An AI capacity building project that strengthens AI/ML capacities in developing countries through mentoring activities and workshops on tinyML technology. The goal is to create a sustainable ecosystem where local developers can innovate with AI/ML for development and prosperity.
Activity Type Networks/Mentorship/ExchangeThe urgency to mitigate the impact of humanity on global biodiversity necessitates innovative strategies. Artificial Intelligence (AI) holds transformative potential for navigating the complex policy landscapes of biodiversity conservation and accelerating action. When applied through a human-centered approach that minimizes risk, AI can democratize access to cutting-edge analytics, empowering a broader range of stakeholders. UNDP has now supported almost 60 countries to use AI to uncover patterns in the alignment of national policies with global biodiversity aims. Developed on an on-demand basis through the Early Action Support (EAS) Project, funded by the Global Environment Facility, NBSAP Target Similarity Assessments offer customized insights on synergies between global and national biodiversity targets and provide recommendations for enhanced alignment to bring about a transformation in our societies’ relationship with biodiversity by 2030. Developed with governments to address their unique needs, these assessments can foster dynamic, inclusive, and effective national stakeholder engagement to fill gaps, raise political will, and improve sectoral collaboration, resulting in accelerated progress towards global biodiversity commitments. The GEF-8 Umbrella Programme to Support NBSAP Update and the 7th National Reports in now scaling up this GPT-based methodology to also provide insights on alignment between nature and climate targets, through a partnership between the Nature and Climate Hubs and with the UNDP contribution to the UN System's coordinated support on NDC 3.0 Funding Window.
Activity Type AI Tools/SolutionsResearch/Reports/Assessments
The Data Dive for Development Hackathon is a unique competition inviting participants to develop innovative microservices to derive insights from data on Official Development Assistance (ODA). Upon selection, winning teams engaged in a two-month agreement to refine their initial prototypes.
UNDP Seoul Policy Centre selected prototype solutions with potential to be scaled to support both our internal processes and work on the ground. By developing microservices that effectively combine a comprehensive ODA database with complementary datasets, we aimed to uncover hidden ODA patterns, predict future trends, and better understand the complex relationships that shape development cooperation.
In support of the Integrated National Financing Frameworks (INFF), this project developed a data pipeline and interactive PowerBI dashboard to visualize financing strategies. The dashboard and standardized taxonomy help analyze national reforms and identify trends in sustainable financing, laying the groundwork for future AI applications.
Activity Type AI Tools/SolutionsTechnical assistanceResearch/Reports/Assessments