This paper addresses and rejects claims that one can demonstrate experimentally that most untutored subjects are systematically and incurably irrational in their probability judgements and in some deductive reasoning tasks. From within a strongly subjectivist theory of probability, it develops the notions of resiliency —a measure of stability of judgements—and robustness —a measure of expected stability. It then becomes possible to understand subjects' behaviour in the Wason selection task, in examples which have been claimed to involve a 'base-rate fallacy', in (...) appearing to ignore laws of large numbers and to overestimate their own success rate as entirely rational: a matter of combining first-order probability assignments with judgements about the robustness of those assignments. (shrink)

This paper presents an integrative framework for analyzing decisions. Three generic modes of decision making are identified: consequential choice , matching and reassessment . The three generic modes are compared on a common set of attributes, and the conditions for their proper use are outlined. Two case analyses illustrate how the framework can be used to analyze specific decisions from multiple perspectives.

Philosophers have traditionally held that claims about necessities and possibilities are to be evaluated by consulting our philosophical intuitions; that is, those peculiarly compelling deliverances about possibilities that arise from a serious and reflective attempt to conceive of counterexamples to these claims. But many contemporary philosophers, particularly naturalists, argue that intuitions of this sort are unreliable, citing examples of once-intuitive, but now abandoned, philosophical theses, as well as recent psychological studies that seem to establish the general fallibility of intuition.In the (...) first two sections of this paper, I evaluate these arguments, and also the counter-arguments of contemporary defenders of tradition. In the next two sections, I sketch an alternative account of the role of philosophical intuitions that incorporates elements of traditionalism and naturalism - and defend it against other such views. In the final section, however, I discuss intuitions about conscious experience, and acknowledge that my view may not extend comfortably to this case. This may seem unfortunate, since so much contemporary discussion of the epistemology of modality seems motivated by worries about the mind-body problem, and informed by the position one wishes to endorse. But, as I argue, if conscious experience is indeed an exception to the view I suggest in this paper, it is an exception that proves - and can illuminate - the rule. (shrink)

Koehler's target article attempts a balanced view of the relevance of knowledge of base rates to judgments of subjective or credal probability, but he is not sensitive enough to the difference between requiring and permitting the equation of probability judgments with base rates, the interaction between precision of base rate and reference class information, and the possibility of indeterminate probability judgment.

In his early experimental work with Suppes, Davidson adopted rationality assumptions, not as necessary constraints on interpretation, but as practical conceits in addressing methodological problems faced by experimenters studying decision making under uncertainty. Although the content of their theory has since been undermined, their methodological approach—a Galilean form of methodological rationalism—lives on in contemporary psychological research. This article draws on Max Weber’s verstehen to articulate an account of Galilean methodological rationalism; explains how anomalies faced by Davidson’s early experimental work gave (...) rise to his later, canonical claims about rationality and interpretation; and reclaims this Galilean framework for use in contemporary psychological research. (shrink)

Many argue that absolutist moral theories -- those that prohibit particular kinds of actions or trade-offs under all circumstances -- cannot adequately account for the permissibility of risky actions. In this dissertation, I defend various versions of absolutism against this critique, using overlooked resources from formal decision theory. Against the prevailing view, I argue that almost all absolutist moral theories can give systematic and plausible verdicts about what to do in risky cases. In doing so, I show that critics have (...) overlooked: (1) the fact that absolutist theories -- and moral theories, more generally -- underdetermine their formal decision-theoretic representations; (2) that decision theories themselves can be generalised to better accommodate distinctively absolutist commitments. Overall, this dissertation demonstrates that we can navigate a risky world without compromising our moral commitments. (shrink)

The basic Bayesian model of credence states, where each individual’s belief state is represented by a single probability measure, has been criticized as psychologically implausible, unable to represent the intuitive distinction between precise and imprecise probabilities, and normatively unjustifiable due to a need to adopt arbitrary, unmotivated priors. These arguments are often used to motivate a model on which imprecise credal states are represented by sets of probability measures. I connect this debate with recent work in Bayesian cognitive science, where (...) probabilistic models are typically provided with explicit hierarchical structure. Hierarchical Bayesian models are immune to many classic arguments against single-measure models. They represent grades of imprecision in probability assignments automatically, have strong psychological motivation, and can be normatively justified even when certain arbitrary decisions are required. In addition, hierarchical models show much more plausible learning behavior than flat representations in terms of sets of measures, which—on standard assumptions about update—rule out simple cases of learning from a starting point of total ignorance. (shrink)

Certain well-known intuitions suggest that, contrary to traditional thinking in epistemology, knowledge judgements are shifty—i.e., that judgements about whether somebody knows something can shift in stringency with context. Some take these intuitions to show that knowledge judgements are shifty. Jennifer Nagel and Mikkel Gerken have argued, however, that closer attention to the psychological processes which underlie knowledge judgements shows how traditional non-shifty thinking can be preserved. They each defend moderate classical invariantism—the view that the epistemic standard for knowing is always (...) moderate—by drawing on recent work in cognitive psychology. This paper argues that neither attempt succeeds. (shrink)

