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Reconfiguring Human Identity and Social Contracts in the AI Renaissance - Softcover

 
9798337346434: Reconfiguring Human Identity and Social Contracts in the AI Renaissance

Inhaltsangabe

The rapid evolution of artificial intelligence (AI) is reshaping industries and the fundamental fabric of human identity, agency, and societal contracts. As AI systems increasingly participate in decision-making, identity verification, employment, governance, and even creative expression, new questions emerge about what it means to be human in a machine-augmented world. The AI Renaissance challenges traditional understandings of autonomy, responsibility, privacy, ethics, and rights, while redefining societal roles, relationships, and expectations. Reconfiguring Human Identity and Social Contracts in the AI Renaissance critically analyzes how AI technologies are transforming human identity, dignity, and individuality. This book explores emerging socio-political, legal, and ethical dimensions of AI-human interaction. Covering topics such as digital shadows, posthuman employment, and teacher development, this book is an excellent resource for graduate and doctoral students, policymakers, technologists, healthcare professionals, and more.

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Über die Autorinnen und Autoren

Fenio Annansingh is an Associate Professor at York College, City University of New York, where she teaches Information Systems and Knowledge Management classes. She is the Department of Business and Economics Chair and Interim Director of the CUNY Aviation Institute. Her main area of research is Information Systems in two key areas, namely Information Management and Knowledge Management. Her research interests include knowledge leakage, IS risk management, mobile technologies, AI applications in business, cyberattacks in organisations and management, and information systems in SMES. Dr Annansingh has several publications and professional papers with several affiliates.

Adedeji Olugboja ’s journey from practitioner to scholar to policy advisor enriches this book with unique insights. As a machine learning researcher, he has developed systems for disease prediction and risk modeling. His academic work includes optimizing deep learning architectures for object detection and enhancing image classification in medical datasets. His policy work explores AI’s ethical challenges and strategic use in public health and governance.

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