Collective Intelligence
for Climate Action

About the UNDP Accelerator Labs 

The United Nations Development Programme (UNDP) Accelerator Labs is the world’s largest and fastest learning network on wicked sustainable development challenges. Co-built as a joint venture with the Federal Ministry for Economic Cooperation and Development of Germany and the Qatar Fund for Development, along with Partners at Core for UNDP, Italian Ministry of Environment and Energy Security as action partner, and the Japan Cabinet, the Network covers 115 countries, and taps into local innovations to create actionable intelligence and reimagine sustainable development for the 21st century. Learn more at or follow us at @UNDPAccLabs.

About Nesta’s Centre for Collective Intelligence Design

Nesta’s Centre for Collective Intelligence Design helps create new ways for communities to use technology to harness their insights, ideas and power to act on the problems that matter to them and create the futures they want. We design tools and projects that allow communities to respond collectively to challenges, and that help public and voluntary sector institutions strengthen trust and collaboration with citizens.

We use rigorous research methods to test, learn and evaluate each solution. Our flagship Collective Intelligence Design Playbook helped to define the field and is used by practitioners around the world. We have worked with organizations from the UN to the BBC.

To learn more visit or email the team at

Nesta is a registered charity in England and Wales with company number 7706036 and charity number 1144091.Registered as a charity in Scotland number SCO2833. Registered office: 58 Victoria Embankment, London, EC4Y 0DS


Aleks Berditchevskaia, Alex Albert, Kathy Peach, Gina Lucarelli, Alberto Cottica.

Recommended citation: Berditchevskaia, A., Albert, A., Peach, K., Lucarelli, G., Cottica, A. (2023). UNTAPPED: Collective Intelligence for Climate Action. New York: UNDP.

We would like to thank

We’re grateful to the following people who contributed their expertise during our research for their valuable contributions, insight, and feedback on this research: 
Karen Bett, Martin Cadena, Rebecca Carman, Ramit Debnath, Kim Doell, Konstantin Klemmer, Natasha Parker and Jaron Porciello. Thank you to the colleagues from the UNDP Accelerator Lab Network (and their respective Country Offices) for contributing in-depth case studies from their own work, both in the context of the Collective Intelligence for Climate Action Design Studio and elsewhere:  Yawo Mensah Emmanuel Agnigbankou, Yem Kossivisoe Ahiatsi, Aishath Nayasheen Ahmed, Alexandra Antunes, Komi Ognadon Aokou, Jacqueline Aringu (Poni), Tong Atak, Victor Apollo Awuor, Kemal Bajramovic, Maria Bernard, Javier Antonio Brolo, Aníbal Cárdenas, Rocio Chain, Betty Chemier, Paola Constantino, Marissa Corinna Asen, Arijana Drinic, Innocent Fred Ejolu, Patricia Choque Fernandez, Yvonne Nyokabi Gachugi, Giovanni Fernando García, Menna Gebreselassie, Jennifer Hotsko, Igor Izotov, Buay Jacob Tut, Evan Jacobs, Naida Katica, Caroline Kiarie Kimondo, Daniel Kir, Swetha Kolluri, Anita Kodzoman, Desislava Kyurkchieva, Fathimath Lahfa, Carlos Mazariegos, Pragya Mishra, Klariska Moodley, Sharleen Moyo, Zandile Mthembu, Berna Mugema, Ali Muntasir, Hadijah Nabbale, Gloria Namande, Lillian Njoro, Amina Omicevic, Jordan Parker, Kuach Pech, Vedran Pecikoza, Lazar Pop Ivanov, Hussain Rasheed, Mohseen Riaz-Ud-Dean, Beto Saavedra, Basma Saeed, Kaisarina Salesa, Wigdan Seed Ahmed, Simone Smit, Diego Suarez Traverso, Abiziou Tchinguilou, Nathan Tumuhamye, Jessica Young, Ardita Zekiri. We would also like to thank Erika Antoine-Souklaye, Peter Baeck, Jeremy Boy, Naoise Boyle, Mirko Ebelshaeuser, Bas Leurs, Rita Marques and Anthony Ngororano 

Published: April 2024
ISBN: 978-1-916699-14-4
DOI: 10.978.1916699/144
Design: Ahoy Studios

