Swarm Intelligence (SI) is a natural phenomenon that enables social species to quickly converge on optimized group decisions by interacting as real-time closed-loop systems. This process, which has been shown to amplify the collective intelligence of biological groups, has been studied extensively in schools of fish, flocks of birds, and swarms of bees. This paper provides an overview of a new collaboration technology called Artificial Swarm Intelligence (ASI) that brings the same benefits to networked human groups. Sometimes referred to as “human swarming” or building “hive minds,” the process involves groups of networked users being connected in real-time by AI algorithms modeled after natural swarms. This paper presents the basic concepts of ASI and reviews recently published research that shows its effectiveness in amplifying the collective intelligence of human groups, increasing accuracy when groups make forecasts, generate assessments, reach decisions, and form predictions. Examples include significant performance increases when human teams generate financial predictions, business forecasts, subjective judgements, and medical diagnoses.
CITATION STYLE
Rosenberg, L., & Willcox, G. (2020). Artificial swarm intelligence. In Advances in Intelligent Systems and Computing (Vol. 1037, pp. 1054–1070). Springer Verlag. https://doi.org/10.1007/978-3-030-29516-5_79
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