Abstract The typical explanation of an event or process which attracts the label ‘conspiracy theory’ is an explanation that conflicts with the account advanced by the relevant epistemic authorities. I argue that both for the layperson and for the intellectual, it is almost never rational to accept such a conspiracy theory. Knowledge is not merely shallowly social, in the manner recognized by social epistemology, it is also constitutively social: many kinds of knowledge only become accessible thanks to the agent's embedding (...) in an environment that includes other epistemic agents. Moreover, advances in knowledge typically require ongoing immersion in this social environment. But the intellectual who embraces a conspiracy theory risks cutting herself off from this environment, and therefore epistemically disabling herself. Embracing a conspiracy theory therefore places at risk the ability to engage in genuine enquiry, including the enquiry needed properly to evaluate the conspiracy theory. (shrink)

ABSTRACT Understanding is a demanding epistemic state. It involves not just knowledge that things are thus and so, but grasping the reasons why and seeing how things hang together. Understanding, then, typically requires inquiry. Many of our inquiries are conducted online nowadays, with the help of search engines, forums, and social media platforms. In this paper, I explore the idea that online inquiry easily leads to what I will call online illusions of understanding. Both the structure of online information presentation (...) (with hyperlinks, shares, retweets, likes, etc.) and the operation of recommender systems and the like make it easy for people using them to form the impression that they are conducting inquiry responsibly, whereas they are in fact fed with irrelevant information, or, even worse, falsehoods, misinformation, disinformation, or outright conspiracy theories. (shrink)

There is a large gap between the specialized knowledge of scientists and laypeople’s understanding of the sciences. The novice-expert problem arises when non-experts are confronted with (real or apparent) scientific disagreement, and when they don’t know whom to trust. Because they are not able to gauge the content of expert testimony, they rely on imperfect heuristics to evaluate the trustworthiness of scientists. This paper investigates why some bodies of scientific knowledge become polarized along political fault lines. Laypeople navigate conflicting epistemic (...) and social demands in their acceptance of scientific testimony; this might explain their deference to scientific fringe theories, which often goes together with denying established scientific theories. I evaluate three approaches to mitigate denialism: improving the message, improving the messenger, and improving the environment in which the message is conveyed. (shrink)

Explanation is a central concept in human psychology. Drawing upon philosophical theories of explanation, psychologists have recently begun to examine the relationship between explanation, probability and causality. Our study advances this growing literature in the intersection of psychology and philosophy of science by systematically investigating how judgments of explanatory power are affected by the prior credibility of a potential explanation, the causal framing used to describe the explanation, the generalizability of the explanation, and its statistical relevance for the evidence. Collectively, (...) the results of our five experiments support the hypothesis that the prior credibility of a causal explanation plays a central role in explanatory reasoning: first, because of the presence of strong main effects on judgments of explanatory power, and second, because of the gate-keeping role it has for other factors. Highly credible explanations were not susceptible to causal framing effects. Instead, highly credible hypotheses were sensitive to the effects of factors which are usually considered relevant from a normative point of view: the generalizability of an explanation, and its statistical relevance for the evidence. These results advance current literature in the philosophy and psychology of explanation in three ways. First, they yield a more nuanced understanding of the determinants of judgments of explanatory power, and the interaction between these factors. Second, they illuminate the close relationship between prior beliefs and explanatory power. Third, they clarify the relationship between abductive and probabilistic reasoning. (shrink)

Naive physics beliefs can be systematically mistaken. They provide a useful test-bed because they are common, and also because their existence must rely on some adaptive advantage, within a given context. In the second part of the commentary we also ask questions about when a whole family of misbeliefs should be considered together as a single phenomenon.

