A long tradition of psychological research has explored the distinction between characteristics that are part of the self and those that lie outside of it. Recently, a surge of research has begun examining a further distinction. Even among characteristics that are internal to the self, people pick out a subset as belonging to the true self. These factors are judged as making people who they really are, deep down. In this paper, we introduce the concept of the true self and (...) identify features that distinguish people’s understanding of the true self from their understanding of the self more generally. In particular, we consider recent findings that the true self is perceived as positive and moral, and that this tendency is actor-observer invariant and cross-culturally stable. We then explore possible explanations for these findings and discuss their implications for a variety of issues in psychology. (shrink)

There is a robust scientific consensus concerning climate change and evolution. But many people reject these expert views, in favour of beliefs that are strongly at variance with the evidence. It is tempting to try to explain these beliefs by reference to ignorance or irrationality, but those who reject the expert view seem often to be no worse informed or any less rational than the majority of those who accept it. It is also tempting to try to explain these beliefs (...) by reference to epistemic overconfidence. However, this kind of overconfidence is apparently ubiquitous, so by itself it cannot explain the difference between those who accept and those who reject expert views. Instead, I will suggest that the difference is in important part explained by differential patterns of epistemic deference, and these patterns, in turn, are explained by the cues that we use to filter testimony. We rely on cues of benevolence and competence to distinguish reliable from unreliable testifiers, but when debates become deeply politicized, asserting a claim may itself constitute signalling lack of reliability. (shrink)

Causal understanding is a defining characteristic of human cognition. Like many animals, human children learn to control their bodily movements and act effectively in the environment. Like a smaller subset of animals, children intervene: they learn to change the environment in targeted ways. Unlike other animals, children grow into adults with the causal reasoning skills to develop abstract theories, invent sophisticated technologies and imagine alternate pasts, distant futures and fictional worlds. In this Review, we explore the development of human-unique causal (...) learning and reasoning from evolutionary and ontogenetic perspectives. We frame our discussion using an ‘interventionist’ approach. First, we situate causal understanding in relation to cognitive abilities shared with non-human animals. We argue that human causal understanding is distinguished by its depersonalized (objective) and decontextualized (general) representations. Using this framework, we next review empirical findings on early human causal learning and reasoning and consider the naturalistic contexts that support its development. Then we explore connections to related abilities. We conclude with suggestions for ongoing collaboration between developmental, cross-cultural, computational, neural and evolutionary approaches to causal understanding. (shrink)

Previous research in Explainable Artificial Intelligence (XAI) suggests that a main aim of explainability approaches is to satisfy specific interests, goals, expectations, needs, and demands regarding artificial systems (we call these “stakeholders' desiderata”) in a variety of contexts. However, the literature on XAI is vast, spreads out across multiple largely disconnected disciplines, and it often remains unclear how explainability approaches are supposed to achieve the goal of satisfying stakeholders' desiderata. This paper discusses the main classes of stakeholders calling for explainability (...) of artificial systems and reviews their desiderata. We provide a model that explicitly spells out the main concepts and relations necessary to consider and investigate when evaluating, adjusting, choosing, and developing explainability approaches that aim to satisfy stakeholders' desiderata. This model can serve researchers from the variety of different disciplines involved in XAI as a common ground. It emphasizes where there is interdisciplinary potential in the evaluation and the development of explainability approaches. (shrink)

We are constantly called upon to evaluate the evidential weight of testimony, and to balance its deliverances against our own independent thinking. ‘Intellectual autonomy’ is the virtue that is supposed to be displayed by those who engage in cognition in this domain well. I argue that this is at best a misleading label for the virtue, because virtuous cognition in this domain consists in thinking with others, and intelligently responding to testimony. I argue that the existing label supports an excessively (...) individualistic conception of good thinking, both within and outside philosophy. I propose replacing ‘intellectual autonomy’ with ‘intellectual interdependence’, which properly emphasises the depth of our reliance on one another, without suggesting we ought ever to be epistemically servile. (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)

