Integrated information as a metric for group interaction
Name
journal.pone.0205335.pdf
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1.22 MB
Format
Adobe PDF
Checksum (MD5)
bfae61a9269ec58b2cfeb09257a4f88d
Author(s)
Engel, David
Malone, Thomas W
Date Issued
October 2018
Journal
PLOS ONE
Publisher
Public Library of Science
Citation
Engel, David and Thomas W. Malone. “Integrated Information as a Metric for Group Interaction.” Edited by Constantine Dovrolis. PLOS ONE 13, 10 (October 2018): e0205335 © 2018 The Authors
Version
Final published version
Abstract
Researchers in many disciplines have previously used a variety of mathematical techniques for analyzing group interactions. Here we use a new metric for this purpose, called "integrated information" or "phi." Phi was originally developed by neuroscientists as a measure of consciousness in brains, but it captures, in a single mathematical quantity, two properties that are important in many other kinds of groups as well: differentiated information and integration. Here we apply this metric to the activity of three types of groups that involve people and computers. First, we find that 4-person work groups with higher measured phi perform a wide range of tasks more effectively, as measured by their collective intelligence. Next, we find that groups of Wikipedia editors with higher measured phi create higher quality articles. Last, we find that the measured phi of the collection of people and computers communicating on the Internet increased over a recent six-year period. Together, these results suggest that integrated information can be a useful way of characterizing a certain kind of interactional complexity that, at least sometimes, predicts group performance. In this sense, phi can be viewed as a potential metric of effective group collaboration.
MIT Department
Massachusetts Institute of Technology. Center for Collective Intelligence
Sloan School of Management
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1371/journal.pone.0205335
