CollAdapt

Human collectives adapt their cognitive strategies and social networks flexibly in response to multiple changing problems. For example, we as scientists continuously revise our teams and the way we integrate information, depending on the topics we study. As citizens, we participate in diverse collectives that use different strategies to address challenges ranging from economic development to climate change. This ability for collective adaptation contributed to our species’ spectacular success, but sometimes our collectives seem stuck and unable to adapt to the problems they face. We currently do not have a solid scientific paradigm for studying collective adaptation, and its cognitive and social aspects have been studied largely independently in different disciplines. I will develop such a paradigm by building computational models to integrate research on cognition and sociality, and by collecting diverse empirical data on the interaction of cognitive and social processes, including group experiments, natural language processing of large textual corpora, and longitudinal surveys. This will allow me to investigate (i) the interplay of social learning strategies, networks, and problems that collectives face, (ii) the formation and persistence of people’s beliefs about what the important problems are, and (iii) the effect on collective adaptation of individual differences in these beliefs. I am well positioned for this task because of my experience in building computational models grounded in theories and data on human cognition and sociality, and the support from the Complexity Science Hub Vienna that has been designed for this kind of research. This project will enable us to understand why collectives can be stuck in deadlocks about important problems and why they sometimes appear incapable of finding seemingly obvious solutions, ultimately helping us to avoid undesirable societal trajectories such as those leading to extremism and violence.