Cultural Evolution, Disinformation, and Social Division.

The article focuses on how cultural-evolutionary theory can illuminate the dynamics of knowledge diversity, disinformation, and social division in the digital age. It explains that while diversity of expertise historically supported human adaptation, contemporary social media often amplifies popularity bias and reduces transparency of information, fostering homophily and isolating experts, which can fragment shared knowledge and increase social polarization. The authors propose a model using two key parameters—transparency of information and social conformity (popularity bias)—to characterize communication networks and predict when social learning benefits decline due to excessive conformity or information overload. They suggest that computational social science methods, such as Approximate Bayesian Computation, can estimate these parameters from real-world data to help identify "safe operating spaces" for digital communication and mitigate the spread of disinformation.