Most agree that, if all else is equal, patients should be provided with enough information about proposed medical therapies to allow them to make an informed decision about what, if anything, they wish to receive. This is the principle of informed choice; it is closely related to the notion of informed consent. Contemporary clinical trials are analysed according to classical statistics. This paper puts forward the argument that classical statistics does not provide the right sort of information for informing choice. (...) The notion of probability used by classical statistics is complex and difficult to communicate. Therapeutic decisions are best informed by statistical approaches that assign probabilities to hypotheses about the benefits and harms of therapies. Bayesian approaches to statistical inference provide such probabilities. (shrink)

Two distinct issues are sometimes confused in the base rate literature: Why do people make logical mistakes in the assessment of probabilities? and why do subjects not use base rates the way experimenters do? The latter problem may often reflect differences in an implicit reference class rather than a disinclination to update a base rate by Bayes' theorem. Also important are considerations concerning the interaction of several potentially relevant base rates.

We argue that two long-term goals of AI research stand in tension with one another. The first involves creating AI that is safe, where this is understood as solving the problem of value alignment. The second involves creating artificial general intelligence, meaning AI that operates at or beyond human capacity across all or many intellectual domains. Our argument focuses on the human capacity to make what we call “existential choices”, choices that transform who we are as persons, including transforming what (...) we most deeply value or desire. It is a capacity for a kind of value misalignment, in that the values held prior to making such choices can be significantly different from (misaligned with) the values held after making them. Because of the connection to existentialist philosophers who highlight these choices, we call the resulting form of risk “existentialist risk.” It is, roughly, the risk that results from AI taking an active role in authoring its own values rather than passively going along with the values given to it. On our view, human-like intelligence requires a human-like capacity for value misalignment, which is in tension with the possibility of guaranteeing value alignment between AI and humans. (shrink)

Cognitive modules are internal mental structures. Some theorists and empirical researchers hypothesise that the human mind is either partially or massively comprised of structures that are modular in nature. Is the massive modularity of mind hypothesis a cogent view about the ontological nature of human mind or is it, rather, an effective/ineffective adaptationist discovery heuristic for generating predictively successful hypotheses about both heretofore unknown psychological traits and unknown properties of already identified psychological traits? Considering the inadequacies of the case in (...) favour of massive modularity as an ontological hypothesis, I suggest approaching and valuing massive modularity as an adaptationist discovery heuristic. (shrink)

Does the most common response given by participants presented with Tversky and Kahneman’s famous taxi cab problem amount to a violation of Bayes’ theorem? In other words, do they fall victim to so-called base-rate fallacy? In the present paper, following an earlier suggestion by Crupi and Girotto, we will identify the logical arguments underlying both the original diagnosis of irrationality in this reasoning task under uncertainty and a number of objections that have been raised against such a diagnosis. This will (...) enable us to show firstly that, contrary to the dismissive arguments recently put forward by Elqayam and Evans, empirical evidence turns out to be quite useful in addressing questions of this kind. Therefore, it can make a significant contribution to moving the base-rate fallacy controversy forward. Secondly, the available empirical evidence (though limited and sometimes inconclusive) seems to support the charge of irrationality levelled against the majority of participants presented with the taxi cab problem, and hence suggests that base-rate neglect is a real fallacy − that is the conclusion of our analysis. (shrink)

The underutilization of base rates is a consistent finding. The strong claim that base rates are ignored has been rejected and this needs no further emphasis. Following the path of “normal science,” research examines the conditions predicting changes in the degree of underutilization. A scientific revolution that might dethrone the heuristics and biases paradigm is not in sight.

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)

Human beings are internally inconsistent in various ways. One way to develop this thought involves using the language of value alignment: the values we hold are not always aligned with our behavior, and are not always aligned with each other. Because of this self-misalignment, there is room for potential projects of human enhancement that involve achieving a greater degree of value alignment than we presently have. Relatedly, discussions of AI ethics sometimes focus on what is known as the value alignment (...) problem, the challenge of how to build AI that acts in accordance with our human values. We argue that there is an especially close connection between solving the value alignment problem in AI ethics and using AI to pursue certain forms of human enhancement. But in addition, we also argue that there are important limits to what kinds of human enhancement can be pursued in this way, because some forms of human enhancement—namely moral revolutions—involve a kind of value misalignment rather than alignment. (shrink)

Bayesian reasoning has been applied formally to statistical inference, machine learning and analysing scientific method. Here I apply it informally to more common forms of inference, namely natural language arguments. I analyse a variety of traditional fallacies, deductive, inductive and causal, and find more merit in them than is generally acknowledged. Bayesian principles provide a framework for understanding ordinary arguments which is well worth developing.

