Study title

In a large variety of contexts, it is essential to use the available information to extract patterns and behave accordingly. When it comes to social interactions for instance, the information gathered about interaction partners across multiple encounters (e.g., trustworthiness) is crucial in guiding one’s own behavior (e.g., approach the trustworthy and avoid the untrustworthy), a process akin to trial-by-trial learning. Building on associative learning and social cognition literatures, the present research adopts a domain-general approach to learning and explores whether the principles underlying associative learning also govern learning in social contexts. In particular, we examined whether overshadowing, a well-established cue-competition phenomenon, impacts learning of the cooperative behaviors of unfamiliar interaction partners. Across three experiments using an adaptation of the iterated Trust Game, we consistently observed a ‘social overshadowing’ effect, that is, a better learning about the cooperative tendencies of partners presented alone compared to those presented in a pair. This robust effect was not modulated by gender stereotypes or beliefs about the internal communication dynamics within a pair of partners. Drawing on these results, we argue that examining domain-general learning processes in social contexts is a useful approach to understanding human social cognition.In any domain of daily life and cognition, humans solve tasks and make decisions by using information that comes from multiple, different sources. It is quite obvious that we learn from previous experiences. We then use multiple sources of information to guide our behaviour in environments, make decisions about what is beneficial for us, and act in social situations (attributions, imitation). Most times however, not all information in the environment is useful. For example, if we eat fish and chips and later become ill, it is difficult to know which of the two made us ill, and people...