This paper details the content and structure of the folk concept of life, and discusses its relevance for scientific research on life. In four empirical studies, we investigate which features of life are considered salient, universal, central, and necessary. Functionings, such as nutrition and reproduction, but not material composition, turn out to be salient features commonly associated with living beings (Study 1). By contrast, being made of cells is considered a universal feature of living species (Study 2), a central aspect (...) of life (Study 3), and our best candidate for being necessary for life (Study 4). These results are best explained by the hypothesis that people take life to be a natural kind subject to scientific scrutiny. (shrink)

In two recent papers, Rose and Nichols present evidence in favor of the view that humans represent category essences in terms of a telos, such as honey-making, and not in terms of scientific essences, such as bee DNA. In this paper, I challenge their interpretation of the evidence, and show that it is directly predicted by the main theory they seek to undermine. I argue that their results can be explained as instances of diagnostic reasoning about scientific essences.

Over the past several decades, psychological essentialism has been an important topic of study, incorporating research from multiple areas of psychology, philosophy and linguistics. At its most basic level, essentialism is the tendency to represent certain concepts in terms of a deeper, unobservable property that is responsible for category membership. Originally, this concept was used to understand people’s reasoning about natural kind concepts, such as TIGER and WATER, but more recently, researchers have identified the emergence of essentialist-like intuitions in a (...) number of other contexts, including people’s representation of concepts like SCIENTIST or CHRISTIAN. This paper develops an account that aims to capture how essentialism may operate across these varied cases. In short, we argue that while there is diversity in the forms essentialism can take, these varied cases reflect the same underlying cognitive structure. (shrink)

The ability to generalize from the known to the unknown is central to learning and inference. Two experiments explore the relationship between how a property is explained and how that property is generalized to novel species and artifacts. The experiments contrast the consequences of explaining a property mechanistically, by appeal to parts and processes, with the consequences of explaining the property functionally, by appeal to functions and goals. The findings suggest that properties that are explained functionally are more likely to (...) be generalized on the basis of shared functions, with a weaker relationship between mechanistic explanations and generalization on the basis of shared parts and processes. The influence of explanation type on generalization holds even though all participants are provided with the same mechanistic and functional information, and whether an explanation type is freely generated (Experiment 1), experimentally provided (Experiment 2), or experimentally induced (Experiment 2). The experiments also demonstrate that explanations and generalizations of a particular type (mechanistic or functional) can be experimentally induced by providing sample explanations of that type, with a comparable effect when the sample explanations come from the same domain or from a different domains. These results suggest that explanations serve as a guide to generalization, and contribute to a growing body of work supporting the value of distinguishing mechanistic and functional explanations. (shrink)

Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...) psychology. Despite the ubiquity of causal reasoning, textbooks of cognitive psychology have neglected this growing field. The goal of The Oxford Handbook of Causal Reasoning is to fill this gap. The handbook brings together the leading researchers in the field of causal reasoning and offers state-of-the-art presentations of theories and research. It provides introductions of competing theories of causal reasoning, and discusses its role in various cognitive functions and domains. The final section presents research from neighboring fields. 1. Causal Reasoning: An Introduction Michael R. Waldmann Part I: Theories of Causal Cognition 2. Associative Accounts of Causal Cognition Mike E. Le Pelley, Oren Griffiths, and Tom Beesley 3. Rules of Causal Judgment: Mapping Statistical Information Onto Causal Beliefs José C. Perales, Andrés Catena, Antonio Cándido, and Antonio Maldonado 4. The Inferential Reasoning Theory of Causal Learning: Toward a Multi- Process Propositional Account Yannick Boddez, Jan De Houwer, and Tom Beckers 5. Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World: Generalizing the Invariance of Causal Power Patricia W. Cheng and Hongjing Lu 6. The Acquisition and Use of Causal Structure Knowledge Benjamin Margolin Rottman 7. Formalizing Prior Knowledge in Causal Induction Thomas L. Griffiths 8. Causal Mechanisms Samuel G. B. Johnson and Woo-kyoung Ahn 9. Force Dynamics and Causation Phillip Wolff and Robert Thorstad 10. Mental Models and Causation P. N. Johnson- Laird and Sangeet S. Khemlani 11. Pseudocontingencies Klaus Fiedler and Florian Kutzner 12. Singular Causation David Danks 13. Cognitive Neuroscience of Causal Reasoning Joachim T. Operskalski and Aron K. Barbey Part II: Basic Cognitive Functions 14. Visual Impressions of Causality Peter White 15. Goal-Directed Actions Bernhard Hommel 16. Planning and Control Magda Osman 17. Reinforcement Learning and Causal Models Samuel J. Gershman 18. Causation and the Probability of Causal Conditionals David E. Over 19. Causal Models and Conditional Reasoning Mike Oaksford and Nick Chater 20. Concepts as Causal Models: Categorization Bob Rehder 21. Concepts as Causal Models: Induction Bob Rehder 22. Causal Explanation Tania Lombrozo and Nadya Vasilyeva 23. Diagnostic Reasoning Björn Meder and Ralf Mayrhofer 24. Inferring Causal Relations by Analogy Keith J. Holyoak and Hee-Seung Lee 25. Causal Argument Ulrike Hahn, Roland Bluhm, and Frank Zenker 26. Causality in Decision- Making York Hagmayer and Philip M. Fernbach Part III: Domains of Causal Reasoning 27. Intuitive Theories Tobias Gerstenberg and Joshua B. Tenenbaum 28. Space, Time, and Causality Marc J. Buehner 29. Causation in Legal and Moral Reasoning David A. Lagnado and Tobias Gerstenberg 30. The Role of Causal Knowledge in Reasoning About Mental Disorders Woo-kyoung Ahn, Nancy S. Kim, and Matthew S. Lebowitz 31. Causality and Causal Reasoning in Natural Language Torgrim Solstad and Oliver Bott 32. Social Attribution and Explanation Denis Hilton Part IV: Development, Phylogeny, and Culture 33. The Development of Causal Reasoning Paul Muentener and Elizabeth Bonawitz 34. Causal Reasoning in Non-Human Animals Christian Schloegl and Julia Fischer 35. Causal Cognition and Culture Andrea Bender, Sieghard Beller, and Douglas L. Medin. (shrink)

Recent theoretical and empirical work suggests that explanation and categorization are intimately related. This paper explores the hypothesis that explanations can help structure conceptual representations, and thereby influence the relative importance of features in categorization decisions. In particular, features may be differentially important depending on the role they play in explaining other features or aspects of category membership. Two experiments manipulate whether a feature is explained mechanistically, by appeal to proximate causes, or functionally, by appeal to a function or goal. (...) Explanation type has a significant impact on the relative importance of features in subsequent categorization judgments, with functional explanations reversing previously documented effects of [”]causal status’. The findings suggest that a feature’s explanatory importance can impact categorization, and that explanatory relationships, in addition to causal relationships, are critical to understanding conceptual representation. (shrink)

The general question (G) How do we categorize artifacts? can be subject to three different readings: an ontological, an epistemic and a semantic one. According to the ontological reading, asking (G) is equivalent to asking in virtue of what properties, if any, a certain artifact is an instance of some artifact kind: (O) What is it for an artifact a to belong to kind K? According to the epistemic reading, when we ask (G) we are investigating what properties of the (...) object we exploit in order to decide whether a certain artifact belongs to a certain kind. (G) thus becomes: (E) How can we know that artifact a belongs to kind K? Finally, (G) can also be read as a question concerning the semantics of artifact kind terms. The semantic reading of (G) is: (S) What kind of reference do artifact kind terms have, if any? In this editorial we expand on the different answers to (O), (E) and (S) that are given in the selected literature on the topic. The result should give us an overall picture of the possible answers to (G). (shrink)

