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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

Ethical AI upskilling and education

An AI governance framework helps establish the parameters to maintain public safety in the face of AI harm, promote fairness, and ensure efficient markets by preventing biased and anti-competitive practices. However, with AI bias being a socio-technical problem, human oversight remains important for detecting and building useful strategies to mitigate bias. For these reasons, it’s important not only to upskill workers in order to manage these technologies but also build ethical safeguards into the algorithms themselves.

Upskilling of knowledge workers is required to stay ahead of the AI regulatory curve and remain competitive in the market. With the rapid advancement of artificial intelligence and machine learning technology, it is becoming increasingly difficult for those without the proper skill set to keep up. Human oversight is important in artificial intelligence as it can help prevent errors and ensure that systems are working as...

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