The Wisdom Of Crowds: When Collective Intelligence Surpasses Individual Intelligence

2016 ◽

Vol 44 (1) ◽

pp. 30-35 ◽

Cited By ~ 6

Author(s):

Kurt Matzler ◽

Andreas Strobl ◽

Franz Bailom

Keyword(s):

Decision Making ◽

Leadership Styles ◽

Design Methodology ◽

Collective Intelligence ◽

Peer Pressure ◽

Wisdom Of Crowds ◽

Cognitive Diversity ◽

Content Type ◽

The Wisdom Of Crowds

Purpose – Under certain conditions, a mass of people can be smarter than the best expert – even if the expert is part of the group. In this paper we show how leaders can improve decision making by tapping into the collective intelligence of their organization. Design/methodology/approach – Based on James Surowiecki’s four conditions of collective intelligence (cognitive diversity, independence, utilization of decentralized knowledge, and effective aggregation of dispersed knowledge), we discuss how leaders can tap into the wisdom of the crowd of their organizations. Findings – We show how leaders can increase cognitive diversity in decision making, access decentralized knowledge in their organizations, encourage individuals to contribute their knowledge without interference from peer pressure, conformity or influence from superiors, and how knowledge can effectively be aggregated to make wiser decisions. Originality/value – While various tools exist to reap the collective intelligence of a group, we argue that leaders also must change their attitudes and leadership styles. Using evidence from various studies and several examples we show what leaders can do to make smarter decisions.

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The wisdom of partisan crowds

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1817195116 ◽

2019 ◽

Vol 116 (22) ◽

pp. 10717-10722 ◽

Cited By ~ 9

Author(s):

Joshua Becker ◽

Ethan Porter ◽

Damon Centola

Keyword(s):

Social Information Processing ◽

Information Exchange ◽

Collective Intelligence ◽

Social Information ◽

Political Polarization ◽

Primary Concern ◽

Wisdom Of Crowds ◽

Partisan Bias ◽

Before And After ◽

The Wisdom Of Crowds

Theories in favor of deliberative democracy are based on the premise that social information processing can improve group beliefs. While research on the “wisdom of crowds” has found that information exchange can increase belief accuracy on noncontroversial factual matters, theories of political polarization imply that groups will become more extreme—and less accurate—when beliefs are motivated by partisan political bias. A primary concern is that partisan biases are associated not only with more extreme beliefs, but also with a diminished response to social information. While bipartisan networks containing both Democrats and Republicans are expected to promote accurate belief formation, politically homogeneous networks are expected to amplify partisan bias and reduce belief accuracy. To test whether the wisdom of crowds is robust to partisan bias, we conducted two web-based experiments in which individuals answered factual questions known to elicit partisan bias before and after observing the estimates of peers in a politically homogeneous social network. In contrast to polarization theories, we found that social information exchange in homogeneous networks not only increased accuracy but also reduced polarization. Our results help generalize collective intelligence research to political domains.

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