Philosophers and psychologists widely hold that artifact categories – just like biological categories – are individuated by their function. But recent empirical findings in psychology question this assumption. My proposal is to suggest a way of squaring these findings with the central role function should play in individuating artifact categories. But in order to do so, we need to give up on the standard account of artifact function, according to which function is fixed by design, and replace it with a (...) more context-sensitive account, according to which function attributions depend on the explanatory context and, as a result, categorization also depends on the explanatory context, just as the empirical findings from psychology suggest. I argue that the recent ‘modal theory of function’ originally proposed to explain biological function, is capable of providing such an account of artifact function. (shrink)

Five experiments provide evidence for a class of ‘dual character concepts.’ Dual character concepts characterize their members in terms of both (a) a set of concrete features and (b) the abstract values that these features serve to realize. As such, these concepts provide two bases for evaluating category members and two different criteria for category membership. Experiment 1 provides support for the notion that dual character concepts have two bases for evaluation. Experiments 2-4 explore the claim that dual character concepts (...) have two different criteria for category membership. The results show that when an object possesses the appropriate concrete features, but does not fulfill the appropriate abstract value, it is judged to be a category member in one sense but not in another. Finally, Experiment 5 uses the theory developed here to construct artificial dual character concepts and examines whether participants react to these artificial concepts in the same way as naturally occurring dual character concepts. The present studies serve to define the nature of dual character concepts and distinguish them from other types of concepts (e.g., natural kind concepts), which share some, but not all of the properties of dual character concepts. More broadly, these phenomena suggest a normative dimension in everyday conceptual representation. (shrink)

Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual dependence or on physical connections. This paper argues that both approaches to causation are psychologically real, with different modes of explanation promoting judgments more or less consistent with each approach. Two sets of experiments isolate the (...) contributions of counterfactual dependence and physical connections in causal ascriptions involving events with people, artifacts, or biological traits, and manipulate whether the events are construed teleologically or mechanistically. The findings suggest that when events are construed teleologically, causal ascriptions are sensitive to counterfactual dependence and relatively insensitive to the presence of physical connections, but when events are construed mechanistically, causal ascriptions are sensitive to both counterfactual dependence and physical connections. The conclusion introduces an account of causation, an "exportable dependence theory," that provides a way to understand the contributions of physical connections and teleology in terms of the functions of causal ascriptions. (shrink)

The goal of this essay is to put forward an original theory of artifact function, which takes on board the results of the debate on the notion of biological function and also accommodates the distinctive aspects of artifacts. More precisely, the paper develops and defends the Dual-Aspect Theory, which is a monist account according to which an artifact’s function depends on intentional and reproductive aspects. It is argued that this approach meets a set of theoretical and meta-theoretical desiderata and is (...) superior to alternative views. (shrink)

Putnam’s suggestion of extending the scope of his semantic theory has opened an ongoing debate. The majority seem to agree with Putnam as long as he restricts his analysis to natural kind terms, whereas many doubts have arisen about whether or not it can be applied to artifactual kind terms as well. Specifically, this disagreement originated with the thought experiment that Putnam laid out in order to prove his controversial thesis. Here I analyze it in detail in order to evaluate (...) whether it proves what it has been alleged to prove. Unlike the other authors engaged in the debate, I point out that this particular argument cannot demonstrate that artifactual words refer externalistically. I claim that, on closer inspection, Putnam’s thought experiment only shows that an artifactual term like ‘pencil’ can turn out to be a natural kind word, but, in the end, it tells us little about how our “actual” artifactual kind terms work. In order to make my point, I also bring out the two fundamental requirements that a genuine externalist argument about artifactual words ought to meet. Finally, I report, albeit briefly, the main externalist accounts in this respect, illustrating how none of them actually meet the challenge. (shrink)

