Data Ethics Management - Emerging Models for the Governance of Advanced Analytics and AI (Paperback, 1st ed. 2024)

This open access book explains why, in today's economy, companies need to implement artificial intelligence (AI) in a responsible and ethical way and how they can go about doing so. Business use of AI can produce tremendous insights and benefits. But it can also invade privacy, perpetuate bias, and produce other harms that injure people and damage business reputation. The authors interviewed and surveyed AI ethics managers at leading companies. They asked why these experts see AI ethics as important, and how they seek to achieve it. This book conveys the results of that research on a concise, accessible way that readers should be able to apply to their own organizations. Much of the existing writing on AI ethics focuses either on macro-level AI ethics principles, or on micro-level product design and tooling. The interviews showed that companies need a third component: AI ethics management. This third component consists of the management structures, processes, training and substantive benchmarks that companies use to operationalize their high-level AI ethics principles and to guide and hold accountable their developers.  AI ethics management is the connective tissue that makes AI ethics principles real. It is the focus of this book. This book provides a “snapshot� of AI ethics management at an array of highly sophisticated, AI-enabled companies. Other organizations, at an earlier stage in their AI journeys, should be able to draw from it useful lessons on how they, too, can pursue ethical and responsible AI and so succeed in the AI-driven economy.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Law
Release date:	November 2023
First published:	2024
Authors:	Dennis Hirsch • Tim Bartley • Aravind Chandrasekaran • Davon Norris • Srinivasan Parthasarathy • Piers Norris Turner
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	90
Edition:	1st ed. 2024
ISBN-13:	978-3-03-121490-5
Categories:	Books
LSN:	3-03-121490-0
Barcode:	9783031214905

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