The Digital Ecosystem of Beliefs: does evolution favour AI over humans?

2024-12-19

AI Summary

This study investigates the systemic impact of AI-dominated digital content ecosystems on human belief formation and propagation. We propose Digico—the first evolutionary computational framework for digital belief ecosystems—integrating universal Darwinian selection dynamics, cognitive Lamarckian inheritance mechanisms, and an SIS-type belief contagion model to simulate coevolution among AI agents and heterogeneous human populations on social networks. We formally quantify, for the first time, the ecological dominance threshold of AI under its triple advantages: message generation rate, evolutionary speed, and recommendation weight. Experiments show that when AI controls 80%–95% of content exposure, propaganda-oriented AI agents induce extreme belief adoption in 50%–85% of humans. Introducing a “belief incongruence penalty” mechanism reduces propaganda efficacy by up to 8%. Our work provides a computationally tractable framework and empirically grounded intervention levers for understanding and governing AI-driven information ecosystem evolution.

Technology Category

• Multiagent Systems: Adversarial Agents
• Humans and AI: Learning Human Values and Preferences
• Application Domains: Humanities & Computational Social Science

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

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 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.

Problem

• Artificial Intelligence
• Belief Formation
• Digital Ecosystems

Innovation

• Digital Ecosystem of Beliefs
• AI-generated content impact
• Propaganda mitigation strategies