Enhancing AI applications for European public bodies: A data quality-centric approach

Abstract

Artificial Intelligence (AI) has become a pivotal tool in the digital transformation of organisations across all sectors and types of organisations, including public bodies. For these, AI offers significant potential benefits such as improving the efficiency of internal operations, the effectiveness of policymaking, the responsiveness of public services, and enhancing transparency and accountability. The quality of the data used to train AI models is a key factor for the success or failure of an AI application. The main contribution of this work lies in the adoption of a data-centric approach, through which critical categories of data quality alerts are identified and related to inherent data quality characteristics for machine learning and analytics. In addition, current ISO standards and European regulations concerning AI and data quality are considered, highlighting both their technical foundations and existing limitations.