A theory of conceptual development must specify the innate representational primitives, must characterize the ways in which the initial state differs from the adult state, and must characterize the processes through which one is transformed into the other. The Origin of Concepts (henceforth TOOC) defends three theses. With respect to the initial state, the innate stock of primitives is not limited to sensory, perceptual, or sensorimotor representations; rather, there are also innate conceptual representations. With respect to developmental change, conceptual development (...) consists of episodes of qualitative change, resulting in systems of representation that are more powerful than, and sometimes incommensurable with, those from which they are built. With respect to a learning mechanism that achieves conceptual discontinuity, I offer Quinian bootstrapping. TOOC concludes with a discussion of how an understanding of conceptual development constrains a theory of concepts. (shrink)

The commentators raised issues relevant to all three important theses of The Origin of Concepts (henceforth TOOC). Some questioned the very existence of innate representational primitives, and others questioned my claims about their richness and whether they should be thought of as concepts. Some questioned the existence of conceptual discontinuity in the course of knowledge acquisition and others argued that discontinuity is much more common than was portrayed in TOOC. Some raised issues with my characterization of Quinian bootstrapping, and others (...) questioned the dual factor theory of concepts motivated by my picture of conceptual development. (shrink)

To introduce the issue of the tracking and identification of human agents, I examine the ability of an agent to track a human person and distinguish this target from other individuals: The ability to perform person identification. First, I discuss influential mechanistic models of the perceptual recognition of human faces and people. Such models propose detailed hypotheses about the parts and activities of the mental mechanisms that control the perceptual recognition of persons. However, models based on perceptual recognition are incomplete (...) theories of person identification because they do not explain several identification behaviors that are fundamental to human social interactions. Furthermore, recognition-based models tend to appeal to the controversial concept of the “identity” of a person without explaining what determines personal identity and persistence. To overcome these limitations, I propose to integrate the face-recognition program into a broader causal-historical theory of identification. The causal-historical theory of identification complements models focused on perceptual recognition because it can account for the types of non-perceptual identification overlooked by the face-recognition program. Moreover, it can decompose the identification behaviors into tracking processes that succeed or fail to be sensitive to causal characteristics of a target. I illustrate these advantages with a discussion of the difference between the tracking of a person understood as either a causally continuous biological organism or a psychologically continuous mind. Finally, I argue that the causal-historical theory provides a theoretical framework for investigating the tracking of relations between a target and its contextual and historical attributes, such as a target's possessions. (shrink)

Although recent trends in politics and media make it appear that conspiracy theories are on the rise, in fact they have always been present, probably because they are sustained by natural dispositions of the human brain. This is also the case with medical conspiracy theories. This article reviews some of the most notorious health-related conspiracy theories. It then approaches the reasons why people believe these theories, using concepts from cognitive science. On the basis of that knowledge, the article makes normative (...) proposals for public health officials and health workers as a whole, to deal with conspiracy theories, in order to preserve some of the fundamental principles of medical ethics. (shrink)

Should cognitive scientists be any more embarrassed about their lack of a discipline-fixing definition of cognition than biologists are about their inability to define “life”? My answer is “no”. Philosophers seeking a unique “mark of the cognitive” or less onerous but nevertheless categorical characterizations of cognition are working at a level of analysis upon which hangs nothing that either cognitive scientists or philosophers of cognitive science should care about. In contrast, I advocate a pluralistic stance towards uses of the term (...) ‘cognition’ that eschews the urge to treat cognition as a metaphysically well-defined “natural” kind. (shrink)

Twenty years ago Leif Lewin made the case that altruistic motives are more common than selfish motives among voters, politicians, and bureaucrats. We propose that motives and beliefs emerge as reactions to immediate feedback from technical-causal, material-economic, and moral-social aspects of the political task environment. In the absence of certain kinds of technical-causal and material-economic feedback, moral-social feedback leads individuals to the altruism Lewin documents, but also to righteousness (moralized regard for the in-group and disregard for the out-group) and myopia (...) (disregard for distant consequences). The mix of altruism, righteousness, and myopia increases the focus on winning the next high-stakes election rather than on discovering or enforcing socially productive institutions. (shrink)

