Collective Intelligence is the emergent capacity of groups to perceive, learn, decide, and act together more effectively than any individual could alone. This civic innovation domain encompasses the methods, platforms, and practices that enable distributed cognition — from deliberative democracy and citizen assemblies to prediction markets, swarm intelligence, and AI-augmented sense-making. Collective intelligence recognizes that the complexity of modern challenges exceeds individual cognitive capacity, requiring new ways of thinking together that harness diversity, aggregate knowledge, and surface wisdom from the edges of networks.
The intellectual foundations span multiple disciplines: James Surowiecki's work on the wisdom of crowds, Pierre Lévy's concept of distributed cognition, and Thomas Malone's research at MIT on collective intelligence design. Key insights include the conditions under which groups outperform individuals (diversity, independence, decentralization, and aggregation mechanisms) and the failure modes that lead to groupthink, polarization, and collective blindness. Contemporary research increasingly focuses on human-AI collaboration, exploring how machine learning can augment rather than replace human judgment in collective decision-making.
Practical applications range from citizen assemblies that have shaped policy in Ireland and France, to prediction markets used by corporations and governments for forecasting, to platforms like Polis that enable large-scale deliberation and consensus-finding. Organizations like Nesta's Centre for Collective Intelligence Design, the MIT Center for Collective Intelligence, and The Collective Intelligence Project are advancing both theory and practice. The field is evolving rapidly as AI capabilities expand, with growing focus on "collective intelligence safety" — ensuring that AI systems amplify rather than undermine humanity's capacity for wise collective action.