Overview
- Builds your awareness of the potential risks and harms that AI algorithms pose
- Covers the issues that must be addressed by AI practitioners in relation to responsibility and ethics
- Presents a framework for implementing AI responsibly
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About this book
The approach in this book raises your awareness of the missteps that can lead to negative outcomes in AI technologies and provides a Responsible AI framework to deliver responsible and ethical results in ML. It begins with an examination of the foundational elements of responsibility, principles, and data. Next comes guidance on implementation addressing issues such as fairness, transparency, safety, privacy, and robustness. The book helps you think responsibly while building AI and ML models and guides you through practical steps aimed at delivering responsible ML models, datasets, and products for your end users and customers.
What You Will Learn
- Build AI/ML models using Responsible AI frameworks and processes
- Document information on your datasets and improve data quality
- Measure fairness metrics in ML models
- Identify harms and risks per task and run safety evaluations on ML models
- Create transparent AI/ML models
- Develop Responsible AI principles and organizational guidelines
Who This Book Is For
AI and ML practitioners looking for guidance on building models that are fair, transparent, and ethical; those seeking awareness of the missteps that can lead to unintentional bias and harm from their AI algorithms; policy makers planning to craft laws, policies, and regulations that promote fairness and equity in automated algorithms
Keywords
Table of contents (10 chapters)
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Foundation
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Implementation
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Ethical Considerations
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Building Responsible AI Algorithms
Book Subtitle: A Framework for Transparency, Fairness, Safety, Privacy, and Robustness
Authors: Toju Duke
DOI: https://doi.org/10.1007/978-1-4842-9306-5
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Toju Duke 2023
Softcover ISBN: 978-1-4842-9305-8Published: 17 August 2023
eBook ISBN: 978-1-4842-9306-5Published: 16 August 2023
Edition Number: 1
Number of Pages: XVII, 190
Number of Illustrations: 4 b/w illustrations, 1 illustrations in colour
Topics: Machine Learning, Engineering Ethics, Artificial Intelligence