To approach the many challenges involved in the notion of engineering concepts, it is important to have a clear idea of the starting point – the concepts that people use in their everyday lives, in conversations and in expressing beliefs, desires, intentions and so forth. The first Section of this chapter introduces evidence that I have accumulated over the last many years concerning the flexibility, context-dependence, and vagueness of such common concepts. The concept engineer needs to understand the structure of (...) the “raw material” with which she is working. In Section 2, I summarise some results concerning the amount of individual variation that exists within a single relatively homogenous population of individuals, both in what examples are considered most typical of a category, and in what properties are considered most central to a category (Hampton & Passanisi, 2016). The demonstration of a significant degree of reliable variation in responses to these questions, that is stable over time, illustrates the potential for conceptual engineering interventions to affect individuals’ concepts. Concepts are rarely fixed or uniformly understood in the same way. I then discuss the different ways in which concepts track the world, and I speculate about how different conceptual domains are governed by different criteria of validity or acceptability. This reflection will lead to Section 3 in which I summarise some results from recent research (Thorne, Quilty-Dunn, Smortchova, Shea, & Hampton, 2021), investigating for the first time how people view the value of different familiar concepts. Knowing how people appraise concepts will be a key to developing ideas for improving the reliability and validity of the concepts that they commonly use. A final section contains some (largely speculative) discussion about the implications of work in psychology of concepts for the project of conceptual engineering. (shrink)

Are causal explanations (e.g., “she switched careers because of the COVID pandemic”) treated differently from the corresponding claims that one factor caused another (e.g., “the COVID pandemic caused her to switch careers”)? We examined whether explanatory and causal claims diverge in their responsiveness to two different types of information: covariation strength and mechanism information. We report five experiments with 1,730 participants total, showing that compared to judgments of causal strength, explanatory judgments tend to bemoresensitive to mechanism andlesssensitive to covariation – (...) even though explanatory judgments respond to both types of information. We also report exploratory comparisons to judgments of understanding, and discuss implications of our findings for theories of explanation, understanding, and causal attribution. These findings shed light on the potentially unique role of explanation in cognition. (shrink)

In this dissertation, I argue that understanding possesses unique epistemic value. I propose and defend a novel account of understanding that I call the management account of understanding, which is the view that an agent A understands a subject matter S just in case A has the ability to extract the relevant information and exploit it with the relevant cognitive capacities to answer questions in S. Since inquiry is the process of raising and answering questions, I argue that without understanding, (...) it would be impossible to engage in successful inquiry. I argue that understanding is indispensable for effective cognition and that it is irreducible to other epistemic categories, such as knowledge, justification, or rationality. Understanding is an irreducible component of epistemic excellence. In arguing for this account, I focus on the nature and requirements of cognition and pay less attention to intuitions about hypothetical cases, in contrast to previous approaches to understanding. I draw upon psychology and cognitive science, especially work on the frame problem, to demonstrate the importance (and difficulty) of finding relevant information and exploiting it in relevant ways to answer questions. One’s cognitive system must be organized in such a way that one has the ability to think the relevant thoughts in the relevant ways to answer the relevant questions. This reveals well-defined directions in which future research on understanding should move. In addition to proposing and defending the management account of understanding, I explore several features of understanding, including some interesting consequences of the management account. I argue that the management account and commonly used methods of measuring degrees of understanding imply that understanding can be based on false beliefs. I argue that the management account (and any account of understanding that implies understanding is an ability) implies that understanding can be acquired by luck. I also argue that understanding is ontologically prior to explanation: a good explanation is essentially an act that produces understanding in the relevant cognitive background. (shrink)

Abductive reasoning assigns special status to the explanatory power of a hypothesis. But how do people make explanatory judgments? Our study clarifies this issue by asking: How does the explanatory power of a hypothesis cohere with other cognitive factors? How does probabilistic information affect explanatory judgments? In order to answer these questions, we conducted an experiment with 671 participants. Their task was to make judgments about a potentially explanatory hypothesis and its cognitive virtues. In the responses, we isolated three constructs: (...) Explanatory Value, Rational Acceptability, and Entailment. Explanatory judgments strongly cohered with judgments of causal relevance and with a sense of understanding. Furthermore, we found that Explanatory Value was sensitive to manipulations of statistical relevance relations between hypothesis and evidence, but not to explicit information about the prior probability of the hypothesis. These results indicate that probabilistic information about statistical relevance is a strong determinant of Explanatory Value. More generally, our study suggests that abductive and probabilistic reasoning are two distinct modes of inference. (shrink)