Except for a patina of twenty-first century modernity, in the form of logic and language, philosophy is exactly the same now as it ever was; it has made no progress whatsoever. We philosophers wrestle with the exact same problems the Pre-Socratics wrestled with. Even more outrageous than this claim, though, is the blatant denial of its obvious truth by many practicing philosophers. The No-Progress view is explored and argued for here. Its denial is diagnosed as a form of anosognosia, a (...) mental condition where the affected person denies there is any problem. The theories of two eminent philosophers supporting the No-Progress view are also examined. The final section offers an explanation for philosophy 's inability to solve any philosophical problem, ever. The paper closes with some reflections on philosophy 's future. (shrink)

In this paper, we aim to show that the framework of embedded, distributed, or extended cognition offers new perspectives on social cognition by applying it to one specific domain: the psychology of memory. In making our case, first we specify some key social dimensions of cognitive distribution and some basic distinctions between memory cases, and then describe stronger and weaker versions of distributed remembering in the general distributed cognition framework. Next, we examine studies of social influences on memory in cognitive (...) psychology, and identify the valuable concepts and methods to be extended and embedded in our framework; we focus in particular on three related paradigms: transactive memory, collaborative recall, and social contagion. Finally, we sketch our own early studies of individual and group memory developed within our framework of distributed cognition, on social contagion of autobiographical memories, collaborative flashbulb memories, and memories of high school at a high school reunion. We see two reciprocal benefits of this conceptual and empirical framework to social memory phenomena: that ideas about distributed cognition can be honed against and tested with the help of sophisticated methods in the social cognitive psychology of memory; and conversely, that a range of social memory phenomena that are as yet poorly understood can be approached afresh with theoretically motivated extensions of existing empirical paradigms. (shrink)

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)

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)

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)

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)

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)

Scientific understanding is a fundamental goal of science. However, there is currently no good way to measure the scientific understanding of agents, whether these be humans or Artificial Intelligence systems. Without a clear benchmark, it is challenging to evaluate and compare different levels of scientific understanding. In this paper, we propose a framework to create a benchmark for scientific understanding, utilizing tools from philosophy of science. We adopt a behavioral conception of understanding, according to which genuine understanding should be recognized (...) as an ability to perform certain tasks. We extend this notion of scientific understanding by considering a set of questions that gauge different levels of scientific understanding, covering information retrieval, the capability to arrange information to produce an explanation, and the ability to infer how things would be different under different circumstances. We suggest building a Scientific Understanding Benchmark (SUB), formed by a set of these tests, allowing for the evaluation and comparison of scientific understanding. Benchmarking plays a crucial role in establishing trust, ensuring quality control, and providing a basis for performance evaluation. By aligning machine and human scientific understanding we can improve their utility, ultimately advancing scientific understanding and helping to discover new insights within machines. (shrink)

This paper provides an inferentialist account of model-based understanding by combining a counterfactual account of explanation and an inferentialist account of representation with a view of modeling as extended cognition. This account makes it understandable how the manipulation of surrogate systems like models can provide genuinely new empirical understanding about the world. Similarly, the account provides an answer to the question how models, that always incorporate assumptions that are literally untrue of the model target, can still provide factive explanations. Finally, (...) the paper shows how the contrastive counterfactual theory of explanation can provide tools for assessing the explanatory power of models. (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)

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)

Scientific and ‘intuitive’ or ‘folk’ theories are typically characterized as serving three critical functions: prediction, explanation, and control. While prediction and control have clear instrumental value, the value of explanation is less transparent. This paper reviews an emerging body of research from the cognitive sciences suggesting that the process of seeking, generating, and evaluating explanations in fact contributes to future prediction and control, albeit indirectly by facilitating the discovery and confirmation of instrumentally valuable theories. Theoretical and empirical considerations also suggest (...) why explanations may nonetheless feel intrinsically valuable. The paper concludes by considering some implications of the psychology of explanation for a naturalized philosophy of explanation. (shrink)

