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)
Part 1: Bigot in the Machine – A Primer
Part 2: Enterprise Risk Observability Model Governance
Part 3: Explainable AI in Action

The indispensable role of the C-suite in fostering responsible AI adoption

As generative AI continues to transform the business world, companies are increasingly exploring and utilizing diverse AI resources to enhance resilience, optimize costs, and navigate ongoing economic uncertainty. To fully capitalize on AI’s potential while mitigating its associated risks, CEOs must champion the responsible deployment of AI systems, known as Responsible AI (RAI). RAI ensures the alignment of AI systems with a company’s purpose, values, and risk management frameworks, while addressing regulatory, customer trust, and ethical concerns. By adopting RAI, companies can accelerate innovation, differentiate their brands, and build customer trust.

To successfully implement RAI, CxOs must take the following steps:

  1. Develop a clear RAI strategy: CxOs need to establish a comprehensive strategy that aligns RAI with their organization’s values, purpose, and business objectives...