In metaethics, evolutionary debunking arguments combine empirical and epistemological premises to purportedly show that our moral judgments are unjustified. One objection to these arguments has been to distinguish between those judgments that evolutionary influence might undermine versus those that it does not. This response is powerful but not well understood. In this paper I flesh out the response by drawing upon a familiar distinction in the natural sciences, where it is common to distinguish folk judgments from theoretical judgments. I argue (...) that this in turn illuminates the proper scope of the evolutionary debunking argument, but not in an obvious way: it is a very specific type of undermining argument that targets those theories where theoretical judgments are inferred merely from folk judgments. One upshot of this conclusion is that it reveals a verboten methodology in metaethics. The evolutionary debunking argument is therefore much less powerful than its proponents have supposed, but it nevertheless rules out what is perhaps a common way of attempting to justify moral judgments. (shrink)

Political protests, debates on college campuses, and social media tirades make it seem like everyone is speaking their minds today. Surveys, however, reveal that many people increasingly feel like they're walking on eggshells when communicating in public. Speaking your mind can risk relationships and professional opportunities. It can alienate friends and anger colleagues. Isn't it smarter to just put your head down and keep quiet about controversial topics? In this book, Hrishikesh Joshi offers a novel defense of speaking your mind. (...) He explains that because we are social creatures, we never truly think alone. What we know depends on what our community knows. And by bringing our unique perspectives to bear upon public discourse, we enhance our collective ability to reach the truth on a variety of important matters. Speaking your mind is also important for your own sake. It is essential for developing your own thinking. And it's a core aspect of being intellectually courageous and independent. Joshi argues that such independence is a crucial part of a well-lived life. The book draws from Aristotle, John Stuart Mill, Friedrich Nietzsche, Bertrand Russell, and a range of contemporary thinkers to argue that it's OK to speak your mind. Key Features Shows that we have not just a right but a moral duty to publicly share what we know. Argues that discussing your unique ideas with others is essential for developing as a critical thinker. Explores the value of intellectual honesty and independence in the writings of John Stuart Mill and Friedrich Nietzsche and connects their thinking to contemporary problems. Argues that avoiding cultural blind spots today is important for the fate of future generations. (shrink)

The Architecture of the Mind is itself built on foundations that deserve probing. In this brief commentary I focus on these foundations—Carruthers’ conception of modularity, his arguments for thinking that the mind is massively modular in structure, and his view of human cognitive architecture.

The bullshit receptivity scale—a methodological tool that measures the level of profoundness that participants assign to a series of obscure and new-agey, randomly generated statements—has become increasingly popular since its introduction in 2015. Researchers that deploy this scale often frame their research in terms of Harry Frankfurt’s analysis of bullshit, according to which bullshit is discourse produced without regard for the truth. I argue that framing these studies in Frankfurtian terms is detrimental and has led to some misguided theorizing about (...) the mental processes implicated in bullshit receptivity. I argue that we should, instead, frame these studies in terms of what G.A. Cohen calls unclarifiable bullshit. After reviewing some recent theorizing about the psychology of bullshit receptivity, I show how reframing the bullshit receptivity scale in terms of unclarifiable bullshit generates plausible conjectures about the psychological factors responsible for bullshit receptivity. I draw from the literature on the illusion of explanatory depth and the misplaced meaning effect to develop a novel account of bullshit detection and receptivity. I consider some empirical support for my account and draw attention to ways that it can also be extended to account for results from studies that don’t use the bullshit receptivity scale. (shrink)

