论文标题

集体智能的网络结构:小组讨论的偶然性好处

Network Structures of Collective Intelligence: The Contingent Benefits of Group Discussion

论文作者

Becker, Joshua, Almaatouq, Abdullah, Horvát, Emőke-Ágnes

论文摘要

关于信仰形成的研究产生了矛盾的发现,即小组成员之间的交流是否以及何时会提高数字估计的准确性,例如经济预测,医学诊断和候选候选人评估。尽管一些证据表明,诸如“ Delphi方法”之类的精心介导的过程比非结构化讨论产生更准确的信念,而其他人则认为,非结构化的讨论的表现优于介导的过程。还有一些人认为独立个人产生了最准确的信念。本文展示了信仰形成的网络理论如何解决这些不一致之处,即使小组缺乏明显的结构,就像非正式的对话中一样。影响力的紧急网络结构与讨论前信仰分布相互作用,以减轻交流对信仰形成的影响。结果,沟通有时会增加,有时会降低一组平均信念的准确性。介导过程和非结构化通信的效果有所不同,因此每种通信格式的相对好处都取决于群体动力学以及交互前信仰的统计特性。这些结果解决了以前的研究中的矛盾,并为团队和组织提供了实用的建议。

Research on belief formation has produced contradictory findings on whether and when communication between group members will improve the accuracy of numeric estimates such as economic forecasts, medical diagnoses, and job candidate assessments. While some evidence suggests that carefully mediated processes such as the "Delphi method" produce more accurate beliefs than unstructured discussion, others argue that unstructured discussion outperforms mediated processes. Still others argue that independent individuals produce the most accurate beliefs. This paper shows how network theories of belief formation can resolve these inconsistencies, even when groups lack apparent structure as in informal conversation. Emergent network structures of influence interact with the pre-discussion belief distribution to moderate the effect of communication on belief formation. As a result, communication sometimes increases and sometimes decreases the accuracy of the average belief in a group. The effects differ for mediated processes and unstructured communication, such that the relative benefit of each communication format depends on both group dynamics as well as the statistical properties of pre-interaction beliefs. These results resolve contradictions in previous research and offer practical recommendations for teams and organizations.

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