracy by increasing the chances that only 1 object is recognized. Simulations of the fluency heuristic, which arrives at the same inference on the basis of the speed with which objects are recognized, indicate that forgetting aids the discrimination between the objects' recognition speeds. (shrink)

According to a widely held view of the matter, whenever we assess beliefs as ‘rational’ or ‘justified’, we are making normative judgements about those beliefs. In this discussion, I shall simply assume, for the sake of argument, that this view is correct. My goal here is to explore a particular approach to understanding the basic principles that explain which of these normative judgements are true. Specifically, this approach is based on the assumption that all such normative principles are grounded in (...) facts about values, and the normative principles that apply to beliefs in particular are grounded in facts about alethic value––a kind of value that is exemplified by believing what is true and not believing what is false. In this chapter, I shall explain what I regard as the best way of interpreting this approach. In doing so, I shall also show how this interpretation can solve some problems that have recently been raised for approaches of this kind by Selim Berker, Jennifer Carr, Michael Caie, and Hilary Greaves. (shrink)

For epistemic subjects like us, updating our credences incurs epistemic costs. Expending our limited processing power and working memory to properly update our credences by some information can come at the cost of not responding to other available information. It is thus desirable to flesh out and compare alternative ways of taking information into account in light of cognitive shortcomings like our own. This paper is a preliminary attempt to do so. I argue that it is better, in a range (...) of circumstances and from the point of view of expected credal accuracy, for epistemic subjects like us not to update on available information that bears on propositions for which substantial evidence has been gathered than it is to update on information as it presents itself. In order to clarify the argument, and enable comparisons between information-response policies more generally, I develop a queue-theoretic model of learning for subjects with cognitive limitations. The model characterizes how policies for responding to information interact with a subject’s limitations to yield confidences. Finally, I discuss implications of the discussion for work on confidence, outright belief, and the relationship between those two states. The comparison of information-response policies helps to explain how some of the “biases” revealed by psychological research might be cognitively valuable, clarify views that take outright belief to be a kind of epistemic plan that resists reconsideration, and assuage certain “demandingness” worries for the hypothesis that we are credal reasoners. (shrink)

True beliefs and truth-preserving inferences are, in some sense, good beliefs and good inferences. When an inference is valid though, it is not merely truth-preserving, but truth-preserving in all cases. This motivates my question: I consider a Modus Ponens inference, and I ask what its validity in particular contributes to the explanation of why the inference is, in any sense, a good inference. I consider the question under three different definitions of ‘case’, and hence of ‘validity’: the orthodox definition given (...) in terms of interpretations or models, a metaphysical definition given in terms of possible worlds, and a substitutional definition defended by Quine. I argue that the orthodox notion is poorly suited to explain what's good about a Modus Ponens inference. I argue that there is something good that is explained by a certain kind of truth across possible worlds, but the explanation is not provided by metaphysical validity in particular; nothing of value is explained by truth across all possible worlds. Finally, I argue that the substitutional notion of validity allows us to correctly explain what is good about a valid inference. (shrink)

Ideal theorists aim to describe the ideally just society. Problem solvers aim to identify concrete changes to actual societies that would make them more just. The relation between these two sorts of theorizing is highly contested. According to the benchmark view, ideal theory is prior to problem solving because a conception of the ideally just society serves as an indispensable benchmark for evaluating societies in terms of how far they deviate from it. In this paper, I clarify the benchmark view, (...) argue that existing criticisms of it are unsuccessful, and develop a novel redundancy objection to the benchmark view and the claim of priority it allegedly entails. I then consider the extent to which ideal theory might facilitate problem solving without being prior to it and argue that it can only play a modest role in this regard. The upshot is that ideal theory is neither required for nor especially relevant to problem solving—but it is not completely irrelevant either. It facilitates problem solving to some limited degree, but no more, say, than theorizing about dystopia. (shrink)

My aim in this paper is to develop a unified solution to two paradoxes of bounded rationality. The first is the regress problem that incorporating cognitive bounds into models of rational decisionmaking generates a regress of higher-order decision problems. The second is the problem of rational irrationality: it sometimes seems rational for bounded agents to act irrationally on the basis of rational deliberation. I review two strategies which have been brought to bear on these problems: the way of weakening which (...) responds by weakening rational norms, and the way of indirection which responds by letting the rationality of behavior be determined by the rationality of the deliberative processes which produced it. Then I propose and defend a third way to confront the paradoxes: the way of level separation. (shrink)