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

Artefacts are usually understood in contrast with natural kinds and conceived as a unitary kind. Here we propose that there is in fact a variety of artefacts: from the more concrete to the more abstract ones. Moreover, not every artefact is able to fulfil its function thanks to its physical properties: Some artefacts, particularly what we call “institutional” artefacts, are symbolic in nature and require a system of rules to exist and to fulfil their function. Adopting a standard method to (...) measure conceptual representation (the property generation task), we have experimentally explored how humans conceptualise these different kinds of artefacts. Results indicate that institutional artefacts are typically opposed to social objects, while being more similar to standard artefacts, be they abstract or concrete. (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)

Psychological essentialism is the hypothesis that humans represent some categories as having an underlying essence that unifies members of a category and is causally responsible for their typical attributes and behaviors. Throughout the past several decades, psychological essentialism has emerged as an extremely active area of research in cognitive science. More recently, it has also attracted attention from philosophers, who put the empirical results to use in many different philosophical areas, ranging from philosophy of mind and cognitive science to social (...) philosophy. This article aims to give philosophers who are new to the topic an overview of the key empirical findings surrounding psychological essentialism, and some of the ways the hypothesis and its related findings have been discussed, extended, and applied in philosophical research. (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)

Vaesen and van Amerongen (Philosophical Psychology 21:779-797, 2008) criticize Dennett’s design stance, arguing that as a cognitive thesis about artifact categorization, it is falsified by empirical findings. I assess their criticism in light of both further results and alternate findings the authors acknowledge (but did not discuss in detail). I argue that the design stance still stands in virtue of the conflicting character of these findings, and suggest shifting the domain of empirical scrutiny.

People often think of objects teleologically. For instance, we might understand a hammer in terms of its purpose of driving in nails. But how should we understand teleological thinking in the first place? This paper separates mere teleology (simply ascribing a telos) and teleological explanation (thinking something is explained by its telos) by examining cases where an object was designed for one purpose but is now widely used for a different purpose. Across four experiments, we show that teleology judgments and (...) teleological explanation judgments are dissociable, and identify three factors that influenced teleology judgments (and one that did not). (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)

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)

Designers’ intentions are important for determining an artifact’s proper function (i.e., its perceived real function). However, there are disagreements regarding why. In one view, people reason causally about artifacts’ functional outcomes, and designers’ intended functions become important to the extent that they allow inferring outcomes. In another view, people use knowledge of designers’ intentions to determine proper functions, but this is unrelated to causal reasoning, having perhaps to do with intentional or social forms of reasoning (e.g., authority). Regarding these latter (...) social factors, researchers have proposed that designers’ intentions operate through a mechanism akin to social conventions, and that therefore both are determinants of proper function. In the current work, participants learned about an object’s creation, about social conventions for its use and about a specific episode where the artifact was used. The function implemented by the user could be aligned with the designer’s intended function, the social convention, both, or neither (i.e., an opportunistic use). Importantly, the use episode always resulted in an accident. Data show that the accident negatively affected proper function judgments and perceived efficiency for conventional and opportunistic functions, but not for designers’ intended functions. This is inconsistent with the view that designers’ intentions are conceptualized as causes of functional outcomes and with the idea that designers’ intentions and social conventions operate through a common mechanism. (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)