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

Azure OpenAI

Azure OpenAI Service offers REST API access to powerful language models, including GPT-3, Codex, and embedding models, with DALL-E 2 available to invited customers. These models can be adapted for various tasks, such as content generation, summarization, and natural language-to-code translation.

Responsible AI plays a huge role in the deployment and availability of these models, and therefore, Microsoft, which is committed to responsible AI use, has taken measures to prevent abuse and unintended harm by requiring well-defined use cases, incorporating responsible AI principles, building content filters, and providing guidance to onboarded customers. The service can be accessed through REST APIs, Python SDK, or a web-based interface in Azure OpenAI Studio.

Access to Azure OpenAI

Access to Azure OpenAI is currently limited due to high demand, upcoming product improvements, and Microsoft’s commitment to responsible AI. Customers with an existing partnership...