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Responsible AI in the Enterprise

You're reading from   Responsible AI in the Enterprise Practical AI risk management for explainable, auditable, and safe models with hyperscalers and Azure OpenAI

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Product type Paperback
Published in Jul 2023
Publisher Packt
ISBN-13 9781803230528
Length 318 pages
Edition 1st Edition
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Authors (2):
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Heather Dawe Heather Dawe
Author Profile Icon Heather Dawe
Heather Dawe
Adnan Masood Adnan Masood
Author Profile Icon Adnan Masood
Adnan Masood
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Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1: Bigot in the Machine – A Primer
2. Chapter 1: Explainable and Ethical AI Primer FREE CHAPTER 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

Model Governance, Audit, and Compliance

“In this era of profound digital transformation, it’s important to remember that business, as well as government, has a role to play in creating shared prosperity – not just prosperity. After all, the same technologies that can be used to concentrate wealth and power can also be used to distribute it more widely and empower more people.”

– Erik Brynjolfsson, director of the MIT initiative on the digital economy

“Some cultures embrace privacy as the highest priority part of their culture. That’s why the U.S., Germany, and China may be at different levels in the spectrum. But I also believe fundamentally that every user does not want his or her data to be leaked or used to hurt himself or herself. I think GDPR is a very good first step, even though I might disagree with the way it was implemented and the effect it has on companies. I think governments should put a stake in the ground and say...

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