This project aims to build a Database of Data Use by developing AI models to detect when and how data is mentioned or used in documents. Just as citation databases like Google Scholar have transformed our ability to measure the impact of research, this initiative aims to create a framework for assessing the utility and impact of data. By systematically tracking data use, we can better understand the return on investment in data production, identify data gaps, and guide future funding and policy decisions. However, this challenge cannot be solved through manual methods. There is no widely adopted standard for citing data; references often appear in inconsistent or unstructured forms. AI makes this task feasible for the first time. By learning to recognize the context in which data is referenced, regardless of how it is cited or described, AI enables scalable and intelligent detection of data use across large volumes of text. By uncovering where and how data is used—or not—this project helps ensure that development efforts are grounded in evidence and that investments in data yield real-world impact.
Activity Type AI Tools/SolutionsResearch/Reports/AssessmentsInfrastructure/Systems DevelopmentThe project is leveraging Artificial Intelligence (AI) in various aspects such as the identification and reduction of fraud and corrupt practices using electronic invoices, the use of AI for automated data analysis to guide new policies, the adoption of AI for identifying "red flags" for fraud in public procurement, and the implementation of AI for automated wage bill audits. Additionally, the project aims to use AI to support actions leading to an increase in women’s participation in leadership positions. These initiatives demonstrate the project's strategic use of AI to enhance efficiency, combat fraud, and support decision-making processes across different components, including procurement, human resource management, and public investment management.
Activity Type AI Tools/SolutionsTechnical AssistancePolicy/Regulatory GuidanceThis project is leveraging AI and machine learning through a gap analysis on the data protection framework and a regulatory impact assessment of emerging technologies such as AI and machine learning. Additionally, it aims to strengthen the operational capacity to implement and maintain additional data protection controls by funding activities such as strengthening of platforms and applications of the Ghana Registration System. This demonstrates a clear intention to harness AI and machine learning for enhancing data protection and regulatory frameworks, contributing to better project outcomes.
Activity Type Policy/Regulatory GuidanceInfrastructure/Systems DevelopmentDevelopment of a module for tax accounting and analysis based on artificial intelligence (AI) ; Module for integration of payments for tax and other tax services with existing and alternative payment systems; Development and implementation of "Taxpayer" - an interactive electronic application for mobile devices for Android and IOS platforms; Electronic residency confirmation; Development of MoF information and analytical system for automation of state revenue accounting, analysis and forecasting.
Activity Type AI Tools/SolutionsInfrastructure/Systems Development