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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

AI in hiring and recruitment

AI and machine learning have great potential to make the hiring process efficient, objective, and fair, taking away human biases. However, from the talent acquisition perspective, AI and machine learning are faced with a dilemma. There is mounting evidence and case studies that show that these systems end up amplifying existing human biases. The technology has the potential to transform the recruitment industry and help organizations that are lagging behind since they end up losing top talent in competition. However, due to the inherent algorithmic bias, executives now must consider AI as an effective solution to a higher attrition rate, but also be ready for the risk of lawsuits. The American Bar Association (ABA) warns that AI hiring systems are highly risky. The group highlights the possibility of disparate impact arising from algorithm-based methods. Disparate impact can still exist even if there is no “explicit intent to discriminate.”...

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