Book Image

Responsible AI in the Enterprise

By : Adnan Masood, Heather Dawe
5 (1)
Book Image

Responsible AI in the Enterprise

5 (1)
By: Adnan Masood, Heather Dawe

Overview of this book

Responsible AI in the Enterprise is a comprehensive guide to implementing ethical, transparent, and compliant AI systems in an organization. With a focus on understanding key concepts of machine learning models, this book equips you with techniques and algorithms to tackle complex issues such as bias, fairness, and model governance. Throughout the book, you’ll gain an understanding of FairLearn and InterpretML, along with Google What-If Tool, ML Fairness Gym, IBM AI 360 Fairness tool, and Aequitas. You’ll uncover various aspects of responsible AI, including model interpretability, monitoring and management of model drift, and compliance recommendations. You’ll gain practical insights into using AI governance tools to ensure fairness, bias mitigation, explainability, privacy compliance, and privacy in an enterprise setting. Additionally, you’ll explore interpretability toolkits and fairness measures offered by major cloud AI providers like IBM, Amazon, Google, and Microsoft, while discovering how to use FairLearn for fairness assessment and bias mitigation. You’ll also learn to build explainable models using global and local feature summary, local surrogate model, Shapley values, anchors, and counterfactual explanations. By the end of this book, you’ll be well-equipped with tools and techniques to create transparent and accountable machine learning models.
Table of Contents (16 chapters)
1
Part 1: Bigot in the Machine – A Primer
4
Part 2: Enterprise Risk Observability Model Governance
9
Part 3: Explainable AI in Action

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

abrupt drift 81

Adaptive Window (ADWIN) 82

adversarial example attacks 74

Aequitas 126, 188-191

AI alignment problem 19

AI Center of Excellence 154, 155, 156

AI ethics

Alan Turing Institute guide 120

AI governance

case, building 5, 6

Oxford’s recommendations 120

AI governance testing framework and toolkit 112

AI Incident Database (AIID) 34

AI-related standards 117

AI risk governance

in enterprise 15

AI risk management

distinctive challenges 105, 106

AI RMF Core 104

AI safety 8

hidden cost 28, 29

reference link 9

AI STEPS FORWARD 139, 140

capabilities 153

categories 140, 141

framework principles 140, 141

implementing, in enterprise 142, 143

in enterprise governance 144, 145

maturity model 146, 147

...