Social and non-social categorisation in investment decisions and learning

Categorical processes allow us to make sense of the environment effortlessly by grouping stimuli sharing relevant features. Although these processes occur in both social and non-social contexts, motivational, affective, and epistemic factors specific to the social world may motivate individuation over categorisation of social compared with non-social stimuli. In one experiment, we tested this hypothesis by analysing the reliance on categorical versus individuating information when making investment decisions about social and non-social targets. In an adaptation of the iterative trust game, participants from three experimental groups had to predict the economic outcomes associated with either humans (i.e., social stimuli), artificial races (i.e., social-like stimuli), or artworks (i.e., non-social stimuli) to earn economic rewards. We observed that investment decisions with humans were initially biased by categorical information in the form of gender stereotypes, but later improved through an individuating learning approach. In contrast, decisions made with non-social stimuli were initially unbiased by categorical information, but the category-outcomes associations learned through repeated interactions were quickly used to categorise new targets. These results are discussed along with motivational and perceptual mechanisms involved in investment decisions and learning about social and non-social agents.