Globalization and the rise and fall of cognitive control

The modern world is characterized by unprecedented interconnectedness and globalization, alongside significant technological advancements. However, these advancements are often misused (e.g., antibiotic overuse), and there's a growing backlash against rational, deliberative thinking (e.g., rejection of scientific expertise). This research investigates how this interconnectedness influences societal dynamics by integrating cognitive psychology (specifically, the automatic versus controlled processing distinction) and evolutionary dynamics. Automatic processing is efficient but inflexible, while controlled processing is flexible but costly. Evolutionary game theory is the ideal tool to model the population-level dynamics and the impact of cognition on the environment, particularly concerning the interplay of automatic and controlled processing in human behavior and societal outcomes. This study builds on previous models exploring cooperation and cognition-environment feedback effects, and extends these by integrating social network models to examine the impact of local versus global interaction structures on the evolution of cognitive control.

The authors review existing literature on automatic versus controlled processing in cognitive psychology and neuroscience, highlighting the trade-off between efficiency (automatic) and flexibility (controlled). They cite studies demonstrating the advantages and disadvantages of each type of processing in various contexts, such as decision-making, resource management, and response to environmental changes. The literature on evolutionary game theory, particularly regarding cooperation and the co-evolution of cooperation and cognition, is also reviewed. The authors mention previous models demonstrating the emergence of cycles between automatic and controlled processing due to cognition-environment feedback. Finally, the paper draws on research related to social network models and the influence of population structure on evolutionary dynamics.

The researchers developed an agent-based model simulating a population of agents with varying probabilities of using automatic versus controlled processing (*x*). Agent fitness (*f*) is determined by the payoff of their chosen processing mode (controlled payoff π^c or automatic payoff π^a), incorporating a fixed cost (*c*) for controlled processing, and the impact (*w*) of automatic agents on controlled agents' payoffs. The environment's state (*p*) influences automatic processing payoffs, and is updated based on the population's average level of controlled processing. The model incorporates a death-birth Moran process with exponential fitness for strategy updating, allowing for both genetic and cultural evolution interpretations. A key innovation is the introduction of population structure, modeling agents on a ring network and varying the scale of interaction in three dimensions: learning (local or global teacher selection), contact (local or global calculation of <*x*> affecting controlled processing payoffs), and environment (local or global updating of *p*). Eight scenarios (2³ combinations of local/global for learning, contact, and environment) were simulated to examine the impact of different forms of globalization. The model also includes a time lag (*τ_ρ*) parameter to explore the effects of delayed feedback between cognition and the environment. Simulations were run for 8 × 10⁴ generations (except for lag analysis which used 1.2 × 10⁶), with parameters systematically varied across simulations, and results averaged over 10 replicates.

The study's key findings reveal the complex and multifaceted impact of globalization on the evolution of cognitive control. Analysis of the simplified model and agent-based simulations showed that when automatic processing harms controlled processing (*w* < 0), globalization of learning, contact, or environment substantially reduces the average level of controlled processing. Conversely, when automatic processing benefits controlled processing (*w* > 0), globalization of contact can somewhat increase the average level of controlled processing. The analysis of spatial and temporal dynamics revealed the emergence of mesoscale communities of agents with similar cognitive strategies when learning is local. Interestingly, global environments, contrary to expectations, fostered stronger mesoscale communities compared to local environments. Global environments also led to greater variance in the level of control within the population. The introduction of a time lag in cognition-environment feedback resulted in strong temporal fluctuations even in fully globalized scenarios, although local learning dampened the magnitude of these fluctuations. Overall, the results emphasize the importance of considering the specific forms of globalization and the nature of the interaction between automatic and controlled processing in predicting outcomes.

The findings highlight the complex and context-dependent effects of globalization on cognitive control. The impact of globalization varies greatly depending on the nature of interactions between automatic and controlled agents (*w*), the scale of interaction (learning, contact, environment), and the presence of time lags in cognition-environment feedback. The results contrast with previous findings on the evolution of cooperation, where local spatial structure maintains heterogeneity, demonstrating the importance of considering the specific game structure and forms of globalization. The study provides further support for the emergence of cycles in automaticity versus control due to lagged cognition-environment feedback, suggesting a potential risk of societal collapse or fluctuation in highly complex societies. This is because globalization eliminates the buffering effects of local communities in the face of environmental change and allows for rapid global spread of suboptimal strategies, ultimately affecting the long-term stability and survival of society.

This research contributes a novel theoretical framework to understand the impact of globalization on cognitive evolution, emphasizing the importance of considering different types of globalization (learning, contact, environment) and the interplay between automatic and controlled processing. The findings suggest that promoting interactions where control benefits from contact with automaticity, addressing global-level environmental issues, and acknowledging the potential for global collapse due to globalized learning are crucial for fostering a sustainable future. Future research could explore these findings in laboratory experiments and by analyzing observational data from real-world systems.

The model is a simplification of complex social and environmental dynamics. The ring network structure, while useful for analysis, may not fully capture the complexity of real-world interaction networks. Furthermore, the model's parameters (e.g., *c*, *w*, *τ_ρ*) represent stylized abstractions of potentially multifaceted phenomena. Despite these limitations, the model provides valuable insights into the broad principles governing the interplay between globalization and cognitive evolution.