Artificial Intelligence for Social Good

Herausgegeben:Cowls, Josh

• Broschiertes Buch

Produktbeschreibung

This text interrogates the notion and considers the implication that AI functionally could and ethically should be harnessed for 'socially good' purposes. It includes an introduction, as well as research articles followed by commentaries. It appeals to students and researchers working in or interested in philosophy of technology.
Previously published in Philosophy & Technology Volume 34, supplement issue 1, November 2021
Chapters Artificial Intelligence for Social Good and Testing the Black Box: Institutional Investors, Risk Disclosure, and Ethical AI are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Produktdetails

• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-18372-0
• 1st ed. 2022
• Seitenzahl: 132
• Erscheinungstermin: 15. Oktober 2023
• Englisch
• Abmessung: 235mm x 155mm x 8mm
• Gewicht: 213g
• ISBN-13: 9783031183720
• ISBN-10: 303118372X
• Artikelnr.: 68999992

Autorenporträt

Josh Cowls is a Research Associate in Data Ethics at The Alan Turing Institute and a member of the Institute's public policy programme, where he works with government bodies to translate principles of digital ethics into practice for policymakers. A Turing Doctoral Student, Josh's research agenda centers on democratic decision-making in the digital era, and he is the author or co-author of work on AI ethics, state surveillance, online agenda-setting and the use of web archives, in publications such as New Media & Society, Minds and Machines, and in numerous edited volumes.

Inhaltsangabe

'AI for Social Good': Whose Good and Who's Good? Introduction to the Special Issue on Artificial Intelligence for Social Good.- Artificial Moral Agents Within an Ethos of AI4SG.- In the Frame: the Language of AI.- Artificial Interdisciplinarity: Artificial Intelligence for Research on Complex Societal Problems.- Engineering Equity: How AI Can Help Reduce the Harm of Implicit Bias.- Beyond a Human Rights-Based Approach to AI Governance: Promise, Pitfalls, Plea.- Testing the Black Box: Institutional Investors, Risk Disclosure, and Ethical AI.- How to Handle Armed Conflict Data in a Real-World Scenario?.