Recently, philosophers and psychologists defending the embodied cognition research program have offered arguments against mindreading as a general model of our social understanding. The embodied cognition arguments are of two kinds: those that challenge the developmental picture of mindreading and those that challenge the alleged ubiquity of mindreading. Together, these two kinds of arguments, if successful, would present a serious challenge to the standard account of human social understanding. In this paper, I examine the strongest of these embodied cognition arguments and argue that mindreading approaches can withstand the best of these arguments from embodied cognition.

Abstract:Disagreeing with others about how to interpret a social interaction is a common occurrence. We often find ourselves offering divergent interpretations of others' motives, intentions, beliefs, and emotions. Remarkably, philosophical accounts of how we understand others do not explain, or even attempt to explain such disagreements. I argue these disparities in social interpretation stem, in large part, from the effect of social categorization and our goals in social interactions, phenomena long studied by social psychologists. I argue we ought to expand our accounts of how we understand others in order to accommodate these data and explain how such profound disagreements arise amongst informed, rational, wellmeaning individuals.

One version of the Humean Theory of Motivation holds that all actions can be causally explained by reference to a belief-desire pair. Some have argued that pretense presents counter-examples to this principle, as pretense is instead causally explained by a belief-like imagining and a desire-like imagining. We argue against this claim by denying imagination the power of motivation. Still, we allow imagination a role in guiding action as a script. We generalize the script concept to show how things besides imagination can occupy this same role in both pretense and non-pretense actions. The Humean Theory of Motivation should then be modified to cover this script role.

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How are biases encoded in our representations of social categories? Philosophical and empirical discussions of implicit bias overwhelmingly focus on salient or statistical associations between target features and representations of social categories. These are the sorts of associations probed by the Implicit Association Test and various priming tasks. In this paper, we argue that these discussions systematically overlook an alternative way in which biases are encoded, i.e., in the dependency networks that are part of our representations of social categories. Dependency networks encode information about how the features in a conceptual representation depend on each other, which determines their degree of centrality in a conceptual representation. Importantly, centrally encoded biases systematically disassociate from those encoded in salient-statistical associations. Furthermore, the degree of centrality of a feature determines its cross-contextual stability: in general, the more central a feature is for a concept, the more likely it is to survive into a wide array of cognitive tasks involving that concept. Accordingly, implicit biases that are encoded in the central features of concepts are predicted to be more resilient across different tasks and contexts. As a result, our distinction between centrally encoded and salient-statistical biases has important theoretical and practical implications.