The public sector is an immensely valuable resource of data, which has the potential to be harnessed for a wide range of applications. However, there are several challenges that impede the collection and dissemination of this data, including high variability and rapid obsolescence. Despite these challenges, emerging technologies such as Artificial Intelligence (AI) offer the potential to create intelligent applications that can unlock the full potential of public sector data. In this work, we propose a holistic ecosystem that can be utilized for the implementation and evaluation of AI technologies in public administration. To illustrate this, we present a case study focusing on dynamic government data, specifically transport data, in order to extract the various components of the ecosystem and their interdependencies. This case study was chosen due to the fact that real-time dynamic data remains an underexplored form of public sector data.
CITATION STYLE
Karamanou, A., Mangou, E., & Tarabanis, K. (2023). An Ecosystem for Deploying Artificial Intelligence in Public Administration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 14130 LNCS, pp. 192–207). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-41138-0_13
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