Collective intelligence is the ability of groups to solve problems and make decisions more effectively than their individual members can. The phenomenon appears across the natural world. We see it when shoals of fish decide as a group which direction to travel, and in the elaborate mound systems built by ants through the decentralized activity of thousands of individuals. In humans, collective intelligence is exhibited in the accumulation of knowledge transmitted across generations, and in procedures such as majority voting, used to decide questions for a group. This theme issue brings together scholars from multiple disciplines to explore the evolutionary origins of collective intelligence, its role in contemporary societies, and how emerging technologies may reshape it in the future.

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Munjung Kim, Sadamori Kojaku, and Yong-Yeol Ahn
Science Advances Vol 12, Issue 14

Progress in science and technology is punctuated by disruptive innovation and breakthroughs. To understand disruptive innovations and their drivers, the ability to operationalize and estimate “disruptiveness” is critical. Yet, this task remains difficult because scientific influence propagates through both direct and indirect citation paths, and discoveries are often fragmented across multiple papers. Here, we introduce an embedding-based metric of disruptiveness. When applied to large-scale publication data, the measure not only reliably identifies canonical breakthroughs, such as Nobel Prize–winning papers, but also finds simultaneous disruptions that eluded standard approaches. By enabling more robust identification of disruptive innovations and simultaneous discoveries, our method facilitates more accurate attribution of transformative contributions while providing insights into the mechanisms driving scientific breakthroughs.

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