In everyday life, people typically observe fragments of causal networks. From this knowledge, people infer how novel combinations of causes they may never have observed together might behave. I report on 4 experiments that address the question of how people intuitively integrate multiple causes to predict a continuously varying effect. Most theories of causal induction in psychology and statistics assume a bias toward linearity and additivity. In contrast, these experiments show that people are sensitive to cues biasing various integration rules. (...) Causes that refer to intensive quantities (e.g., taste) or to preferences (e.g., liking) bias people toward averaging the causal influences, whereas extensive quantities (e.g., strength of a drug) lead to a tendency to add. However, the knowledge underlying these processes is fallible and unstable. Therefore, people are easily influenced by additional task‐related context factors. These additional factors include the way data are presented, the difficulty of the inference task, and transfer from previous tasks. The results of the experiments provide evidence for causal model and related theories, which postulate that domain‐general representations of causal knowledge are influenced by abstract domain knowledge, data‐driven task factors, and processing difficulty. (shrink)

The demarcation of pseudoscience has been one of the most important philosophical tasks since the 1960s. During the 1980s, an atmosphere of defeatism started to spread among philosophers of science, some of them claimed the failure of the demarcation project. I defend that the more auspicious approach to the problem might be through the intellectual character of epistemic agents, i.e., from the point of view of vice epistemology. Unfortunately, common lists of undesirable character features are usually based on a priori (...) reasoning, and therefore might be considered artificial or too vague. When we base our position on contemporary behavioural sciences, we can see that the epistemic character of believers in pseudoscience is for the most part determined by two related factors. Firstly, these epistemic agents show a higher level of cognitive laziness. By this I mean an inability or unwillingness to engage in reflective thinking and a reluctance to account for counterevidence. Secondly, they yield more easily to metacognitive overconfidence. This can be broadly understood as so-called “knowledge illusion”, the inability to recognize one’s own intellectual limits. The deficiency usually stems from a misunderstanding of the division of cognitive labour and of the agent’s role in epistemic society. I find the proposed epistemological approach to pseudoscience crucial. Only if we understand the descriptive aspects of the problem, can we think of normative solutions to it. (shrink)

Philosophers agree that scientific explanations aim to produce understanding, and that good ones succeed in this aim. But few seriously consider what understanding is, or what the cues are when we have it. If it is a psychological state or process, describing its specific nature is the job of psychological theorizing. This article examines the role of understanding in scientific explanation. It warns that the seductive, phenomenological sense of understanding is often, but mistakenly, viewed as a cue of genuine understanding. (...) The article closes with a discussion of several new paths of research that tie the psychology of scientific explanation to cognate notions of learning, testimony, and understanding. (shrink)

Behavioral economists have proposed that people are subject to an IKEA effect, whereby they attach greater value to products they make for themselves, like IKEA furniture, than to otherwise indiscernible goods. Recently, cognitive psychologist Tom Stafford has suggested there may be an epistemic analog to this, a kind of epistemic IKEA effect. In this paper, I use Stafford’s suggestion to defend a certain thesis about epistemic value. Specifically, I argue that there is a distinctive epistemic value in being an active (...) producer of epistemic goods, like true belief, as opposed to just a passive recipient of such goods, and that because of this it can be rationally permissible to sacrifice truth in a certain way for the sake of this other value. In particular, it is rationally permissible for an epistemic agent to prefer a belief set that contains fewer overall truths but more truths obtained through the agent’s own intellectual labor, in something like the way that a practical agent might prefer furniture they have made through their own manual labor to inherently superior furniture made by someone else. In making my case, I draw on Ernest Sosa’s discussion of causation and praxical epistemic values, and Jennifer Lackey’s testimony-based criticism of the credit view of knowledge. After defending my thesis about epistemic value, I further clarify it by connecting it to the focus of Stafford’s discussion, conspiracy theorists. (shrink)

