Artificial Swarming Shown to Amplify Accuracy of Group Decisions in Subjective Judgment Tasks
Artificial Swarming Shown to Amplify Accuracy of Group Decisions in Subjective Judgment Tasks
复制标题
人工集群可以提高主观判断任务中群体决策的准确性
DOI：
10.1007/978-3-030-12385-7_29
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Colin Domnauer
中科院分区：
文献类型：
--
作者：
G. Willcox;Louis B. Rosenberg;David A. Askay;L. Metcalf;Erick Harris;Colin Domnauer
新技术使分布式人类团队能够形成模仿自然群体的实时系统。这些实时系统通常被称为人工群体智能 (ASI) 或简称为“人类群体”，已被证明可以在各种任务中增强群体智能，从阻碍体育运动到预测金融市场。虽然大多数先前的研究都是针对 20-100 名成员的人类群体进行研究，但本研究探讨了 ASI 在 3-6 名成员的小团队中提高准确性的能力。本研究还探讨了进行多个群体并通过“群体投票”进行聚合是否可以进一步提高准确性。共有 66 个小团队参与了这项研究。每个团队都接受了标准的主观判断测试。参与者以个人和实时群体的形式参加了测试。个体的平均正确率为 69%，而群体的平均正确率为 84% (p < 0.001)。此外，多个群体的聚集揭示了准确性的额外放大。例如，通过随机选择 3 个群并通过多数投票进行聚合，平均准确度提高到 91% (p < 0.001)。这些结果表明，当小团队作为实时群体做出主观判断时，它们可以比单个成员更准确，并且通过聚合小群体的输出可以进一步放大它们的准确性。
New technologies enable distributed human teams to form real-time systems modeled after natural swarms. Often referred to as Artificial Swarm Intelligence (ASI) or simply “human swarming”, these real-time systems have been shown to amplify group intelligence across a wide range of tasks, from handicapping sports to forecasting financial markets. While most prior research has studied human swarms with 20–100 members, the present study explores the ability of ASI to amplify accuracy in small teams of 3–6 members. The present study also explores if conducting multiple swarms and aggregating by taking a “vote of swarms” can further amplify the accuracy. A large set of 66 small teams were engaged in this study. Each team was given a standard subjective judgement test. Participants took the test both as individuals and real-time swarms. The average individual scored 69% correct, while the average swarm scored 84% correct (p < 0.001). In addition, aggregation of multiple swarms revealed additional amplifications of accuracy. For example, by randomly selecting sets of 3 swarms and aggregating by plurality vote, average accuracy increased to 91% (p < 0.001). These results suggest that when small teams make subjective judgements as real-time swarms, they can be significantly more accurate than individual members, and that their accuracy can be further amplified by aggregating the output across small sets of swarms.
人工智能群体智能用于提高放射学诊断的准确性
DOI：
10.1109/iemcon.2018.8614883
发表时间：
2018
期刊：
IEMCON 2018
影响因子：
--
作者：
Rosenberg, Louis;Lungren, Matthew;Halabi, Safwan;Willcox, Gregg;Baltaxe, David;Lyons, Mimi
通讯作者：
Lyons, Mimi