Amplifying the Social Intelligence of Teams Through Human Swarming

Artificial Swarm Intelligence (ASI) is a method for amplifying the collective intelligence of human groups by connecting networked participants into real-time systems modeled after natural swarms and moderated by AI algorithms. ASI has been shown to amplify performance in a wide range of tasks, from forecasting financial markets to prioritizing conflicting objectives. This study explores the ability of ASI systems to amplify the social intelligence of small teams. A set of 61 teams, each of 3 to 6 members, was administered a standard social sensitivity test -“Reading the Mind in the Eyes” or RME. Subjects took the test both as individuals and as ASI systems (i.e. “swarms”). The average individual scored 24 of 35 correct (32% error) on the RME test, while the average ASI swarm scored 30 of 35 correct (15% error). Statistical analysis found that the groups working as ASI swarms had significantly higher social sensitivity than individuals working alone or groups working together by plurality vote (p<;0.001). This suggests that when groups reach decisions as real-time ASI swarms, they make better use of their social intelligence than when working alone or by traditional group vote.