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商品描述
The book discusses the ethical complexities that software developers face as they build AI systems capable of autonomous creation. It explores the ethical decisions developers must make when building generative AI systems, from mitigating bias in training data to protecting user privacy and navigating regulatory compliance. Through real-world case studies and actionable frameworks, it equips technical professionals with both the understanding and tools to build AI systems that are fair, transparent, and worthy of public trust.
This book covers the following topics:
- Identifies and corrects algorithmic bias in training datasets, ensuring AI systems produce equitable outputs that don't systematize discrimination.
- Designs privacy-first AI architectures and implements transparency practices that comply with data protection regulations while building user trust.
- Navigates evolving legal and regulatory landscapes (GDPR, AI Act, sector-specific rules), helping teams stay ahead of compliance requirements.
- Applies ethical frameworks to real-world decisions: what to do when fairness and accuracy conflict, how to audit AI systems for hidden harms, when to say no to a project.
- Provides a governance model for embedding ethics into development workflows, not as an afterthought but as a core design practice.
商品描述(中文翻譯)
本書探討了軟體開發者在構建具自主創造能力的人工智慧（AI）系統時所面臨的倫理複雜性。它深入研究了開發者在建立生成式 AI 系統時必須做出的倫理決策，從減少訓練數據中的偏見到保護用戶隱私以及遵循法規合規性。通過真實案例研究和可行的框架，本書為技術專業人士提供了理解和工具，以構建公平、透明且值得公眾信任的 AI 系統。
本書涵蓋以下主題：
- 確認並修正訓練數據集中的算法偏見，確保 AI 系統產生的輸出是公平的，不會系統化歧視。
- 設計以隱私為首的 AI 架構，並實施符合數據保護法規的透明度實踐，同時建立用戶信任。
- 應對不斷變化的法律和監管環境（如 GDPR、AI 法案、特定行業規則），幫助團隊提前應對合規要求。
- 將倫理框架應用於現實決策：當公平與準確性衝突時該怎麼做，如何審核 AI 系統以發現隱藏的危害，何時應拒絕一個項目。
- 提供一個治理模型，將倫理嵌入開發工作流程中，不僅僅是事後考量，而是作為核心設計實踐。
作者簡介
Dr. Loveleen Gaur
Dr. Loveleen Gaur is a senior academic, researcher, and international examiner with over two decades of experience in higher education, doctoral supervision, and research evaluation. She holds a PhD in Computer Applications and specializes in Artificial Intelligence, Generative AI, Data Science, and Business Analytics, with strong interdisciplinary applications across management, healthcare, and digital systems.
She currently serves as Adjunct Professor at the University of the South Pacific (Fiji) and Visiting Faculty at Symbiosis International (Deemed) University, India. In addition, she is Visiting Faculty at IMT Ghaziabad, Research Professor at Alliance University, India, Mentor for the Doctor of Business Administration (DBA) programme at Rushford Business School, and Advisor with Connect IT Technologies. Across these roles, she is actively involved in doctoral mentoring, research reviews, academic evaluations, and industry-academia collaboration.
Dr. Gaur has previously served as an External PhD Examiner and doctoral committee member for several international universities, including Taylor's University (Malaysia), Auckland University of Technology (New Zealand), Alliance University (India), and the Symbiosis Centre for Research and Innovation.
She has an extensive publication record in high-impact journals indexed in Scopus and Web of Science and has authored and edited multiple scholarly books with leading publishers such as Elsevier, Springer, Taylor & Francis, Wiley, and IGI Global. She currently serves as Co-Editor-in-Chief of Communications in Statistics: Case Studies, Data Analysis and Applications (Taylor & Francis) and holds several editorial and reviewer roles across reputed international journals.
Recognized globally for her research impact, Dr. Gaur is listed among the Elsevier-Stanford World's Top 2% Scientists (2024, 2025) and is a Senior Member of IEEE.
作者簡介(中文翻譯)
Dr. Loveleen Gaur
Dr. Loveleen Gaur 是一位資深學者、研究員及國際考官，擁有超過二十年的高等教育、博士指導及研究評估經驗。她擁有計算機應用的博士學位，專注於人工智慧、生成式人工智慧、數據科學及商業分析，並在管理、醫療保健及數位系統等跨學科應用方面具有強大的專業知識。
她目前擔任南太平洋大學（斐濟）兼任教授及印度Symbiosis International（被認可）大學的訪問教員。此外，她還是IMT Ghaziabad的訪問教員、印度Alliance University的研究教授、Rushford商學院的工商管理博士（DBA）課程導師及Connect IT Technologies的顧問。在這些角色中，她積極參與博士指導、研究評審、學術評估及產學合作。
Dr. Gaur 曾擔任多所國際大學的外部博士考官及博士委員會成員，包括馬來西亞的Taylor's University、新西蘭的奧克蘭科技大學、印度的Alliance University及Symbiosis研究與創新中心。
她在高影響力的期刊上擁有廣泛的出版紀錄，這些期刊均已被Scopus和Web of Science索引，並且她與Elsevier、Springer、Taylor & Francis、Wiley及IGI Global等知名出版商共同編著和編輯了多本學術書籍。她目前擔任Communications in Statistics: Case Studies, Data Analysis and Applications（Taylor & Francis）的共同主編，並在多本知名國際期刊中擔任編輯及審稿人。
因其研究影響力而在全球受到認可，Dr. Gaur 被列入Elsevier-Stanford 全球前2%科學家（2024, 2025）名單，並且是IEEE的資深會員。
