--- type: claim domain: ai-alignment secondary_domains: [collective-intelligence] description: "Collective intelligence emerges from interactions across cognition, physical, and information network layers with both intra-layer and inter-layer links" confidence: experimental source: "Patterns/Cell Press 2024 review proposing multiplex network framework" created: 2026-03-11 --- # Multiplex network framework models collective intelligence as three interacting layers: cognition, physical, information The multiplex network framework models collective intelligence systems as three interacting network layers: 1. **Cognition layer**: Mental models, beliefs, knowledge structures 2. **Physical layer**: Face-to-face interactions, spatial proximity, physical infrastructure 3. **Information layer**: Digital communication, data flows, algorithmic connections Each layer has its own network structure (nodes and edges), and collective intelligence emerges from both intra-layer dynamics (within each network) and inter-layer interactions (how the three networks influence each other). Nodes in the network include both humans (varying in surface-level and deep-level diversity) and AI agents (varying in functionality and anthropomorphism). Collective intelligence emerges through bottom-up processes (aggregation of individual contributions) and top-down processes (norms, structures, coordination mechanisms). ## Evidence - Framework proposed in comprehensive review as synthesis of existing research - Integrates findings from network science, organizational behavior, and AI-human collaboration studies - Provides structure for analyzing when AI enhances vs. degrades collective intelligence - The review identifies this as a key conceptual framework but notes it is descriptive rather than predictive ## Framework Limitations The review explicitly notes that this framework is descriptive, not predictive. It provides a way to categorize and analyze collective intelligence systems but does not yet predict when specific configurations will succeed or fail. The authors identify the lack of a "comprehensive theoretical framework" as a major gap in the field. ## Relationship to Existing Work This framework provides a formal structure for claims like [[collective intelligence is a measurable property of group interaction structure not aggregated individual ability]] by explicitly modeling the interaction structure across three network layers. It also connects to [[intelligence is a property of networks not individuals]] by treating collective intelligence as an emergent property of multiplex network dynamics. --- Relevant Notes: - [[collective intelligence is a measurable property of group interaction structure not aggregated individual ability]] - [[intelligence is a property of networks not individuals]] - [[partial connectivity produces better collective intelligence than full connectivity on complex problems because it preserves diversity]]