Abstract

In this study, the authors discuss and show how new kinds of digital data and analytics methods and tools falling under the umbrella term of Big Data, including Artificial Intelligence (AI) systems, can help measure development effectiveness. Selected case studies provide examples of assessments of the effectiveness of ODA-funded policies and programmes. They use different data and techniques. For example, analysis of mobile phone data and satellite images: to estimate poverty and inequality, traffic congestion, social cohesion or machine learning approaches to social media analysis to understand social interactions and networks, and natural language processing to study changes in public awareness. A toolkit contains resources and suggestions on key steps and considerations, including legal and ethical, when designing and implementing projects aimed at measuring development effectiveness through new digital data and tools. The chapter closes by describing the core principles and requirements of a vision of a ‘Human AI’, which would reflect and leverage the key features of current narrow AI systems that are able to identify and reinforce the neurons that help them reach their goals. A Human AI would be a data and machine-enabled human system (such as a society) that would seek to continuously learn and adjust to improve—rather than prove after the facts—the effectiveness of its collective actions, including development programming and public policies.