A descriptive analysis of collective intelligence publications since 2000, and the emerging influence of artificial intelligence

Author:

Berditchevskaia Aleks1ORCID,Maliaraki Eirini1,Stathoulopoulos Konstantinos2

Affiliation:

1. Centre for Collective Intelligence Design, Nesta, London, UK

2. Util, London, UK

Abstract

Collective intelligence (CI) is an interdisciplinary field that draws on a wide range of academic disciplines but has struggled to capitalise on cross-pollination between fields, particularly ones which do not self-identify with the collective intelligence label. Past studies have largely undertaken a qualitative and manual approach to classifying different trends in the CI literature. This method risks missing a significant proportion of publications in the field. To this end, we present the first attempt to reflect the field to itself through an automated and quantitative descriptive approach using Microsoft Academic Graph (MAG) to collect and analyse 39,334 CI papers. We further focus our investigation on a subset of the CI literature, at the intersection of artificial intelligence (AI) and CI to understand how these two fields are interacting. We show that while the annual number of CI-only publications has remained steady since 2015, AI+CI research has continued to increase. Publications in the crossover of AI+CI are growing at a faster rate than CI-only papers but show less topical and disciplinary breadth. This may be having a spillover effect on the topical focus of non-AI collective intelligence research. We hope this analysis sheds more light on the dynamics of the CI ecosystem.

Funder

Centre for Collective Intelligence Design, Nesta

Publisher

SAGE Publications

Reference19 articles.

1. Berditchevskaia A, Baeck P (2020) The future of minds and machines: how AI can scale and enhance collective intelligence. Nesta: London. Available at www.nesta.org.uk/mindsmachines

2. The evolution of citation graphs in artificial intelligence research

3. Artificial Intelligence in the Management of Knowledge Production, Organizations, and Teams

4. An Analysis of the Microsoft Academic Graph

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