---
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 dynamics"
confidence: experimental
source: "Patterns/Cell Press 2024 review proposing multiplex network framework for AI-enhanced collective intelligence"
created: 2026-03-11
---

# Multiplex network framework models collective intelligence as three interacting layers cognition physical information

Collective intelligence in AI-human systems can be modeled as a multiplex network with three distinct but interacting layers: cognition (mental models, knowledge, reasoning), physical (spatial proximity, embodied interaction), and information (communication channels, data flows). Each layer has intra-layer dynamics (connections within the layer) and inter-layer dynamics (how layers influence each other).

Nodes in this framework represent both humans (varying in surface-level and deep-level diversity) and AI agents (varying in functionality and anthropomorphism). Collective intelligence emerges through both bottom-up processes (aggregation of individual contributions) and top-down processes (norms, structures, coordination mechanisms).

The framework provides a structured way to analyze where AI integration enhances versus degrades collective intelligence: enhancements and degradations can be localized to specific layers and specific types of connections. For example, AI might enhance information layer connectivity while degrading physical layer social bonds.

## Evidence

- Patterns/Cell Press 2024 review proposes multiplex network framework as organizing structure for AI-enhanced collective intelligence research
- Framework distinguishes three layers: cognition, physical, information
- Nodes = humans (with diversity attributes) + AI agents (with functionality/anthropomorphism attributes)
- Collective intelligence emerges through bottom-up (aggregation) and top-down (norms/structures) processes

## Limitations

The review notes this is a proposed framework, not a validated model. The authors explicitly state there is "no comprehensive theoretical framework" explaining when AI-CI systems succeed or fail, suggesting this multiplex network model is a research direction rather than established theory.

---

Relevant Notes:
- [[collective intelligence is a measurable property of group interaction structure not aggregated individual ability]]
- [[intelligence is a property of networks not individuals]]
- [[domains/ai-alignment/_map]]
- [[foundations/collective-intelligence/_map]]

Topics:
- [[foundations/collective-intelligence/_map]]
- [[domains/ai-alignment/_map]]