Young children’s intuitions about the meanings of novel nouns have revealed foundational biases in language learning. Nevertheless, existing work on such word-learning biases has focused primarily on only one spatial domain to which nouns might refer—objects—not the large-scale and navigable places in which objects are situated. Previous research has nevertheless shown that adults and children treat objects and places differently not only in recognition and navigation tasks, but also in symbolic tasks, like drawing production. In a noun-extension task, we thus evaluate young children’s and adults’ word-learning biases across these two spatial domains—objects and places—and show that young children and adults treat objects and places differently in language: Young children and adults preferentially extend novel nouns to objects over places. This bias suggests a specific role for spatial domain in word learning and may reflect greater attention to objects over places in symbolic contexts like language.

Young children tend to prioritize objects over layouts in their drawings, often juxtaposing “floating” objects in the picture plane instead of grounding those objects in drawn representations of the extended layout. In the present study, we explore whether implicitly directing children’s attention to elements of the extended layout through a drawing’s communicative goal—to indicate the location of a hidden target to someone else—might lead children to draw more layout information. By comparing children’s drawings to a different group of children’s verbal descriptions, moreover, we explore how communicative medium affects children’s inclusion of layout and object information. If attention modulates children’s symbolic communication about layouts and objects, then children should both draw and talk about layouts and objects when they are relevant to the communicative task. If there are challenges or advantages specific to either medium, then children might treat layouts and objects differently when drawing versus describing them. We find evidence for both of these possibilities: Attention affects what children include in symbolic communication, like drawings and language, but children are more concise in their inclusion of relevant layout or object information in language versus drawings.

Human infants have remarkable abilities to reason about the underlying and invisible causes that drive others' actions. These abilities are at the core of human social cognition throughout life. Artificial Intelligence (AI) systems continue to fall short in achieving this same commonsense social knowledge. Recent benchmarks focusing on social cognition and theory of mind have begun to address the gap between human and machine social intelligence, but they do not fully consider the social reasoning required to understand scenarios with multiple interacting agents. Building on such benchmarks, we present eight new tasks focusing on different early social competencies, as informed by behavioral experiments with infants. We use a self-supervised Transformer model as a baseline test of our new tasks, and in addition, we evaluate this model on a previous social-cognitive benchmark. While our model shows improved performance on the previous benchmark compared with other data-driven models, it performs sub-optimally on our new tasks, revealing the challenge of learning complex social interactions through visual data alone.

Young infants reason about the goals, preferences, and actions of others. State of the art computational models, however, still fail in such reasoning. The Baby Intuitions Benchmark (BIB) was designed to test agency reasoning in AI using an infant behavioral paradigm. While BIB’s presentation of simple animations makes it particularly suitable for testing AI, such vignettes have yet to be validated with infants. In this pilot, 11-month-old infants watched two sets of animations from BIB, one on agents’ consistent preferences and the other on agents’ efficient actions. Infants looked longer towards violations in agents’ behavior in both the preference (N = 24, β = 3.24 p = .040) and efficiency task (N = 24, β = 4.50 p = .016). These preliminary results suggest that infants’ agency reasoning is abstract enough to be elicited by simple animations and validate BIB as a test of agency reasoning for humans and AIs.

Throughout the lifespan and across cultures, all human behavior happens in space. By early childhood, people are capable of navigating complex 3D environments, executing sophisticated motor plans, and coordinating action with others. They also use their representations of space to structure a variety of non-spatial concepts, including time, number, similarity, and emotion. How do people perform these cognitive feats? One source of insight comes from studying the diversity of spatial cognition: Although the physical properties of space are invariant, the way people typically conceptualize space varies radically across groups, between individuals, and over development. By studying this variation in spatial cognition, we can better understand the universal set of cognitive and neural mechanisms that underlie it, with implications for the cognitive sciences, education, and design.