Collective Intelligence is an emerging field, drawing from a broad range of disciplines including biology, psychology, economics and computer science.1 The methods of collective intelligence make it possible to look more systematically at how organisations and whole systems think, how they observe, analyse, plan and create, using a mix of human and machine intelligence, as well as pointing to how they can think more successfully.
Principles from CI are being applied in areas as varied as organisational management, citizen science and open democracy, and can help to improve everything from social media moderation to predicting and responding to natural disasters. Harnessing it could provide a new, more inclusive and more effective model for global governance,2 and play a vital role in tackling the UN's Sustainable Development Goals.3
In the last decade, there has been significant growth in the use of technology to enhance the CI of groups both large and small. This ranges from web platforms designed to coordinate large-scale collaboration to the use of artificial intelligence to facilitate group discussions. However, although efforts to harness CI are widespread, the practice is often well ahead of the theory. Significant research is required to improve our understanding of the fundamentals of CI and how to design and apply new tools to enhance it.
Selection of GESDA best reads and further key reports
Released in January 2023, Balancing Autonomy and Collaboration in Large-Scale and Disciplinary Diverse Teams for Successful Qualitative Research by a team of UK researchers spotlights the art of harmonising individual and collaborative efforts in large, interdisciplinary research. Beyond collective intelligence: Collective adaptation was published in February by an international collaboration, and broke new ground by offering a fresh perspective on collective behaviour, emphasising the delicate balance between social strategies and environmental factors, and advocating for a multi-disciplinary lens. Collective Intelligence in Human-AI Teams: A Bayesian Theory of Mind Approach was launched in June by Northeastern University researchers, and introduces a Bayesian framework enhancing human-AI team synergy, showcasing remarkable advances in performance prediction.
