Dark Side of AI

Artificial Intelligence (AI) is transforming how data is collected, processed, analysed, and used across society, creating significant opportunities while introducing new risks to privacy, security, safety, and trust. This volume examines these challenges from technical, ethical, social, and regulatory perspectives.The book explores the AI–privacy paradox, deceptive AI-driven design and data exploitation, AI-enabled cyberattacks, adversarial threats, deepfakes, cryptanalysis, facial recognition, biometric security, and privacy risks in intelligent learning and smart-device environments. It also addresses emerging concerns surrounding generative AI in healthcare and mental health, including bias, hallucinations, sensitive-data protection, and responsible deployment.Alongside these challenges, the book presents approaches for building more secure and privacy-conscious AI systems, including federated learning, differential privacy, secure multi-party computation, homomorphic encryption, privacy-by-design, privacy-preserving architectures, adversarial robustness, and user-centric data governance.Bringing together diverse perspectives on the evolving risks and safeguards of AI, this edited volume provides a valuable reference for researchers, graduate students, AI and cybersecurity professionals, policymakers, and practitioners seeking to understand the privacy and security implications of AI and develop responsible, transparent, and trustworthy intelligent systems.