Towards Sustainable Artificial Intelligence : A Framework to Create Value and Understand Risk / by Ghislain Landry Tsafack Chetsa.

Format:

Book

Author/Creator:

Chetsa, Ghislain Landry Tsafack, author.

Language:

English

Subjects (All):

Artificial intelligence.

Technology--Moral and ethical aspects.

Technology.

Data protection.

Artificial intelligence--Data processing.

Machine learning.

Artificial Intelligence.

Ethics of Technology.

Data and Information Security.

Data Science.

Symbolic AI.

Machine Learning.

Local Subjects:

Artificial Intelligence.

Ethics of Technology.

Data and Information Security.

Data Science.

Symbolic AI.

Machine Learning.

Physical Description:

1 online resource (145 pages)

Edition:

1st ed. 2021.

Place of Publication:

Berkeley, CA : Apress : Imprint: Apress, 2021.

System Details:

Mode of access: World Wide Web.

Summary:

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. .

Contents:

Chapter 1: AI in our Society

Chapter 2 Ethics of the Data Science Practice

Chapter 3 Sustainable AI Framework (SAIF): Overview of SAIF framework

Chapter 4 Intra-organizational understanding of AI: Towards Transparency

Chapter 5 AI Performance Measurement: Think business values

Chapter 6 SAIF in Action: A Case Study

Chapter 7 Alternative Avenues for Regulating AI Development

Chapter 8 AI in the Medical Decision Context: The use case of healthcare

Chapter 9 Conclusions and discussion.

Notes:

Includes bibliographical references and index.

Print version record.

ISBN:

9781484272145

1484272145

OCLC:

1262553436