Image credits:
All photos featured in the report were obtained with participants’ informed consent.
Page 6, Michael Kibuku, UNDP Kenya; P.8, Carlos Arce, PNUD Bolivia; P. 14, M. Kibuku, UNDP Kenya; P. 23, left to right, Lilian Quinteros, PNUD Guatemala, Igor Alecsander, iStock; P. 24, M. Kibuku, UNDP Kenya; P. 28, José Mendez PNUD Bolivia; P. 30, left to right, M. Kibuku, UNDP Kenya, Jünior Rodríguez, Unsplash, Jéan Béller, Unsplash; P. 32, left to right, L. Quinteros, PNUD Guatemala, Paola Constantino, PNUD Guatemala; P. 37, Yaroslav Astakhov, iStock; P. 38, left to right, Julio Sierra, UNV, J. Mendez PNUD Bolivia, Steve Douglas, Unsplash; P. 41, left to right, Landon Parenteau, Unsplash, Misbahul Aulia, Unsplash; P. 44, left to right, T.O., iStock, National Cancer Institute, Unsplash, M. Kibuku, UNDP Kenya; P. 49, J.R.Ripper/BrazilPhotos, Alamy; P. 50, Victor Karanja, iStock; P. 52, Randy Navarro; P. 54, left to right, Mus Lihat, Unsplash, Matt Houghton, Unsplash, L. Quinteros, PNUD Guatemala; P. 59, Aldo Murillo, iStock; P. 60, left to right, Randy Navarro, Nagera Vicente, PNUD Bolivia, Omotayo Tajudeen, Unsplash; P. 65, Siempreverde22, iStock; P. 67, top to bottom, M. Kibuku, UNDP Kenya (also on P. 68), N. Vicente, PNUD Bolivia (also on P. 70), Let me Breathe, with support from UNDP Business and Human Rights Asia Program and the European Union (also on P.72), C. Arce, PNUD Bolivia (also on P.76); P. 74, GeoAI Platform,; P. 75, Let me Breathe, with support from UNDP Business and Human Rights Asia Program and the European Union; P. 78, C. Arce, PNUD Bolivia; P. 89, top, M. Kibuku, UNDP Kenya, bottom, UNDP Kenya; P. 93, top, Fathimath Lahfa, UNDP Maldives, bottom, Ashwa Faheem, UNDP Maldives; P. 97, N. Vicente, PNUD Bolivia; P. 102, left to right, L. Quinteros, PNUD Guatemala, M. Kibuku, UNDP Kenya, Juan Pablo Rustrián, UNV; P. 105, R. Navarro; P. 107, L. Quinteros, PNUD Guatemala; P. 111, ZUMA Press, Inc., Alamy; P. 112, left to right, P. Constantino, PNUD Guatemala, M. Kibuku, UNDP Kenya; P. 117, Diego Suarez, PNUD Bolivia. 


This study was carried out from December 2022 to March 2023. We identified over 100 case studies for our core analysis (Section called “Collective Intelligence”) of current collective intelligence initiatives for climate action. This analysis was limited to case studies from the Global South that had been active in the period since 2015. This included some case studies that started in the Global North and had expanded to other countries. Focusing on the Global South allowed us to identify the collective intelligence applications that are most relevant and practically feasible for the communities on the frontlines of the climate crisis. The primary analysis was carried out by two Nesta researchers who coded case studies independently and verified each others’ work.

To identify emerging and future opportunities (Section called “Advancing the Practice”), we broadened our analysis to include examples from the Global North and initiatives where collective intelligence is applied to issues beyond climate. Case studies were drawn from existing repositories, as well as a rapid review of the academic and gray literature. The five case studies from UNDP Accelerator Labs were analyzed through semi-structured interviews carried out by a Nesta researcher during August 2023.

We contextualized our findings to broader sectoral trends through a rapid literature review drawing on official reports published by international institutions and development actors (e.g. IPCC, UNEP, WRI), other gray literature and peer-reviewed publications. We tested an early version of our findings with seven experts through two semi-structured interviews and a facilitated online workshop, held in April 2023.



This guide provides a description of key collective intelligence methods referred to throughout this report. 

Collective intelligence methods

Description of method

What is it good for?


Challenge prize

A competition that offers a financial reward to a person or team who can solve a problem.

Attracting new innovators who might challenge the status quo, or redirecting the efforts of incumbents - encouraging them to think about the problem in a new way.

An offer of seed funding and mentoring is made to innovators who can develop new technologies to help people with health conditions stay independent for longer.

Citizen science

A process where scientists and volunteers work together to collect or analyze scientific data or observations.

Creating or analyzing high quality data faster, or at larger scale, or with more granularity.

People use a pre-built testing kit to collect local data on water quality which informs research on ecological health.


A type of crowdsourcing that generates information associated with and linked to a specific  geographical location.

Creating new, more detailed data about a place more quickly. Can enrich and/or verify ‘big data’ e.g. from satellites. Also allows people to share information with each other.

People provide detailed information on human rights violations that they have seen or experienced and the location where it took place.


An umbrella term for a variety of approaches that source data, information, opinions or ideas from large crowds of people - often by open calls for contribution.

Gathering diverse inputs from a wider range of people.

Residents report opinions on the progress of government initiatives via a platform.


A method of weighing up different options through dialogue.

Weighing up trade-offs on difficult or contentious issues and helping to arrive at more consensus-driven recommendations.

A representative sample of the population is brought together online to discuss and rank policy options to achieve net zero by 2050.


An umbrella term for when a larger activity is split into small, simple, repeatable tasks that can be distributed among volunteers.

Allows quicker progress on a given challenge and lowers the threshold for contributing, meaning that more people can be engaged.

Individual volunteers in different locations planting trees to achieve regional and global reforestation targets.

Participatory modeling

People work together to create a realistic model (often digital) of an issue by identifying relevant data inputs, relationships and impacts of different actions.

Helps a group to create a shared understanding of an issue and to explore different options for action.

Local decision makers, water companies and farmers work together to create a model of water use and management in their region.

Participatory sensing

People using cheap sensors to collectively monitor the environment around them.

Helps to deepen community members’ understanding of the issue.

A local community installs devices that help measure noise pollution in their neighborhood.

Peer-to-peer exchange

People sharing their knowledge or skills with one another.

Fast-tracks learning by sharing most relevant advice and increases likelihood of information being taken up because it comes from people ‘like me’.

People share questions over SMS, and then receive back suggestions from others in their community.

Serious (digital) games

Using game-like elements to make engagement in a project more fun and motivate audiences to explore or contribute to complex topics or research.

Increasing participants’ contributions, motivation and retention - enabling the collection of more data, faster.

Students receive points and awards for identifying malaria in blood samples on an online app.