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Responsible AI: Principles and Practices.
・ISBN 978-1-394-35544-0 2026 hard US$ 225.00
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電子版あり 大学・学術機関向け電子ブック（eBook）ISBN 978-1-394-35547-1
| 著者・編者 | Kumar, Manish / Sambyal, N. / Singh, L. P. et al. (eds.), |
|---|---|
| 出版社 | (Wiley-Scrivener, US) |
| ページ数 | 448 pp. |
| 言語 | ENG |
| ニュース番号 | ＜251-60193＞ |
解説
Bridge the gap between groundbreaking AI innovation and ethical responsibility with this comprehensive guide to the expert-led frameworks needed to navigate the complex legal, social, and moral landscapes of our digital future.
Artificial Intelligence (AI) has emerged as a transformative force with the ability to bring new innovations to reshape economies, industries, and our daily lives. From advanced medical diagnostics to autonomous vehicles, AI systems are driving incomparable innovations in every sector. These advancements promise unmatched benefits and provide the potential to solve some of humanity's most pressing challenges. However, there are many potential challenges and significant risks that come alongside the benefits provided by AI.
This book offers a multidisciplinary viewpoint on how to develop and use AI systems responsibly by offering a deep dive into the ethical, legal, and societal ramifications of artificial intelligence. It explores important subjects such as algorithmic fairness, transparency, accountability, and governance through contributions from notable academics, engineers, and policy specialists. It highlights how crucial it is to match AI development with democratic norms and human values, offering both theoretical frameworks and workable implementation solutions for a range of industries. This comprehensive guide is an essential resource for scholars, professionals, and legislators dedicated to making sure that AI technology is created and applied in ways that are moral, inclusive, and advantageous to society.
The reader will find the volume:
- Provides a multidisciplinary exploration of the ethical, legal, and social dimensions of AI;
- Bridges the gap between AI theory and real-world applications through practical frameworks;
- Covers key topics such as fairness, transparency, accountability, and governance;
- Serves as a valuable resource for researchers, practitioners, and policymakers aiming to build trustworthy AI systems.
Audience
AI practitioners, data scientists, developers, business leaders, and executives actively engaged in the development and implementation of AI systems.