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Responsible AI in the Enterprise

You're reading from  Responsible AI in the Enterprise

Product type Book
Published in Jul 2023
Publisher Packt
ISBN-13 9781803230528
Pages 318 pages
Edition 1st Edition
Languages
Authors (2):
Adnan Masood Adnan Masood
Profile icon Adnan Masood
Heather Dawe Heather Dawe
Profile icon Heather Dawe
View More author details

Table of Contents (16) Chapters

Preface 1. Part 1: Bigot in the Machine – A Primer
2. Chapter 1: Explainable and Ethical AI Primer 3. Chapter 2: Algorithms Gone Wild 4. Part 2: Enterprise Risk Observability Model Governance
5. Chapter 3: Opening the Algorithmic Black Box 6. Chapter 4: Robust ML – Monitoring and Management 7. Chapter 5: Model Governance, Audit, and Compliance 8. Chapter 6: Enterprise Starter Kit for Fairness, Accountability, and Transparency 9. Part 3: Explainable AI in Action
10. Chapter 7: Interpretability Toolkits and Fairness Measures – AWS, GCP, Azure, and AIF 360 11. Chapter 8: Fairness in AI Systems with Microsoft Fairlearn 12. Chapter 9: Fairness Assessment and Bias Mitigation with Fairlearn and the Responsible AI Toolbox 13. Chapter 10: Foundational Models and Azure OpenAI 14. Index 15. Other Books You May Enjoy

Getting started with enterprise AI governance

In some business settings such as finance and healthcare, the machine learning algorithms that underpin AI are already regulated. For example, in the UK, the Financial Conduct Authority (FCA) is responsible for ensuring that credit agencies who use risk modeling (typically logistic regression) to estimate the likelihood of a customer defaulting on a loan do so in ways that are consistently fair to the customer. The credit agency must assure the FCA that the machine learning models they use for this are not biased for certain customer groups, are robust estimators of default risk, and similar assurances.

So, we can say that in some instances, AI Assurance Frameworks already exist and are used regularly in business today. However, as the use of AI grows exponentially across industry and the machine learning models used to produce this AI increase in their power and complexity, there is arguably a growing requirement for AI Assurance in...

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