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    An Introduction to Ethics in Robotics and AI

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    Author(s)
    Bartneck, Christoph
    Lütge, Christoph
    Wagner, Alan
    Welsh, Sean
    Language
    English
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    Abstract
    This open access book introduces the reader to the foundations of AI and ethics. It discusses issues of trust, responsibility, liability, privacy and risk. It focuses on the interaction between people and the AI systems and Robotics they use. Designed to be accessible for a broad audience, reading this book does not require prerequisite technical, legal or philosophical expertise. Throughout, the authors use examples to illustrate the issues at hand and conclude the book with a discussion on the application areas of AI and Robotics, in particular autonomous vehicles, automatic weapon systems and biased algorithms. A list of questions and further readings is also included for students willing to explore the topic further.
    URI
    https://library.oapen.org/handle/20.500.12657/41303
    Keywords
    Engineering Ethics; Robotics; Applied Psychology; Moral Philosophy and Applied Ethics; Behavioral Sciences and Psychology; AI and ethics; ethics and robotics; descriptive ethics; relationship between ethics and law; machine ethics; machine meta-ethics; machine normative ethics; types of AI systems; strong and weak AI; challenges of AI; Open Access; Ethics & moral philosophy; Technology: general issues; Artificial intelligence; Psychology; Textbook
    DOI
    10.1007/978-3-030-51110-4
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    2021
    Imprint
    Springer
    Series
    SpringerBriefs in Ethics,
    Classification
    Ethics and moral philosophy
    Artificial intelligence
    Psychology
    Pages
    117
    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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