Generative AI Ethics, Privacy, and Security

Generative AI is transforming industries globally, with the majority of organizations using generative AI in at least one business function. From the fundamental evolution of transformer models to the complex ethical questions they raise, this book equips readers with the knowledge to navigate AI with confidence.

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.

Upon completing this book, readers will possess the knowledge and skills to lead generative AI initiatives, balancing innovation with ethical responsibility. They will be able to make informed decisions about AI deployment, implement security and privacy measures, ensure regulatory compliance, and build AI systems that drive business value while maintaining public trust and societal benefit.

WHAT YOU WILL LEARN
● Explore transformer models, GANs, and autoencoder architectures.
● Implement ethical AI frameworks and bias mitigation strategies.
● Design privacy-preserving systems for sensitive data handling.
● Deploy security measures against adversarial attacks and misuse.
● Navigate global AI regulations and compliance requirements.
● Build responsible governance structures for AI deployment.
● Educate stakeholders on AI capabilities and limitations.
● Apply best practices through real-world case studies.

WHO THIS BOOK IS FOR
This book is designed for ML engineers, architects, developers, business leaders, and AI strategists who need to understand both the technical and ethical dimensions of generative AI. Whether you are steering organizational AI strategy or implementing AI solutions hands-on, this guide provides the essential knowledge for responsible deployment.

1. Introduction to Generative AI
2. Foundations of Transformers, GANs, and Other Generative Models
3. Ethical Considerations in Generative AI
4. Privacy Challenges and Implications
5. Security Risks and Mitigation Strategies
6. Responsible Development and Governance
7. Legal and Regulatory Landscape of AI Systems
8. User Awareness and Education
9. Case Studies
10. Best Practices in Generative AI Deployment
11. Future Directions and Ethical Innovation

Wrick Talukdar brings over 20 years of expertise in artificial intelligence, cloud technologies, and product innovation to his role as a generative AI technology leader at Amazon. Throughout his career, he has championed AI-powered enterprise transformation, directing extensive modernization programs that deliver value to millions of users globally. His leadership in developing cutting-edge AI/ML solutions has resulted in award-winning technologies that Fortune 500 companies now utilize at scale across their operations.

His contributions to generative AI, multimodal systems, NLP, and computer vision research have earned widespread recognition and citations within the academic and industry communities. Wrick serves as a senior IEEE member and co-chair, contributing his expertise to numerous industry panels while providing strategic guidance to international committees, including CTSoc Industry Forums and NIC, where he helps establish industry benchmarks and define AI's future trajectory. He regularly shares his groundbreaking work at leading global conferences, including World Technology Summit, IEEE HKN, ICCE, CERAWeek, ADIPEC, and re:Invent, effectively connecting advanced research with practical AI implementations to foster innovation across industries.

With strong foundations in computer science, Wrick dedicates time to mentoring the next generation through his role as IEEE NIC co-chair, supporting emerging professionals in the field. In his capacity as an author and industry thought leader, he remains committed to advancing AI capabilities and motivating tomorrow's innovators. He resides in California with his family.

Anjanava Biswas is an accomplished senior AI specialist solutions architect who brings more than 17 years of expertise to the field. His technical proficiency spans machine learning, generative AI, NLP, deep learning, data analytics, and cloud infrastructure, enabling him to collaborate with major enterprises in developing and deploying sophisticated AI solutions at scale. Anjanava has earned industry recognition through his significant contributions to applied AI, with research published across numerous scientific publications and active involvement in open-source AI/ML initiatives. His professional achievements include fellowships from prestigious organizations: BCS (UK), IET (UK), and IETE (India), alongside his senior membership in IEEE. As a sought-after speaker in the technology community, Anjanava has served in leadership roles at global corporations including IBM and Oracle Corp. Having originally hailed from India, he currently resides in San Diego, California, with his wife and son, while continuing to drive innovation and mentor others in the technology sector.