Measuring Collective Intelligence in Human-Machine Systems
Abstract
Psychologists have repeatedly shown that a single statistical factor often called general intelligence emerges from the correlations among people's performance on a wide variety of cognitive tasks. But no one had systematically examined whether a similar kind of collective intelligence exists for groups of people. In this work, we have found converging evidence of a general collective intelligence factor that explains a group's performance on a wide variety of tasks. We also found that this c factor is not strongly correlated with the average or maximum individual intelligence of group members, but it is correlated with the average social perceptiveness of group members, the equality in distribution of conversational turn-taking, and the proportion of females in the group. After the initial work with face-to-face groups, we have also developed an online test of collective intelligence that can measure a group s collective intelligence in under an hour. Among other results, we found that the average social perceptiveness of group members predicts a group s collective intelligence equally strongly in both face-to-face groups and in online groups that never see each other.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 09, 2013
- Accession Number
- ADA602979
Entities
People
- David Engel
- Thomas Malone
Organizations
- Massachusetts Institute of Technology