The rise of appeals to intuitive theories in many areas of cognitive science must cope with a powerful fact. People understand the workings of the world around them in far less detail than they think. This illusion of knowledge depth has been uncovered in a series of recent studies and is caused by several distinctive properties of explanatory understanding not found in other forms of knowledge. Other experimental work has shown that people do have skeletal frameworks of expectations that constrain (...) richer ad hoc theory construction on the fly. These frameworks are supplemented by an ability to evaluate and rely on the division of cognitive labour in one's culture, an ability shown to be present even in young children. (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)

What does it take to understand a phenomenon ideally, or to the highest conceivable extent? In this paper, we answer this question by arguing for five necessary conditions for ideal understanding: (i) representational accuracy, (ii) intelligibility, (iii) truth, (iv) reasonable endorsement, and (v) fitting. Even if one disagrees that there is some form of ideal understanding, these five conditions can be regarded as sufficient conditions for a particularly deep level of understanding. We then argue that grasping, novel predictions, and transparency (...) are not reasonable conditions for ideal understanding. (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)

Conviction Narrative Theory (CNT) is a theory of choice underradical uncertainty– situations where outcomes cannot be enumerated and probabilities cannot be assigned. Whereas most theories of choice assume that people rely on (potentially biased) probabilistic judgments, such theories cannot account for adaptive decision-making when probabilities cannot be assigned. CNT proposes that people usenarratives– structured representations of causal, temporal, analogical, and valence relationships – rather than probabilities, as the currency of thought that unifies our sense-making and decision-making faculties. According to CNT, (...) narratives arise from the interplay between individual cognition and the social environment, with reasoners adopting a narrative that feels “right” to explain the available data; using that narrative to imagine plausible futures; and affectively evaluating those imagined futures to make a choice. Evidence from many areas of the cognitive, behavioral, and social sciences supports this basic model, including lab experiments, interview studies, and econometric analyses. We identify 12 propositions to explain how the mental representations (narratives) interact with four inter-related processes (explanation, simulation, affective evaluation, and communication), examining the theoretical and empirical basis for each. We conclude by discussing how CNT can provide a common vocabulary for researchers studying everyday choices across areas of the decision sciences. (shrink)

Resource rationality may explain suboptimal patterns of reasoning; but what of “anti-Bayesian” effects where the mind updates in a direction opposite the one it should? We present two phenomena — belief polarization and the size-weight illusion — that are not obviously explained by performance- or resource-based constraints, nor by the authors’ brief discussion of reference repulsion. Can resource rationality accommodate them?

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

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)

People are often inaccurate in their predictions of performance on a variety of cognitive tasks. We tested whether receptivity to bullshit – the tendency to perceive meaningless statements as profound – would relate to the accuracy of metacognitive judgments on several problem-solving tasks. Individuals who were highly receptive to bullshit were less accurate in their predictions of performance on creative problem-solving tasks, but not on verbal analogy or recall tasks. Further, individuals with high BS receptivity were less able to discriminate (...) between solvable and unsolvable problems when making metacognitive judgments. These findings support the possibility that the tendency to perceive semantic connections where none exist, as indicated by high bullshit receptivity, may lead to inaccurate predictions of performance on tasks that require noticing and utilizing distant semantic connections. (shrink)

The division of cognitive labor is fundamental to all cultures. Adults have a strong sense of how knowledge is clustered in the world around them and use that sense to access additional information, defer to relevant experts, and ground their own incomplete understandings. One prominent way of clustering knowledge is by disciplines similar to those that comprise the natural and social sciences. Seven studies explored an emerging sense of these discipline‐based ways of clustering of knowledge. Even 5‐year‐olds could cluster knowledge (...) in a manner roughly corresponding to the departments of natural and social sciences in a university, doing so without any explicit awareness of those academic disciplines. But this awareness is fragile early on and competes with other ways of clustering knowledge. Over the next few years, children come to see discipline‐based clusters as having a privileged status, one that may be linked to increasingly sophisticated assumptions about essences for natural kinds. Possible mechanisms for this developmental shift are examined. (shrink)

