The 2020 Yearbook of the Digital Ethics Lab (eBook, PDF)

Redaktion: Cowls, Josh; Morley, Jessica

• Format: PDF

Produktbeschreibung

This annual edited volume presents an overview of cutting-edge research areas within digital ethics as defined by the Digital Ethics Lab of the University of Oxford. It identifies new challenges and opportunities of influence in setting the research agenda in the field.

The 2020 edition of the yearbook presents research on the following topics: governing digital health, visualising governance, the digital afterlife, the possibility of an AI winter, the limits of design theory in philosophy, cyberwarfare, ethics of online behaviour change, governance of AI, trust in AI, and Emotional Self-Awareness as a Digital Literacy. This book appeals to students, researchers and professionals in the field.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 227
• Erscheinungstermin: 30. Oktober 2021
• Englisch
• ISBN-13: 9783030800833
• Artikelnr.: 62857657

Autorenporträt

Josh Cowls and Jessica Morley are doctoral researchers at the Oxford Internet Institute, University of Oxford.

Inhaltsangabe

Introduction.- Are The Dead Taking Over Instagram? A Follow-up To Öhman & Watson (2019).- Emotional Self-Awareness as a Digital Literacy.- The Marionette Question - What is yet to be answered about the ethics of online behaviour change?.- On the limits of design: What are the conceptual constraints on designing artificial intelligence for social good?.- AI and its new winter: from myths to realities.- The Governance of AI and its Legal Context-dependency.- How to design a governable digital health ecosystem.- Ethical Guidelines for SARS-CoV-2 Digital Tracking and Tracing Systems.- On The Risks of Trusting Artificial Intelligence: The Case of Cybersecurity.- The Explanation Game: A Formal Framework for Interpretable Machine Learning.- Algorithmic fairness in mortgage lending: from absolute conditions to relational trade-offs.- Ethical Foresight Analysis: What it is and Why it is Needed?.- Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions.