Collective Intelligence
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.
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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.
| Geoff Mulgan | University College London, UK |
| Scott Page | University of Michigan, USA |
| Thomas W. Malone | Massachusetts Institute of Technology, USA |
| Andrew Adamatzky | UWE Bristol, UK |
| Danielle Bassett | University of Pennsylvania, USA |
| Joshua Becker | University College London School of Management, UK |
| 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 |
| Michael Hogan | University of Galway, Ireland |
| 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 |
| Iqbal Quadir | Belfer Center, Harvard KS, USA |
| Iyad Rahwan | Max-Planck Institute for Human Development, Germany |
| Dana Randall | Georgia Institute of Technology, USA |
| Christoph Riedl | Northeastern University, 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 |
Manuscript submission guidelines can be accessed on Sage Journals.