This document sets out recommendations for the responsible use of synthetic data in AI training. The use of synthetic data has the potential to enhance existing data to allow for more efficient and inclusive practices and policies. However, we cannot assume synthetic data to be automatically better or even equivalent to data from the physical world.
Activity Type Research/Reports/AssessmentsPolicy/Regulatory GuidanceAwareness/AdvocacyThis project explored AI's vision for the future of digital governance as UNU approaches its 50th anniversary, imagining citizen-government interactions in 2074.
Activity Type Research/Reports/AssessmentsThe project provided technical support to develop a thorough assessment of the opportunities and constraints for local government development to responsibly implement, use and govern Artificial Intelligence (AI) technologies in cities. It included designing and analyzing a global survey for cities, performing desk-based research to capture case studies, and drafting a research paper with findings and policy recommendations.
Activity Type Technical AssistanceResearch/Reports/AssessmentsPolicy/Regulatory GuidanceThe seminar showcases an AI engine for ranking partnership success factors and improving decision-making in multilateral development organizations.
Activity Type Research/Reports/Assessments