Amplifying the Social Intelligence of Teams Through Human Swarming

Abstract

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

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通过人类群体放大团队的社会智力

人工群体智能(ASI)是一种通过将网络参与者连接到以自然群体为模型并由人工智能算法调节的实时系统中来放大人类群体集体智慧的方法。从预测金融市场到确定相互冲突的目标的优先级，ASI已被证明可以在广泛的任务中增强性能。本研究探讨了ASI系统增强小团队社会智能的能力。一组61个小组，每组3到6名成员，进行了一个标准的社会敏感性测试——“从眼睛里读心”或RME。受试者以个人和ASI系统(即“群体”)的形式参加测试。在RME测试中，个体平均35分中有24分正确(32%错误)，而ASI群体平均35分中有30分正确(15%错误)。统计分析发现，作为ASI群体工作的群体的社会敏感性显著高于单独工作的个体或通过多数投票共同工作的群体(p< 0.01)。这表明，当群体以实时ASI群体的方式做出决策时，他们比单独工作或传统的群体投票更能利用自己的社会智力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。