The idea that concepts play a significant role in some perceptions is widespread but everybody seems to differ as to where to draw the line. Some researchers say that the difference between direct and indirect, concept driven acts of perception manifests itself whenever we perceive abstract or general properties. Others point at second order properties or causal properties. I call this inability to precisely differentiate between acts of direct and indirect perception “The Division Problem”. Furthermore there is always a question (...) as to how widespread indirect perceptions are. Can we attribute them to prelingual cognitive systems? I call this second problem “The Distribution Problem”. -/- The main aim of the paper is providing a solution to both problems by proposing a naturalistic explication of the notion of “concept”. -/- I propose to identify the role concepts were supposed to play in perception with a mechanism of “soft detection”. Unlike hard detectors which react to a specific target in virtue of their constitution and placement in the system, soft detectors are understood as dynamic categorization devices enabling the cognitive system to selectively react to an undetectable property via flexible exploitation of data from hard detectors. -/- I conclude by showing how the notion of soft detection retains some of the aspects traditionally attributed to concepts and how does it differ from similar accounts known from contemporary literature. (shrink)

This paper is a reply to a discussion of my paper The Essentialist Aspect of Naive Theories by Ahn, Kalish, Gelman, Medin, Luhmann, Atran, Coley and Shafto; both the discussion and my reply appeared in the November 2001 issue of Cognition.

Hybrid and pluralist accounts of concepts agree that the class of concepts includes a multiplicity of heterogeneous representational structures, such as prototypes, sets of exemplars and theories. In this paper I argue that these accounts agree on two additional central claims related to the ways in which they articulate those structures: each type of representational structure can be used independently in psychological processes, and co-referential concepts are associated in a distinctive way as representations of the same category. Although they disagree (...) on concept individuation, they seem to agree that on a processing dimension there are multiple independent representations for a given category and on a long-term storage dimension concepts that represent the same category conform an epistemic unity. (shrink)

We investigated how people design interventions to affect the outcomes of causal systems. We propose that the abstract structural properties of a causal system, in addition to people's content and mechanism knowledge, influence decisions about how to intervene. In Experiment 1, participants preferred to intervene at specific locations in a causal chain regardless of which content variables occupied those positions. In Experiment 2, participants were more likely to intervene on root causes versus immediate causes when they were presented with a (...) long-term goal versus a short-term goal. These results show that the structural properties of a causal system can guide the design of interventions. (shrink)

A feature is central to a concept to the extent that other features depend on it. Four studies tested the hypothesis that people will project a feature from a base concept to a target concept to the extent that they believe the feature is central to the two concepts. This centrality hypothesis implies that feature projection is guided by a principle that aims to maximize the structural commonality between base and target concepts. Participants were told that a category has two (...) or three novel features. One feature was the most central in that more properties depended on it. The extent to which the target shared the feature's dependencies was manipulated by varying the similarity of category pairs. Participants' ratings of the likelihood that each feature would hold in the target category support the centrality hypothesis with both natural kind and artifact categories and with both well-specified and vague dependency structures. (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)

Carey argues that the aspects of categorization that are diagnostic of deep conceptual structure and, by extension, narrow conceptual content, must be distinguished from those aspects that are incidental to categorization tasks. For natural kind concepts, discriminating between these two types of processes is complicated by the role of explanatory stance and the causal history of features in determining category structure.

This paper considers three package deals combining views in philosophy of mind, meta-philosophy, and experimental philosophy. The most familiar of these packages gives center-stage to pumping intuitions about fanciful cases, but that package involves problematic commitments both to a controversial descriptivist theory of reference and to intuitions that “negative” experimental philosophers have shown to be suspiciously variable and context-sensitive. In light of these difficulties, it would be good for future-minded experimental philosophers to align themselves with a different package deal. This (...) paper suggests two alternatives. Experimentalists might help fans of “naturalized” approaches discover what natural kinds have been playing an appropriate role in causing us to use concepts as we do. Or, better still, experimentalists might instead help pragmatists and teleo-semanticists discover how our concept usage regularly yields beneficial outcomes, so that we can then craft philosophical analyses that will.. (shrink)

