Interdisciplinary Approaches to Data Governance, AI, and Digital Society

In a data-driven world, the governance of digital technologies and artificial intelligence (AI) is a concern for governments, businesses, and societies. Addressing the complex social, ethical, legal, and technical challenges posed by AI and digital systems requires an interdisciplinary approach that draws from fields like computer science, law, sociology, public policy, ethics, economics, and communication studies. Interdisciplinary perspectives enable a more comprehensive understanding of how data governance frameworks shape privacy, accountability, algorithmic bias, digital inclusion, and democratic participation. Integrating diverse forms of expertise may develop more equitable and transparent systems that balance technological innovation with societal values and human rights in a digital society. Interdisciplinary Approaches to Data Governance, AI, and Digital Society explores how various disciplines and fields collaborate to govern the social, ethical, legal, and technological impacts of data and AI in society. It examines issues like privacy, bias, digital rights, governance, and the influence of emerging technologies on institutions, communities, and everyday life. This book covers topics such as digital sovereignty, regulatory compliance, and technostress, and is a useful resource for business owners, government officials, engineers, policymakers, academicians, researchers, and data scientists.