This paper explores the complex nature of social biases, arguing for a functional framework that recognizes their unity and diversity. The functional approach posits that all biases share a common functional role in overcoming underdetermination. This framework, I argue, provides a comprehensive understanding of how all psychological biases, including social biases, are unified. I then turn to the question of disunity, demonstrating how psychological social biases differ systematically in the mental states and processes that constitute them. These differences indicate that (...) biases at various levels of the cognitive architecture require distinct treatment along at least two dimensions: epistemic evaluation and mitigation strategies. By examining social biases through this dual lens of unity and diversity, we can more effectively identify when and how to intervene on problematic biases. Ultimately, this approach provides a nuanced understanding of the nature of social bias, offering practical guidance for addressing existing biases and proactively managing emerging biases in both human and artificial minds. (shrink)

Consider the following two (hypothetical) generic causal claims: “Living in a neighborhood with many families with children increases purchases of bicycles” and “living in an affluent neighborhood with many families with children increases purchases of bicycles.” These claims not only differ in what they suggest about how bicycle ownership is distributed across different neighborhoods (i.e., “the data”), but also have the potential to communicate something about the speakers’ values: namely, the prominence they accord to affluence in representing and making decisions (...) about the social world. Here, we examine the relationship between the level of granularity with which a cause is described in a generic causal claim (e.g., neighborhood vs. affluent neighborhood) and the value of the information contained in the causal model that generates that claim. We argue that listeners who know any two of the following can make reliable inferences about the third: 1) the level of granularity at which a speaker makes a generic causal claim, 2) the speaker’s values, and 3) the data available to the speaker. We present results of four experiments (N=1,323) in the domain of social categories that provide evidence in keeping with these predictions. (shrink)

Generic statements (‘Tigers have stripes’) are pervasive and early-emerging modes of generalization with a distinctive linguistic profile. Previous experimental work found that generics display a unique asymmetry between their acceptance conditions and the implications that are typically drawn from them. This paper presents evidence against the hypothesis that only generics display an asymmetry. Correcting for limitations of previous designs, we found a generalized asymmetry effect across generics, various kinds of explicitly quantified statements (‘most’, ‘some’, ‘typically’, ‘usually’), and variations in types (...) of predicated properties (striking vs. neutral). We discuss implications of these results for our understanding of the source of asymmetry effects and whether and in which ways these effects might introduce biased beliefs into social networks. (shrink)

Predicate nominals (e.g., “is a female”) seem to label or categorize their subjects, while their adjectival correlates (e.g., “is female”) merely attribute a property. Predicate nominals also elicit essentializing inferential judgments about inductive potential and stable explanatory membership. Data from psychology and semantics support that this distinction is robust and productive. I argue that while the difference between predicate nominals and predicate adjectives is elided by standard semantic theories, it ought not be. I then develop and defend a psychologically motivated (...) semantic account on which predicate nominals attribute kind membership and trigger a presupposition that underpins our essentialist judgments. (shrink)

Kind representations, concepts like table, triangle, dog, and planet, underlie generic language. Here, we investigate the formal structure of kind representations—the structure that distinguishes kind representations from other types of representations. The present studies confirm that participants distinguish generic‐supporting properties of individuals (e.g., this watch is made of steel) and accidental properties (e.g., this watch is on the nightstand). Furthermore, work dating back to Aristotle establishes that only some generic‐supporting properties bear a principled connection to the kind, that is, are (...) true of an individual by virtue of its being a member of a specific kind (e.g., telling time for a watch). The present studies tested the hypothesis that principled connections are part of the formal structure of kind representations. Specifically, they tested whether they structure a newly learned kind representation. Experiment 1 found that introducing a property of a newly encountered novel kind in any one of four linguistic frames that provide evidence that a property has a principled connection to a kind (e.g., “It has fur because it is a blick”) led participants to infer a different conceptual consequence of principled connections (i.e., “There is something wrong with this blick, which does not have fur”) for which they had no direct evidence. Two introduction frames that provided no evidence for principled connections (e.g., “Almost all blicks have fur”) did not generate the same consequence. Experiment 2 found that all of the targeted properties were generic licensing, irrespective of the introduction frame. That the distinction between properties that bear principled connections to their kinds, and merely generic‐supporting properties structures novel kind representations, provides strong evidence that this distinction is part of the formal structure of kind representations. (shrink)

Are causal explanations (e.g., “she switched careers because of the COVID pandemic”) treated differently from the corresponding claims that one factor caused another (e.g., “the COVID pandemic caused her to switch careers”)? We examined whether explanatory and causal claims diverge in their responsiveness to two different types of information: covariation strength and mechanism information. We report five experiments with 1,730 participants total, showing that compared to judgments of causal strength, explanatory judgments tend to bemoresensitive to mechanism andlesssensitive to covariation – (...) even though explanatory judgments respond to both types of information. We also report exploratory comparisons to judgments of understanding, and discuss implications of our findings for theories of explanation, understanding, and causal attribution. These findings shed light on the potentially unique role of explanation in cognition. (shrink)