Locations
Orchestrating and scaling collective intelligence for the SDGs
As we embark on a ‘decade of action’ for Agenda 2030, most would agree that to achieve the global goals and avert climate catastrophe the world will need to mobilize power and money as never before. But to use power and money well it will also be vital that governments, organizations, and communities become skilled in mobilizing intelligence of all kinds – data, information and ideas.
The big challenge for the next few years will be to orchestrate collective intelligence more strategically or at scale. We suggest the following priorities:
Help governments make better use of collective intelligence
Local communities are collecting and sharing data on an unprecedented scale, while civil society organizations and social movements are doing pioneering work. Yet many governments are unfamiliar with the new sources of data available.
Make open source the default
Open source software and data such as OpenStreetMap, Ushahidi, Consul, Landsat and Sentinel have accelerated distributed experimentation with collective intelligence by a wide range of organizations. These open infrastructures are critical for collective intelligence and are increasingly underpinning effective action on the SDGs.
Considerations of ethics and personal privacy must be taken seriously in the design of collective intelligence projects
Collective intelligence depends on the trust and goodwill of participants. Organizations must prioritize people and purpose over technology – and ensure their projects promote data empowerment, not data extraction.
Funders should support AI and collective intelligence experimentation testbeds in real-world settings
Many have been slow to appreciate the vital importance of linking AI to collective human intelligence. But there is great scope to combine them together and in many fields AI risks being ineffective if it’s not integrated with human intelligence. A related priority should be to build up centers of expertise, particularly in sub-Saharan Africa, to counter the concentration of data and AI expertise in mainly US firms.
Create a stronger evidence base around impact and support collaborative experimentation in a greater number of communities
The field will also develop faster with greater support for innovators to share information and knowledge.
