A Review on Artificial Intelligence in Public service

Abstract

Public administration is undergoing a transformation with the advent of artificial intelligence (AI) that provides new tools for improving the efficiency, accuracy and responsiveness of public services. It looks at the evolving role of AI in public service delivery, focusing on healthcare, education, tax administration and citizen-facing government services. It addresses the key advantages that come with the adoption of AI, such as better operational efficiency, data-driven and more accurate decision-making, increased automation of repetitive administrative tasks, better citizen services and resource optimisation in public services. The review also takes into account the ethical and governance issues that arise with the use of AI in government such as concerns regarding data privacy, algorithmic bias, lack of transparency, and loss of trust when AI systems are opaque or biased. The difficulties underscore current and emerging problems requiring responsible governance solutions to guarantee that AI systems are used fairly, transparently, and legally and ethically. The review also identifies areas for future research and development of AI in public administration, focusing on human-centred design, explainability, accountability and the creation of comprehensive public sector AI governance frameworks. The review finds that public administration's successful use of AI will require both technical capability and robust institutional protection of the rights of citizens and the maintenance of citizens' trust in government. Governments will need to continue to focus on responsible AI use to reap the benefits of digital transformation while keeping their public institutions accountable, fair, and trustworthy. This paper examines the role of AI in public administration and the creation of e-governments from the perspective of digital transformation. This paper explores the involvement of AI in public administration and the development of e-governments through the lens of digital transformation, while taking care to highlight potential algorithmic bias.