Certain generalizations are teleological, e.g., forks are foreating. But not all properties relevant to a particular conceptpermit teleological generalization. For instance, forks getwashed roughly as often as they’re used for eating, yet thegeneralization, forks are for washing, might strike reasoners asunacceptable. What explains the discrepancy? A recenttaxonomic theory of conceptual generalization (Prasada, 2017;Prasada & Dillingham, 2006; Prasada et al., 2013) argues thatcertain kinds of conceptual connections – known as“principled” connections – license generalizations, whereasassociative, “statistical” connections license only probabilisticexpectations. We apply this taxonomy to explain teleologicalgeneralization: it predicts that acceptable teleologicalgeneralizations concern concept-property pairs in which theconcept bears a principled connection to a property. Under thisanalysis, the concept fork bears a principled connection toeating and a statistical connection to washing. Twoexperiments and a regression analysis tested and corroboratedthe predictions of the theory.

Explanations have no bound in principle, but in practice, people prefer explanations that are complete (Zemla etal., 2017), and the explanations that they generate are bounded (Miyake, 1986). We tested reasoners’ ability to assess whethersome explanations are incomplete. Participants in three experiments received explanations, i.e., chains of causal events, e.g., Acauses B causes C. Their task was to choose questions relevant to links in the chain. Some explanations contained ”breaks” inthe chain, whereas others did not. Participants in three studies were able to detect the breaks, and preliminary data suggest thatthey assess explanations with breaks as less complete than those without breaks. Many participants also chose to ask questionsabout the initial event in a causal chain (e.g., A in the chain above), suggesting that such initial events are themselves seen asincomplete. The studies reveal a novel pattern in reasoners’ ability to formulate explanations.

In theory, there exists no bound to a causal explanation – every explanation can be elaborated further. But reasoners rate some explanations as more complete than others. To account for this behavior, we developed a novel theory of the detection of explanatory incompleteness. The theory is based on the idea that reasoners construct mental models of causal explanations. By default, each causal relation refers to a single mental model. Reasoners should consider an explanation complete when they can construct a single mental model, but incomplete when they must consider multiple models. Reasoners should thus rate causal chains, e.g., A causes B and B causes C, as more complete than “common cause” explanations (e.g., A causes B and A causes C) or “common effect” explanations (e.g., A causes C and B causes C). Two experiments validate the theory's prediction. The data suggest that reasoners construct mental models when generating explanations.

Individuals with autism spectrum disorders (ASD) are said to have deficits in “theory of mind.” The present paper explores two main accounts of the mechanisms underlying these deficits. On one account, high-functioning adults with ASD struggle to infer others’ mental states. On another account, they lack an ability to integrate those mental states into a coherent understanding of action. We tested these two accounts by making several modifications to the Faux Pas task—a commonly used advanced theory of mind task— including the presentation of explicit mental state information. Surprisingly, in contrast to previous work, individuals on the autism spectrum exhibited both intact integration and intact inference.

Studies show that people begin to associate objects with functions early in development (Atran, 1995; Carey, 1985; Csibra& Gergely, 1998; Keil, 1992). They can describe generalizations about the functions of objects by producing teleologicalgeneric language, i.e., statements that express generalities about the purposes of objects. A recent study shows thatpeople accept teleological generics about body parts such as eyes are for seeing but reject statements such as eyes are forblinking. Nevertheless, little is known about whether people associate living, volitional agents with functions. In a seriesof experiments, we show that they do: they accept statements of the form ”horses are for riding” but not ”horses are forneighing”. The studies show further that people appear to have normative expectations about the functions of agents, e.g.,they accept statements such as ”all normal horses are for riding” and ”horses are supposed to be for riding”. The resultcorroborates Korman and Khemlani’s (2018, 2020) proposal that people mentally represent principled connections, i.e.,privileged conceptual links, between kinds and their functional properties.

Microaggressions are unintentional or thoughtless behaviors that convey negative messages to members of minoritygroups. Due to the attributional ambiguity of microaggressions, people often differ in their judgments about how morally badacts of microaggression are. To account for this individual variation, we explored the potential influence of heavy social mediause on individuals’ moral judgments of microaggressive behaviors. We hypothesized that, because of the relative acceptance ofstrong blame expressions on social media, heavy Facebook users would endorse intense moral criticism of microaggressions.Participants read about several agents who committed microaggressions and judged the appropriateness of moral criticism(pretested to vary in degrees from “disapprove of,” “chastise,” “chew out,” to “lash out at”) that a friend directed towards theoffender. Consistent with our hypothesis, we found a strong correlation (r = .47) between increasing degrees of Facebook useand increasing acceptance of harsher moral criticism for microaggressions.

Speech-acts can have literal meaning as well as pragmaticmeaning, but these both involve consequences typically in-tended by a speaker. Speech-acts can also have unintentionalmeaning, in which what is conveyed goes above and beyondwhat was intended. Here, we present a Bayesian analysis ofhow, to a listener, the meaning of an utterance can significantlydiffer from a speaker’s intended meaning. Our model em-phasizes how comprehending the intentional and unintentionalmeaning of speech-acts requires listeners to engage in sophisti-cated model-based perspective-taking and reasoning about thehistory of the state of the world, each other’s actions, and eachother’s observations. To test our model, we have human partic-ipants make judgments about vignettes where speakers makeutterances that could be interpreted as intentional insults or un-intentional faux pas. In elucidating the mechanics of speech-acts with unintentional meanings, our account provides insightinto how communication both functions and malfunctions.

Jörg Cassens, Rebekah Wegener, Lorenz Habenicht, and Julian Blohm discuss the dialogic form of explanations. Explanations are a long established research topic in a wide variety of disciplines, ranging from philosophy (van Fraassen, 1980; Achinstein, 1983) over the cognitive sciences and psychology (Lalljee et al., 1983; Keil and Wilson, 2000; Lombrozo, 2006) to computer science in general and artificial intelligence in particular (Schank, 1986; Leake, 1992; Leake (1995); Sørmo et al., 2005). However, while there is compelling research supporting the value, structure and function of explanation, as Edwards et al. (2019) argue, “accounts of explanation typically define explanation (the product) rather than explaining (the process)”. By contrast, we aim at an understanding of explanation as a functional variety of language behaviour that treats explanations as being: