Trustworthy AI: A Business Guide for Navigating Trust and Ethics in AI
- 5h 56m 37s
- Beena Ammanath
- Gildan Media
- 2022
An essential resource on artificial intelligence ethics for business leaders
In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI.
Filled with deep insights and actionable steps for enabling trust across the entire AI lifecycle, the book presents in-depth investigations of the key characteristics of trustworthy AI, including transparency, fairness, reliability, privacy, safety, robustness, and more; a close look at the potential pitfalls, challenges, and stakeholder concerns that impact trust in AI application; and best practices, mechanisms, and governance considerations for embedding AI ethics in business processes and decision making. Written to inform executives, managers, and other business leaders, Trustworthy AI breaks new ground as an essential resource for all organizations using AI.
About the Author
BEENA AMMANATH is a global thought leader in AI ethics and an award-winning senior technology executive with extensive experience across a variety of industries. She is currently Executive Director of the Global Deloitte AI Institute and Founder of Humans For AI. She has also worked with companies such as General Electric, Bank of America, Hewlett Packard Enterprise, Thomson Reuters, British Telecom, and more. She has served on the boards of several tech startups, nonprofits and universities.
In this Audiobook
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Introduction
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Chapter 1 - A Primer on Modern AI
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Chapter 2 - Fair and Impartial
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Chapter 3 - Robust and Reliable
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Chapter 4 - Transparent
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Chapter 5 - Explainable
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Chapter 6 - Secure
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Chapter 7 - Safe
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Chapter 8 - Privacy
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Chapter 9 - Accountable
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Chapter 10 - Responsible
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Chapter 11 - Trustworthy AI in Practice
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Chapter 12 - Looking Forward
