Ethics in Artificial Intelligence and Information Technologies

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Ethics in Artificial Intelligence and Information Technologies

Arriagada-Bruneau, Gabriela/ López, Claudia/ Mendoza, Marcelo

ウェブストア価格 ¥32,440（本体¥29,491）
CRC Press（2025/07発売）
外貨定価 US$ 160.00
ポイント 294pt

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製本 Hardcover:ハードカバー版／ページ数 226 p.
言語 ENG
商品コード 9781032594187

Full Description

This book addresses the challenges posed by adopting and developing new AI technologies and how they impact people. Ethics, the scope, and the impact of technology on people are vital. The book starts with the ethical aspects of AI, presenting a socio-technical approach to integrating Ethics into AI projects, and outlines perspectives around feminism, sustainability, and labor transformation. Next, the concepts of fairness, accountability, and transparency are introduced, discussing their implications for developing information systems such as recommender systems, including aspects related to data privacy. Then the book covers the relevance of natural language processing systems, highlighting debias strategies and evaluation methodologies. The scopes of fairness-based approaches for ChatGPT and other generative text models are also introduced. Finally, advanced topics that include the relationship between AI and disinformation are addressed, including a discussion of the scope of news-generative models such as deep fakes. The book ends with a discussion of the perspectives and challenges in the area.

The book is meant for an audience of advanced undergraduate and graduate students from all disciplines related to information systems. It is also helpful for researchers and practitioners interested in the subject.

Preface. SECTION I: ETHICS AND AI. 1. What is AI ethics? 2. A sociotechnical approach to integrate ethics into AI projects. 3. Beyond the Mainstream: Sustainability and the Replicability crisis. SECTION II: FAIRNESS, ACCOUNTABILITY, AND TRANSPARENCY. 4. Bias in AI. 5. Fairness, accountability and transparency in AI. 6. Regulatory Initiatives in AI. SECTION III: ETHICS AND AI APPLICATIONS. 7. Explainable Artificial Intelligence. 8. Transformers and Generative AI. 9. NLP and representational bias. SECTION IV: ADVANCED TOPICS. 10. Benefits and risks of LLMs. 11. Visual transformers and the rise of multi-modality. 12. Perspectives and challenges. References.