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Abstract

Science communication plays a crucial role in maintaining public trust in science amid complex societal challenges. This study addresses a gap in understanding science communication dynamics by conceptualizing it as a complex adaptive system of actors. It introduces the CASSCO (Complex Adaptive Systems in Science Communication) model, which integrates complex adaptive systems theory with game theory to analyze strategic interactions in science communication. The model encompasses decision-making processes, impact evaluation, and learning mechanisms among actors, distinguishing between altruistic and self-interested roles across three communication modes: dissemination, dialogue, and participation. By applying the CASSCO model to two scenarios—citizen science and generative AI—the study demonstrates its potential for predicting nonlinear dynamics and emergent outcomes in science communication. This approach yields insights into the impact of communication strategies on public trust and contestations of science. The CASSCO model serves as a strategic thinking template, enabling actors to select strategies while considering the behaviors of others. The study concludes with theoretical and practical implications, model limitations, and future research directions.

Keywords

Science communication trust complex adaptive systems systems theory

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Strategic Interactions in Science Communication: A Complex Adaptive Systems Framework

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