Computations underlying social decision-making in naturalistic situations

• Applicant: Tessa Rusch, Ph.D.
• Subject Area: General, Cognitive and Mathematical Psychology
• Term: from 2021 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 469957399

In this project, I aim to examine how humans make sense of other people’s mental processes during naturalistic interaction. Vast social psychology research has successfully characterized the inferences people make about other people, separating them into mental states (dynamically changing properties such as emotions) and traits (temporally stable properties such as personality). These approaches typically rely on static and limited stimuli, such as pictures of people’s faces. However, real social interaction leads to very different experiences and creates behavioural relevance that is absent in commonly applied laboratory settings. A more interactive approach to query similar questions is taken in behavioural economics. Using structured interactive decision scenarios (so called “games”) behavioural economics investigates the factors driving interactive behaviours. The simple and well structed tasks lend themselves well to computational cognitive modelling which allows quantifying the hidden variables (like state and trait inferences) that drive interactive behaviours. However, in these games modes of interaction are limited and usually very brief in duration, which again severely limits the generalisation of the results to real-world social settings which usually involve repeated interactions across longer windows of time. Here, I plan to combine and expand on methodologies from both fields to create naturalistic, representative scenarios that allow querying the inferences humans make about another during unconstrained and long-lasting real-world interaction (through a text-based chat) and structured strategic interaction (through interactive economic games). I propose two longitudinal interactive studies conducted over the internet in a relatively large and carefully selected sample of subjects. In a first study, participants will repeatedly interact with multiple previously unknown partners via text-based chat. In a second study, another group of participants will repeatedly interact via structured economic decision games. In both studies I will quantify the inferences they make about their partner’s traits and states and how these are updated as participants get to know each other over multiple months of interaction. Three highly innovative features of my planned work are (1) representative sampling of subjects, based on their facial appearance and personality; (2) extraction of features from the chat or the games that can explain the state and trait inferences subjects make; and (3) a longitudinal component, whereby pairs of participants will interact repeatedly over several months. This project will provide novel insights into how we represent and learn about other people in naturalistic environments, a question that is of great interest to social psychology, neuroscience and artificial intelligence.

• DFG Programme: WBP Fellowship
• International Connection: USA
• Host: Professor Dr. Ralph Adolphs