In pedagogical contexts and in everyday life, we often come to believe something because it would best explain the data. What is it about the explanatory endeavor that makes it essential to everyday learning and to scientific progress? There are at least two plausible answers. On one view, there is something special about having true explanations. This view is highly intuitive: it’s clear why true explanations might improve one’s epistemic position. However, there is another possibility—it could be that the process (...) of seeking, generating, or evaluating explanations itself puts one in a better epistemic position, even when the outcome of the process is not a true explanation. In other words, it could be that accurate explanations are beneficial, or it could be that high-quality explaining is beneficial, where there is something about the activity of looking for an explanation that improves our epistemic standing. The main goal of this paper is to tease apart these two possibilities, both theoretically and empirically, which we align with “Inference to the Best Explanation” and “Explaining for the Best Inference”, respectively. We also provide some initial support for EBI and identify promising directions for future research. (shrink)

Currently, two frameworks of causal reasoning compete: Whereas dependency theories focus on dependencies between causes and effects, dispositional theories model causation as an interaction between agents and patients endowed with intrinsic dispositions. One important finding providing a bridge between these two frameworks is that failures of causes to generate their effects tend to be differentially attributed to agents and patients regardless of their location on either the cause or the effect side. To model different types of error attribution, we augmented (...) a causal Bayes net model with separate error sources for causes and effects. In several experiments, we tested this new model using the size of Markov violations as the empirical indicator of differential assumptions about the sources of error. As predicted by the model, the size of Markov violations was influenced by the location of the agents and was moderated by the causal structure and the type of causal variables. (shrink)

If folk science means individuals having well worked out mechanistic theories of the workings of the world, then it is not feasible. Laypeople’s explanatory understandings are remarkably coarse, full of gaps, and often full of inconsistencies. Even worse, most people overestimate their own understandings. Yet recent views suggest that formal scientists may not be so different. In spite of these limitations, science somehow works and its success offers hope for the feasibility of folk science as well. The success of science (...) arises from the ways in which scientists learn to leverage understandings in other minds and to outsource explanatory work through sophisticated methods of deference and simplification of complex systems. Three studies ask whether analogous processes might be present not only in laypeople but also in young children and thereby form a foundation for supplementing explanatory understandings almost from the start of our first attempts to make sense of the world. (shrink)

It has sometimes been suggested that people represent the structure of action in terms of an action tree. A question now arises about the relationship between this action tree representation and people’s moral judgments. A natural hypothesis would be that people first construct a representation of the action tree and then go on to use this representation in making moral judgments. The present paper argues for a more complex view. Specifically, the paper reports a series of experimental studies that appear (...) to show that people’s moral judgments can actually impact their representations of the action tree itself. (shrink)

Interest in the topic of wisdom-focused education has so far not resulted in empirically validated programs for teaching wisdom. To start filling this void, we explore the emerging empirical evidence concerning the fundamental elements required for understanding how one can foster wisdom, with a particular focus on wise reasoning. We define wise reasoning through a combination of intellectual humility, recognition of world in flux/change, open-mindedness to diverse viewpoints, and search for compromise/integration of diverse perspectives. In this article, we review evidence (...) concerning how wise reasoning can be facilitated through experiences, teaching materials, environments and cognitive strategies. We also focus on educators, reviewing emerging evidence on how the process of explaining and guiding others impacts one’s wisdom. We conclude by discussing the development of wisdom-focused education, proposing that greater attention to the situational demands and the variability in wisdom-related characteristics across social contexts should play a critical role in its development. (shrink)

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)

Interest in the demarcation problem is undergoing a boom after being shelved and even given up for dead. Nevertheless, despite current philosophical discussions, there are no substantial advances i...

