Understanding Partner S election for Cooperation
Cooperation and cooperative social re lationships are the cornerstone of human social success and well-bein g. The puzzle of our cooperative psychology has been a topic of inter est for many decades. In recent years, this puzzle has become relevan t in computational fields, given the rapid development of artificial intelligence. Research efforts in this area envision AI systems as re commenders or social catalysts. While these applications have shown p romise in enabling humans to reflect on their behavior during meeting s, their utilization in everyday social interactions remains limited. Extending the usability of such systems can help people to reflect o n their behavior in social interactions or how they select partners f or cooperation. Thus, the main proposition of Tiffany Matej Hrkalovic 's thesis is that before we design such systems, we must first expand our understanding of how people initiate cooperative behavior and se lect partners for cooperative interactions.
People want partner s who are high on warmth and competence when selecting partners. Howe ver, this relationship is dependent on specific tasks, where people p refer warmer partners when warmth is important for a task, while they prefer competent partners in tasks where a partner's competence is m ore important. Additionally, people are more cooperative towards part ners they select and want to interact with, compared to partners they don't want to interact with. However, people are not very good at se lecting partners who will cooperate back when selecting partners in r eal-life interactions. Matej Hrkalovic tested these research question s in real social interactions and purely non-interactive settings. La stly, she also shows how people think and describe their relationship s can help predict their prosocial and punishment behavior towards th eir relationship partners.
AI systems are growing in popularity , yet they remain limited in their ability to support human decision- making in social interactions. Matej Hrkalovic's thesis addresses tha t gap by exploring key social phenomena involved in how people choose partners for cooperation. It provides empirical resources and a data set to support modeling efforts in this area. Her research offers val uable contributions to both psychology and human-AI interaction, pres enting insights that can inform future studies in both disciplines.
More information on the
DESCRIPTION: Cooperation and cooperative social relationships are the cornerstone of human social success and well-being. The puzzle of our cooperative psychology has been a topic of interest for many decades . In recent years, this puzzle has become relevant in computational f ields, given the rapid development of artificial intelligence. Resear ch efforts in this area envision AI systems as recommenders or social catalysts. While these applications have shown promise in enabling h umans to reflect on their behavior during meetings, their utilization in everyday social interactions remains limited. Extending the usabi lity of such systems can help people to reflect on their behavior in social interactions or how they select partners for cooperation. Thus , the main proposition of Tiffany Matej Hrkalovic's thesis is that be fore we design such systems, we must first expand our understanding o f how people initiate cooperative behavior and select partners for co operative interactions. People want partners who are high on warmth a nd competence when selecting partners. However, this relationship is dependent on specific tasks, where people prefer warmer partners when warmth is important for a task, while they prefer competent partners in tasks where a partner's competence is more important. Additionall y, people are more cooperative towards partners they select and want to interact with, compared to partners they don't want to interact wi th. However, people are not very good at selecting partners who will cooperate back when selecting partners in real-life interactions. Mat ej Hrkalovic tested these research questions in real social interacti ons and purely non-interactive settings. Lastly, she also shows how p eople think and describe their relationships can help predict their p rosocial and punishment behavior towards their relationship partners. AI systems are growing in popularity, yet they remain limited in the ir ability to support human decision-making in social interactions. M atej Hrkalovic's thesis addresses that gap by exploring key social ph enomena involved in how people choose partners for cooperation. It pr ovides empirical resources and a dataset to support modeling efforts in this area. Her research offers valuable contributions to both psyc hology and human-AI interaction, presenting insights that can inform future studies in both disciplines. More information on the thesi s Understanding Partner Selection for Cooperation END:VEVENT END:VCALENDAR