For the last two years Nesta’s Centre for Collective Intelligence Design has been supporting UNDP’s network of Accelerator Labs around the world to use and apply collective intelligence design for the Sustainable Development Goals.
‘13 Stories from the UNDP Accelerator Labs’ offers a deep dive into how collective intelligence is being used by the UNDP Accelerator Labs – from participatory sensing to understand the informal economy around waste in Viet Nam to combining multiple datasets to tackle gender-based violence in Mexico. It summarizes some of the successes to be built on, and common challenges to be addressed in order to mainstream collective intelligence for the SDGs.
The thirteen case studies in this report illustrate how UNDP’s network of Accelerator Labs have begun using collective intelligence to tackle the Sustainable Development Goals:
- Real-time monitoring of the environment: Examples from Ukraine and Argentina show how citizen science, crowdsourcing and in-situ or remote sensing methods (such as satellites) complement existing ways of monitoring the state of environments to fill data gaps in environmental monitoring, as well as stimulating policy and community action.
- Understanding and working with complex systems: In five case studies from Tanzania, Zimbabwe, Serbia, Lao PDR and Viet Nam we demonstrate how collective intelligence is helping policy makers and development organizations to visualize the dynamics of complex systems to uncover insights that have previously been hidden and understand the experiences of diverse or changing populations.
- Distributed problem solving: Organisations are tapping into people’s problem solving capabilities to make progress on issues where there is a lack of established solutions and practices, or when locally-appropriate solutions are in high demand. Examples from Colombia, Bosnia and Herzegovina, Guinea Bissau and Ecuador show how collective intelligence has helped in the wake of the COVID-19 pandemic.
- New forms of accountability and governance: Two early-stage case studies from Mexico demonstrate how combining open datasets or making sense of data crowdsourced from civil servants using AI can be used to evaluate the success and stimulate improvement of government programmes.
If we hope to get closer to achieving the global goals over the next decade, it will be necessary to mobilize intelligence of all kinds to better understand problems, broaden the range of effective solutions, and implement new ideas more effectively. The experiences of the Accelerator Labs highlight the following areas for focus:
Working with people to create change
- Move beyond the usual suspects to build new coalitions for the SDGs: the Accelerator Labs have demonstrated the benefit of engaging with existing networks to expand the potential reach, quality and impact of their collective intelligence efforts. This may be particularly important for collective intelligence design efforts that involve vulnerable communities and where the engagement is short term, remote, or there is little time to build trust.
- Combine ‘big’ data and ‘thick’ data for contextualized insights: Official data can lack granularity of insight and can often be out of date. Novel sources of data, such as satellite data, can help address this. Collective intelligence methods can bridge these gaps by generating both quantitative measurements and qualitative insights that offer complementary perspectives on an issue.
Embracing new ways of working with data
- Use novel data and technology to help build relationships and trust with communities: Grassroots communities can often question the motivations of institutional actors and the credibility of official data. While this challenge applies to development initiatives more broadly, it’s especially critical when it comes to the collective intelligence methods, which by definition rely on mobilizing insights and action with, and by, communities.
- Establish responsible data stewardship and remain flexible during data partnerships: Negotiating access to private sector and other closed data requires high levels of technical proficiency and can take many months. Involving communities or volunteers in data collection complicates considerations around privacy and ethics. Developing a central or regional support function for data stewardship that can provide guidance about different models for data partnerships and ethical data practices, may encourage local teams to work with new data sources.
Building pathways to impact
- Emphasize the potential of collective intelligence for agile policy-making and program design: A number of the Labs have demonstrated the value of collective intelligence approaches to inform more agile, localized and responsible governance. These examples are helping governments make complex systems visible and understand problems closer to real time – enabling them to respond more effectively to localized issues.
- Develop clear ‘hand-off’ mechanisms and routes to impact for prototypes: Many of the Labs have focused on creating prototypes using new methods. Clearly identifying a ‘sponsor’ within the UNDP or government from the outset, and ensuring those stakeholders’ needs are factored into the design from the get-go, may help increase the likelihood that insights or prototypes find traction.
- Invest in building capacity for the wider ecosystem: The most successful collective intelligence initiatives within the UNDP Accelerator Lab Network have been achieved by partnering with local NGOs who already have some methodological expertise or the Labs have helped to build an understanding of collective intelligence amongst the organizations and stakeholders they work with. For collective intelligence methods to thrive, the entire development sector will need to invest in developing these 21st-century innovation skills locally, as well as across borders.
This report is published in conjunction with Collective Intelligence for Sustainable Development: Getting Smarter Together, which sets out how governments and the many organisations involved in global development are increasingly mobilising not just money but also intelligence to speed up progress towards the Sustainable Development goals.