Koehler's call for a reanalysis of the base rate fallacy is particularly important in the applied domain of accounting, since base rate data appear to be an important input for many accounting tasks. In this commentary I discuss the use of base rates in accounting and explain why more flexible standards of performance are important when judging the use of base rates.

Davidsonian analyses of action reports like ‘Alvin chased Theodore around a tree’ are often viewed as supporting the hypothesis that sentences of a human language H have truth conditions that can be specified by a Tarski-style theory of truth for H. But in my view, simple cases of adverbial modification add to the reasons for rejecting this hypothesis, even though Davidson rightly diagnosed many implications involving adverbs as cases of conjunct-reduction in the scope of an existential quantifier. I think the (...) puzzles in this vicinity reflect “framing effects,” which reveal the implausibility of certain assumptions about how linguistic meaning is related to truth and logical form. We need to replace these assumptions with alternatives, instead of positing implausible values of event-variables or implausible relativizations of truth to linguistic descriptions of actual events. (shrink)

Over the past few decades, cognitive science has identified several forms of reasoning that make essential use of conceptual knowledge. Despite significant theoretical and empirical progress, there is still no unified framework for understanding how concepts are used in reasoning. This paper argues that the theory of conceptual spaces is capable of filling this gap. Our strategy is to demonstrate how various inference mechanisms which clearly rely on conceptual information—including similarity, typicality, and diagnosticity-based reasoning—can be modeled using principles derived from (...) conceptual spaces. Our first topic analyzes the role of expectations in inductive reasoning and their relation to the structure of our concepts. We examine the relationship between using generic expressions in natural language and common-sense reasoning as a second topic. We propose that the strength of a generic can be described by distances between properties and prototypes in conceptual spaces. Our third topic is category-based induction. We demonstrate that the theory of conceptual spaces can serve as a comprehensive model for this type of reasoning. The final topic is analogy. We review some proposals in this area, present a taxonomy of analogical relations, and show how to model them in terms of distances in conceptual spaces. We also briefly discuss the implications of the model for reasoning with concepts in artificial systems. (shrink)

We have been oversold on the base rate fallacy in probabilistic judgment from an empirical, normative, and methodological standpoint. At the empirical level, a thorough examination of the base rate literature (including the famous lawyer–engineer problem) does not support the conventional wisdom that people routinely ignore base rates. Quite the contrary, the literature shows that base rates are almost always used and that their degree of use depends on task structure and representation. Specifically, base rates play a relatively larger role (...) in tasks where base rates are implicitly learned or can be represented in frequentist terms. Base rates are also used more when they are reliable and relatively more diagnostic than available individuating information. At the normative level, the base rate fallacy should be rejected because few tasks map unambiguously into the narrow framework that is held up as the standard of good decision making. Mechanical applications of Bayes's theorem to identify performance errors are inappropriate when (1) key assumptions of the model are either unchecked or grossly violated, and (2) no attempt is made to identify the decision maker's goals, values, and task assumptions. Methodologically, the current approach is criticized for its failure to consider how the ambiguous, unreliable, and unstable base rates of the real world are and should be used. Where decision makers' assumptions and goals vary, and where performance criteria are complex, the traditional Bayesian standard is insufficient. Even where predictive accuracy is the goal in commonly defined problems, there may be situations (e.g., informationally redundant environments) in which base rates can be ignored with impunity. A more ecologically valid research program is called for. This program should emphasize the development of prescriptive theory in rich, realistic decision environments. (shrink)

Commentators agree that simple conclusions about a general base rate fallacy are not appropriate. It is more constructive to identify conditions under which base rates are differentially weighted. Commentators also agree that improving the ecological validity of the research is desirable, although this is less important to those interested exclusively in psychological processes. The philosophers and ecologists among the commentators offer a kinder perspective on base rate reasoning than the psychologists. My own perspective is that the interesting questions (both psychological (...) and normative/prescriptive) are best answered through empirical studies that use real-world performance standards. (shrink)

This commentary discusses three points: (1) The implications of the fact that it is rational to ignore base rates if probabilities are estimated by frequencies from samples without missing data (natural sampling); (2) second order probabilities distributions are a plausible way to model imprecise probabilities; and (3) Bayesian networks represent a normative reference for multi-cue models of probabilistic inference.

Failure to consider base rate is regarded as potentially hazardous, mainly because its consideration is assumed to be determined solely by P(H/D), the probability of the individuating data if the hypothesis is true, and not at all by P(D/˜H), the probability if the hypothesis is false. However, when P(D/˜H) is unconfounded from P(D/H), it turns out to be the stronger determinant of base rate consideration.

