Crowds vs swarms, a comparison of intelligence
Crowds vs swarms, a comparison of intelligence
复制标题
群体与群体，智力的比较
DOI：
10.1109/shbi.2016.7780278
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
N. Pescetelli
中科院分区：
文献类型：
--
作者：
Louis B. Rosenberg;David Baltaxe;N. Pescetelli
世纪以来，集体智慧领域的研究人员已经证明，在做出决策、预测和预测时，群体的表现可以超过个人。利用群体智慧的最常见方法是将人口视为独立代理人的“群体”，这些代理人以民意测验、调查和市场交易的形式孤立地提供投入。虽然这种基于群体的方法可能是有效的，但它们与自然系统利用群体智慧的方式明显不同。在自然界中，群体通常形成实时闭环系统（即“群”），同步收敛于解决方案。本研究在挖掘人类群体的智力时，比较了群体和蜂群的预测能力。更具体地说，本研究要求469名足球迷和29名足球迷参加一项挑战，以预测2016年超级碗期间的20个道具投注。结果显示，虽然人群的规模大16倍，但准确率（47%）明显低于群体（68%）。此外，在整个研究中，蜂群的表现超过了98%的个体。这些结果表明，具有闭环反馈的群集可能是比传统民意调查更有效的挖掘群体见解的方法。
For well over a century, researchers in the field of Collective Intelligence have shown that groups can outperform individuals when making decisions, predictions, and forecasts. The most common methods for harnessing the intelligence of groups treats the population as a “crowd” of independent agents that provide input in isolation in the form of polls, surveys, and market transactions. While such crowd-based methods can be effective, they are markedly different from how natural systems harness group intelligence. In the natural world, groups commonly form real-time closed-loop systems (i.e. “swarms”) that converge on solutions in synchrony. The present study compares the predictive ability of crowds and swarms when tapping the intelligence of human groups. More specifically, the present study tasked a crowd of 469 football fans and a swarm of 29 football fans in a challenge to predict 20 Prop Bets during the 2016 Super Bowl. Results revealed that the crowd, although 16 times larger in size, was significantly less accurate (at 47% correct) than the swarm (at 68% correct). Further, the swarm outperformed 98% of the individuals in the full study. These results suggest that swarming, with closed-loop feedback, is potentially a more effective method for tapping the insights of groups than traditional polling.