Home Accelerator Labs Smarter Together Collective Intelligence and The SDGs: Six Use Cases Collective Intelligence and the SDGs: Six Use cases 1. New forms of governance and accountability (link is external) In this use case methods such as eyewitness video and crowdmapping are being used to document violence or human rights abuses, with a view to holding perpetrators to account. This use case also sees how governments are crowdsourcing ideas and opinions from citizens during policy making, and how citizens are generating new forms of data to monitor policy implementation. SDGs 16 (link is external) Read More (link is external) (link is external) 2. Anticipating, monitoring and adapting to systemic risks(link is external) A wide range of collective intelligence methods are helping organizations to improve their capacity for early warning and monitoring of, and response to, natural disasters, conflict and epidemics. These include working with on-the-ground volunteers to provide data about emerging issues, or with crowdmappers to capture location information for crisis preparedness. Others combine datasets, including web scraped social media data, for real-time public health surveillance, or ask large groups of people to forecast geopolitical events. SDGs 3, 13, 16 (link is external) Read More (link is external) 3. Real-time monitoring of the environment(link is external) Collective intelligence methods like citizen science and in-situ or remote sensing methods (such as satellites) have been gaining traction as complements to existing ways of monitoring the state of environments – from air quality to deforestation. Web scraping social media and citizen reporting tools are also being used to generate information on environmental hazards from people in affected areas. This use case has the potential to fill data gaps in environmental monitoring. SDGs 11, 14, 15 (link is external) Read More (link is external) 4. Understanding and working with complex systems(link is external) Collective intelligence approaches that combine multiple data sources are helping policy makers and development organizations to visualize the dynamics of complex systems and uncover insights that have previously been hidden. City leaders are also increasingly turning to crowdsourcing ideas and opinions of their constituents to understand the different needs or experiences of diverse or changing populations. SDGs 10, 11, 12(link is external) Read More (link is external) 5. Inclusive development and technologies(link is external) The SDGs’ promise to ‘leave no one behind’ brings with it an imperative to involve marginalized communities in development initiatives. Collective intelligence methods like crowdmapping, citizen reporting and mobile phone surveys can be used to engage people whose voices are often not counted. Crowdsourcing data from under-represented groups to train machine learning models is another growing trend that is important for developing fairer artificial intelligence (AI) systems. SDGs 5, 10(link is external) Read More (link is external) 6. Distributed problem solving(link is external) To tap into people’s problem solving capabilities, organizations are: crowdsourcing solutions; convening peer-to-peer crowdsourcing of knowledge and experience; using open source repositories to share solutions for others to adapt and use; and crowd labeling data to train machine learning models. These collective intelligence methods have broad application across the majority of the SDGs, but become especially relevant for targets such as climate action, where there might be a lack of established solutions and practices, or when new and locally-appropriate solutions are in high demand. SDGs 2, 3, 13(link is external) Read More (link is external) Next: Why Collective Intelligence? 🡪 (link is external)