Machine Learning for High-Risk Applications: Approaches to Responsible AI

by Patrick Hall, James Curtis, Parul Pandey

The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes approaches to responsible AI—a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public.

Genres: Artificial Intelligence

466 pages, Paperback

Published May 23, 2023

Reviews

[Peter · Rating 2 out of 5]

Content seems to be good, but the organization of information is all over the place.

I have no doubt that this book could be great, but as it stands it could definitely benefit from a few more rounds of editorial work.