Responsible AI: Implementing Ethical and Unbiased Algorithms (1st ed. 2021)

Synopsis

This book is written for software product teams that use AI to add intelligent models to their products or are planning to use it. As AI adoption grows, it is becoming important that all AI driven products can demonstrate they are not introducing any bias to the AI-based decisions they are making, as well as reducing any pre-existing bias or discrimination. The responsibility to ensure that the AI models are ethical and make responsible decisions does not lie with the data scientists alone. The product owners and the business analysts are as important in ensuring bias-free AI as the data scientists on the team. This book addresses the part that these roles play in building a fair, explainable and accountable model, along with ensuring model and data privacy. Each chapter covers the fundamentals for the topic and then goes deep into the subject matter – providing the details that enable the business analysts and the data scientists to implement these fundamentals. AI research is one of the most active and growing areas of computer science and statistics. This book includes an overview of the many techniques that draw from the research or are created by combining different research outputs. Some of the techniques from relevant and popular libraries are covered, but deliberately not drawn very heavily from as they are already well documented, and new research is likely to replace some of it.

Copyright:

2021

Book Details

Book Quality:

Publisher Quality

ISBN-13:

9783030768607

Related ISBNs:

9783030768591

Publisher:

Springer International Publishing

Date of Addition:

10/15/21

Copyrighted By:

The Editor

Adult content:

No

Language:

English

Has Image Descriptions:

No

Categories:

Nonfiction, Computers and Internet, Law, Legal Issues and Ethics, Philosophy, Sociology

Submitted By:

Bookshare Staff

Usage Restrictions:

This is a copyrighted book.