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Collective Intelligence

Collective Intelligence

With the collaboration of Nesta

eISSN: 26339137 | ISSN: 26339137 | Current volume: 3 | Current issue: 1 Frequency: Quarterly

Collective Intelligence, co-published by SAGE and the Association for Computing Machinery (ACM), with the collaboration of Nesta's Centre for Collective Intelligence Design, is a global, peer-reviewed, open-access journal that publishes trans-disciplinary work bearing on collective intelligence across the disciplines. The journal embraces a policy of creative rigor in the study of collective intelligence to facilitate the discovery of principles that apply across scales and new ways of harnessing the collective to improve social, ecological, and economic outcomes. In that spirit, the journal encourages a broad-minded approach to collective performance. We welcome perspectives that emphasize traditional views of intelligence as well as optimality, satisficing, robustness, adaptability, and wisdom. In more technical terms, this includes issues related to collective output quality and assessment, aggregation of information and related topics (e.g., network structure and dynamics, higher-order vs. pairwise interactions, spatial and temporal synchronization, diversity, etc.), accumulation of information by individuals/components, environmental complexity, evolutionary considerations, and design of systems and platforms fostering collective intelligence.

VISION STATEMENT

Collective Intelligence is a transdisciplinary journal devoted to advancing the theoretical and empirical understanding of collective performance in diverse systems, including human organizations, hybrid AI-human teams, computer networks, adaptive matter, cellular systems, neural circuits, animal societies, nanobot swarms, and others. The journal embraces a policy of creative rigor in the study of collective intelligence to facilitate the discovery of principles that apply across scales and new ways of harnessing the collective to improve social, ecological, and economic outcomes. In that spirit, the journal encourages a broad-minded approach to collective performance. We welcome perspectives that emphasize traditional views of intelligence as well as optimality, satisficing, robustness, adaptability, and wisdom.

In more technical terms, this includes issues related to collective output quality and assessment, aggregation of information and related topics (e.g., network structure and dynamics, higher-order vs. pairwise interactions, spatial and temporal synchronization, diversity, etc.), accumulation of information by individuals/components, environmental complexity, evolutionary considerations, and design of systems and platforms fostering collective intelligence.

SIGNIFICANCE STATEMENT

The Internet and other digital technologies have given the world powerful new means to harness collective intelligence at a time when it has never been more needed, not least to address unprecedented challenges such as climate change, pandemics, and inequality. But our understanding of how collective intelligence works, particularly at a large scale - whether in biology, social contexts, or computing - remains nascent. This journal will bring together the various communities and disciplines working on collective intelligence to advance our understanding of its foundations and equip us better to put its principles into practice.

Editors-in-Chief
Geoff Mulgan University College London, UK
Scott Page University of Michigan, USA
Founding Editor & Chair of the Steering Committee
Thomas W. Malone Massachusetts Institute of Technology, USA
Founding Associate Editors
Andrew Adamatzky UWE Bristol, UK
Danielle Bassett University of Pennsylvania, USA
Michael Bernstein Stanford University, USA
Jeffrey Bigham Carnegie Mellon University, USA
Iain D. Couzin Max Planck Institute of Animal Behavior and University of Konnstance, Germany
James Evans The University of Chicago, USA
Deborah M. Gordon Stanford University, USA
Calin C. Guet Institute of Science and Technology, Austria
Vishwesha Guttal Indian Insitute of Science, India
David Ha Google Brain, Japan
Sabine Hauert University of Bristol, UK
César A. Hidalgo ANITI, France, University of Manchester, UK, Harvard University, USA
John Krakauer Johns Hopkins University School of Medicine and The Santa Fe Institute, USA
Karim R. Lakhani Harvard University, USA
Naomi Ehrich Leonard Princeton University, USA
Michael Levin Allen Discovery Center at Tufts University, USA
Simon Levin Princeton University, USA
Pierre Levy University of Montréal and INTLEKT Metadata, Inc., Canada
Hernan Makse Levich Institute and Physics Department, City College of New York, USA
Barbara Mellers University of Pennsylvania, USA
Melanie Mitchell Santa Fe Institute, USA
Beth Noveck The Governance Lab and NYU Tandon School of Engineering , USA
Annie Murphy Paul Science journalist and fellow in New America’s Learning Sciences Exchange, USA
Orit Peleg University of Colorado Boulder, USA
David Pennock Rutgers School of Arts and Sciences, USA
Jill Perry-Smith Goizueta Business School, Emory University, USA
Iqbal Quadir Belfer Center, Harvard KS, USA
Iyad Rahwan Max-Planck Institute for Human Development, Germany
Dana Randall Georgia Institute of Technology, USA
Lionel P. Robert Jr. University of Michigan, USA
Daniel N. Rockmore Dartmouth College, USA
Ville Satopää INSEAD, USA
Rajiv Sethi Columbia University, USA
Guy Theraulaz Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative, Centre National de la Recherche Scientifique, Université de Toulouse—Paul Sabatier, France
Elke U. Weber Princeton University, USA
Thalia Wheatley Dartmouth College, USA
Anita Williams Woolley Carnegie Mellon University, USA
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