Why are different features central for natural kinds and artifacts?: the role of causal status in determining feature centrality.

By Woo-Kyoung Ahn. 1998

Ahn and Lassaline [Ahn, W., Lassaline, M.E., 1995. Causal structure in categorization. Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society, Pittsburgh, PA, pp. 521-526] recently proposed a causal status hypothesis which states that features that play a causal role in a relational structure are more central than their effects. This hypothesis can account for previous research demonstrating that compositional features are generally important for natural kinds but functional features are generally important for artifacts. The causal status hypothesis explains this category-feature interaction effect in terms of differences in the causal status of compositional and functional features between natural kinds and artifacts. Experiments 1 and 2 examined real-life categories used in previous studies, and found positive correlations between the causal status of the features and their centrality across natural and artifactual kinds. Experiments 3 and 4 manipulated the causal status of compositional and functional features in artificial categories, and showed that it was causal status rather than the interaction between the type of feature and the type of category per se that accounted for feature centrality. The implications of these results on the distinctions between natural kinds and artifacts are discussed.

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Citations in the corpus

Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI (2019, background): “Relevant research on causal reasoning relevant to explanation includes: Ahn (1998); Ahn et al. (1995); Ahn and Kalish (2000); Chater and Oaksford, (2006); Cheng (1997, 2000); Einhorn and Hogarth (1986); Eiter and Lukasiewicz (2002, 2006); Feltovich, Hoffman, Woods, and Roesler (2004); Graesser,…”
The parallel distributed processing approach to semantic cognition (2003, background): “Children and adults place more weight on the CAUSAL PROPERTIES of certain objects than on their appearance, or on other properties that are seen as effects of underlying causal properties 93–95 .”
Explanation and inference: mechanistic and functional explanations guide property generalization (2014, background): “, DeJong, 2004; see also Ahn et al., 1992). Understanding the role of explanation in generalization will require–among other things– an understanding of which prior beliefs particular explanations invoke (e.g., Chin-Parker and Bradner, 2010; Landy and Hummel, 2010), why those particular beliefs are ”
Explanation and Abductive Inference (2012, background): “In addition, the way in which a category's features are explained can influence the relative importance of those features in making judgments about category membership: Features that support more explanations (Sloman, Love, & Ahn, 1998), causally deeper explanations (Ahn, 1998; Ahn & Kim, 2000), or ”
Précis of Semantic Cognition: A Parallel Distributed Processing Approach (2008, background): “First, several studies demonstrate that knowledge about the sequence of events through which an object comes to have its observed properties can influence how an adult or child conceives of the object (e.g. Keil, 1989; Gopnik & Sobel, 2000; Ahn, 1998; Ahn, Marsh, & Luhmann, 2002).”
Explanation and categorization: how "why?" informs "what?". (2009, background): “Indeed, Ahn (1998) attempts to assimilate effects of functional information to causal status, and causal status is itself partially motivated in terms of inferential utility (Ahn, 1998; Proctor & Ahn, 2007).”
Goals Affect the Perceived Quality of Explanations (2015, background): “For example, Lombrozo and Gwynne (2014) and Vasilyeva and Coley (2013) found that different types of explanations predicted different patterns of property generalization (for similar effects in categorization, see Lombrozo, 2009; Ahn, 1998).”
Explanation and understanding (2015, background): “Similarly, a preference for the first element in a causal chain, the causal status effect, has been found to be influential in both artifact and biological domains (Ahn 1998).”
Causal-explanatory pluralism: How intentions, functions, and mechanisms influence causal ascriptions. (2010, background): “This effect was sufficiently strong to outweigh previously documented preferences for features that are earlier in a causal chain in categorization (Ahn & Kim, 2000; see also Ahn, 1998).”
A causal-model theory of conceptual representation and categorization. (2003, background): “For example, Ahn and her colleagues (Ahn, 1998; Ahn et al., 2000; Sloman et al., 1998) have proposed the causal status hypothesis, in which features are more important to categorization to the extent that they are " more causal, " that is, more deeply embedded in a causal network as causes.”
Semantic Cognition: A Parallel Distributed Processing Approach (2004, methodology): “Using methods similar to Keil’s, Ahn and colleagues (Ahn, 1998; Ahn et al., 2000) have demonstrated that both children and adults are apt to weight “cause” properties more heavily than “effect” properties when categorising novel objects.”
Category Stretching: Reorienting Research on Categories in Strategy, Entrepreneurship, and Organization Theory (2013, background): “Drawing on fundamental insights from Ahn (1998), Rehder (2003a, 2003b), and Barsalou (1983, 1991), we revisit the idea that categorizing is a mechanical cognitive © 2011 The Authors Journal of Management Studies © 2011 John Wiley & Sons Ltd and Society for the Advancement of Management…”
Artifacts are not ascribed essences, nor are they treated as belonging to kinds (2003, background): “In general, properties are given more weight in the categorisation decision to the extent they are causally central (Ahn, 1998) because the ease of explaining away a property is inversely proportional to its centrality (Sloman, Love, & Ahn, 1998). Note that essence plays no role in the explanation o”
Learning from others: children's construction of concepts. (2009, background): “Essentialist beliefs have implications for a broad range of concepts, including social categories (Haslam et al. 2000), evolutionary theory (Evans 2000, Kelemen 2004, Mayr 1991, Shtulman 2006), and causal reasoning (Ahn 1998, Rehder 2007).”