Responsible AI: Best Practices for Creating Trustworthy AI Systems
暫譯: 負責任的人工智慧：建立可信賴的人工智慧系統最佳實踐

Csiro, Lu, Qinghua, Zhu, Liming

Responsible AI: Best Practices for Creating Trustworthy AI Systems
  • 出版商: Addison Wesley
  • 出版日期: 2023-12-29
  • 售價: $1,820
  • 貴賓價: 9.5 折 $1,729
  • 語言: 英文
  • 頁數: 320
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 0138073929
  • ISBN-13: 9780138073923
  • 相關分類: 人工智慧

    • 立即出貨 (庫存=1)

商品描述

AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility. In this timely, practical guide, pioneering AI practitioners bridge these gaps. The authors illuminate issues of AI responsibility across the entire system lifecycle and all system components, offer concrete and actionable guidance for addressing them, and demonstrate these approaches in three detailed case studies.

Writing for technologists, decision-makers, students, users, and other stake-holders, the topics cover:

  • Governance mechanisms at industry, organisation, and team levels
  • Development process perspectives, including software engineering best practices for AI
  • System perspectives, including quality attributes, architecture styles, and patterns
  • Techniques for connecting code with data and models, including key tradeoffs
  • Principle-specific techniques for fairness, privacy, and explainability
  • A preview of the future of responsible AI

商品描述(中文翻譯)

AI 系統正在解決現實世界的挑戰並改變各行各業，但對於它們在代表依賴它們的人類時的運作責任，存在著嚴重的擔憂。許多倫理原則和指導方針已經被提出用於 AI 系統，但這些原則往往過於「高層次」，難以轉化為實踐。相反地，AI/ML 研究人員通常專注於過於「低層次」的演算法解決方案，無法充分解決倫理和責任問題。在這本及時且實用的指南中，開創性的 AI 從業者彌補了這些差距。作者闡明了整個系統生命週期及所有系統組件中的 AI 責任問題，提供具體且可行的指導來解決這些問題，並在三個詳細的案例研究中展示這些方法。

針對技術專家、決策者、學生、使用者及其他利益相關者，主題涵蓋：

- 行業、組織和團隊層級的治理機制
- 開發過程的觀點，包括 AI 的軟體工程最佳實踐
- 系統觀點，包括品質屬性、架構風格和模式
- 將程式碼與數據和模型連接的技術，包括關鍵的權衡
- 針對公平性、隱私和可解釋性的原則特定技術
- 負責任的 AI 未來的預覽

作者簡介

Dr. Qinghua Lu is a principal research scientist and leads the Responsible AI science team at CSIRO's Data61. She received her PhD from University of New South Wales in 2013. Her current research interests include responsible AI, software engineering for AI/GAI, and software architecture. She has published 150+ papers in premier international journals and conferences. Her recent paper titled "Towards a Roadmap on Software Engineering for Responsible AI" received the ACM Distinguished Paper Award. Dr. Lu is part of the OECD.AI's trustworthy AI metrics project team. She also serves a member of Australia's National AI Centre Responsible AI at Scale think tank. She is the winner of the 2023 APAC Women in AI Trailblazer Award.

 

Dr./Prof. Liming Zhu is a Research Director at CSIRO's Data61 and a conjoint full professor at the University of New South Wales (UNSW). He is the chairperson of Standards Australia's blockchain committee and contributes to the AI trustworthiness committee. He is a member of the OECD.AI expert group on AI Risks and Accountability, as well as a member of the Responsible AI at Scale think tank at Australia's National AI Centre. His research program innovates in the areas of AI/ML systems, responsible/ethical AI, software engineering, blockchain, regulation technology, quantum software, privacy, and cybersecurity. He has published more than 300 papers on software architecture, blockchain, governance and responsible AI. He delivered the keynote "Software Engineering as the Linchpin of Responsible AI" at the International Conference on Software Engineering (ICSE) 2023.

 

Prof. Jon Whittle is Director at CSIRO's Data61, Australia's national centre for R&D in data science and digital technologies. With around 850 staff and affiliates, Data61 is one of the largest collections of R&D expertise in Artificial Intelligence and Data Science in the world. Data61 partners with more than 200 industry and government organisations, more than 30 universities, and works across vertical sectors in manufacturing, health, agriculture, and the environment. Prior to joining Data61, Jon was Dean of the Faculty of Information Technology at Monash University.

 

Dr. Xiwei Xu is a principal research scientist and the group leader of the software systems research group at Data61, CSIRO. With a specialization in software architecture and system design, she is at the forefront of research in these fields. Xiwei is identified by the Bibliometric Assessment of Software Engineering Scholars and Institutions as a top scholar and ranked 4th in the world (2013-2020) as the most impactful SE researchers by JSS (Journal of Systems and Software), a well-recognized academic journal in software engineering research.

作者簡介(中文翻譯)

陸青華博士是CSIRO Data61的首席研究科學家，負責負責任人工智慧科學團隊。她於2013年獲得新南威爾士大學的博士學位。她目前的研究興趣包括負責任的人工智慧、人工智慧/通用人工智慧的軟體工程以及軟體架構。她在國際頂尖期刊和會議上發表了150多篇論文。她最近的論文《朝向負責任人工智慧的軟體工程路線圖》獲得了ACM傑出論文獎。陸博士是OECD.AI可信人工智慧指標專案小組的成員，並且是澳大利亞國家人工智慧中心負責任人工智慧擴展智庫的成員。她是2023年亞太地區女性人工智慧開拓者獎的得主。

朱黎明博士/教授是CSIRO Data61的研究主任，並且是新南威爾士大學（UNSW）的兼任全職教授。他是澳大利亞標準局區塊鏈委員會的主席，並為人工智慧可信性委員會做出貢獻。他是OECD.AI人工智慧風險與問責專家小組的成員，也是澳大利亞國家人工智慧中心負責任人工智慧擴展智庫的成員。他的研究計畫在人工智慧/機器學習系統、負責任/倫理人工智慧、軟體工程、區塊鏈、監管技術、量子軟體、隱私和網路安全等領域進行創新。他在軟體架構、區塊鏈、治理和負責任人工智慧方面發表了300多篇論文。他在2023年國際軟體工程會議（ICSE）上發表了主題演講《軟體工程作為負責任人工智慧的關鍵》。

喬恩·惠特爾教授是CSIRO Data61的主任，該中心是澳大利亞在數據科學和數位技術方面的國家研發中心。Data61擁有約850名員工和合作夥伴，是全球人工智慧和數據科學領域最大的研發專業集團之一。Data61與200多家行業和政府機構、30多所大學合作，並在製造、健康、農業和環境等垂直行業中運作。在加入Data61之前，喬恩曾擔任莫納什大學資訊科技學院的院長。

徐西偉博士是CSIRO Data61的首席研究科學家，並且是軟體系統研究小組的組長。她專注於軟體架構和系統設計，處於這些領域研究的前沿。根據軟體工程學者和機構的文獻計量評估，西偉被認定為頂尖學者，並在2013年至2020年間被JSS（系統與軟體期刊）評為全球第四位最具影響力的軟體工程研究者。

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