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Previous research suggests that children can infer causal relations from patterns of events. However, what appear to be cases of causal inference may simply reduce to children recognizing relevant associations among events, and responding based on those associations. To examine this claim, in Experiments 1 and 2, children were introduced to a “blicket detector,” a machine that lit up and played music when certain objects were placed upon it. Children observed patterns of contingency between objects and the machine's activation that (...) |
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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. |
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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. |
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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 (...) |
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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 (...) |
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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 (...) No categories |
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Previous research suggests that children can infer causal relations from patterns of events. However, what appear to be cases of causal inference may simply reduce to children recognizing relevant associations among events, and responding based on those associations. To examine this claim, in Experiments 1 and 2, children were introduced to a “blicket detector”, a machine that lit up and played music when certain objects were placed upon it. Children observed patterns of contingency between objects and the machine’s activation that (...) |
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We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or “Bayes nets”. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children (...) |
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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 (...) |
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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 (...) |
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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 (...) |
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