Our society must continuously adapt to numerous, fast changing challenges, from pandemics to climate change and violent conflicts. This collective adaptation requires that at least some members of the society change their beliefs about the best courses of action. Such “anticonformity” of some members can sometimes be problematic, but at other times can help collectives to explore very different and perhaps better solutions than the current ones.
Anticonformity is still not fully understood. It can assume many different forms and can have varying short and long term effects on others beliefs, depending at least partially on the position of an anticonformist in the social network. To understand the underlying complex adaptive system of cognitions and social networks, we combine knowledge and methods from different disciplines.
Building on theories from cognitive and social psychology, and on quantitative frameworks from applied mathematics and statistical physics, we develop agent based models of anticonformity in different social networks. We then test the predictions of these models in group experiments with human participants. This will enable us to answer the following questions:
This project contributes to science and society in several ways. First, it will help us understand when and why anticonformity occurs in the process of collective adaptation. Second, we will elucidate different types of anticonformity, with some manifesting only on the level of private beliefs and others also on the level of expressed beliefs. Third, we will understand when and why anticonformity helps collective performance on different time and social scales. Finally, this project will break new ground in creating a truly transdisciplinary collaboration in developing experimentally driven and tested computational models of social and belief dynamics.
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