Behavioral economists have proposed that people are subject to an IKEA effect, whereby they attach greater value to products they make for themselves, like IKEA furniture, than to otherwise indiscernible goods. Recently, cognitive psychologist Tom Stafford has suggested there may be an epistemic analog to this, a kind of epistemic IKEA effect. In this paper, I use Stafford’s suggestion to defend a certain thesis about epistemic value. Specifically, I argue that there is a distinctive epistemic value in being an active (...) producer of epistemic goods, like true belief, as opposed to just a passive recipient of such goods, and that because of this it can be rationally permissible to sacrifice truth in a certain way for the sake of this other value. In particular, it is rationally permissible for an epistemic agent to prefer a belief set that contains fewer overall truths but more truths obtained through the agent’s own intellectual labor, in something like the way that a practical agent might prefer furniture they have made through their own manual labor to inherently superior furniture made by someone else. In making my case, I draw on Ernest Sosa’s discussion of causation and praxical epistemic values, and Jennifer Lackey’s testimony-based criticism of the credit view of knowledge. After defending my thesis about epistemic value, I further clarify it by connecting it to the focus of Stafford’s discussion, conspiracy theorists. (shrink)

This paper reports the first empirical investigation of the hypothesis that epistemic appraisals form part of the structure of concepts. To date, studies of concepts have focused on the way concepts encode properties of objects and the way those features are used in categorization and in other cognitive tasks. Philosophical considerations show the importance of also considering how a thinker assesses the epistemic value of beliefs and other cognitive resources and, in particular, concepts. We demonstrate that there are multiple, reliably (...) judged, dimensions of epistemic appraisal of concepts. Four of these dimensions are accounted for by a common underlying factor capturing how well people believe they understand a concept. Further studies show how dimensions of concept appraisal relate to other aspects of concepts. First, they relate directly to the hierarchical organization of concepts, reflecting the increase in specificity from superordinate to basic and subordinate levels. Second, they predict inductive choices in category-based induction. Our results suggest that epistemic appraisals of concepts form a psychologically important yet previously overlooked aspect of the structure of concepts. These findings will be important in understanding why individuals sometimes abandon and replace certain concepts; why social groups do so, for example, during a “scientific revolution”; and how we can facilitate such changes when we engage in deliberate “conceptual engineering” for epistemic, social, and political purposes. (shrink)

ABSTRACT The illusion of explanatory depth, which has been identified by cognitive psychologists, may play a prominent role in encouraging regulatory action. This special type of overconfidence would logically lead regulators to believe that they are aware of the relevant causes and consequences of the activities they might regulate, and of the unintended side effects of the regulatory actions they are contemplating. So, as with other cognitive biases, the illusion of explanatory depth is likely to lead to mistakes. And unlike (...) the biases that have been the focus of so much behavioral economics, the illusion of explanatory depth is uniquely resistant to correction by those who are aware of it as a general problem and rigorously attempt to keep it under control. (shrink)

Definitions may seem marginal to the sociological enterprise but can be very useful; however, they can also lead to serious errors. Examples of both are given in this article. Different types of definitions are presented, and their relevance for sociology is highlighted. A stipulative definition, for example, is very useful in sociology, as opposed to lexical and ostensive definitions. The definition of a concept that is used in a sociological analysis has to be sociological in nature, and the concept cannot (...) have the same meaning as it has in everyday language. Additional items to bear in mind when a definition is put together are discussed, including some tips on how to proceed that come from political science (Sartori, Collier, Goertz). A definition can also be very helpful in the research process itself by indicating which are the important aspects of some phenomenon to focus on (Weber, Blumer). On the negative side, a term that is not properly defined may lead to misunderstandings as well as to a false sense of agreement with other uses of the term. (shrink)

This article focuses on an area of study that may be called folk economics and that is currently not on the social science agenda. Folk economics has as its task to analyze and explain how people view the economy and how it works; what categories they use in doing so; and what effect this has on the economy and society. Existing studies in economics and sociology that are relevant to this type of study are presented and discussed. A theoretical framework (...) for analyzing folk economic issues is suggested, centered on the distinction between episteme and doxa or between scientific knowledge, on the one hand, and everyday knowledge, on the other. This is then applied to an exploratory case study of the role that folk economics played in Trump’s presidential campaign. It is shown that Trump and his voters thought in a parallel way on key economic issues, especially protectionism. (shrink)

The orthodox view of social cognition maintains that mentalizing is an important and pervasive element of our ordinary social interactions. The orthodoxy has come under scrutiny from various sources recently. Critics from the phenomenological tradition argue that phenomenological reflection on our social interactions tells against the orthodox view. Proponents of pluralistic folk psychology argue that our ordinary social interactions extend far beyond mentalizing. Both sorts of critics argue that emphasis in social cognition research ought to be on other elements of (...) our social practices. In this paper, I consider social explanations specifically and argue that social explanations are implicated in many of the social practices highlighted by critics of the orthodox view. (shrink)

Topics in Cognitive Science, Volume 14, Issue 1, Page 31-44, January 2022.

