In an era where generative artificial intelligence (AI) is reshaping industries and daily life, trust has become a cornerstone for its successful adoption and application. Building Trust in the Generative Artificial Intelligence Era: Technology Challenges and Innovations explores how trust can be built, maintained, and evaluated in a world increasingly reliant on AI technologies. Designed to be accessible to a broad audience, thi book blends theoretical insights with practical approaches, offering readers a comprehensive understanding of the topic.

This book is divided into three parts. The first part examines the foundations of trust in generative AI, highlighting trends and ethical challenges such as "greenwashing" and remote work dynamics. The second part provides actionable frameworks and tools for assessing and enhancing trust, focusing on topics like cybersecurity, transparency, and explainability. The final section presents global case studies exploring university students'' perceptions of ChatGPT, generative AI''s applications in European agriculture, and its transformative impact on financial systems.

By addressing both the opportunities and risks of generative AI, this book delivers groundbreaking insights for academics, professionals, and policymakers worldwide. It emphasizes practical solutions, ensuring readers gain the knowledge needed to navigate the evolving technological landscape and foster trust in transformative AI systems.

In an era where generative artificial intelligence (AI) is reshaping industries and daily life, trust has become a cornerstone for its successful adoption and application. Building Trust in the Generative Artificial Intelligence Era: Technology Challenges and Innovations explores how trust can be built, maintained, and evaluated in a world increasingly reliant on AI technologies. Designed to be accessible to a broad audience, thi book blends theoretical insights with practical approaches, offering readers a comprehensive understanding of the topic.

This book is divided into three parts. The first part examines the foundations of trust in generative AI, highlighting trends and ethical challenges such as "greenwashing" and remote work dynamics. The second part provides actionable frameworks and tools for assessing and enhancing trust, focusing on topics like cybersecurity, transparency, and explainability. The final section presents global case studies exploring university students'' perceptions of ChatGPT, generative AI''s applications in European agriculture, and its transformative impact on financial systems.

By addressing both the opportunities and risks of generative AI, this book delivers groundbreaking insights for academics, professionals, and policymakers worldwide. It emphasizes practical solutions, ensuring readers gain the knowledge needed to navigate the evolving technological landscape and foster trust in transformative AI systems.