In this prcis we focus on phenomena central to the reaction against similarity-based theories that arose in the 1980s and that subsequently motivated the approach to semantic knowledge. Specifically, we consider (1) how concepts differentiate in early development, (2) why some groupings of items seem to form or coherent categories while others do not, (3) why different properties seem central or important to different concepts, (4) why children and adults sometimes attest to beliefs that seem to contradict their direct experience, (...) (5) how concepts reorganize between the ages of 4 and 10, and (6) the relationship between causal knowledge and semantic knowledge. The explanations our theory offers for these phenomena are illustrated with reference to a simple feed-forward connectionist model. The relationships between this simple model, the broader theory, and more general issues in cognitive science are discussed. (shrink)

A theory of categorization is presented in which knowledge of causal relationships between category features is represented in terms of asymmetric and probabilistic causal mechanisms. According to causal‐model theory, objects are classified as category members to the extent they are likely to have been generated or produced by those mechanisms. The empirical results confirmed that participants rated exemplars good category members to the extent their features manifested the expectations that causal knowledge induces, such as correlations between feature pairs that are (...) directly connected by causal relationships. These expectations also included sensitivity to higher‐order feature interactions that emerge from the asymmetries inherent in causal relationships. Quantitative fits of causal‐model theory were superior to those obtained with extensions to traditional similarity‐based models that represent causal knowledge either as higher‐order relational features or “prior exemplars” stored in memory. (shrink)

Two experiments examined the impact of causal relations between features on categorization in 5- to 6-year-old children and adults. Participants learned artificial categories containing instances with causally related features and noncausal features. They then selected the most likely category member from a series of novel test pairs. Classification patterns and logistic regression were used to diagnose the presence of independent effects of causal coherence, causal status, and relational centrality. Adult classification was driven primarily by coherence when causal links were deterministic (...) (Experiment 1) but showed additional influences of causal status when links were probabilistic (Experiment 2). Children’s classification was based primarily on causal coherence in both cases. There was no effect of relational centrality in either age group. These results suggest that the generative model (Rehder, 2003a) provides a good account of causal categorization in children as well as adults. (shrink)

Consent transforms an otherwise illegitimate act into a legitimate one. To be valid, however, it must be adequately informed. The legal requirement is vague and provides little assistance in predicting when it will be satisfied. This is particularly so when a patient consents to a procedure and the physician subsequently varies one of the components of that procedure. Using three legal judgments and one General Medical Council decision as a springboard, I have explored the concept of a medical procedure within (...) the context of consent and developed a theoretical model to elucidate a more predictable and consistent informational requirement. (shrink)

This article considers how people judge the identity of objects (e.g., how people decide that a description of an object at one time, t₀, belongs to the same object as a description of it at another time, t₁). The authors propose a causal continuer model for these judgments, based on an earlier theory by Nozick (1981). According to this model, the 2 descriptions belong to the same object if (a) the object at t₁ is among those that are causally close (...) enough to be genuine continuers of the original and (b) it is the closest of these close-enough contenders. A quantitative version of the model makes accurate predictions about judgments of which a pair of objects is identical to an original (Experiments 1 and 2). The model makes correct qualitative predictions about identity across radical disassembly (Experiment 1) as well as more ordinary transformations (Experiments 2 and 3). (shrink)

The question of how people represent emotions is eminently important for a number of different domains of psychological research. The present study tested the assumption that emotion concepts are represented similar to theories in that they are comprised of a set of causally interrelated features. Using emotional scenarios and investigating the emotion concepts of anger, anxiety, and sadness it was found that people's representations of emotion concepts essentially involved the representation of the causal relation of emotion features and that the (...) causal status of a feature determined the feature's centrality in the concept. Moreover, people's representations of emotion concepts corresponded to basic assumptions of cognitive emotion theories, namely that cognitive appraisals cause other surface features of emotion, like expression and behaviour. By providing evidence for a theory-based representation, the present results show that the classical and the prototype approach are insufficient to model the representation of emotion concepts. (shrink)

