Literature DB >> 34001598

Quantifying collective intelligence in human groups.

Christoph Riedl1,2,3,4,5, Young Ji Kim6, Pranav Gupta7, Thomas W Malone4,5, Anita Williams Woolley7.   

Abstract

Collective intelligence (CI) is critical to solving many scientific, business, and other problems, but groups often fail to achieve it. Here, we analyze data on group performance from 22 studies, including 5,279 individuals in 1,356 groups. Our results support the conclusion that a robust CI factor characterizes a group's ability to work together across a diverse set of tasks. We further show that CI is predicted by the proportion of women in the group, mediated by average social perceptiveness of group members, and that it predicts performance on various out-of-sample criterion tasks. We also find that, overall, group collaboration process is more important in predicting CI than the skill of individual members.

Entities:  

Keywords:  collective intelligence; human groups; team performance

Mesh:

Year:  2021        PMID: 34001598      PMCID: PMC8166150          DOI: 10.1073/pnas.2005737118

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  13 in total

1.  Evidence for a collective intelligence factor in the performance of human groups.

Authors:  Anita Williams Woolley; Christopher F Chabris; Alex Pentland; Nada Hashmi; Thomas W Malone
Journal:  Science       Date:  2010-09-30       Impact factor: 47.728

2.  The increasing dominance of teams in production of knowledge.

Authors:  Stefan Wuchty; Benjamin F Jones; Brian Uzzi
Journal:  Science       Date:  2007-04-12       Impact factor: 47.728

3.  Large teams develop and small teams disrupt science and technology.

Authors:  Lingfei Wu; Dashun Wang; James A Evans
Journal:  Nature       Date:  2019-02-13       Impact factor: 49.962

4.  Reading the Mind in the Eyes or reading between the lines? Theory of Mind predicts collective intelligence equally well online and face-to-face.

Authors:  David Engel; Anita Williams Woolley; Lisa X Jing; Christopher F Chabris; Thomas W Malone
Journal:  PLoS One       Date:  2014-12-16       Impact factor: 3.240

5.  The Insensitive Ruins It All: Compositional and Compilational Influences of Social Sensitivity on Collective Intelligence in Groups.

Authors:  Nicoleta Meslec; Ishani Aggarwal; Petru L Curseu
Journal:  Front Psychol       Date:  2016-05-09

6.  Visualized Automatic Feedback in Virtual Teams.

Authors:  Ella Glikson; Anita W Woolley; Pranav Gupta; Young Ji Kim
Journal:  Front Psychol       Date:  2019-04-16

7.  The Impact of Cognitive Style Diversity on Implicit Learning in Teams.

Authors:  Ishani Aggarwal; Anita Williams Woolley; Christopher F Chabris; Thomas W Malone
Journal:  Front Psychol       Date:  2019-02-07

8.  The "Reading the Mind in the Eyes" Test revised version: a study with normal adults, and adults with Asperger syndrome or high-functioning autism.

Authors:  S Baron-Cohen; S Wheelwright; J Hill; Y Raste; I Plumb
Journal:  J Child Psychol Psychiatry       Date:  2001-02       Impact factor: 8.982

9.  How intermittent breaks in interaction improve collective intelligence.

Authors:  Ethan Bernstein; Jesse Shore; David Lazer
Journal:  Proc Natl Acad Sci U S A       Date:  2018-08-13       Impact factor: 11.205

10.  A World Unto Itself: Human Communication as Active Inference.

Authors:  Jared Vasil; Paul B Badcock; Axel Constant; Karl Friston; Maxwell J D Ramstead
Journal:  Front Psychol       Date:  2020-03-25
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  2 in total

1.  Overcoming Individual Limitations Through Distributed Computation: Rational Information Accumulation in Multigenerational Populations.

Authors:  Mathew D Hardy; Peaks M Krafft; Bill Thompson; Thomas L Griffiths
Journal:  Top Cogn Sci       Date:  2022-01-15

2.  An Active Inference Model of Collective Intelligence.

Authors:  Rafael Kaufmann; Pranav Gupta; Jacob Taylor
Journal:  Entropy (Basel)       Date:  2021-06-29       Impact factor: 2.524

  2 in total

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