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    Business Data Ethics

    Emerging Models for Governing AI and Advanced Analytics

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    Author(s)
    Hirsch, Dennis
    Bartley, Timothy
    Chandrasekaran, Aravind
    Norris, Davon
    Parthasarathy, Srinivasan
    Turner, Piers Norris
    Language
    English
    Show full item record
    Abstract
    This open access book explains how leading business organizations attempt to achieve the responsible and ethical use of artificial intelligence (AI) and other advanced information technologies. These technologies can produce tremendous insights and benefits. But they can also invade privacy, perpetuate bias, and otherwise injure people and society. To use these technologies successfully, organizations need to implement them responsibly and ethically. The question is: how to do this? Data ethics management, and this book, provide some answers. The authors interviewed and surveyed data ethics managers at leading companies. They asked why these experts see data ethics as important and how they seek to achieve it. This book conveys the results of that research on a concise, accessible way. Much of the existing writing on data and AI ethics focuses either on macro-level ethical principles, or on micro-level product design and tooling. The interviews showed that companies need a third component: data ethics management. This third element consists of the management structures, processes, training and substantive benchmarks that companies use to operationalize their high-level ethical principles and to guide and hold accountable their developers. Data ethics management is the connective tissue makes ethical principles real. It is the focus of this book. This book should be of use to organizations that wish to improve their own data ethics management efforts, legislators and policymakers who hope to build on existing management practices, scholars who study beyond compliance business behavior, and members of the public who want to understand better the threats that AI poses and how to reduce them.
    URI
    https://library.oapen.org/handle/20.500.12657/86099
    Keywords
    AI Ethics; Data Ethics; AI Ethics Management; Responsible AI; Governance of AI; Responsible data science; Ethical data science; Ethical data analytics; Business ethics; Corporate social responsibility; Risk management
    DOI
    10.1007/978-3-031-21491-2
    ISBN
    9783031214912, 9783031214905, 9783031214912
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    Cham, 2024
    Grantor
    • Ohio State University - [...]
    Imprint
    Springer International Publishing
    Series
    SpringerBriefs in Law,
    Classification
    Entertainment & media law
    International law
    Artificial intelligence
    Business ethics & social responsibility
    Corporate governance
    Pages
    101
    Rights
    http://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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