Research on the division of cognitive labor has found that adults and children as young as age 5 are able to find appropriate experts for different causal systems. However, little work has explored how children and adults decide when to seek out expert knowledge in the first place. We propose that children and adults rely on “mechanism metadata,” information about mechanism information. We argue that mechanism metadata is relatively consistent across individuals exposed to similar amounts of mechanism information, and it (...) is applicable to a wide range of causal systems. In three experiments, we show that adults and children as young as 5 years of age have a consistent sense of the causal complexity of different causal systems, and that this sense of complexity is related to decisions about when to seek expert knowledge, but over development there is a shift in focus from procedural information to internal mechanism information. (shrink)

When does a model explain? When does it promote understanding? A dominant approach to scientific explanation is the interventionist view. According to this view, when X explains Y, intervening on X can produce, prevent or alter Y in some predictable way. In this paper, I argue for two claims. First, I reject a position that many interventionist theorists endorse. This position is that to explain some phenomenon by providing a model is also to understand that phenomenon. While endorsing the interventionist (...) view, I argue that explaining and understanding are distinct scientific achievements. Second, I defend a novel theory of scientific understanding. According to this view, when some model M promotes understanding, M makes available a distinctive mental state. This state is of the same psychological kind as when we grasp events in a narrative as bearing on some ultimate conclusion. To conclude, I show that, given this view, mechanistic explanations often provide a powerful source of understanding that many causal-historical models lack. This paper will be of interest to both philosophers of science and epistemologists engaged in the topics of explanation and understanding. (shrink)

A tradition of work in cognitive science indicates that much of our mental lives is not available to introspection . Though the researchers often present these results as surprising, little has been done to explore the degree to which people presume introspective access to their mental events. In this paper, we distinguish two dimensions of introspective access: the power of access, i.e. whether people believe they can unfailingly or only typically introspect mental events; and the domain of access, i.e. what (...) types of mental events people believe they are able to introspect. We report five experiments carried out to discover where lay beliefs about introspection fall on these dimensions. In our experiments, people did not presume universal introspective access, but they did overestimate the amount of access they actually have, particularly in the case of decisions. (shrink)

If political fake news is a serious concern for democratic politics, no less worrisome is scientific news with patently distorted content. Prima facie, scientific misinformation partially escapes the definition of fake news provided by empirical and philosophical analysis, mainly patterned after political disinformation. Most notably, we aim to show that people are often unaware not only of disseminating, but also of producing false or misleading information. However, by leveraging the philosophical and psychological literature, we advance some reasons for keeping scientific (...) misinformation under the same umbrella, broadening the definition of fake news in order to account for it as well. In concluding, we shall advance some ideas on how to reform scientific communication, which may help to address the issue of scientific misinformation. (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)

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.

Are we entering a major new phase of modern science, one in which our standard, human modes of reasoning and understanding, including heuristics, have decreasing value? The new methods challenge human intelligibility. The digital revolution inspires such claims, but they are not new. During several historical periods, scientific progress has challenged traditional concepts of reasoning and rationality, intelligence and intelligibility, explanation and knowledge. The increasing intelligence of machine learning and networking is a deliberately sought, somewhat alien intelligence. As such, it (...) challenges the traditional, heuristic foresight of expert researchers. Nonetheless, science remains human-centered in important ways—and yet many of our ordinary human epistemic activities are alien to ourselves. This fact has always been the source of “the discovery problem”. It generalizes to the problem of understanding expert scientific practice. Ironically, scientific progress plunges us ever deeper into complexities beyond our grasp. But how is progress possible without traditional realism and the intelligibility realism requires? Pragmatic flexibility offers an answer. (shrink)

In rebellion against low‐dimensional (e.g., two‐factor) theories in psychology, the authors make the case for high‐dimensional theories. This change in perspective requires a shift towards a focus on computation and quantitative reasoning.