Socially responsible AI : theories and practices / Lu Cheng (University of Illinois at Chicago, USA), Huan Liu (Arizona State University, USA)

Englisch

New Jersey ; London ; Singapore ; Beijing ; Shanghai ; Hong Kong ; Taipei ; Chennai ; Tokyo : World Scientific, [2023]

© 2023

xv, 179 Seiten : Illustrationen, Diagramme ; 24 cm

Literaturverzeichnis: Seite 161-175

Erscheint auch als: Online-Ausgabe- Lu, Chen: Socially responsible AI. - New Jersey : World Scientific, 2023. - 1 Online-Ressource (xv, 179 Seiten)

978-981-12-6662-1 hardcover

978-0-00-099118-8 paperback

Weitere Ausgaben: 978-981-12-6663-8 (Fernzugriff) ebook for institutions, 978-981-12-6664-5 (Fernzugriff) ebook for individuals

*Künstliche Intelligenz / Soziale Verantwortung / Theorie / Praxis

*Artificial intelligence -- Social aspects -- DLC ; Artificial intelligence -- Moral and ethical aspects -- DLC

Klassifikation der Library of Congress: Q334.7

Dewey Dezimal-Klassifikation: 006.301;

"In the current era, people and society have grown increasingly reliant on artificial intelligence (AI) technologies. AI has the potential to drive us towards a future in which all of humanity flourishes. It also comes with substantial risks for oppression and calamity. In response, researchers and organizations have been working to publish principles and develop AI regulations for the responsible use of AI in consequential application domains. However, these theoretically formulated principles and regulations also need to be turned into actionable algorithms to materialize AI for good. This book introduces a unified perspective of Socially Responsible AI to help bridge conceptual AI principles to responsible AI practice. It begins with an interdisciplinary definition of socially responsible AI and the AI responsibility pyramid. Existing efforts seeking to materialize the mainstream responsible AI principles are then presented. The book also discusses how to leverage advanced AI techniques to address the challenging societal issues through Protecting, Informing, and Preventing, and concludes with open problems and challenges. This book serves as a convenient entry point for researchers, practitioners, and students to understand the problems and challenges of socially responsible AI, and to identify how their areas of expertise can contribute to making AI socially responsible"--

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