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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

Policing and surveillance

Predictive policing is an object of major concern where police departments can predict hotspots for future crime, Minority Report-style. The consequences? Over-policing the neighborhoods of people of color, essentially exacerbating the existing situation.33

There is no narrative of AI gone bad that can be complete without mentioning Correctional Offender Management Profiling for Alternative Sanctions (COMPAS). A ProPublica report34 analyzed the risk assessment algorithm, which predicts the risk of recidivism, and found it to be biased against black people35. There has been a lot written about automated decision-making in predictive policing and sentencing since COMPAS, but using computer vision-style surveillance approaches to determine criminality36 continues in one form or another. The Department of Homeland Security is using37 a terrorist-predicting algorithm that utilizes features such as age, address, destination and/or transit airports, trip information...

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