Recorded 20 November 2024. Alice Schwarze of Utah AI Policy Office presents "Emerging Intelligence: from neurons to social dynamics" at IPAM's Modeling Multi-Scale Collective Intelligences Workshop. Abstract: Many classical models of collective behavior assume that emergent dynamics result from external and observable interactions among individuals. However, how collective dynamics in human populations depend on the internal psychological processes of individuals remains underexplored. Here, we develop a mathematical model to investigate the effects of internal psychology on the dynamics of collective action. Our model is grounded in the theory of planned behavior -- a well-established conceptual framework in social psychology that links intrinsic beliefs to behavior. By incorporating temporal biases in social perception and individual differences in decision-making processes into our model, we find that the interplay between internal and external drivers of behavior can produce diverse outcomes, ranging from partial participation in collective action to rapid or delayed cascades of action-taking. These distinct outcomes are preceded by transient dynamics that are qualitatively similar to one another, which, just as in real-world scenarios, makes it difficult to predict long-term collective dynamics from early observations. Our model thus provides a useful test bed for methods that aim to predict the emergence of collective action, and it lays the groundwork for studying the nuanced dynamics of collective human behavior arising from the interaction between psychological processes and observable actions. Learn more online at: https://www.ipam.ucla.edu/programs/workshops/workshop-iv-modeling-multi-scale-collective-intelligences/?tab=overview