Moral masters or moral apprentices? A connectionist account of sociomoral evaluation in preverbal infants

Young Children's Understanding of Helping as Increasing Another Agent's Utility

Instrumental helping is one of the paradigmatic "prosocial" behaviors featured in developmental research on sociomoral reasoning, but not much is known about how children recognize instances of helping behaviors or understand the term 'help'. Here, we examined whether young children represent helping as a second-order goal and take it to mean increasing the utility of another agent. In Study 1, we tested whether 12-month-old infants would expect an agent who previously helped to perform an action that reduced the Helpee's action cost. We found that while infants expected agents to act individually efficiently (Experiment 1C), they did not expect the agent to choose the action that maximally reduced the Helpee's cost compared to an action that reduced the cost less (Experiment 1A) or not at all (Experiment 1B). In Study 2, we examined whether three-year-old preschoolers (1) maximize a Helpee's cost reduction when prompted to help in a first-person task, and (2) identify in a third-party context which of two agents, performing superficially similar behaviors with varying effects on the Helpee's action options, actually helped. Contrary to our predictions, preschoolers did not help in a way that maximally reduced the Helpee's cost in (1). In (2), however, they indicated that the agent who reduced the Helpee's action cost was the one who helped. Taken together, these results support the proposal that, at least by preschool age, children possess a second-order utility-based concept of helping, but that they may not exhibit efficiency when choosing their own helping actions.

The Cognitive Architecture of Infant Attachment

Meta-analytic evidence indicates that the quality of the attachment relationship that infants establish with their primary caregiver has enduring significance for socioemotional and cognitive outcomes. However, the mechanisms by which early attachment experiences contribute to subsequent development remain underspecified. According to attachment theory, early attachment experiences become embodied in the form of cognitive-affective representations, referred to as internal working models (IWMs), that guide future behavior. Little is known, however, about the cognitive architecture of IWMs in infancy. In this article, we discuss significant advances made in the field of infant cognitive development and propose that leveraging insights from this research has the potential to fundamentally shape our understanding of the cognitive architecture of attachment representations in infancy. We also propose that the integration of attachment research into cognitive research can shed light on the role of early experiences, individual differences, and stability and change in infant cognition, as well as open new routes of investigation in cognitive studies, which will further our understanding of human knowledge. We provide recommendations for future research throughout the article and conclude by using our collaborative research as an example.

Seeing social interactions

Seeing the interactions between other people is a critical part of our everyday visual experience, but recognizing the social interactions of others is often considered outside the scope of vision and grouped with higher-level social cognition like theory of mind. Recent work, however, has revealed that recognition of social interactions is efficient and automatic, is well modeled by bottom-up computational algorithms, and occurs in visually-selective regions of the brain. We review recent evidence from these three methodologies (behavioral, computational, and neural) that converge to suggest the core of social interaction perception is visual. We propose a computational framework for how this process is carried out in the brain and offer directions for future interdisciplinary investigations of social perception.

Relational visual representations underlie human social interaction recognition

Humans effortlessly recognize social interactions from visual input. Attempts to model this ability have typically relied on generative inverse planning models, which make predictions by inverting a generative model of agents' interactions based on their inferred goals, suggesting humans use a similar process of mental inference to recognize interactions. However, growing behavioral and neuroscience evidence suggests that recognizing social interactions is a visual process, separate from complex mental state inference. Yet despite their success in other domains, visual neural network models have been unable to reproduce human-like interaction recognition. We hypothesize that humans rely on relational visual information in particular, and develop a relational, graph neural network model, SocialGNN. Unlike prior models, SocialGNN accurately predicts human interaction judgments across both animated and natural videos. These results suggest that humans can make complex social interaction judgments without an explicit model of the social and physical world, and that structured, relational visual representations are key to this behavior.

Helpers or halos: examining the evaluative mechanisms underlying selective prosociality

This research examines the proximate evaluative mechanisms underlying prosocial partner choice-based reciprocity. Across four studies we presented 855 university undergraduates (online for course credit) and 76 4- to 6-year-olds (offline at a university laboratory) with vignettes describing prosocial, social and non-social characters, and asked participants about their person preferences in prosocial, social and general contexts. Adults demonstrated sophisticated appraisals, coordinating between relevant trait and contextual cues to make selections. Adults were particularly attentive to prosocial cues in costly conditions, suggesting that they were using dispositional attributions to make their selections. By contrast, children were largely unable to integrate trait and contextual cues in determining their partner preferences, instead displaying valenced preferences for non-social cues, suggesting the use of affective tagging. Together, these studies demonstrate that the mechanisms underlying prosocial, partner choice-based reciprocity are not early emerging and stable but show considerable development over the lifespan.