beliefs.To understand such questions, this paper proposes the Digital Ecosystem of Beliefs (Digico), the first evolutionary framework for controlled experimentation with multi-population interactions in simulated social networks. The framework models a population of agents which change their messaging strategies due to evolutionary updates following a Universal Darwinism approach, interact via messages, influence each other's beliefs through dynamics based on a contagion model, and maintain their beliefs through cognitive Lamarckian inheritance. Initial experiments with an abstract implementation of Digico show that: a) when AIs have faster messaging, evolution, and more influence in the recommendation algorithm, they get 80% to 95% of the views, depending on the size of the influence benefit; b) AIs designed for propaganda can typically convince 50% of humans to adopt extreme beliefs, and up to 85% when agents believe only a limited number of channels; c) a penalty for content that violates agents' beliefs reduces propaganda effectiveness by up to 8%. We further discuss implications for control (e.g. legislation) and Digico as a means of studying evolutionary principles.
As AI systems are integrated into social networks, there are AI safety concerns that AI-generated content may dominate the web, e.g. in popularity or impact on