Scientific cognition is a hard-won achievement, both from a historical point of view and a developmental point of view. Here, I review seven facets of lay cognition that run counter to, and often impede, scientific cognition: incompatible folk theories, missing ontologies, tolerance for shallow explanations, tolerance for contradictory explanations, privileging explanation over empirical data, privileging testimony over empirical data, and misconceiving the nature of science itself. Most of these facets have been investigated independent of the others, and I propose directions (...) for future research that might integrate them so as to explore potential commonalities among seemingly disparate obstacles to science learning, as well as potential strategies for bridging lay cognition and scientific cognition in the context of science education. (shrink)

In this article we focus on the concept of concept in conceptual change. We argue that (1) theories of higher learning must often employ two different notions of concept that should not be conflated: psychological and scientific concepts. The usages for these two notions are partly distinct and thus straightforward identification between them is unwarranted. Hence, the strong analogy between scientific theory change and individual learning should be approached with caution. In addition, we argue that (2) research in psychology and (...) cognitive science provides a promising theoretical basis for developing explanatory mechanistic models of conceptual change. Moreover, we argue that (3) arguments against deeper integration between the fields of psychology and conceptual change are not convincing, and that recent theoretical developments in the cognitive sciences might prove indispensable in filling in the details in mechanisms of conceptual change. (shrink)

A central question in cognitive research concerns how new properties are generalized to categories. This article introduces a model of how generalizations involve a process of causal inference in which people estimate the likely presence of the new property in individual category exemplars and then the prevalence of the property among all category members. Evidence in favor of this causal‐based generalization (CBG) view included effects of an existing feature’s base rate (Experiment 1), the direction of the causal relations (Experiments 2 (...) and 4), the number of those relations (Experiment 3), and the distribution of features among category members (Experiments 4 and 5). The results provided no support for an alternative view that generalizations are promoted by the centrality of the to‐be‐generalized feature. However, there was evidence that a minority of participants based their judgments on simpler associative reasoning processes. (shrink)

Can understanding be based on false beliefs? I argue that it can. I first argue that the best way to understand the question is that it is whether one can increase one's degree of understanding by adopting an overall less accurate body of beliefs. I identify three sufficient conditions for one body of beliefs to be more accurate than another. Next, I appeal to two widely used methods of comparing degrees of understanding. With these methods, I show that understanding can (...) be gained by acquiring false beliefs. In addition, I show that this implies that understanding is not factive. (shrink)

Consider people’s ordinary concept of belief. This concept seems to pick out a particular psychological state. Indeed, one natural view would be that the concept of belief works much like the concepts one finds in cognitive science – not quite as rigorous or precise, perhaps, but still the same basic type of notion. But now suppose we turn to other concepts that people ordinarily use to understand the mind. Suppose we consider the concept happiness. Or the concept love. How are (...) these concepts to be understood? One obvious hypothesis would be that they are best understood as being more or less like the concept of belief. Maybe these concepts, too, pick out a particular mental state and thereby enable people to predict, explain and understand others’ behavior. We will argue that this hypothesis is mistaken. Instead, we suggest that the different concepts people use to understand the mind are fundamentally different from each other. Some of these concepts do indeed serve simply to pick out a particular mental state, but others allow a role for evaluative judgments. So, for example, our claim will be that when people are wondering whether a given agent is truly ‘happy’ or ‘in love,’ they are not merely trying to figure out whether this agent has a particular sort of mental state. They are also concerned in a central way with evaluating the agent herself. In short, our aim is to point to a striking sort of difference between the different concepts that people use to pick out psychological attitudes. We will be.. (shrink)