Building Trust in the Generative Artificial Intelligence Era
Written by Joanna Paliszkiewicz,Magdalena Mądra-Sawicka,Kuanchin Chen,Jerzy Gołuchowski
307 pages, about 6 hours of reading
Chaptra reads alongside you — AI insights, chapter breakdowns and reader discussions for every book. Join free
About this book
Read it with a club
Chaptra's ideas and essays clubs — small groups reading the same books and talking as they go.
Books That Changed My Mind
Ideas and essays
- 5 members
- 4 discussions
- Active 10h ago
Not books you enjoyed. Books that moved you off a position you'd genuinely held for years. This is a Chaptra house club — set up and moderated by us to get the conversation going. Open to everyone; jump in anywhere.
Read Building Trust in the Generative Artificial Intelligence Era alongside people who are reading it too.
Chaptra Prime — paid clubs, every club feature, and unlimited reading support, for $5 a month or $60 once.
See PrimeReading guide
Themes, characters and key ideas in Building Trust in the Generative Artificial Intelligence Era, written by Chaptra AI.
- about 8 hours
- intermediate
- Informative
- Analytical
- Practical
Building Trust in the Generative Artificial Intelligence Era is a timely and comprehensive exploration of the critical role of trust in the widespread adoption and effective application of generative AI. The book meticulously blends theoretical insights with practical strategies, guiding readers through the complex landscape of AI's ethical implications, technological challenges, and innovative solutions. Divided into three distinct parts, it first establishes the foundational concepts of trust and its ethical dilemmas, then provides actionable frameworks for its assessment and enhancement, and finally showcases real-world applications and perceptions through global case studies. Targeting a diverse audience of academics, professionals, and policymakers, this work serves as an essential guide for navigating the evolving AI ecosystem and fostering dependable AI systems.
“Trust is not merely a desirable attribute but the foundational cornerstone for the successful adoption and ethical deployment of generative artificial intelligence.”
Key themes
- Trust in Generative AI
- This is the central theme, exploring trust as the fundamental requirement for the successful adoption and ethical application of generative AI. It delves into how trust is formed, maintained, and evaluated in the context of autonomous and often opaque AI systems, emphasizing its role in societal acceptance and effective integration.
- Ethical Challenges of Generative AI
- This theme examines the moral and societal dilemmas posed by generative AI, including issues like algorithmic bias, data privacy, the spread of misinformation, and novel concerns such as 'greenwashing' and its impact on remote work. It highlights the necessity of ethical frameworks and responsible design to mitigate harm and ensure AI aligns with human values.
- Transparency and Explainability (XAI)
- This theme explores the mechanisms and importance of making AI systems understandable and accountable. Transparency refers to openness about AI's capabilities, limitations, and data sources, while explainability focuses on providing clear justifications for AI's decisions or outputs. Both are presented as crucial for building user trust and enabling effective governance.
Worth discussing
What specific ethical challenges of generative AI (e.g., 'greenwashing,' deepfakes, bias) do you find most pressing, and how can the frameworks presented in the book address them?
Chapter-by-chapter breakdowns, character arcs and the full thematic analysis come with a free account.
Discussions
No one has started one yet
Questions this book opens up
No discussions yet
Be the first to start a discussion about this book!
Sign up to start the discussionReviews
No reviews yet
Be the first to review this book!