Journal Collective Intelligence

Aim & Scope

Collective Intelligence is a transdisciplinary journal devoted to advancing the theoretical and empirical understanding of collective performance in diverse systems, including human organizations, hybrid AI-human teams, computer networks, adaptive matter, cellular systems, neural circuits, animal societies, nanobot swarms, and others. The journal embraces a policy of creative rigor in the study of collective intelligence to facilitate the discovery of principles that apply across scales and new ways of harnessing the collective to improve social, ecological, and economic outcomes. In that spirit, the journal encourages a broad-minded approach to collective performance. We welcome perspectives that emphasize traditional views of intelligence as well as optimality, satisficing, robustness, adaptability, and wisdom. In more technical terms, this includes issues related to collective output quality and assessment, aggregation of information and related topics (e.g., network structure and dynamics, higher-order vs. pairwise interactions, spatial and temporal synchronization, diversity, etc.), accumulation of information by individuals/components, environmental complexity, evolutionary considerations, and design of systems and platforms fostering collective intelligence. ^[1]

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