Categories, as mental structures, are more than simply sums of property frequencies. A number of recent studies have supported the view that the properties of categories may be organised along functional lines and possibly dependency structures more generally. The study presented here investigates whether earlier findings reflect something unique in the English language/North American culture or whether the functional structuring of categories is a more universal phenomenon. A population of English-speaking Americans was compared to a population of Cantonese-speaking Hong Kong (...) Chinese. The findings clearly support the view that functional influences on category centrality are universal (or at least common to Cantonese-speaking Hong Kong Chinese and English-speaking Americans), albeit with specific cross-cultural/cross-linguistic group differences in the particular properties that are considered central to categories. (shrink)

People commonly think of the mind and the brain as distinct entities that interact, a view known as dualism. At the same time, the public widely acknowledges that science attributes all mental phenomena to the workings of a material brain, a view at odds with dualism. How do people reconcile these conflicting perspectives? We propose that people distort claims about the brain from the wider culture to fit their dualist belief that minds and brains are distinct, interacting entities: Exposure to (...) cultural discourse about the brain as the physical basis for the mind prompts people to posit that mind–brain interactions are asymmetric, such that the brain is able to affect the mind more than vice versa. We term this hybrid intuitive theory neurodualism. Five studies involving both thought experiments and naturalistic scenarios provided evidence of neurodualism among laypeople and, to some extent, even practicing psychotherapists. For example, lay participants reported that “a change in a person's brain” is accompanied by “a change in the person's mind” more often than vice versa. Similarly, when asked to imagine that “future scientists were able to alter exactly 25% of a person's brain,” participants reported larger corresponding changes in the person's mind than in the opposite direction. Participants also showed a similarly asymmetric pattern favoring the brain over the mind in naturalistic scenarios. By uncovering people's intuitive theories of the mind–brain relation, the results provide insights into societal phenomena such as the allure of neuroscience and common misperceptions of mental health treatments. (shrink)

Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words. We present a Bayesian model that, unlike previous work, learns both categories and their features in a single process. We model category induction as two interrelated subproblems: the acquisition of features that discriminate among categories, and the grouping of concepts into categories based on those features. (...) Our model learns categories incrementally using particle filters, a sequential Monte Carlo method commonly used for approximate probabilistic inference that sequentially integrates newly observed data and can be viewed as a plausible mechanism for human learning. Experimental results show that our incremental learner obtains meaningful categories which yield a closer fit to behavioral data compared to related models while at the same time acquiring features which characterize the learned categories. (shrink)

Empirical studies indicate that analogy consists of two main processes: retrieval and mapping. While current theories and models of analogy have revealed much about the mainly structural constraints that govern the mapping process, the similarities that underpin the correspondences between individual representational elements and drive retrieval are understood in less detail. In existing models symbol similarities are externally defined but neither empirically grounded nor theoretically justified. This paper introduces a new model (EMMA: the environmental model of analogy) which relies on (...) co‐occurrence information provided by LSA (Latent Semantic Analysis; Landauer & Dumais, 1997) to ground the relations between the symbolic elements aligned in analogy. LSA calculates a contextual distribution for each word encountered in a corpus by counting the frequency with which it co‐occurs with other words. This information is used to define a model that locates each word encountered in a high‐dimensional space, with relations between elements in this space representing contextual similarities between words. A series of simulation experiments demonstrate that the environmental approach to semantics embodied in LSA can produce appropriate patterns of analogical retrieval, but that this semantic measure is not sufficient to model analogical mapping. The implications of these findings, both for theories of representation in analogy research and more general theories of semantics in cognition, are explored. (shrink)