A guide to generative AI, its ethical considerations, privacy measures, security strategies, and approaches
This book begins by introducing foundational concepts of generative AI and transformer model evolution, along with architectures, including GANs and autoencoders. It explores ethical frameworks and societal impacts, examines privacy challenges in data usage and generated content, and addresses security threats with mitigation strategies. Readers will learn responsible development and governance practices, navigate the legal and regulatory landscape, and learn how to educate users about AI capabilities and limitations. The book concludes with real-world case studies, best practices for deployment, and future directions for ethical innovation.