Explaining the abundance of distant analogies in naturalistic observations of experts

Analogical reasoning is a landmark of human cognition. Based on the realization that the elements of two situations are organized by similar systems of relations, analogical inferences allow the transfer of knowledge structures from a better-known situation (the base analog) to a target situation that is relatively less understood (the target analog). Experimental research has demonstrated that the retrieval of base analogs from long term memory in response to the proceesing of a target analog is infrequent in the lack of semantic similarities between both situations (Gick and Holyoak, 1980; Keane, 1987; Gentner et al., 1993; Trench and Minervino, 2014). With the turn of the century, several naturalistic observations of experts working in their domains of expertise yielded a more complex picture. While molecular biologists (Dunbar, 1997) and psychologists (Saner and Schunn, 1999) still exhibited mostly within-domain analogizing, the observation of journalists and politicians (Blanchette and Dunbar, 2001), teachers (Richland et al., 2004), managers (Bearman et al., 2007) and design engineers (Christensen and Schunn, 2007) showed a more frequent use of long-distance analogies. The naturalistic study by Kretz and Krawczyk (2014) on the use of analogies by economists also demonstrates an abundance of distant analogies in the sevice of an impressive variety of communicative purposes, most of which were not evident in prior research. These goals included the generation of concrete source examples of more general target concepts, the formation of visual images of source concepts, the addition of colorful speech, the inclusion of a target into a source concept, or the differentiation between source and target concepts. With these results in mind, the time is ripe to assert that the naturalistic observation of experts shows a more flexible use of analogical sources than is predicted by experimental studies on analogical transfer, and simulated by dominant computer models of analogical retrieval (e.g., MAC/FAC, Forbus et al., 1995; LISA, Hummel and Holyoak, 1997). How, then, to explain this analogical abundance? In trying to account for the contrasting results of the experimental and the naturalistic traditions, the default explanations revolve around the expertise of the analogizers and the psychological constraints of the target tasks. I will argue that although both factors are likely to bear some responsibility for this empirical inconsistency, there are reasons to expect a heavier weight of the latter.