The model proposed by Redish et al. considers vulnerabilities within decision systems based on expectancy-value assumptions. Further understanding of processes leading to addiction can be gained by considering other inputs to decision-making, particularly affective associations with behaviors. This consideration suggests additional decision-making vulnerabilities that might explain addictive behaviors.

Bounded rationality gets a bad rap in epistemology. It is argued that theories of bounded rationality are overly context‐sensitive; conventionalist; or dependent on ordinary language (Carr, 2022; Pasnau, 2013). In this paper, I have three aims. The first is to set out and motivate an approach to bounded rationality in epistemology inspired by traditional theories of bounded rationality in cognitive science. My second aim is to show how this approach can answer recent challenges raised for theories of bounded rationality. My (...) third aim is to clarify the role of rational ideals in bounded rationality. (shrink)

Setting the two hypotheses of complete neglect and full use of base rates against each other is inappropriate. The proper question concerns the degree to which base rates are used (or neglected), and under what conditions. We outline alternative approaches and recommend regression analysis. Koehler's conclusion that we have been oversold on the base rate fallacy seems to be premature.

In an influential recent paper, Hawthorne, Rothschild, and Spectre (“HRS”) argue that belief is weak. More precisely: they argue that the referent of believe in ordinary language is much weaker than epistemologists usually suppose; that one needs very little evidence to be entitled to believe a proposition in this sense; and that the referent of believe in ordinary language just is the ordinary concept of belief. I argue here to the contrary. HRS identify two alleged tests of weakness – the (...) neg-raising and weak upper bounds tests, as I call them – which they claim believe and think pass. But I identify several other expressions in ordinary English for attributing belief, all of which fail both tests. Therefore, even if HRS are correct that believe and think refer to a weak attitude, it does not follow that the ordinary concept of belief is weak. I conclude by raising some problems for the accounts of belief as guessing, building on HRS's arguments, due to Kevin Dorst, Matt Mandelkern, and Ben Holguín. (shrink)

This article conceptualises theories of ethics relevant to the recognised problem of decision variability in child protection. Within this field, social workers are faced with multiple ethical imperatives when making decisions about children’s care. They must respond to justice principles concerned with duties and consequences, as well as ethical obligations created by the relational and contextual elements of each case. Recent scholarship on decision variability highlights the justice issues that arise when decisions in response to apparently similar cases differ. An (...) ethical imperative is that similar cases should be treated ‘like for like’ so that children’s and family’s rights are upheld consistently. This article contends that ethical concepts relating to both universalist duties such as respect for persons, extended by the concept of interactive universalism, and contextual responses based on an ethic of care, help theorise the complexities of ethical decisions in child protection. These concepts develop a nuanced understanding of the ways social workers resist risk discourses, may make decisions reflecting the participation of service users, and contextual evaluations of risk based on understanding service user’s life histories. Understanding this combination helps explain the reasons behind variability, and evaluate the moral acceptability or otherwise of apparently variable decisions. (shrink)

Any ethical argument involving the problems of access to assisted reproductive technologies should entail the discussion of the decision protocol and consider the individual deliberating on the appropriateness of these remedies from the point of view of self and community. Yet, arguments based on patients' own moral calculations are rare in the bioethics literature. The moral voice behind most discourses concerning ARTs is that of an outwardly independent spectator, who nonetheless proceeds to justify a personally significant worldview in the utilization (...) of these resources. Investigators grounded in social and legal sciences have offered relevant arguments in this regard, but because their discourses are derived from research protocols specific to their respective disciplines, they fail to provide a general rationale applicable to moral deliberation. (shrink)

This paper studies information transmission between an uninformed decision maker and an informed agent who have asymmetric beliefs on the sender’s ability to observe the state of nature. We find that even when the material payoffs of the players are perfectly aligned, the sender’s over- and underconfidence on his information give rise to information loss in communication, although they do not by themselves completely eliminate information transmission in equilibrium. However, an underconfident sender may prefer no communication to informative communication. We (...) also show that when the sender is biased, overconfidence can lead to more information transmission and welfare improvement. (shrink)

Is logic normative for belief? A standard approach to answering this question has been to investigate bridge principles relating claims of logical consequence to norms for belief. Although the question is naturally an epistemic one, bridge principles have typically been investigated in isolation from epistemic debates over the correct norms for belief. In this paper we tackle the question of whether logic is normative for belief by proposing a Kripkean model theory accounting for the interaction between logical, doxastic, epistemic and (...) deontic notions and using this model theory to show which bridge principles are implied by epistemic norms that we have independent reason to accept, for example, theknowledge normand thetruth norm. We propose a preliminary theory of the interaction between logical, doxastic, epistemic and deontic notions that has among its commitments bridge principles expressing how logic is normative for belief. We also show how our framework suggests that logic is exceptionally normative. (shrink)