Artificial Intelligence and Government offers a timely and comprehensive exploration of how AI is transforming public institutions across the globe. From climate resilience and urban planning to justice and equitable service delivery, this book examines the profound opportunities and challenges that AI brings to the heart of governance. Drawing on insights from leading scholars and practitioners, it reveals how governments are harnessing advanced technologies—such as machine learning, data analytics, and robotics—to anticipate societal needs, improve policy outcomes, and engage citizens in new ways.
Yet, as algorithms increasingly shape the fabric of public life, the book does not shy away from the pressing ethical, legal, and societal dilemmas that accompany AI’s rise. It confronts questions of algorithmic bias, accountability, privacy, and the urgent need for democratic oversight in a world run by data. Through in-depth case studies, empirical and conceptual investigations, policy insights, and expert analyses, Artificial Intelligence and Government provides a multidimensional understanding of AI’s influence on government operations, offering practical guidance for policymakers, public administrators, technologists, researchers, and engaged citizens alike.
The book’s central aim is to bridge the critical knowledge gap surrounding AI’s integration into government. It examines the current state of AI adoption across governments worldwide, including adoption strategies, readiness frameworks, and how governments are innovating with AI technologies, while offering philosophical and forward-looking critique. Additionally, the book analyzes the barriers to AI adoption, assesses the impact on policy, service quality and citizen engagement, and offers solutions to mitigate implementation challenges. By examining both the innovations and the ethical complexities of AI in the public sector, the book equips readers with the insights and principles needed to build fairer, more transparent, and future-ready institutions.
Chapters 5 and 10 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
