In the current era, people and society have grown increasingly reliant on artificial intelligence (AI) technologies. AI has the potential to drive us towards a future in which all of humanity flourishes. It also comes with substantial risks for oppression and calamity. In response, researchers and organizations have been working to publish principles and develop AI regulations for the responsible use of AI in consequential application domains. However, these theoretically formulated principles and regulations also need to be turned into actionable algorithms to materialize AI for good.
This book introduces a unified perspective of Socially Responsible AI to help bridge conceptual AI principles to responsible AI practice. It begins with an interdisciplinary definition of socially responsible AI and the AI responsibility pyramid. Existing efforts seeking to materialize the mainstream responsible AI principles are then presented. The book also discusses how to leverage advanced AI techniques to address the challenging societal issues through Protecting, Informing, and Preventing, and concludes with open problems and challenges.
This book serves as a convenient entry point for researchers, practitioners, and students to understand the problems and challenges of socially responsible AI, and to identify how their areas of expertise can contribute to making AI socially responsible.
Contents:
- Preface
- About the Authors
- Acknowledgments
- Defining Socially Responsible AI
- Theories in Socially Responsible AI
- Practices of Socially Responsible AI
- Challenges of Socially Responsible AI
- Bibliography
- Index
Readership: Undergraduate & graduate students in AI, Machine Learning, Data Science, and Computer Science courses, and AI researchers, AI technologists, researchers, and practitioners from other disciplines who would like to contribute to making AI socially responsible with their expertise.
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