Artificial Intelligence in Government Decision-Making

The growing interest in Artificial Intelligence (AI) in the public sector is evident in the literature. Although numerous government initiatives have been set up to leverage AI’s potential, there is still a lack of empirical research and evidence-based insights in this area. The purpose of this special issue is to expand both theoretical and practical understanding of AI in the public sector to improve governmental decision-making and governance, ultimately creating more value for the public. The articles in this issue explore AI risks and guidelines, governance issues, privacy concerns, the role of AI in improving citizen satisfaction, and challenges related to its implementation in different public sectors, such as healthcare and public policy. These papers not only enhance our understanding of AI’s role in government but also propose a new research agenda.

Introduction

Data analytics, although still in its early stages, is playing an increasingly critical role in evidence-based decision-making across the globe in public sectors. Various organizations, both public and private, generate enormous amounts of data in areas such as healthcare, traffic management, energy, education, fraud detection, and the environment. Yet, many government bodies fail to fully harness this data to improve decision-making and governance. Utilizing this data can lead to better policies, improved public values such as transparency, accountability, and security, and overall improved service quality. In today’s world, where Big, Open, and Linked Data (BOLD) is prevalent, Artificial Intelligence (AI) techniques enhance the effectiveness of data analytics, particularly in Big Data Algorithmic Systems (BDAS). AI helps in uncovering patterns within vast datasets to make better predictions, thereby supporting improved decision-making and governance.

However, BDAS relies heavily on data from various sources, which sometimes may be under different controls. As such, data governance is crucial in ensuring the quality and compliance of data used in AI systems. Researchers have noted that much of the existing research focuses primarily on the technological aspects of AI applications without considering the broader implications for governance and public administration. There is a need for further research to understand the processes, outputs, and impacts of AI in the public sector.

AI Adoption in Government

Although many governments are beginning to use AI, empirical research on the challenges and opportunities posed by the growing amount of data and technological advancements is still limited. Historically, governments have lagged behind in adopting cutting-edge technologies, and AI is no exception. Only a few governmental bodies have implemented AI and Machine Learning in their daily operations. Moreover, the impact of AI adoption often takes years to manifest in visible or tangible changes. Research on AI’s integration into public sectors has been conducted in areas like education, healthcare, energy, security, and transport, but there is a noticeable gap in empirical studies on the challenges of implementing AI in government settings.

AI is seen as an ideal tool for the public sector because of its ability to address the dynamic and ever-changing environmental factors that governments face. However, despite the potential of AI in public administration, its full impact has not yet been fully explored, particularly regarding how AI can be used for better decision-making and governance. Additionally, the use of AI raises ethical concerns, especially regarding privacy and the potential replacement of human workers by autonomous machines.

Research Agenda and Focus Areas

This special issue aims to push the boundaries of AI research in the public sector. It covers a wide range of topics, including AI-enabled services, challenges in AI implementation, the role of AI in public healthcare, data privacy, and governance, and the impact of AI on citizen satisfaction. Papers also explore AI’s role in emerging economies, the analysis of social media and political opinions, and how AI can improve government efficiency and public value. The research presented here focuses on data-driven AI applications, with an emphasis on evidence-based decision-making in public administration.

Future Research Directions

The research presented in this special issue outlines various critical areas for future exploration. These include understanding AI risks, evaluating its impact on citizens’ privacy, assessing how AI-enhanced government services improve public satisfaction, and investigating the enablers and challenges of AI implementation in sectors such as healthcare and public manufacturing. The research also proposes methods to study political opinions through AI, ultimately contributing to the growing body of knowledge in AI for public governance.