Towards Sustainable Artificial Intelligence: A Framework to Create Value and Understand Risk
暫譯: 邁向可持續的人工智慧：創造價值與理解風險的框架
Tsafack Chetsa, Ghislain Landry
商品描述
So far, little effort has been devoted to developing practical approaches on how to develop and deploy AI systems that meet certain standards and principles. This is despite the importance of principles such as privacy, fairness, and social equality taking centre stage in discussions around AI. However, for an organization, failing to meet those standards can give rise to significant lost opportunities. It may further lead to an organization's demise, as the example of Cambridge Analytica demonstrates. It is, however, possible to pursue a practical approach for the design, development, and deployment of sustainable AI systems that incorporates both business and human values and principles.
This book discusses the concept of sustainability in the context of artificial intelligence. In order to help businesses achieve this objective, the author introduces the sustainable artificial intelligence framework (SAIF), designed as a reference guide in the development and deployment of AI systems.The SAIF developed in the book is designed to help decision makers such as policy makers, boards, C-suites, managers, and data scientists create AI systems that meet ethical principles. By focusing on four pillars related to the socio-economic and political impact of AI, the SAIF creates an environment through which an organization learns to understand its risk and exposure to any undesired consequences of AI, and the impact of AI on its ability to create value in the short, medium, and long term.
What You Will Learn
- See the relevance of ethics to the practice of data science and AI
- Examine the elements that enable AI within an organization
- Discover the challenges of developing AI systems that meet certain human or specific standards
- Explore the challenges of AI governance
- Absorb the key factors to consider when evaluating AI systems
Who This Book Is For
Decision makers such as government officials, members of the C-suite and other business managers, and data scientists as well as any technology expert aspiring to a data-related leadership role.商品描述(中文翻譯)
到目前為止，對於如何開發和部署符合特定標準和原則的人工智慧系統，幾乎沒有投入實際的努力。儘管隱私、公平和社會平等等原則在人工智慧的討論中佔據了重要地位，但對於一個組織而言，未能達到這些標準可能會導致重大的機會損失。這可能進一步導致組織的衰亡，正如劍橋分析公司（Cambridge Analytica）的例子所示。然而，追求一種實用的方法來設計、開發和部署可持續的人工智慧系統，並結合商業和人類的價值觀及原則是可能的。
本書討論了在人工智慧背景下的可持續性概念。為了幫助企業實現這一目標，作者介紹了可持續人工智慧框架（Sustainable Artificial Intelligence Framework, SAIF），該框架旨在作為開發和部署人工智慧系統的參考指南。
本書中開發的SAIF旨在幫助決策者，如政策制定者、董事會、高層管理人員、經理和數據科學家，創建符合倫理原則的人工智慧系統。通過專注於與人工智慧的社會經濟和政治影響相關的四個支柱，SAIF創造了一個環境，使組織能夠學習理解其風險和對人工智慧任何不良後果的暴露，以及人工智慧對其在短期、中期和長期內創造價值能力的影響。
您將學到的內容：
- 了解倫理與數據科學和人工智慧實踐的相關性
- 檢視促進組織內部人工智慧的要素
- 探索開發符合特定人類或特定標準的人工智慧系統的挑戰
- 探討人工智慧治理的挑戰
- 吸收評估人工智慧系統時需考慮的關鍵因素
本書適合對象：
決策者，如政府官員、高層管理人員及其他商業經理、數據科學家，以及任何渴望擔任數據相關領導角色的技術專家。
作者簡介
Ghislain's work in the healthcare industry at EC involves supporting the development of data related healthcare products for his clients. This made him appreciate the challenges and the complexity of developing AI systems that people trust to make the right decision for them and stimulated him to write this book.Before joining EC Ghislain held positions as data scientist in the telecommunications and energy sectors. Prior to this, Ghislain worked as an academic at the French National Institute for Research and Automation (INRIA) and the University of Lyon 1. His work primarily focused on analyzing the behaviors of high performance systems to improve their energy efficiency and gave him the opportunity to co-author several scientific books presenting methodologies for improving the energy efficiency for large scale computing infrastructures. He holds a PhD in computer science from Ecole Normale Supérieure of Lyon, France.
作者簡介(中文翻譯)
**Ghislain Tsafack** 是 Elemental Concept 2016 LTD (EC) 的數據科學部門負責人，他負責該組織的人工智慧（AI）策略。作為這項工作的組成部分，他領導公司利用最新的 AI 進展，幫助客戶從數據中創造價值，並對第三方為潛在投資者開發的 AI 系統進行審核。
Ghislain 在 EC 的醫療保健行業工作中，支持為客戶開發與數據相關的醫療產品。這使他認識到開發人們信任的 AI 系統以做出正確決策的挑戰和複雜性，並激勵他撰寫這本書。在加入 EC 之前，Ghislain 曾在電信和能源行業擔任數據科學家。更早之前，Ghislain 在法國國家自動化研究所（INRIA）和里昂大學 1 任教，主要專注於分析高效能系統的行為，以改善其能源效率，並使他有機會共同撰寫幾本科學書籍，介紹改善大規模計算基礎設施能源效率的方法論。他擁有法國里昂高等師範學院的計算機科學博士學位。
